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Mode Specific Assessment M4 Active Travel

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Mode Specific Assessment

M4 – Active Travel

Draft for Stakeholder Consultation – Active Travel

Transport and Infrastructure Council | National Guidelines for Transport System Management in Australia i

Providing Feedback

This draft document has been published for stakeholder feedback.

Submissions are due: 5pm, Thursday 31 March 2016

All submissions should be in writing and preferably emailed to: [email protected]

Hard copy submissions can be sent to:

NGTSM Steering Committee Secretariat

National Guidelines for Transport System Management

Commonwealth Department of Infrastructure and Regional Development

GPO Box 594 CANBERRA ACT 2601

For enquiries please contact the NGTSM Steering Committee Secretariat:

[email protected] | (02) 6274 7921

Disclaimer

This document is a draft for public comment. Please note that as a draft document it has not been approved

by any jurisdiction, therefore should not be relied upon for any purpose. An approved revised edition is due

to be published in May 2016.

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Table of contents

Economic appraisal of active travel initiatives ..................................................................... 1

1 Introduction ........................................................................................................................ 3

1.1 What is active travel .................................................................................................... 3

1.2 Why evaluate active travel projects.............................................................................. 4

2 Key characteristics of active travel .................................................................................. 7

2.1 Introduction .................................................................................................................. 7

2.2 Characteristics of active travel ..................................................................................... 7

2.2.1 Mode share ...................................................................................................... 7

2.2.2 Trip length ........................................................................................................ 9

2.2.3 Trip frequency ..................................................................................................10

2.2.4 Crash risk ........................................................................................................11

2.3 Determinants of active travel ......................................................................................12

2.4 Active travel infrastructure ..........................................................................................13

3 Option identification .........................................................................................................15

3.1 Problem identification .................................................................................................15

3.2 Potential active travel approaches ..............................................................................15

3.2.1 Triple Bottom Line ...........................................................................................15

3.3 How interventions influence demand ..........................................................................16

3.4 How interventions influence safety and security..........................................................16

3.4.1 Cycle Safety at Roundabouts ..........................................................................17

3.5 The cost of active travel interventions .........................................................................17

4 Modelling and Forecasting...............................................................................................18

4.1 Difference between modelling and forecasting ...........................................................18

4.2 Difference between walking and cycling .....................................................................18

4.3 Relationship to other modes .......................................................................................18

4.4 Range of approaches .................................................................................................19

4.4.1 Comparison studies .........................................................................................19

4.4.2 Aggregate behaviour studies ...........................................................................20

4.4.3 Sketch planning method ..................................................................................20

4.4.4 Discrete choice models ....................................................................................20

4.4.5 Traditional demand models ..............................................................................21

4.4.6 GIS based approaches ....................................................................................21

4.5 Limitations of modelling ..............................................................................................22

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5 Estimation of benefits ......................................................................................................23

5.1 Overview ....................................................................................................................23

5.1.1 Change in users’ willingness to pay for active travel infrastructure ...................24

5.1.2 Externalities .....................................................................................................24

5.1.3 Resource adjustment .......................................................................................26

5.2 Steps applicable to all benefit categories ....................................................................26

5.2.1 Identifying active travel segments ....................................................................26

5.2.2 Perceived versus unperceived costs ................................................................26

5.2.3 Identifying the relevant trip length ....................................................................27

5.2.4 Choosing appropriate annual expansion factors ..............................................28

5.3 Health benefits ...........................................................................................................29

5.3.1 Morbidity and mortality .....................................................................................29

5.3.2 Health and physical activity ..............................................................................30

5.3.3 Valuing active travel .........................................................................................31

5.3.4 Benefits of reduced morbidity and mortality .....................................................31

5.3.5 Health system benefits ....................................................................................32

5.3.6 Total health benefits ........................................................................................33

5.3.7 Parameter values for walking and cycling benefits ...........................................33

5.3.8 Indexing health benefit parameter values ........................................................35

5.3.9 Updating health benefit parameter values ........................................................36

5.3.10 Application issues ............................................................................................37

5.3.11 Health benefits summary .................................................................................39

5.3.12 Calculating health benefits ...............................................................................40

5.4 Congestion reduction benefits ....................................................................................41

5.5 Crash benefits ............................................................................................................42

5.5.1 Active travel crash risk .....................................................................................43

5.5.2 Effectiveness of interventions ..........................................................................44

5.5.3 Estimating unit crash costs ..............................................................................47

5.5.4 Estimating crash reduction benefits .................................................................48

5.5.5 Safety in numbers ............................................................................................49

5.6 Savings in vehicle operating costs ..............................................................................50

5.7 Savings in parking costs .............................................................................................50

5.8 Savings in public transport operating costs .................................................................50

5.9 Savings in road infrastructure costs ............................................................................51

5.10 Environmental benefits ...............................................................................................51

5.11 Travel time benefits ....................................................................................................51

5.11.1 General ............................................................................................................51

5.11.2 Weighting for cycling infrastructure quality .......................................................52

5.11.3 Active travel speeds .........................................................................................53

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6 Performance monitoring ..................................................................................................55

6.1 Why monitor ...............................................................................................................55

6.2 Measures of success ..................................................................................................55

6.3 Data collection ............................................................................................................55

6.4 Timing of performance monitoring ..............................................................................56

References ..............................................................................................................................57

Appendix A Physical Activity Definition ...........................................................................61

Appendix B Active Travel Interventions and Options .....................................................62

Appendix C Appendix C Assessment of interventions ...................................................73

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Table of tables

Table 1 Active travel trip and project types addressed in NGTSM ..................................... 3

Table 2 Active travel benefits and costs ............................................................................ 5

Table 3 Comparative Australian estimates of active travel benefits ................................... 6

Table 4 Benefits according to active travel type and scale ...............................................25

Table 5 Application of the rule of half to benefit categories...............................................27

Table 6 Identifying the relevant trip lengths for benefit estimation ....................................28

Table 7 Per capita annual value (morbidity and mortality) using DALYs ...........................32

Table 8 Per capita annual health sector costs attributable to inactivity .............................32

Table 9 Physical activity levels in the Australian adult population .....................................33

Table 10 Per-km weighted health and health system benefits of walking (2013) ................34

Table 11 Per-km weighted health and health system benefits of cycling (2013) .................34

Table 12 Total health price index, Australia ........................................................................36

Table 13 Trip diversion rates from Brisbane intercept surveys ...........................................39

Table 14 Mortality and morbidity benefits of active travel per km according to physical activity status 2013 ................................................................................39

Table 15 Health system benefits of active travel per km according to physical activity status 2013 ..............................................................................................40

Table 16 Fatality rates for motorists and active travellers, Australia (2002 to 2006) ...........43

Table 17 Serious injury rates for motorists and active travellers Australia (2002 to 2006) ...................................................................................................................43

Table 18 Cyclists killed in road crashes, Australia, 1997 to 2004 .......................................44

Table 19 Effectiveness of active travel safety interventions - cycling ..................................44

Table 20 Effectiveness of signalisation countermeasures – walking (US) ..........................45

Table 21 Effectiveness of geometric countermeasures – walking (US) ..............................46

Table 22 Effectiveness of operational countermeasures – walking (US) ............................46

Table 23 Crash costs by mode per vehicle km (2013) ........................................................47

Table 24 Suggested travel time weightings ........................................................................52

Table 25 Travel time weightings for cycling ........................................................................53

Table 26 Average speeds for active travel modes ..............................................................54

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Table of figures

Figure 1 Main mode of travel to work ................................................................................. 8

Figure 2 Main mode of travel to work or study, 2000 - 2012 ............................................... 9

Figure 3 Proportion of distance travelled by mode .............................................................10

Figure 4 Proportion of population that rode a bicycle .........................................................11

Figure 5 Fatality rates by mode ........................................................................................12

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Economic appraisal of active travel initiatives

At a glance

This Mode Specific Guidance outlines the methodology for undertaking an economic appraisal of an active travel initiative. Active travel in these Guidelines encompasses walking and bicycling.

The first three sections of this Mode Specific Guidance provide background describing active travel including its relative importance, trip characteristics, and its implications for health and safety outcomes.

Section 4 of this Guidance provides a broad overview of modelling and demand forecasting as they apply to active travel.

Section 5 describes the benefit categories that are relatively specific to active travel including:

– Health

– Safety

– Congestion

– Travel time.

Other relevant benefit categories that have more general application including private vehicle operating costs, public transport costs, parking and environmental costs are addressed briefly here but the main coverage of these benefits is contained in other parts of the Guidelines.

Issues that are common to transport appraisal generally such as treatment of capital and operating costs, discount rates and project life are also addressed in detail elsewhere in the Guidelines.

Overview

Active travel can embrace any mode of travel that relies on human powered mobility but these Guidelines address the main active travel modes of walking and cycling.

The focus of these Guidelines is principally on the benefits of active travel the most important of these being:

Improved health outcomes: The physical activity generated by active travel reduces the risk of premature illness and death and also reduces the related health costs;

Reduced congestion: Active travel can reduce road congestion resulting in lower costs to remaining road users;

Changes in safety risk: Active travellers may encounter higher crash risk in switching from motorised modes to active travel;

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Changes in travel time: Whether active travellers save time will be a function of trip distance and route in the base and project cases. In some circumstances at the trip distances that are popular for active travellers, they may sometimes achieve a time saving in switching to active travel.

Changes in public transport fares and private vehicle parking and operating costs.

The Guidelines cover the derivation of these benefits and contain suggested parameter values. Appropriate application of the rule of the half which is particular relevant to health benefits is also addressed. At relevant places this mode specific guidance refers readers to other relevant parts of the NGTSM.

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1 Introduction

1.1 What is active travel

Active travel is defined here as comprising walking and cycling. Active travel could be considered as embracing all forms of non-motorised transport – such as skateboards, scooters, and even kayaks – but there is little if any data available for modes other than walking and cycling. The defining characteristic of active travel is that it uses ‘human powered mobility’. (DIT 2012, p 4).

Walking and cycling trips may be self-contained such as a trip from home to the shops and back or form part of a multi-modal trip such combining a bicycle or walk segment from home to the bus stop and a walk segment from the bus stop to the office.

Active travel includes both trips made for transport purposes (i.e. to work, school, shops, activities) or for purely recreational purposes. It does not include walking or cycling for competition.

These guidelines here can be applied to all trip purposes other than competition.

Because active travel can form a component of many trip purposes and types, active travel infrastructure projects can have many contexts and forms. Projects could include bicycle storage and bus stops or railway stations, end of trip facilities including showers and bicycle storage, on road or off-road cycleways or off-road pedestrian/cycle paths.

For simplicity, the guidelines here focus on independent projects – that is, those projects that do not have strong synergies with other projects or other parts of the network. The more complex scenarios of for example improved pedestrian/cycle facilities delivered with an enhanced level of public transport service are not explicitly addressed, but the principles outlined in this and other parts of the guidelines could be used to evaluate those more complex, integrated projects.

Table 1 Active travel trip and project types addressed in NGTSM

Walk Cycle

Trip purpose

Transport (eg work, education, shopping)

Recreation

Competition x x

Project type

Self-standing new infrastructure eg new pedestrian/cycle paths, signalized pedestrian cycle crossings, end of trip facilities

Self-standing Infrastructure enhancements (eg widening or extension of pedestrian cycle paths)

Active travel projects as part of other transport upgrades (eg rail station improvements including access and safety upgrades)

x x

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1.2 Why evaluate active travel projects

There is no conceptual difference from an evaluation perspective between active travel projects on the one hand and the more conventional road and public transport projects. Active travel projects differ in nature and also in cost but like other investment projects they consume scarce resources. This is the primary reason for evaluation.

Until recently, evaluation of active travel initiatives has been somewhat neglected.

However, cogent policy reasons have been emerging from an increased emphasis on active travel in transport planning and investment programming activities. In particular a growing consensus about the health consequences of inactivity is engendering interest in the potential role of active travel – whether for transport or recreation – in improving health outcomes in the Australian community. For example a study prepared by Garrard (2009) for VicHealth cited research results1 that found commuter cycling to:

Reduce all-cause mortality

Improve physical performance particularly for people with a low initial fitness level

Have a favourable impact on body fat markers and body mass gain

Reduce the risk of colon cancer, and breast cancer in women, and improve cancer survival

Be associated with reducing overweight/obesity.

The potential range of benefits and costs of active travel in Table 2 is clearly broader than individual health and includes other private benefits (such as reduced parking costs) and social benefits such as open space preservation. Active travel also carries with it a range of social and private costs including infrastructure provision and maintenance, personal cycling and walking equipment including bicycle, shoes helmet and the like, and possibly increased crash risk because in some circumstances cycling and walking can have higher crash risk than driving.

1 Note that evidence referred to by Garrard is confined to cycling because of a relative absence of walking related

research

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Table 2 Active travel benefits and costs

Improved active travel conditions

Increased active travel

Reduced motor vehicle travel

More compact communities

Potential Benefits Improved user convenience and comfort

User enjoyment Reduced traffic congestion

Improved accessibility, particularly for non- drivers

Improved accessibility for non- drivers, which supports equity objectives

Improved public fitness and health

Road and parking facility cost savings

Transport cost savings

Option value Increased community cohesion (positive interactions among neighbours due to more people walking on local streets) which tends to increase local security

Consumer savings Reduced sprawl costs

Higher property values

Reduced chauffeuring burdens

Open space preservation

Increased security Increased traffic safety

More liveable communities

Energy conservation Higher property values

Pollution reductions Improved security

Economic development

Potential Costs Facility costs Equipment costs (shoes, bikes, etc.)

Slower travel Increases in some development costs

Lower traffic speeds Increased crash risk

Source: Litman (2014) p 14

As Part F3 the guidelines discusses, not all of these benefits are quantifiable. Perhaps for these reasons recent Australian studies that have estimated or sourced benefit estimates from elsewhere have tended to concentrate on a more limited benefit set. Health is generally the largest benefit category in dollar terms, followed by congestion reduction, although this balance does tend to vary between studies and between cities.

Table 3 shows the range of values used in a number of recent studies.

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Table 3 Comparative Australian estimates of active travel benefits

Benefit categories Range of estimates ($/km)

Decongestion benefit $0.207 - $0.258

Savings in car user costs $0.135 - $0.350

Parking cost savings $0.010 - $0.024

Travel time costs $0.000

Bicycle injury cost -$0.020 to -$0.370

Walking injury cost -$0.031 to -$0.240

Health benefits cycling $0.014 - $1.660

Health benefits walking $1.018 - $1.680

Air pollution reduction $0.017 - $0.028

Noise reduction $0.005 - $0.009

Infrastructure provision $0.024 - $0.052

Greenhouse gas reduction $0.006 - $0.022

Note: Estimates are for a range of years between 2008 and 2010

Source: PWC (2009), SKM PWC (2011), PWC SKM (2010), Fishman et al (2011)

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2 Key characteristics of active travel

2.1 Introduction

Understanding the level of demand for active travel and relevant demand characteristics is critical to efficient provision of active travel infrastructure.

The demand for active travel facilities is driven primarily by population (ie trip generation) and land-use (ie trip generation and purpose). The extent, location and demography of the population will create the demand. The demography of the population (ie gender, age and ability) is an influencing factor. For example, a high density residential area within active travel proximity to an education institute and large employment centre could have a high active travel demand for employees and students. This case shows that land-use is a significant aspect as it relates to trip purpose and the trip generation. Land-use planning also relates to trip distance which is an important factor in determining whether people consider walking or riding for their daily commute.

2.2 Characteristics of active travel

2.2.1 Mode share

Walking is probably the most common form of travel as it is to some degree involved in all trips undertaken by all other modes. However, only about 4% of work or study trips in Australia rely solely on walking making it the third most common mode as shown in Figure 1. By comparison, cycling accounts for between 1.1% and 2.8% of trips for work or study.

According to international comparisons in Litman (2014, p7) Australian levels of active travel are a fraction of those in European countries and among the lowest in the developed world.

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Figure 1 Main mode of travel to work

Source: ABS (2012)

Between 2000 and 2012 cycling trips as a proportion of all adult work or study work or study trips increased from 1.1% to 1.6% while walking trips declined from 4.4% to 3.8%. Over that period the proportion of trips made by public transport increased from 12.2% to 15.8% and private motor vehicle trips decreased from 81.9% to 77.7% (see Figure 2). By 2012 walking and cycling made up 5.4% of all adult work or study trips.

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Figure 2 Main mode of travel to work or study, 2000 - 2012

Source: ABS (2012)

2.2.2 Trip length

The majority of walk and cycling commuting trips are less than 5 km (96% and 52% respectively), as shown in Figure 3.

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Figure 3 Proportion of distance travelled by mode

Source: ABS (2009)

2.2.3 Trip frequency

According to the National Cycling Strategy (Australian Bicycle Council 2014, p 44 et seq), cycling is dominated in terms of numbers of cyclists by those who cycling for recreational purposes; this group outweighs ‘transport’ cyclists by a factor of nearly three to one2. Surveys of walkers and cyclists conducted in Brisbane in 2011 (SKM/PWC 2011, pp 78-79) found that on major off- road pedestrian/cycle corridors, transport trips were generally dominant on weekdays and recreational trips on weekends. Estimates for Sydney contained in Aecom (2010, p 22) suggest that work trips by bicycle make up about 8% of all cycle trips. Trip frequency estimates are not available for walkers but according to the National Cycling Strategy, 83% of Australians did not cycle in the week prior to being surveyed (Australian Bicycle Council 2014, p 44 et seq).

The proportion of the population that rode a bicycle in the last week, month or year is shown in Figure 4. Tasmania has the lowest proportion of people regularly riding a bicycle (13%) with the Australian average being 17%. A further 25% of Australians had ridden a bicycle in the previous month.

2 This is not the same as saying however that recreational trips make up 75% of all cycling trips, because

recreational cycling trip frequency might be lower than transport trip frequency

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Figure 4 Proportion of population that rode a bicycle

Source: Australian Bicycle Council (2014)

2.2.4 Crash risk

Between 2002 and 2006, pedestrians and cyclists represented 2% and 15% of all road-related fatalities (see section 6.4.1 later). After accounting for distance travelled, walking and cycling are two of the more dangerous modes, with a fatality rate (ie deaths per 10 million km) exceeded only by motorcycling. In 2010 there were 0.62 pedestrian fatalities per 10 million km walked and 0.103 cyclist fatalities per 10 million km cycled in Australia. Fatal crash incidence for car occupants was 0.044 to 0.048 per 10 million vehicle km travelled.

The data in Table 5 shows fatality rates for pedestrians and cyclists that are two to twelve times those for car drivers.

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Figure 5 Fatality rates by mode

Source: Austroads (2010)

2.3 Determinants of active travel

A number of factors determine the propensity for people to choose walking and cycling over other modes.

Infrastructure: Good quality, appropriately designed active travel infrastructure with meaningful network connectivity will maximise the levels of active travel given the underlying demand for walking and cycling.

Gender: on average, males and females tend to walk about the same distance each day, although males cycle about 2.75 times further than females.

Age: those aged 10-34 years tend to walk about 1.4 times the average, while persons aged 65+ years tend to walk significantly less (eg 0.4 of the average). Those aged 10-14 years tend to cycle 2.8 times the average compared with persons aged 15-34 years who cycle about 1.5 times the average, while those aged 60+ years tend to cycle about 0.25 times the average.

Land use: some land uses tend to have a higher incidence of walk trips (eg outdoor recreation facilities, indoor sports facilities, schools, tertiary institutions, public transport interchanges and hotels / motels) than others (eg retail shops, health services and bulky goods stores). By comparison the incidence of cycle trips tends to be relatively low for schools, tertiary institutions and retail shops uses.

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Fatalities per 10 million km travelled

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Complementary uses / facilities: the propensity for active travel can be enhanced by the proximity of complementary land uses and facilities (eg a public transport interchange located close to a regional shopping centre or university).

Scale and proximity: the propensity for active travel would be expected to increase with the scale of development, albeit at a diminishing rate, while active travel would be expected to increase with proximity of related uses.

Safety, incorporating:

– physical safety (eg trip hazards, inadequate width, location of power/light poles and paths not navigable by wheelchairs, prams and the elderly)

– the effect on trip demand of perceptions that active travel infrastructure is unsafe (eg narrow footpaths or cycle lanes along a carriageway or poor crossing facilities).

Security: personal security, or the lack of it, can be a major factor in limiting walking and cycling, particularly for females travelling either at night and/or on their own.

Topography and climate: heat, high humidity, steep hills and rain have the potential to make walking and cycling less attractive relative to other modes of travel.

Ancillary infrastructure: the availability of seating, drink fountains, shade planting, bicycle parking and directional signage can impact on active travel demand.

Awareness: Potential active travel users might be unaware of the availability and advantages of active travel networks.

End of trip facilities such as showers, and cycle storage may reduce impediments to active travel.

Most of these determinants of active travel demand are pertinent to both walking and cycling. The availability of bicycle parking and end of trip facilities - ie showers and lockers - are more associated with cyclists. Perceptions about personal security might be more relevant to pedestrians, particularly at night.

2.4 Active travel infrastructure

A sustainable active travel network incorporates good quality walking and cycling infrastructure that is well maintained, safe, accessible, connected, illuminated and signed. The infrastructure should provide direct routes to trip destinations, including public transport facilities, and have appropriate end-of-trip facilities such as bike parking, showers, change rooms and lockers.

An active travel network will encompass:

The road corridor enabling pedestrians and cyclists to travel along and across road (ie on-road facilities)

Routes over public land such as parks, rivers and coastal paths, at transport interchanges and car parks (ie off-road facilities)

Private land including access points to buildings and parking areas and routes through private developments.

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Nowadays, an established road user hierarchy forms part of many state and local transport planning authority strategies. Most active travel infrastructure is capable of accommodating or is relevant to both pedestrians and cyclists. On-road cycle lane facilities (including intersection treatments), bicycle parking and to a lesser extent end of trip facilities are exceptions.

Walking is included in most trips made by other modes. Whatever the main means of travel, walking is usually the first and last mode used (eg footpaths from public transport interchanges, parking areas). The majority of active travel takes place on, around or along the road corridor. Some elements of active travel infrastructure are complementary to the road network (eg footpaths along the edge of the carriageway) while other elements such as cycle lanes compete for road space. The design and construction of new roads and road upgrades should incorporate all road users at the earliest possible point in the planning process.

Off-road cycle paths can also provide an alternative route to the roadway. They may provide connectivity between appropriate land-uses and offer a viable active transport alternative to using motorised modes.

Some pathways such as recreational paths through parks are independent of other transport modes.

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3 Option identification

3.1 Problem identification

Problems and issues that prevent or discourage walking or cycling should be identified so that solutions and opportunities for improvement can be identified and implemented appropriately. These problems and issues can take various forms including:

Lack of active travel infrastructure or appropriate facilities

Poor connectivity between paths, public transport interchanges, appropriate land-uses

Physical safety concerns with inappropriate infrastructure for the speed and volume of traffic or poor quality facilities not navigable by wheelchairs, prams or the elderly – these inadequacies may be the result of poorly designed and maintained infrastructure (eg trip hazards, lack of ramps, inadequate path widths or excessive poles)

Lack of security as people may feel unsafe without CCTV, lighting or ‘passive surveillance’ from activity of nearby building or facilities along the path

Inadequate ancillary infrastructure (eg drinking fountains, shade planting, seating, signage, bicycle parking, end-of-trip facilities)

Poor knowledge and awareness of the facilities available and associated benefits (eg health, travel time).

3.2 Potential active travel approaches

3.2.1 Triple Bottom Line

Triple Bottom Line (TBL) assessment is a potentially important tool in identifying, designing and assessing active travel initiatives. Relevant TBL criteria include:

Health: Research indicates that increases in levels of physical activity including walking and cycling are associated with long term health benefits for individuals and the community

Physical Safety: Again this criterion has social and economic benefits. Improvements in active travel infrastructure can reduce the incidence and severity of crashes involving walkers and cyclists, as well as the personal trauma and economic costs caused by crashes

Personal Security: This is primarily a social indicator relating to how likely a person is to use a facility depending on the perceived personal security

Pedestrian Amenity: Incorporates elements of individual developments that directly affect the quality and character of the public domain

Cyclist Amenity: A social and environmental criterion that is affected by the quality and character of the active travel facility

Encouraging Mode Shift: New or enhanced active travel infrastructure may produce a mode shift towards non-motorised transport benefiting with consequent economic and environmental benefits including reduced congestion and reduced environmental impacts such as air and noise pollution

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Active Travel Time Saving: This is a component of the economic benefit of an active travel project

Installation Cost: The upfront component of the economic cost of an active travel project

Maintenance Cost: The ongoing (recurrent) component of the economic cost of an active travel project.

A list of infrastructure options available to support active travel is included in Appendix B. The majority of these options are associated with the road network where road crossing facilities and interactions at intersections are significant. Appendix B includes images/diagrams of some of the less known interventions and options available and a reference table is attached in Appendix C, which can act as a guide to assessing the impacts of the interventions described.

3.3 How interventions influence demand

The potential for a specific active travel initiative to influence active travel demand will be determined by its location, scale and quality. For example, a new pedestrian/cycle bridge would heavily influence active travel demand if providing a connection to/from areas or facilities of significant population or land-use (ie residential to educational facility). On the other hand, a refuge island treatment on an existing road would not increase demand along a route but would provide additional safety to existing users. Similarly, a new off-road shared pedestrian/cycle path may increase the number of active travellers along that route while an on-road cycle lane might only improve safety for existing active travel users. Incorporating end-of-trip facilities at a new office development such as bicycle parking, changing rooms, showers and lockers could have a significant impact on active travel demand, particularly work trip demand. However, installation of a water fountain on a pedestrian/cycle path would primarily benefit existing users.

3.4 How interventions influence safety and security

Active travel poses a relatively high crash risk when compared with car travel (see section 2.2.4).

The primary risk to safety of active travel users is a crash, most likely from interactions with motorised transport. There are four levels of causality severity following a crash incident. These are as follows:

1 Fatality

2 Hospitalised

3 Medical treatment

4 Minor injury

There are also risks to physical safety posed by inadequate infrastructure such as trip hazards (e.g. uneven surface, heaving in concrete footpaths, potholes in roads), lack of ramps, inadequate path widths or excessive or poor placement of power and light poles.

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Continuing the example above, a new off-road shared pedestrian/cycle path would likely see a significant improvement in safety for cyclists as they no longer need to interact with vehicles. By comparison, delineation of an on-road cycle lane may improve drivers’ awareness of cyclists but have only a minor safety benefit because the potential for conflict between cyclists and motorised is not greatly reduced.

Personal security needs to be considered where facilities are not properly monitored through CCTV or passive surveillance, or where there is poor lighting. This can be dealt with using Crime Prevention through Environmental Design (CPTED), a crime prevention strategy which outlines how physical environments can be designed in order to lessen the opportunity for crime.

Cyclists are more at risk of physical injury or being involved in a crash with motorised transport as cycle routes are more likely to interact and compete with the road carriageway.

3.4.1 Cycle Safety at Roundabouts

Roundabouts generally form a safe intersection for motorists but result in higher crash rates for cyclists. This is especially the cases when roundabout design prioritises capacity over safety. Multi-lane roundabouts are particularly a concern with fast moving vehicles interacting with bicycles.

As outlined in Austroads (2014), there is strong evidence that on-carriageway painted cycle lanes on approach, through and departing the roundabout are associated with negative safety outcomes. The dominant cyclist safety issue involves a motorist entering a roundabout failing to give way to a circulating cyclist. Strong evidence was found in the Austroads research that lane marking that encourages a shared traffic and cycle lane approach to the roundabout and circulation at similar speeds can be effective for safety. The physical separation of bicycle movements on approach and departure should be considered where consistency between motor vehicle and cycle speeds is unachievable.

3.5 The cost of active travel interventions

The cost of active travel infrastructure will vary depending on its type, location, scale and quality. By way of example, the cost for a grade separated facility for a bridge crossing a four lane road is approximately $1.5 million. That cost could increase by about $4.25 million were the bridge to be accessed by ramps rather than stairs. A pedestrian refuge island could cost between $5000 and $30 000 depending on the style and extent of the facility. On-road cycle lane marking is estimated to cost about $2500 per km plus $100 per bicycle symbol. An off-road shared pedestrian and cycle path would be of the order of $130 per m2 for a concrete pathway with an additional $650 per linear metre for minor associated works and line marking. DIT (2012 p 65) cites construction costs for pedestrian/cycle paths in a number of Australian capital cities ranging between $1.5 million and $3 million per km.

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4 Modelling and Forecasting

4.1 Difference between modelling and forecasting

Modelling and forecasting are both used to estimate demand for transport facilities. Demand estimates, for base and project cases, are then important inputs to evaluation of transport initiatives.

The principle differences between forecasts and models lie in structure and complexity. A transport model including the traditional four step model encompasses forecasts, but a forecast does not necessarily entail modelling. Forecasts, in which current demand is projected from some existing base demand using assumed changes in population or trip incidence for example, are more likely to be relevant to simple evaluation problems. An example might be an extension to an existing pedestrian/cycle path. A forecast might also be made drawing growth rates from analogous projects elsewhere which have already been subjected to some form of ex post evaluation.

Transport models on the other hand with their much greater complexity are more suited to analysis of large projects such as the development of an active travel network or a ‘missing link’ active travel project that is significant enough to have network consequences. Use of a transport model in this circumstance would facilitate estimation of the active travel project on demand for other modes. Estimation of those impacts can be a useful input to the evaluation of network-significant active travel projects.

4.2 Difference between walking and cycling

There are limitations to modelling pedestrian activity given the variations in length and purpose of trips. The variation in trip purposes involved can also limit modelling accuracy, for example the amount of commuting and leisure travel will respond differently to an intervention.

4.3 Relationship to other modes

The main difference between modelling for active transport and other modes (ie private vehicles or public transport) is that the zone systems and networks used in an active transport model would need to be significantly smaller as the majority of trip lengths would be much shorter (eg 0.4 - 1.2 km). Active travel models need to have greater spatial detail to account for the various paths and routes available.

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Models may be used to estimate future demand for transport facilities where walking and cycling schemes form part of a larger set of transport proposals. In this context, demand and spatially aggregate models3 would be relevant. Different modelling approaches may be required where walking and cycling schemes are promoted separately from other modes of transport. Modelling may not be required for active travel depending on the extent and scale of the intervention proposed. Forecasting may be sufficient to determine the impact of an active travel intervention.

4.4 Range of approaches

A range of approaches to modelling/forecasting active travel demand have been successfully applied. All of the approaches described would be equally applicable to walking and cycling travel mode but the choice of one approach over the other will depend on the:

Scale of the initiative

Availability of existing models and data

Budget and time available

Level of accuracy required.

4.4.1 Comparison studies

This method aims to predict the active travel demand of a facility or intervention by comparing it to usage and surrounding population and land use of a similar or comparable facility. The aggregate data from comparable facilities can be assessed in an attempt to identify variables that contribute to the different levels of usage between areas, time or facility.

An example of the comparative study method is given in the United Kingdom Department for Transport (DfT) online Transport Analysis Guidance (WebTAG) for active travel mode appraisal. The demand impact is estimated by reference to before and after demand surveys conducted for an already completed active travel project in a similar area. The comparative demand impact estimated from the before and after surveys of an analogous project in a similar area is used to derive ‘with project’ (project case) demand estimates. Underlying demand growth rates in the catchment area of the proposed active travel project are used to estimate ‘without project’ (base case) demand.

In this example, the existing base year survey data was increased using different growth rates for the ‘without’ and ‘with’ scheme scenarios. The ‘without’ improvement scheme uses local network or city wide annual growth rates (eg 0.25% for cyclists and 0.5% for pedestrians). The ‘with’ improvement scheme scenario uses growth rates taken from the comparative study which showed a significant increase in pedestrian and cycle demand. The difference in use predicted with the intervention can be determined by subtracting the ‘without’ scheme estimates from the forecast demand predicted ‘with’ the scheme in place.

3 A strategic road network model is an example of a spatially aggregate model.

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4.4.2 Aggregate behaviour studies

This approach relates active travel in an area to its local population, land-use and other characteristics, usually through regression analysis. The model equations can be used to predict demand in other areas. Some data used for these studies is obtainable from census or geographical data sets (eg car ownership, income, average age, gender, journey to work data). This approach may be useful for a large network study but otherwise may not be cost effective. Also, data such as bicycle ownership is not readily available. Geographical information systems (GIS) may be used to obtain data on the topographical profile of an area, network or city which may be a useful characteristic for cycling demand.

4.4.3 Sketch planning method

This method predicts active travel demand of a facility or in an area based on simple calculations and rules of thumb about trip lengths, mode share and other aspects of active travel behaviour. A series of ‘back-of-the-envelope’ calculations are used to estimate the number of pedestrians or cyclists using a facility. Sketch planning relies generally on existing data or easily collected data (eg population or census data, traffic counts, pedestrian counts, cyclist counts, zoning or land-use data, trip length or crash data).

The accuracy is sometimes questionable given that the parameters are generally derived from previous studies which may not necessarily have transferrable results.

4.4.4 Discrete choice models

These models aim to predict an individual’s trip decision including their choice of mode or route as a function of any number of variables. Discrete choice models can be used to estimate the total number of people who change their behaviour in response to an intervention. The change in active travel demand can then be predicted. Parameters from these models can also be used to estimate the elasticity of demand (ie percentage change in pedestrian or bicycle activity) in response to a given change in another particular variable.

Discrete choice models can be calibrated using stated preference survey data and as such can be a cost effective way of estimating active travel demand for new facilities in areas with little or no relevant data.

As an example a discrete choice model may be used to predict the probability of taking a trip by bicycle or by car based on the following three factors:

Time difference between the two modes for the trip

Gender of the individual

The extent of the cycle facilities available.

The weight assigned to each factor (ie coefficient) can be used to derive elasticities. These can indicate the change in mode choice based on one of the three factors, while keeping the other factors constant. Transferring this data to other schemes may be difficult but the elasticity may be used to estimate the change in users as a function of a change in a facility.

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A discrete choice model could also be applied to an entire affected population (eg proximate to an active travel facility). The model would be used to estimate the total number of people who would change their behaviour as a result of the new facility.

4.4.5 Traditional demand models

These models employ the traditional four-step travel demand modelling approach using land use conditions, transport network characteristics and relevant travel behaviour variables to predict future active travel patterns. They predict total trips generated by trip purpose, mode and origin/destination and distribute these trips through a network of transport facilities.

Part T1 of the guidelines provides more detailed discussion of four-step models.

The main difference between modelling for active transport and other modes (ie private vehicles or public transport) is that the zone systems and networks used in an active transport model would need to be significantly smaller as the majority of trip lengths would be much shorter (eg 0.4 - 1.2 km). Active travel models need to have greater detail to account for the various paths and routes available.

Some advance models have been developed to include an active travel component. These primarily deal with bicycle travel and are based in Europe. A British consultancy firm, MVA, has developed two such models:

START, a mode choice model that includes both cycling and walking as options

TRIPS, a network model package that includes a bicycle network option called MVcycle.

Each of these models requires small zone sizes to account for the shorter trips associated with active travel and the variations in the active transport network.

A similar model for cycling activity has also developed in the Netherlands call QUOVADIS-BICYCLE.

4.4.6 GIS based approaches

Geographical Information Systems are used as information management tools with graphical display capabilities that can be used in many ways to evaluate potential demand. GIS can also be used to enhance active travel demand forecasting and project assessment.

An example of this approach was developed in a University of Queensland study (Hutchinson 2000) of cyclists travelling to the campus. An initial multiple criteria analysis was undertaken on survey data to determine the important factors in cycle route choice. This information included directness, quality and topography of the route. Data on these factors were used to construct a layer in the GIS map of the area from which predictions of cyclists’ preferred routes could be made.

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4.5 Limitations of modelling

For small scale initiatives with limited impact (eg pedestrian refuge island, path widening) the comparative study might be the most appropriate approach to forecasting/modelling. A medium sized project (eg sizable extensions to cycle network or off-road shared path) might use the sketch planning method or a discrete choice model. A fully specified four-step network based model would only be justifiable for major infrastructure project (eg bridge over a river connecting with large residential or working populations).

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5 Estimation of benefits

5.1 Overview

Individuals walk and cycle for recreation, for exercise or to access work, shopping or entertainment. Active travel gives rise to private benefits – users would not walk or cycle if they did not perceive it to beneficial. Active travel also causes social benefits including for example reductions in health system costs, noise and air pollution and congestion.

The size and composition of project benefit streams will be a function of:

The type of project under consideration. A project to widen an existing cycle path through a park might reduce the risk of cyclist/cyclist and cyclist/pedestrian crashes but not attract new active travellers.

Project location: Projects in rural towns are unlikely to generate congestion reduction benefits;

– The active travel market segment that the project is targeted towards. Improving the signals at a pedestrian crossing outside a school might yield benefits on school days, particularly in the morning and afternoon school peaks, but have limited impact on crash risk outside those times on school days and in general on non-school days. By comparison, extending a pedestrian/cycle path linking residential, education and employment precincts could generate benefits all week and among a broad spectrum of active travellers.

– Building new active travel infrastructure in an area that already features high levels of active travel use might reduce crash risk if it takes active travellers out of road environments. The impact on health costs might be limited however because with an already high level of active travel use in the catchment, the project might be unlikely to significantly increase active travel.

Benefits of active travel projects fall into three categories.

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5.1.1 Change in users’ willingness to pay for active travel infrastructure

Generally it will be uneconomic and impracticable to survey existing and potential active travellers about their willingness to pay. Instead, surrogate or proxy values are used, based on research into the impacts on users of active travel infrastructure improvements. The benefits that make up or are analogous to a change in willingness to pay include changes in travel time costs, vehicle operating costs and parking costs. As explained in Part F3 of the guidelines, these costs make up the active traveller’s ‘private generalised cost of travel’, with generalised costs being calculated for the base case and project case scenarios. The principle behind the use of these proxy benefit measures is that the active traveller would be prepared to pay at least the total value of these benefits for a given improvement in active travel infrastructure. For existing users (that is, those active travellers who will not change their trip making in response to an infrastructure improvement), the willingness to pay benefit of that improvement is equal to the difference between their base case and project case generalised cost of travel. For new users – those active travellers who would not make their trip in the absence of the proposed infrastructure improvement or who make additional active travel because of new infrastructure– the willingness to pay benefit is equal to half the difference between base case and project case generalised cost of travel4.

This approach to estimation of willingness to pay is less meaningful if there is an infrastructure initiative which has an aesthetic element or environmental element that has a positive influence on the decision to walk or cycle. An example would be a pedestrian cycle path along a river as an alternative to on-road or in-road access. Estimation of those benefits requires more sophisticated cross sectional or discrete choice studies that will be impracticable for most projects. Recent research for Sydney (see Table 25) suggests that cyclists place on a value on the opportunity to shift from on –road cycling to an off-road pathway but it is not clear whether cyclists are valuing amenity or the reduced crash risk associated with off-road cycle paths.

5.1.2 Externalities

Externalities include reduced health system costs because active individuals are less prone to illness and place less demand on health system resources, sometimes reduced crash costs5 if cyclists and pedestrians are diverted from the road environment, and reduced congestion costs if an active travel project causes a modal shift away from motor vehicles towards walking and cycling. Social benefits associated with new active travel are not subject to the rule of the half.

It is useful as in Table 4 to distinguish between benefits associated with existing users and those associated with new users for several reasons: firstly because only willingness to pay benefits for new users are subject to the ‘rule of the half’ (see Part F of the guidelines); and secondly because CBAs might be sensitive to assumptions made about the potential for an active travel project to generate new trips.

4 Part T2, Section 6.3 of NGTSM outlines the rationale for the ‘rule of the half’. 5 Modal shifts towards active travel will not always reduce crash costs. Because pedestrian and cyclist crash risk

in the road environment is relatively high, a modal shift towards on-road and in-road active travel facilities could cause a net increase in crash risk.

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Table 4 Benefits according to active travel type and scale

Benefit category Project type/scale

New off road AT path –

inner city location

New off road AT path –

outer suburban or rural location

On road cycle lane

Improved signals and channelization

for cyclists/pedestrians

End of trip facilities

Willingness to pay benefits for existing active travellers

Health

Vehicle operating costs

Parking

Travel time

Willingness to pay benefits for new active travellers

Health

Vehicle operating costs

Parking

Travel time

Externalities - existing active travellers

Change in crash risk

Noise reduction

Air pollution reduction

Congestion reduction

Externalities - new active travellers

Change in crash risk

Noise reduction

Air pollution reduction

Congestion reduction

Resource correction – new active travellers

Vehicle operating costs

Public transport operating costs

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5.1.3 Resource adjustment

The resource correction is the difference between the price paid by the user and the resource cost of a change in travel behaviour. For example a bus user who decides to become an active traveller saves her bus fare. The resource correction in this instance would be equal to the reduction in bus system costs caused by her decision to switch to active travel less her fare saving. Were our new active traveller to be a former car driver the resource correction would comprise the saving in depreciation on her vehicle that she would be unlikely to perceive whereas she is likely to perceive the more obvious changes in fuel, tyre and maintenance costs associated with her decision to become an active traveller.

Other parts of the Guidelines deal in detail with the resource correction. In the active travel context however, this level of precision might not be warranted because the impacts on the overall quantum of benefits would be relatively small. Instead it should be sufficient to rely on changes in average car and public transport costs as measures of resource correction. For users converting from public transport, some over counting of benefits could occur because fare savings are part of the active travel willingness to pay but the effect would probably be relatively small once the rule of the half is applied to the fare saving.

5.2 Steps applicable to all benefit categories

5.2.1 Identifying active travel segments

Approaches to estimating the benefits of active travel projects differ according to the type of active traveller expected to use a project. The first cause of variation is the rule of the half which is not applicable to all user segments. The segment cause of difference is ‘without project’ trip behaviour. The composition of benefits differs according to whether the project causes changes in trip characteristics. Benefit composition will be quite limited for ‘existing’ users whose trip characteristics do not change. For beneficiaries whose current mode is car/motorcycle travel, benefit composition will be more complex. Public transport users who convert to active travel fall in the middle of these two extremes.

Another reason to identify market segments is that not all segments will have the same trip frequency over the course of a year. For example, data described earlier (in section 2) suggests that work trips might account for only a minor proportion of walk-only and cycle-only trip making. This has potentially important implications for the estimation of project benefits.

5.2.2 Perceived versus unperceived costs

For all benefit categories, benefits per trip are estimated by multiplying the per km benefit in dollars by estimated trip length by number of trips per year to arrive at annual benefits. Benefits will need to be calculated separately for existing active travel trips and new active travel trips because the willingness to pay component of the latter is subject to the rule of the half.

The rule of the half only applies to those components of benefit that influence changes in travel behaviour – in other words to the components of private generalised cost. The rule of the half applies therefore to the willingness to pay component of health benefits and to the vehicle operating cost, travel time cost and parking cost components of private generalised cost. Table 5 shows the application of the rule of half to user types.

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Table 5 Application of the rule of half to benefit categories

User type

Existing Existing, AT more frequently (1)

New active travellers

Diverted from car or motorcycle

Diverted from PT

Applicable benefit categories

Health – willingness to pay

Nil Half Half Half Half

Health – health system costs

Nil Full Full Full Full

Vehicle operating costs

Nil Half Half Half Nil

Parking Nil Half Half Half Nil

Travel time Full Half Half Half Half

PT Fares Nil Half Half NA Half

Change in crash risk

Full Full Full Full Full

Noise reduction Nil Full Full Full Full

Air pollution reduction

Nil Full Full Full Full

Congestion reduction

Nil Full Full Full Full

(1) Includes existing active travellers who decide to walk or cycle more frequently due to provision of enhanced active travel infrastructure.

5.2.3 Identifying the relevant trip length

For existing active travellers

‘Existing’ active travellers are those whose trip pattern is not expected to change when a proposed project is implemented. For them, the length of the proposed project is relevant in benefit estimation. By definition, the project does not change their trip behaviour. Between the base case and project case all that will change is the length of active travel network being affected by the proposed project. Assuming no significant difference in track characteristics – such as surface condition, width and alignment –that would materially alter trip behaviour – benefits will typically be confined to a reduction in crash risk, because for example an on-road cycle path is separated from the traffic stream.

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Table 6 Identifying the relevant trip lengths for benefit estimation

User type

Existing Existing, AT more frequently(1)

New active travellers

Diverted from car or motorcycle

Diverted from PT

Km base for estimating benefits

Length of proposed project

Total AT trip length

Total AT trip length

Total AT trip length

Total AT trip length

(1) Includes existing active travellers who decide to walk or cycle more frequently due to provision of enhanced active travel infrastructure.

For new active travellers

For new active travellers, including those who convert from other modes, an active travel project has broader implications. Active travel benefits now accrue over the total trip length, not merely the portion that includes the proposed active travel initiative. It would be rare for a project such as dedicated pedestrian/cycle path to provide a complete self-contained link to all of the origins and destinations of all its users. Some users might need to utilise on-road paths or footpaths to access the new pedestrian/cycle path.

‘New’ active travellers are those walkers or cyclists who are expected to:

Make a walk or cycle trip because a proposed active travel initiative is implemented. This group could include people who decide to take up walking or cycling because of an improvement in active travel infrastructure (referred to as ‘generated users’); or who

Change their trip characteristics (route, origin, destination, mode or frequency) because a proposed active travel project is implemented. This group could include:

– Walkers or cyclists who change route to take advantage of improved active travel infrastructure

– Current car, motorcycle or public transport users who switch to active travel because of an active travel infrastructure improvement or

– Current walkers or cyclists who walk or cycle more frequently because of an improvement in active travel infrastructure.

5.2.4 Choosing appropriate annual expansion factors

For work, school and tertiary education trips use of annual expansion that reflect the standard work or education year would be appropriate – for example around 220 days for work trips. If an active travel facility features high proportions of recreational use, care is needed to ensure that trip making and therefore benefits are not overstated. Recreational trips are more likely on weekends and public holidays than on work days. For those trips an expansion factor of 104 to 114 (depending on the number of public holidays that fall on weekends) would be suitable.

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5.3 Health benefits

The 2007-2008 National Health Survey identified that physical inactivity is related to chronic health conditions including ischaemic heart disease, stroke, Type 2 diabetes, kidney disease, osteoarthritis, osteoporosis, colorectal cancer and depression (AIHW Cat No PHE 157, 2012).

Active travellers tend to be healthier than people who are relatively inactive or sedentary and suffer less from medical conditions that reduce their life expectancy. Healthy individuals place less demand on the health system for diagnosis, surgery and recovery.

Active travel, including walking and cycling, can contribute to minimising risks of cardiovascular disease, Type 2 diabetes, some cancers and osteoporosis. It can also assist with managing obesity, high blood pressure and high cholesterol. Mental health benefits have also been identified but not quantified. Physical activity can improve self-esteem and confidence, and reduce stress, anxiety, fatigue and depression (AIHW Cat. No. PHE 157 2012). Incorporating the health benefits of active travel into economic evaluations of transport projects requires a tool for valuing non-motorised transport. The following discussion will produce a monetary value for each of walking and cycling active travel modes, applicable to the Australian population.

There are then types of health-related benefit attributable to active travel:

Morbidity and mortality benefits because people who are active get sick less often and have a longer life expectancy than people who are inactive

Reduction in health system costs because active people are less likely to need medical and hospital care.

5.3.1 Morbidity and mortality

Morbidity and mortality benefits are relevant to those active travel trips that are generated by improvements in active travel infrastructure.

Willingness to pay benefits are typically based on the potential of active travel, as a form of physical activity to reduce the number of disability adjusted life years (or DALYs) lost as a consequence of inactivity. Reducing DALYs is analogous to increasing life expectancy. The value of additional reduced DALYs (or increased life expectancy) is based on a value of statistical life (VSL) derived using a willingness to pay approach. The benefit is expressed on a per km basis, derived from the number of km of walking or cycling needed to achieve a desirable level of physical activity. The more active a person is the less additional activity needed to achieve a desirable state of health and the lower the benefit from that additional activity. Walkers generally need more physical activity than cyclists because walking is less vigorous than cycling.

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5.3.2 Health and physical activity

Available data on the health characteristics of Australians derive from the 2003 Burden of Disease study (Begg et al 2007, AIHW Cat No PHE 82), the 2007-2008 National Health Survey (ABS Cat. No. 4364 2009) and the 2011-13 Australian Health Survey (ABS Cat. No. 4364.0.55.004 2013). The Burden of Disease study quantifies the extent to which healthy life is lost to disease manifested as prolonged illness, disability, and/or premature death. The Disability Adjusted Life Year, ‘DALY’, is the measure used to quantify the effects of individual diseases and injuries. One DALY is one year of healthy life lost due to disease or injury (Australia’s Health 2010 Cat. No. AUS 122 2010).

The 2007-2008 National Health Survey identified that physical inactivity is related to chronic health conditions including ischaemic heart disease, stroke, Type 2 diabetes, kidney disease, osteoarthritis, osteoporosis, colorectal cancer and depression (AIHW Cat. No. PHE 157 2012). With the exception of kidney disease and osteoporosis, these conditions were amongst the 20 leading causes of burden of disease in 2003 (AIHW 2007, p 39). The AIHW report ‘Australia’s Health 2010’ (Cat. No. AUS 122 2010) identifies these diseases as continuing to be amongst the leading causes of burden of disease in 2010. Of the total burden of disease, cancer was projected to account for 19% while the second leading cause, cardiovascular disease, was estimated to account for 16%. Type 2 diabetes was projected to become the leading cause of disease burden by 2023, partly attributable to the worsening problem of overweight and obesity. In 2010 diabetes accounted for almost 7% of the total disease burden (Type 2 diabetes was estimated to account for 94% of the diabetes burden). Arthritis and musculoskeletal conditions accounted for 4% of the national disease burden in 2010 (Cat. No. AUS 122 2010).

Using the 2003 burden of disease data Begg et al found that the proportion of health loss attributable to physical inactivity was: 6.6% for all conditions; 5.6% for cancers; and 23.7% for each of cardio vascular disease and diabetes mellitus (Begg et al 2008, p 38).

The National Physical Activity Guidelines for Australians for adults recommend at least 30 minutes of moderate-intensity physical activity on most, preferably all, days of the week. Examples of moderate-intensity activity are brisk walking, swimming, doubles tennis and medium-paced cycling. For activity to be sufficient for accruing health benefits criteria for both time and the number of sessions need to be met. Thus the definition for sufficient time and sessions is: ‘at least 150 minutes of moderate-intensity physical activity accrued over at least five sessions per week, with vigorous activity counted as double’. Sessions of a minimum of 10 minutes can also be included in the weekly count (AIHW Cat. No. AUS 122 2010, p 93).

The 2007-2008 National Health Survey identified that for Australian adults: 37% participated in sufficient time and sessions of physical activity to accrue health benefits; 55% were insufficiently active; 8% were inactive (AIHW Cat. No. AUS 122 2010, p 93). In comparison the 2011-2013 Australian Health Survey found that:

the proportion of sufficiently active adults increased to 43.5%

the proportion of inactive adults decreased to 20.5% and

there was a greater than four times increase to 36% in the proportion of insufficiently active adults (ABS, 43640DO004_20112012, Data cube Table 4, in 4364.0.55.004 - Australian Health Survey: Physical Activity, 2011-12).

Appendix A provides definitions for the levels of physical activity.

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In a review article Rissel et al (2012) found that between 8 and 33 minutes of additional physical activity was attributable to daily walking associated with public transport use in Australia. Rissel et al used statistical modelling to predict that the proportion of the adult population considered ‘sufficiently active’ would increase significantly if 20% of all ‘insufficiently active’ adults increased their walking by 16 minutes a day for five days a week (Rissel et al 2012). While road injury can be associated with cycling and walking, Ker et al (2011, p 16) have identified that the health and fitness benefits more than offset the net road trauma increase.

In 2007 Brisbane public transport users walked on average 2.3 kilometres for approximately 28 minutes, thereby meeting recommended physical activity requirements (Burke & Brown in Ker et al 2011, p 18).

Journeys of less than 5 kilometres are considered appropriate for active travel (WHO in Genter et al 2008, p 22). In New Zealand criteria for active travel distances are destinations within 7 kilometres for cycling and 2 kilometres for walking (Genter et al 2008, p 22). The intensity of 1 minute of walking is considered equivalent to 0.5 minutes of cycling (Genter et al 2008, p 38).

5.3.3 Valuing active travel

These guidelines adopt the methodology adopted by Genter et al (2008) in valuing the health benefits of active travel in New Zealand, to the Australian adult population, using local data where available, to determine a per-km value of the health benefits of active travel modes.

Since inactive adults have most to gain by participating in physical activity, full benefits are allocated to those who were previously inactive, with only marginal benefits allocated to existing active adults (Genter 2008, p 40).

Value of a Statistical Life (VSL) is a monetary value of a human life based on the willingness to pay concept. It is updated using the Consumer Price Index. The value of statistical life is an estimate of the economic value society places on reducing the average number of deaths by one. A related concept is the value of statistical life year (VSLY), which estimates the value society places on reducing the risk of premature death, expressed in terms of saving a statistical life year. The Australian estimate of the value of statistical life is $3.5 m and the value of statistical life year is $151 000 (OBPR, RSCH.040.001.0188 2008). Updating the 2007 VSL for CPI movements yields a 2013 VSL estimate of $4 084 027.

5.3.4 Benefits of reduced morbidity and mortality

Morbidity and mortality costs of inactivity are valued using DALYs associated with inactivity and undiscounted VSL (Genter 2008, p 47). The steps are:

Estimate DALYs for years of life lost to both morbidity and mortality. The Population Attributable Risk Fraction (PAF) for inactivity identified by Begg et al (2008, p 38) in The Burden of Disease and Injury in Australia 2003 study (Begg et al, 2007, AIHW Cat. No. PHE 82) is 6.6% of total DALYs.

Determine the annual ratio of DALY per inactive adult by dividing the DALYs due to inactivity by the estimated adult inactive population in 2010, derived from Australian Health Survey 2007-8 and 2011-12 results (ABS 2012, 43640DO001_20112012 Australian Health Survey: First Results, 2011–12 — Australia.)

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Multiply this ratio by the undiscounted 2013 value of DALY6 to produce the per capita annual benefit of physical activity, shown in Table 7.

Table 7 Per capita annual value (morbidity and mortality) using DALYs

Projected 2 849 000

Population 6.6%

DALYs 188 034

Adult active population 11 483 475

Ratio 0.02

Willingness To Pay DALY 2013 $90 555

Per capita annual value $1483

Source: Economic Associates analysis based on Genter 2008, p 48. See accompanying text.

5.3.5 Health system benefits

Health sector costs of inactivity are estimated by calculating the proportion of costs due to inactivity, and then dividing this value by the number of inactive adults, to determine the per capita health sector costs, as shown in Table 8.

Table 8 Per capita annual health sector costs attributable to inactivity

Total health sector costs 2010 (1) $130 266 000 000

6.6% due to inactivity $8 597 556 000

Inactive population 2010 11 483 475

Per capita health sector costs 2010 $749

Per capita health sector costs 2013 $796

1: See AIHW 2012, Health Expenditure Australia 2010-11, Health and Welfare Expenditure Series No. 47, Cat. No. HWE 56.

Productivity costs are excluded because Genter et al found inadequate evidence supporting the association between active transport and reduced sick days (Genter et al 2008, p 49). Therefore the total annual per capita value in 2010 of health benefits of active travel is $2131 comprising morbidity and mortality costs ($1382), and health sector costs ($749), attributable to inactivity.

6 The annual value of a DALY was calculated by subtracting the average age (37 years) from the average life

expectancy in 2010 (82.1 years) to get 45.1 years. The VSL was then divided by 45.1. (Life expectancy and average life data sourced from ABS 4102.0 - Australian Social Trends, April 2013, and http://www.aihw.gov.au/deaths/life-expectancy/, AIHW 2013, accessed 22/7/2014).

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5.3.6 Total health benefits

Genter et al (2008, p 50) cite research indicating that more health benefits accrue when additional activity is initially taken up, with benefits accruing at a lesser rate for those who are currently active. As mentioned in the ‘Health and physical activity’ discussion earlier, data on the extent of physical activity in the Australian adult (aged 18 years and older) population derive from the 2007-8 National Health Survey and the 2011-12 Australian Health Survey. Table 9 summarises activity data from these surveys. Appendix A provides definitions for the levels of physical activity.

Table 9 Physical activity levels in the Australian adult population

Physical activity level Prevalence 2007-2008 (1) Prevalence 2011-2012 (2)

Inactive 8% 20.5%

Insufficiently active 55% 36.0%

Sufficiently active 37% 43.5%

1: See AIHW Cat. No. AUS 122, 2010, p 93

2: ABS, 4364.0.55.004 - Australian Health Survey: Physical Activity, 2011-12, Download Data cube Table 4 Sufficient physical activity measure by selected population characteristics, Persons aged 18 years and over (estimate) (43640DO004_20112012 Australian Health Survey: Physical Activity, 2011-12-Australia ), 2013

The 2011-12 split of physical activity levels is considered more appropriate to the 2010 population, and therefore used for calculating per-km health benefits.

The three physical activity weightings used and the rationale adopted by Genter et al (2008, pp 50-51) are:

Weighting 1 - Inactive – Shifting the inactive group into some moderate physical activity has most benefits in terms of reduced morbidity and mortality. This group can receive full annual benefits by walking at 5 km per hour for 30minutes, 5 days per week. This is an annual walking distance of 625 km

Weighting 0.85 – Insufficiently active – The insufficiently active group can receive most of the health benefits of increased activity, even though they already engage in some moderate activity. An additional 20 minutes’ physical activity per day for 5 days per week requires an annual distance of 450 km

Weighting 0.15 – Sufficiently active – The sufficiently active group may receive ongoing health benefits and encouragement to maintain physical activity. An additional 14 minutes’ physical activity per day for 5 days per week requires an annual distance of 312 km.

5.3.7 Parameter values for walking and cycling benefits

Parameter values for walking and cycling benefits are shown in Table 10.

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Table 10 Per-km weighted health and health system benefits of walking (2013)

Walking annual health benefits

Benefit weight Weighted sum = annual benefits per person

$2279

1 0.85 0.15

$1314 Inactive Insufficiently Active Sufficiently Active

20.5% 36% 43.5%

$467 $698 $149

Km over which benefits received Weighted per km benefits

625 450 312 $2.77

$0.74 $1.55 $0.48

Based on Genter 2008

Since physical health benefits per minute of cycling are twice those of walking, only half the time is required to achieve benefits. Therefore cycling has half the benefit per km of walking. (Genter et al 2008 p 51).

Table 11 Per-km weighted health and health system benefits of cycling (2013)

Cycling annual health benefits

Benefit weight Weighted sum = annual benefits per person

$2279

1 0.85 0.15

$1314 Inactive Insufficiently Active Sufficiently Active

20.5% 36% 43.5%

$467 $698 $149

Km over which benefits received Weighted per km benefits

1250 900 624 $1.40

$0.38 $0.78 $0.24

Based on Genter 2008

Thus the 2013 monetary value of the health benefits of walking is $2.77 per km and that of cycling is $1.40 per km for Australian adults aged 18 years and older.

Adjusting for local activity levels

The unit benefit values in Table 10 and Table 11 could be amended if information was available about activity levels in an active travel catchment. The activity weights are contained in the fourth row of Table 10 and Table 11 (for example 20.5% of the Australian population is estimated to be inactive). Once new activity weightings have been inserted the unit benefit values in the tables can be recalculated.

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5.3.8 Indexing health benefit parameter values

Indexing of benefits is appropriate in cost benefit analysis because costs used by the cost benefit analyst will have been indexed by the cost engineer or quantity surveyor. Because project costs for budgeting and contract purposes are outturn or values of the day costs, the base year costs will reflect prices in that or in some other recent numeraire year7. For consistency, benefit parameter values established perhaps some years earlier will need to be indexed to the same base year.

The two components of health benefits should be treated differently.

Indexing morbidity/mortality benefits

Morbidity/mortality benefits are based on the value of statistical life (VSL) and should in theory be indexed by reference to the ABS Average Weekly Earnings series for Australia, with adjustment for income elasticity – that is for the tendency for VSL to increase with increases in income, and possibly to changes in wealth as well. The Office of Best Practice Regulation (OBPR 2008) recommends that VSL be indexed to the Consumer Price Index (CPI). Implicit in the OBPR guidance is an income elasticity of one and combined with the link to the CPI he long term value of VSL would be maintained over the long term. Abelson (2008) in a paper prepared for the OBPR notes studies recommending an income elasticity closer to 0.5, but notes also that some studies link VSL to wealth – which will be affected my movements in asset prices – as well as income. Hammitt and Robinson (2011, p 6) also note the prevalence of income elasticity estimates around 0.4 to 0.6. Their research suggests that this value might not be consistent a wide income range as might be relevant when projecting incomes across the thirty-year project life of an infrastructure project.

In light of the controversies surrounding the valuation base for VSL and for changes in VSL over time, and the difficulties associated with income and wealth forecasting, the OBPR guidance that VLS be indexed to CPI with an (implicit) income elasticity of one is a conservative middle position. Adoption of that position would also have the advantage of consistency with Commonwealth regulatory assessments, and in particular those that relate to health and safety.

Indexing health system benefits

The Australian Institute of Health and Welfare (AIHW) produces an annual national composite health cost index incorporating a range of health cost elements or areas of expenditure that include for example public hospitals, private hospitals, medical services, dental services, pharmaceuticals and capital expenditure. Sixteen expenditure areas are included in the index. According to AIHW (2013, p 108):

‘The national THPI [total health price index] provides the most useful available measure of overall health inflation in Australia. As such, it has been integrated into the indexation formula for payments in support of the National Healthcare Agreement under the Intergovernmental Agreement on Federal Financial Relations.’

7 For example, a project costed in 2016 is likely to be costed from a base of 2016 input prices. Benefits estimated

in 2010 values would need to be indexed to 2016 values to ensure consistency between cost and benefit estimates.

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The TPHI is shown in Table 12.

Table 12 Total health price index, Australia

Year Index

2001-02 76.1

2002-03 78.4

2003-04 81.1

2004-05 84.0

2005-06 87.5

2007-08 90.4

2008-09 94.9

2009-10 97.3

2010-11 98.3

2011-12 100.0

Source: AIHW (2013) p 109

5.3.9 Updating health benefit parameter values

Morbidity/mortality benefits

Morbidity/mortality costs estimated in these Guidelines are a product of research into links between inactivity and disease, the effects of inactivity on life expectancy and the quality of life, the potential for physical activity to reduce disease risk and the value of statistical life. Some of the supporting research, for example, the 2003 burden of disease and injury study (Begg et al 2007) and estimates of the value of life is fundamental and likely to require considerable effort.

Because health benefits are central to active travel policy and to health policy generally, updating should be a joint venture between BITRE, Austroads and health agencies such as AIHW. Commonwealth and state regulatory agencies also have an interest because of the importance of health benefits in the broad suite of health and safety regulation including occupational health and safety, product safety, building safety and the like. With the extent of research involved, updating would be impracticable in anything less than a five or even a ten-year interval.

Health system benefits

Health system benefits are based on the proportion of health costs of attributable to inactivity. Updating of that proportion would be a role for the related task of updating morbidity/morbidity costs. Total health care costs in Australia are regularly updated and reported by AIHW.

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5.3.10 Application issues

The estimation of health benefits for individual active travel initiatives presents a range of challenges.

Variations in underlying physical activity levels

Underlying levels of physical activity may well vary between catchments and travel is only one form of physical activity available to people who want to be active. Others include gym or fitness centre work, team sport, swimming and the like. At the level of individual projects, information about the existing activity levels of the catchment is very unlikely to be available.

The implications of different levels of activity for the benefits of active travel infrastructure are potentially quite significant as Table 14 and Table 15 illustrate, with benefits of better infrastructure for active people being only around a quarter of those for people who are sedentary or insufficiently active. Where data about underlying activity levels is unavailable, the per km benefits recommended in Table 14 and Table 15 are weighted for the average distribution of activity levels in the Australian community. The data in those tables can also be used at a disaggregate level in the event that project-specific or catchment-specific information about underlying activity levels was available. Applying an upper limit to the amount of activity that generates benefits for inclusion in cost benefit analyses will be quite difficult for the reasons outlined below. Sensitivity testing is probably the only means to address the issue. For example if the trips generated by a project are estimated to amount to say 1000 km per walker per year and 2000 km per year for each cyclist, a sensitivity test might be carried out in which those benefits only accumulate over 625 km/year for walkers and 1250 km/year for cyclists (as per the limits in Table 14 and Table 15).

How important is trip frequency?

For most benefit categories, the dollar value of benefits is directly related to trip length and trip frequency.

However the picture is less straightforward for health benefits because for activity to be beneficial it must be of sufficient frequency (trips per week) and sufficient length (a proxy for session duration).

In the methodology used to estimate health benefits just presented, there are limits to the amount of activity that is necessary for good health, meaning by implication that further activity will not accrue health benefits. Those limits are higher for inactive people than for those who are active – in other words presently inactive people need to do more additional exercise than is needed by people who are active. Meaningful application of those limits in cost benefit analyses would necessitate quite detailed knowledge of the activity profiles of the market likely to use a proposed infrastructure improvement. Others who use the infrastructure once or twice a week may have no other physical activity sessions of sufficient duration to be effective for health. Some active travellers might only use the infrastructure once or twice or week as part of a wider physical activity regime. For others active travel might meet all their physical activity needs

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The active traveller and trip data that is needed to ensure accurate estimation of health benefits in these circumstances is unlikely to be available. As a partial alternative, sensitivity testing of cost benefit analysis results for the presence of recreational user health benefits would point to those projects for which there was a relatively high risk of benefit overstatement. Program planners could use that information to direct investment towards projects that supported high frequency active travel or collect information about active travel patterns that would allow more effective options development.

Will projects generate long enough trips?

There is no way for project planners and evaluators to determine whether their proposed active travel project will induce levels of activity sufficient to generate improvements in health. This problem arises for a number of reasons. Firstly, the health benefits of increased inactivity are not linear and continuous. A daily five-minute increase in physical activity will not generate one-sixth of the benefit of a 30 minute increase in activity. Secondly project-specific or catchment-specific information about underlying activity levels is unlikely to be available. Project planners and evaluators cannot know then whether a proposed active travel project will generate the increases in activity from which active travellers can benefit.

There is some limited evidence that those new active travel trips generated by better active travel infrastructure will be long enough to produce health improvements. Garrard (2009, p 7) reports Victorian data from 2007 that adults walking for transport8 walked 60 to 70 minutes per week for purposes other than recreation – that is up to 14 minutes per day excluding recreation. Garrard (2009, p 6) also quotes 2006 Census data for Victoria that found that cycle trips to and from work on census day averaged 6.1 km total (about 20 minutes total). For walk to work trips the equivalent results were 2.2 km and 27 minutes. Ker et al (2011, p 52) quoted results from a Bus Association of Victoria Survey that public transport users spend an average of 41 minutes per day walking and cycling (including recreational walking and cycling) which is five times the physical activity of commuters who use motorised private transport.

What is the retention rate for new active travellers?

How confident can we be that forecast levels of new active travel generated by improved infrastructure will be retained? A recent Paper (Goodman et al 2013, p 1) noted the lack of research into this question. However their before and after study of three new active travel infrastructure projects in the UK noted very high retention levels two years after project opening. They did note however that the new projects ‘may have primarily attracted existing walkers and cyclists…’ A similar outcome is evident in the results of intercept surveys in Brisbane reported in SKM PWC 2011 (Table 13).

8 As distinct from walking for recreation.

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Table 13 Trip diversion rates from Brisbane intercept surveys

Trips from Diverting to

Inner city Other areas Inner city Other areas

Car 10% 15% 5% 10%

Public transport 20% 0% 15% 50

Reassign 65% 55% 70% 50%

Induced 5% 30% 10% 40%

Source: SKM PWC (2011) p 33

Until better data becomes available sensitivity testing should be carried out to simulate the effects of lower than expected trip growth outcomes; a ‘no growth’ assumption would be prudent particularly if there is little usage history in the relevant project catchment.

5.3.11 Health benefits summary

Recommended parameter values for estimation of health benefits are shown in Table 14 and Table 15 for the two components – morbidity/mortality benefits and health system benefits. Cyclists are estimated to require twice the active km of walkers because cyclists are assumed to travel at four times the speed of walkers9 and cycling is assumed to have twice the physical intensity of walking10.

Table 14 Mortality and morbidity benefits of active travel per km according to physical activity status 2013

Mortality/morbidity benefit per km/activity level

Inactive Insufficiently active

Sufficiently active

Weighted per km benefit

Walking

Benefits of additional activity per person $1483 $1261 $222

Km over which activity benefits are received 625 450 312

Proportion of population 20.5% 36% 43.5%

Willingness to pay benefit per km $0.49 $1.01 $0.31 $1.81

Cycling

Benefits of additional activity per person $1483 $1261 $222

Km over which activity benefits are received 1250 900 624

Proportion of population 20.5% 36% 43.5%

Willingness to pay benefit per km $0.24 $0.50 $0.15 $0.89

Source: Based on Genter 2008

9 Meaning that cyclists would have to travel four times the distance to get the same activity benefit as walkers. 10 Meaning that cyclists would only need to cycle half the distance to get the same activity benefit as walkers.

Combining this intensity effect with the speed effect in the previous footnotes leads to the result that cyclists need to cycle twice the km in order to get the same activity benefit as walkers.

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Table 15 Health system benefits of active travel per km according to physical activity status 2013

Health benefit per km/activity level

Inactive Insufficiently active

Sufficiently active

Weighted per km benefit

Walking

Benefits of additional activity per person $796 $677 $119

Km over which activity benefits are received 625 450 312

Proportion of population 20.5% 36% 43.5%

Willingness to pay benefit per km $0.26 $0.54 $0.17 $0.97

Cycling

Benefits of additional activity per person $796 $677 $119

Km over which activity benefits are received 1250 900 624

Proportion of population 20.5% 36% 43.5%

Willingness to pay benefit per km $0.13 $0.27 $0.08 $0.48

Source: Based on Genter 2008

5.3.12 Calculating health benefits

Health benefits need to be calculated in two parts because the willingness to pay component for new active travellers is subject to the rule of the half.

Each component of health benefit per km is multiplied by trip km to arrive at benefits per trip.

For existing active travellers

Health benefits are not estimated for existing active travel travellers who by definition are already accruing the health benefits of active travel. New or improved active travel infrastructure does not generate health benefits but could well generate other benefits, in particular crash benefits.

For new active travellers – conversions from other modes

Health benefits arise for this group because of their additional active travel relative to their existing trip. Where suitable trip data is available (zonal origin, zonal destination, route) active travel benefits would be calculated for the project case trip length, less any walk or cycle trip length in the base case trip. Assuming that information is available the benefit estimation steps are:

Step 1: Estimate the average length of new (converting) trips in km.

Step 2: From the average trip length in Step 1, subtract the average active travel length for the base case and multiply the resulting value by the average number of daily trips per converting active traveller.

Step 3: Multiply the net active travel trip length from Step 2 by the weighted average health benefit in Table 14 and then multiply by 0.5 (that is, apply the rule of half).

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Step 4: Multiply the net active travel trip length from Step 2 by the weighted average health system benefit in Table 15.

Step 5: Sum the benefits from Steps 3 and 4 to arrive at daily benefits. Utilise guidance from other parts of NGTSM to estimate annual health benefits in the base year and subsequent years of the analysis period.

For new active travellers – those new to walking and cycling

Some people might become active travellers because a new or improved facility removes a perceived barrier or sparks their interest. For whatever reason they become active travellers, their health benefits are estimated as follows:

Step 1: Estimate the average length in km of new active travel trips.

Step 2: Estimate the average number of daily active travel trips to be made by new users.

Step 3: Multiply the active travel trip length from Step 2 by the weighted average morbidity/mortality benefit in Table 14 and by 0.5.

Step 4: Multiply the active travel trip length from Step 2 by the weighted average health system benefit in Table 15.

Step 5: Sum the benefits from Steps 3 and 4 to arrive at daily benefits in the base year. Utilise guidance from other parts of NGTSM to project benefits over subsequent years of the analysis period.

These steps are equally applicable to existing active travellers who are anticipated to increase their active travel as a consequence of a proposed project.

5.4 Congestion reduction benefits

An active travel project that has the effect of causing private motor vehicle users to walk or cycle rather than drive could reduce congestion depending on the time their trip is made. Trips made during peak periods are much more likely to reduce congestion than say recreational trips made on weekends.

The extent of congestion reduction relates to the length and timing of the replaced trip. Hence for someone who previously drove 5 km to work Mondays to Fridays leaving home at 7 am and now uses a new cycleway to ride 7 km to work leaving home at 6:30 am, the relevant trip characteristics are those of the drive trip, that is, a 5 km drive trip commencing at 7 am.

The estimation of these benefits is covered in other parts of the NGTSM.

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5.5 Crash benefits

Section 2.2.4 earlier noted the high crash risk faced by active travellers relative to the risk for car occupants11. It follows then car occupants who convert to active travel could experience a negative crash benefit that partly offsets other positive benefits of active travel. Interventions such as off road pedestrian/cycle paths that attract new active travellers will attenuate the additional risk for new cyclists and reduce the risk for existing active travellers.

Active travel crash risk is not as well understood as motor vehicle crash risk. Related to that, information about the effectiveness of measures to reduce risk – such as provision of on-road and off road paths is relatively sparse. Finally some commentators maintain that increases in cycling activity actually reduce crash risk – the so called ‘safety in numbers’ theory (see section 5.5.4).

Crash benefits are made up of the reduction in expected crash costs attributable to an active travel infrastructure improvement. They comprise two elements:

Current active travellers will probably experience a crash benefit to the extent that active travel infrastructure aims to separate motorised and non-motorised traffic streams including improving safety at intersections and crossings

Active travellers who walk or cycle more frequently and new active travellers who divert from other modes are likely to experience an elevation in crash risk because as noted in section 0, walking and cycling have a much higher crash risk than public transport or motorised private transport. Improved infrastructure might reduce that expected crash cost, but trip conversion will still produce a negative crash benefit that partly offsets other active travel benefits.

While the crash risk of active travel relative to other modes is well known, there is less certainty about the contribution that specific remediation measures can make to reducing crash risk. In addition because active travel in km travelled terms is less than one-three hundredth of the extent of motorised private transport in Australia, the crash record at a particular site or a particular section of road might be the outcome of chance only12, so that site-or section specific risk reductions attributable to infrastructure will be difficult to estimate. Cost benefit analysts should endeavour to access advice from appropriately qualified safety specialists but the data that is available suggests that in most cases a fairly coarse approach to estimating crash reduction benefits will be all that is possible.

Because the crash record is likely to be patchy on a site specific basis, an exposure based approach is proposed here in which benefits are calculated according reductions or increases per km of travel. This approach will be more satisfactory for projects made up of several elements (such as pedestrian/cycle path through a park with road crossings at either end but will be less satisfactory when applied to specific items of infrastructure, such as pedestrian/cycle bridge over a busy multilane urban road. Accident prediction models for different road elements such as midblocks, roundabouts and T intersections have been developed in New Zealand (Turner et al 2006) but their application may be beyond the time and resource budgets for all but the largest appraisals.

11 Crash rates for motorcyclists are higher again than those for bicyclists and pedestrians. See Table 16 below. 12 A site, say a pedestrian cycle road crossing with low active traffic volumes might have no crash history yet be

inherently risky.

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5.5.1 Active travel crash risk

Relative fatal and serious injury rates for private motor vehicle users and active travellers are shown in Table 16 and Table 17. Active travel risk is up to seven times riskier than private motor vehicle travel. Pedestrians are at higher risk than cyclists. For cyclists, most fatal crashes involve a collision with a motor vehicle.

The data means for example that a car driver who decides to take some trips by bicycle more than doubles their fatal crash risk from 0.048 per 10 million km travelled to 0.103 per 10 million km travelled. A pedestrian making the same trip choices would increase their safety risk more by more than ten times from 0.048 per 10 million km travelled to 0.62 per 10 million km travelled.

Table 16 Fatality rates for motorists and active travellers, Australia (2002 to 2006)

User description Estimated annual travel (10 million km travelled) Fatalities annual average

Fatality rate per 10 million km travelled

Rail passenger (a) - - 0.0816

Bus passenger (a) - - 0.0816

Car driver 11 866 572 0.0480

Car passenger 5611 247 0.0440

Total car 17 477 819 0.0470

Motorcyclist 96 134 1.3960

Total car and motorcycle 17 573 953 0.0540

Bicyclist 124 24 0.2000

Pedestrian 271 168 0.6200

Total active travel 505 192 0.3800

Note: Excludes New South Wales and Queensland due to inconsistencies in data categories. (a) Rail and bus passenger risk has been estimated separately by reference to BTRE (2003) which estimated fatality risk for bus and rail passengers as being 17% of the risk for car occupants.

Source: Estimated from Austroads (2010) p 8 et seq, other than for (a) and (b)

Table 17 Serious injury rates for motorists and active travellers Australia (2002 to 2006)

User description Estimated annual travel (10 million km travelled)

Serious injuries annual average

Serious injury rate per 10 million km travelled

Car driver (a) 7419 6264 0.844

Car passenger (a) 3471 2057 0.593

Total car 10 890 8321 0.764

Motorcyclist 61 1171 19.197

Total car and motorcycle 10 951 9492 0.867

Bicyclist 88 440 5.000

Pedestrian 152 926 6.092

Total active travel 240 1366 5.692

Note: Excludes New South Wales and Queensland due to inconsistencies in data categories. (a) See note to Table 16.

Source: Estimated from Austroads (2010) p 8 et seq

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Table 18 Cyclists killed in road crashes, Australia, 1997 to 2004

Event Counterpart % of cyclist deaths

Collision with Pedestrian 1

Pedal cycle or other motor vehicle 0

Car, pick-up truck, can or other motor vehicle 64

Heavy transport vehicle 22

Railway train or railway vehicle 1

Fixed or stationary object 4

Not a collision 5

Unknown 3

Total 100

Source: ATSB (2006) p 4

5.5.2 Effectiveness of interventions

Empirical evidence about the effectiveness of infrastructure in reducing active travel crash risk is limited but what evidence is available suggests crash risk reductions in the order of 30 to 40% from typical interventions such as kerb lanes, off road active travel lanes and signalisation treatments.

For existing active travellers measures such as these could reduce the crash risks associated with their existing active travel. For new users or users converting to other modes, these measures constrain the increase in risk as they shift from say car or public transport to active travel.

Table 19 Effectiveness of active travel safety interventions - cycling

Intervention

Reduction in Bicycle crash

risk

Reduction in overall crash

risk (all vehicles) Source

Cycle lanes (lane between kerb and parked cars)

10% cited in Schramm and Rakotonirainy (2008); Europe

Cycle lanes (lane between kerb and parked cars)

28% Lusk et al (2013) Montreal

Cycle lanes (lane between kerb and parked cars)

30%-62% Lusk et al (2013) New York City

Mid-block cycle lanes 10% 30% Elvik and Vaa (2004) cited in Turner et al (2011)

Advanced limit lines (storage boxes)

27% 40% Elvik and Vaa (2004) cited in Turner et al (2011)

Adding cycle lanes through an intersection

12% (14%) Elvik and Vaa (2004) cited in Turner et al (2011)

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Intervention

Reduction in Bicycle crash

risk

Reduction in overall crash

risk (all vehicles) Source

Traffic calming 36% 40% Davies et al (1997) cited in Turner et al (2011)

Cycle lanes marked on road, mid-blocks

29% UK, Coates (1999) cited in Turner et al (2009)

Cycle lanes marked on road, intersections

35% UK, Coates (1999) cited in Turner et al (2009)

On roadway cycle lanes 57% York UK: Transport for London (2004) cited in Turner et al (2009)

Shared use footpath 28% York UK: Transport for London (2004) cited in Turner et al (2009)

Signalled intersections 83% York UK: Transport for London (2004) cited in Turner et al (2009)

Cycle track + ^ 100% York UK: Transport for London (2004) cited in Turner et al (2009)

Cycle lane 70% York UK: Transport for London (2004) cited in Turner et al (2009)

Advance stop line at signals** ^

100% York UK: Transport for London (2004) cited in Turner et al (2009)

( ) signifies an increase in crash risk (+) the definition of cycle track is unclear. See Turner et al (2009) **Advance line at signals includes storage box. ^ Turner et al (2009) that reductions of this magnitude are unrealistic.

Table 20 Effectiveness of signalisation countermeasures – walking (US)

Countermeasure (s) % Crash Reduction Factor

Crash severity Left-turn crashes Pedestrian

Add exclusive pedestrian phasing All 34

Improve signal timing [to intervals specified by the ITE Determining Vehicle Change Intervals: A Proposed Recommended Practice (1985)]

Fatal/Injury 37

Replace existing WALK / DON'T WALK signals with pedestrian countdown signal heads

All 25

Modify signal phasing (implement a leading pedestrian interval)

All 5

Remove unwarranted signals (one-way street) All 17

Convert permissive or permissive/protected to protected only left-turn phasing

All 99

Convert permissive to permissive/protected left-turn phasing

All 16

Note: US terminology, dimensions and spelling in original

Source: FHWA (2008)

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Table 21 Effectiveness of geometric countermeasures – walking (US)

Countermeasure (s) % Crash Reduction Factor

Crash severity All crashes Pedestrian

Convert unsignalized intersection to roundabout Fatal/Injury 27 (12)

Install pedestrian overpass/underpass Fatal/Injury 90

All 86

Install pedestrian overpass/underpass (unsignalized intersection)

All 13

Install raised median All 25

Install raised median (marked crosswalk) at unsignalized intersection

All 46

Install raised median (unmarked crosswalk) at unsignalized intersection

All 39

Install raised pedestrian crossing All 30 (67)

Fatal/Injury 36 (54)

Install refuge islands All 56

Install sidewalk (to avoid walking along roadway) 88*

Provide paved shoulder (of at least 4 feet) 71*

Narrow roadway cross section from four lanes to three lanes (two through lanes with centre turn lane)

All 29

*Only applies to ‘walking along the roadway’ type crashes

Note: US terminology, dimensions and spelling in original..( ) signifies standard error. Estimates in bold signify a rigorous study methodology and a small standard error in the value of the crash reduction factor (CRF)

Source: FHWA (2008)

Table 22 Effectiveness of operational countermeasures – walking (US)

Countermeasure (s) % Crash Reduction Factor

Crash severity All crashes Pedestrian

Add intersection lighting Injury 27*

All 21*

Add segment lighting Injury 23*

All 20*

Improve pavement friction (skid treatment with overlay) Fatal/Injury 3

Increase enforcement ** All 23

Prohibit right-turn-on-red All 3

Prohibit left-turns All 10

Restrict parking near intersections (to off-street) All 30

*Applies to night time crashes only. **Applies to crash reductions on corridors where sustained enforcement is used related to motorist yielding in marked crosswalks combined with a public education program.

Note: US terminology, dimensions and spelling in original. Turn directions should be reversed for Australian application.

Source: FHWA (2008)

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5.5.3 Estimating unit crash costs

Crash costs estimated on a distance basis are shown in Table 23. The crash cost estimates are not expressed on a net active travel distance basis, so analysts will need to estimate base case and project case trip length and trip generalised costs separately. The active travel crash cost estimates are based on crash exposure risk calculated separately for driver and passengers, and hence should not need to be adjusted for vehicle occupancy. Two sets of crash costs are shown in Table 23: the hybrid human capital approach that has been used in Australia for some years and which drives from research carried out by the Bureau of Infrastructure, Transport and Regional Economics (BITRE); and the more recent inclusive willingness to pay approach. The Guidelines favour the inclusive willingness to pay approach but in the active travel context the hybrid human capital estimates might be more appropriate13.

Table 23 Crash costs by mode per vehicle km (2013)

Mode Crash cost per veh km

Hybrid human capital approach Inclusive willingness to pay approach

Car/ motorcycle $0.11 0.21

Bicyclist $0.49 0.95

Pedestrian $0.67 1.44

Total active travel $0.59 1.20

Train $0.02 0.04

Bus $0.02 0.04

Source: Estimated from Austroads (2012), Austroads (2010), BTRE (2006), BTRE (2003)

Research results in section 5.5.2 suggest that interventions that separate walkers and cyclists from the traffic stream or which reduce conflicts at intersections can reduce active travel crash risk by around 40%. Until further detailed Australian research is carried out, this value seems appropriate. For corridor projects – which combine a number of infrastructure elements – a large reduction might be appropriate but there is insufficient research to provide guidance on this point.

13 The value of statistical life incorporated in the willingness to pay estimates in Table 23 derive from recent

research into the value road users place on avoiding premature death in a range of trip choice situations (see Austroads (2015) and Volume 2 of NGTSM). Those values might not be readily transferrable to active travellers. The value of statistical life that is included in the health benefit estimates has a broader base, representing the willingness of individuals to pay to avoid a small increase in the risk of premature death.

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5.5.4 Estimating crash reduction benefits

Crash benefits are estimated as follows:

For existing active travellers

Apply these steps for walkers and cyclists separately.

Step 1: Multiply the number of daily trips by estimated trip length.

Step 2: Convert daily trip km estimates to annual estimates. For transport trips, use expansion factors recommended in other parts of NGTSM. For recreation trips an expansion factor of 104 to 114 (weekends plus public holidays) would be suitable.

Step 3: Calculate the base case crash cost by multiplying the crash rates per 10 million km of travel by the crash rates for walkers and cyclists in (fatalities) and (serious injuries) by the crash costs in Table 23. Sum these two estimates (fatal and serious injury crashes).

Step 4: Multiply the annual base cost estimate from Step 3 by 0.6 to arrive at project case crash costs.

Step 5: Subtract the Step 4 cost estimate from the Step 3 cost estimate to arrive at the base year crash reduction benefit.

Step 6: Utilise guidance from other parts of NGTSM to project annual crash benefits in subsequent years of the analysis period.

For new or converting active travellers

Apply these steps for walkers and cyclists separately.

Step 1: Multiply the number of daily trips by estimated trip length base case and project case trip lengths. In some instances the base and project case trip lengths will be similar but in others not.

Step 2: Convert daily trip km estimates to annual estimates for the base and project cases. For transport trips, use expansion factors recommended in other parts of NGTSM. For recreation trips an expansion factor of 104 to 114 (weekends plus public holidays) would be suitable.

Step 3: Calculate the base case and project case crash risk by multiplying the crash rates per 10 million km of travel by the crash rates for the pre-active travel mode in (fatalities) and (serious injuries) to estimate the total number of base case project case crashes. Sum these two estimates (fatal and serious injury crashes).

Step 4: Multiply the annual base cost estimate from Step 3 by 0.6 to arrive at project case crash costs.

Step 5: Subtract the Step 4 cost estimate from the Step 3 cost estimate to arrive at base year crash reduction benefit.

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Step 6: Subtract the project case annual crash cost from the base case annual crash cost to obtain the annual crash benefit. In all likelihood the result will be a negative benefit.

Step 7: Utilise guidance from other parts of NGTSM to project annual crash benefits in subsequent years of the analysis period.

5.5.5 Safety in numbers

The concept of safety in numbers emerges from a seminal paper by Jacobsen (2003)14 which shows that

‘for pedestrians and cyclists, the fatality rate is inversely related to the amount of travel by that mode. The data is demonstrated with fatalities associated with walking and cycling data in Californian cities, injuries associated with cycling in Denmark and walking and cycling fatalities across European countries. All the data sets show diminishing rates of fatal and serious injury with increasing levels of walking or cycling.’ (Austroads 2010, p 31)

Austroads’ review of the literature concludes that empirically demonstrated ‘safety in numbers’ relationships may provide evidence of correlation rather than causation, in that researchers do not control for improvements in infrastructure and other initiatives (safety awareness campaigns) that might encourage cycling at the same time as making cycling safer. Austroads comments that while safety in numbers might have a behavioural basis in that more cyclists on the road encourages motorists to look out for them, the research does not definitively prove causation.

Garrard (undated) reviewed the evidence and concluded that:

There is a safety in numbers association in some but not all situations

The safety in numbers relationship is strongest and most consistent in European countries with high rates of cycling

No studies have controlled for cycling infrastructure of driver/cyclist safety measures

There is no evidence that increased cycling precedes injury rate reductions

Limited Australian evidence, from Melbourne, is mixed.

Until the literature is more certain about the existence of a safety in numbers phenomenon, crash benefit estimates should not be adjusted to reflect a safety in numbers effect.

14 Jacobsen PL (2003) ‘Safety in numbers: more walkers and bicyclists, safer walking and bicycling’ in Injury

Prevention, Vol 9, No 5, pp 205-9

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5.6 Savings in vehicle operating costs

Car and motorcycle users who decide to make their trip on foot or on a bicycle or who make active travel a bigger part of their trip making will incur savings in their motor-vehicle-related costs. Austroads provides a simple model for estimating those costs on a km basis. They include fuel, repairs and maintenance, tyres and depreciation but exclude parking and personal travel time costs.

This component of benefit is part of the consumer surplus accruing to users who switch to active and is therefore subject to active travel. However, the level of detail in the estimation process in section 1 is too coarse to allow perceived and unperceived costs to be identified separately. The resulting loss of precision is unlikely to be critical.

Savings in reduced vehicle operating costs are estimated by reference to the motor vehicle trip that is being replaced by active travel. Therefore, if a 5 km car or motorcycle trip is being replaced by a 7 km active travel trip, the base for estimation of benefits is 5 km.

The estimation of these benefits is covered in other parts of the NGTSM.

5.7 Savings in parking costs

Users converting to active travel or active travellers making additional active travel trips might save in parking costs depending on when and where trip is made. Work and some education trips to inner city areas are the trips for which parking benefits are most likely.

The estimation of these benefits is covered in other parts of the NGTSM.

5.8 Savings in public transport operating costs

Trip conversions from public transport to active travel whether by new active travel users or current active travellers who elect to walk or cycle more frequently in response to an infrastructure improvement have the potential to generate savings in the costs of operating public transport services.

Savings are unlikely to arise in the weekday non-peak periods or on weekends because at this time clock face scheduling will tend to determine public transport operating costs rather than demand. During the weekday peaks on the other hand, there is some potential for savings because service scheduling in those times will be demand driven.

Two recent Australian studies for Queensland and Sydney– by SKM PWC (2011) and PWC SKM (undated) - excluded this category of saving because of estimation difficulties engendered by independence between demand and service scheduling. Aecom (2010) on the other hand in a Sydney network study estimated savings in bus and train operating costs resulting from diversions to active travel.

If public transport cost savings are to be included they should be confined to morning and evening peak trip conversions to active travel. In addition, the savings attributable to walk trips should be adjusted downwards to reflect shorter walk trip distances.

These benefits are covered in other parts of the NGTSM.

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5.9 Savings in road infrastructure costs

Diversion of motorised transport trips to active travel could allow the deferral of road projects aimed at reducing congestion by increasing capacity. Cost savings from deferral would partly offset the costs of any active travel projects that encouraged trip diversion. This relationship can be looked at either from the perspective of deferring construction costs or reducing congestion because a reduction in congestion allows deferral of measures to remediate it.

The methodology proposed earlier for estimating congestion benefits (section 5.4) obviates the need to estimate savings from deferred construction costs. On the other and if savings in construction costs have been estimated – perhaps through an integrated modelling and network planning exercise, congestion reduction benefits should not be included in the cost benefit analysis.

The estimation of these benefits is covered in other parts of the NGTSM.

5.10 Environmental benefits

Environmental benefits arise when car trips convert to walking or cycling. They might also arise when rips convert from public transport nut the likelihood is much less because of the indivisibility in public transport provision associated with clock face timetabling and the complexities of service scheduling in networks. Environmental benefits are only estimated for trips converting to active travel. The basis for calculation will be the in vehicle km of the motorised transport trip that is being replaced.

The method for estimation is the same as for a reduction in motor vehicle km associated with say a town bypass. The estimation of these benefits is covered in other parts of the NGTSM.

5.11 Travel time benefits

5.11.1 General

Typically travel time is a disincentive to travel, so that initiatives which save time generate benefits. For active travel however, time might be a positive feature of travel: for non-transport trips, time might be associated with enjoyment or with the positive outcomes of physical activity. In those circumstances, an infrastructure improvement – such as a pedestrian/cycle overpass that allowed walkers and cyclists to travel faster – might not result in a trip time saving. Active travellers might simply do more exercise within the time available.

Hence for non-transport active travellers – ie those who are travelling for exercise or recreation- travel time savings are unlikely to generate benefits.

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Time savings might be relevant however for those transport trips – for work or education for example - that convert from private or public transport to active travel in response to an infrastructure improvement. An infrastructure improvement – such as a high speed cycleway might reduce trip times so much that some transport trips become feasible by bike15. In this situation the time saving could take one or both of the following forms: a saving in trip time; and/or a saving in time spent exercising at home or at the gym. This time saving is part of the consumers’ surplus motivating the mode shift. Unless specific empirical is availability about the substitutability of cycling for other forms of exercise it would be prudent to confine benefit estimation to travel related savings.

The method for estimating travel time benefits including the application of the rule of the half is outlined in other parts of NGTSM. Unfortunately there appears to be no research available about the weightings to be assigned to the travel time cost components of the active travel trip. Table 24 shows proposed weightings.

Table 24 Suggested travel time weightings

Travel time component Motorised travel Active travel

In vehicle (including on bike) 1 1

Walk at trip ends 1 1

Wait time 3 -

End of trip time - 3

5.11.2 Weighting for cycling infrastructure quality

Australian and international research shows, as would be expected that cyclists place a higher value on quiet street environments and off-road paths than they do on busy roads without any cycling infrastructure. Put another way, cyclists experience less disutility in using quiet streets or off-road paths than they do in using busy roads that lack cycling infrastructure.

The series of weights for Sydney shown in Table 25 imply that:

a cyclist would ride approximately 3 km on an off-road path to avoid riding 1 km on a busy road with no cycling infrastructure

a cyclist would ride 1.26 km on an off-road path to avoid riding 1 km on-road in cycle lanes or in a quiet street.

15 There is evidence from Europe that for a trip length under 5 km, cycling can be quicker door to door than the

private car and for trips under 9 km can be quicker than the train. Walking on the other hand has no time advantage over other modes (see EC 1999, p 11). For walkers, travel time benefits might be negative depending on trip length.

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Table 25 Travel time weightings for cycling

(PriceWaterhouse Coopers/SKM 2010

Wardman et al (2007) Tilahun et al (2007)

Hunt and Abraham (2007)

Location Sydney UK US Canada

On-road 1.00 1.00 1.00 1.00

On-road with lanes or quiet street

0.43 0.48 0.55 0.24

Off-road 0.34 0.29 0.80 0.36

Source: Mulley (2014)

In principle these weights could be used in comparing the perceived costs of cycling on different types of track infrastructure. A major impediment to their use is the potential over counting of crash benefits. It is not possible to determine how much the relative preference for off-road paths is influenced by perceptions of safety and how much by other factors, for example reduced stress caused by interactions with motor vehicles, reduced exposure to road rage or other forms of abuse or the pleasure associated with cycling in a pleasant environment.

Until more research is carried out it is recommended that these weights not be used in the estimation of generalised cost.

5.11.3 Active travel speeds

Values of travel time for use in transport cost benefit analyses are set out in other parts of NGTSM. Methods for estimating speeds of other modes are also set out elsewhere in NGTSM.

Values for active travel speeds are shown in Table 26.

Walk

Estimates of walking speeds in the literature vary according to age and, it would appear, the purposefulness of particular trips, so that someone walking with the intent of exercising walks faster than if they are walking for non-exercise purposes. A 6 km/h is in the middle of the estimates and would be appropriate for CBAs. It is unlikely that analysts will have information about walker age, trip purpose and whether their purpose is mixed with exercise that would allow finer-grained speed estimates to be used.

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Cycling

The data sources for cycling speeds are ambiguous as to whether they are cruising speeds, trip start to trip end speeds16 or door to door speeds. The higher estimates in Table 26 appear to relate to cruising speeds on a dedicated cycleway whereas the Copenhagen estimate more reflects a door to door speed. The door to door estimates would be suitable for estimating the travel time effects of a dedicated cycleway replacing a section of street riding. The door to door speed would be used to calculate travel time effects for users who convert to cycling and their trip involves a mixture of on- and off-street riding.

Table 26 Average speeds for active travel modes

Source Comment Speed description Speed (km/hr)

Parise et al (2004) Older adult males Walk –‘normal brisk walking speed’ 5.75 km/h

Older adult females Walk –‘normal brisk walking speed’ 5.5 km/h

British Heart Foundation (2014)

Person with excellent fitness ‘Moderate’ walking pace 6.4 km/h

‘Fast’ walking pace 7.5 km/h

City of Copenhagen (undated)

Average cycling speed in 2012 15.5 km/h

Haworth (2011) Context suggests the data cited is cruising speed rather than average journey speed

Median cycling speed 24 km/h

Aecom (2010, p 51) Cycle 23 km/h

Aecom (2010 p 3) Dedicated cycleway Cycle 25 km/h

16 Trip start to trip end speed would exclude the walk trip to/from the bicycle storage point or shower/change

facility.

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6 Performance monitoring

6.1 Why monitor

Performance monitoring is a process for testing whether a project is achieving or has achieved its objectives. Performance monitoring results could be used to:

Identify the need for on-going improvements to recently delivered infrastructure; and

Improve the design and delivery of future active travel projects.

Resources available for monitoring tasks– including design of the monitoring program, data collection and reporting - will always be constrained. Monitoring is therefore likely to be confined to high cost projects, projects that are expected to have a significant impact on a specific policy objective (such as reducing crash risk at a blackspot) or projects that are intended to test new design philosophies or concepts.

6.2 Measures of success

Data collection to determine the level of success or changes attributable to an active travel infrastructure upgrade or new facility would include the following:

Facility usage (eg trips/day, trips/hour) disaggregated by:

new trips (ie previous latent demand)

mode shift - from private vehicle or public transport to active travel

mode shift - from private vehicle to supporting public transport trips

Safety improvements (ie fewer crashes)

Personal security (ie lower incidence of crime)

Active travel user satisfaction (ie percentage of users happy with the facility)

Condition of the facilities provided (ie level of feedback from active travel users)

Health benefits (as measured by an increase in the number of active travel trips in an area or a network) may be difficult to discern at the level of individual projects.

6.3 Data collection

The appropriate monitoring methods should be considered at an early stage of the planning process. Suitable approaches are dependent on the objective being monitored and could include:

Pedestrian and cyclists count surveys (observation surveys)

Intercept surveys including face to face interviews on site or self-administered mail-back or email-back questionnaires

Origin-destination surveys (eg Bluetooth, GPS and following surveys)

Facility condition surveys.

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6.4 Timing of performance monitoring

Performance monitoring should be undertaken before and after an intervention is implemented. The same method, location and time period should be replicated where possible for the ‘before’ and ‘after project’ scenarios.

Care needs to be taken when monitoring the performance of a new facility or delivery of a new policy as there will always be a period of time before the up-take reaches expected demand. This is sometimes referred to as the demand ‘ramp-up’ period and it should always be incorporated in demand forecasts to reflect the time for the project to affect user trip making behaviour. For relatively small projects it would be sensible to commence monitoring processes once expected demand volumes have reached the expected level or after sufficient time has elapsed for users to adjust to the new infrastructure. For larger projects the ramp up period could be quite long in which case periodic monitoring initiatives would be appropriate. The length of time between project opening and commencement of monitoring will be project specific. A small facility however (eg a pedestrian refuge island) might be surveyed a month after opening whereas it would be better to wait a year to assess the performance of a new pedestrian bridge).

The time of day, day of the week and time of year at which surveys are taken should be the same for the before and after scenarios. These survey design parameters will be determined by each project’s key origins, destinations and surrounding land-uses. For example:

A commuter shared pedestrian and cycle path would likely be surveyed during the morning and evening commuter peak periods

A monitoring program for an active travel project near a school would need to take account of the school’s start and finish times

A recreational pathway through a park would probably be utilised more during the weekend.

The data collection should take place at the same time of the year without any short term or special event taking place (unless of course the active travel project is specifically designed to address event day demand). Having comparable weather conditions in the ‘before’ and ‘after’ periods is also beneficial. The longer the survey period the more reliable the data but this will be influenced by the time and budget available for performance monitoring.

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SKM PriceWaterhouseCoopers (SKM PWC 2011) Benefits of the inclusion of active travel in

infrastructure projects prepared for Department of Transport and Main Roads, Brisbane.

SMEC (2013) Gungahlin to Civic Cycle Lane Cost-Benefit Analysis Technical Note.

Sunshine Coast Regional Council (2011-2013) Sunshine Coast Sustainable Transport Strategy.

Transport Scotland (2008) Scottish Transport Appraisal Guidance, Edinburgh.

Turner, Shane et al ‘(2011) Safety Performance Functions for Bicycle Crashes in New Zealand and

Australia, TRB 2011 Annual Meeting.

Turner, Shane et al ‘(2009) Cycle Safety: Reducing the crash risk, NZ Transport Agency research report

389, October.

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Turner, SA, et al (2006) Predicting accident rates for cyclists and pedestrians, prepared for Land

Transport New Zealand, Research Report 289.

UK Department for Transport (2014) Transport Analysis Guidance: Active Mode Appraisal, London,

Transport Appraisal and Strategic Modelling Division.

US Department of Transportation (1999) Guidebook on methods to estimate non-motorised travel:

Overview of Methods, Washington DC, Federal Highway Administration.

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Appendix A Physical Activity Definition

A.1 Physical Activity Definitions

Vigorous intensity physical activity was defined as activity undertaken for fitness, recreation or sport that caused a large increase in the respondent's heart rate or breathing. Moderate intensity physical activity was more moderate, and not already reported as vigorous physical activity.

The level of activity reported is based on the following Sufficient Physical Activity measure:

Inactive No walking, moderate or vigorous intensity physical activity

Insufficiently active Some activity* but not enough to reach the levels required for 'sufficiently active'

Sufficiently active (for health)

150 minutes of moderate/vigorous physical activity* from five or more sessions.

*Vigorous physical activity time is multiplied by two.

Source: 4364.0.55.004 - Australian Health Survey: Physical Activity, 2011-12

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Appendix B Active Travel Interventions and Options

A list of infrastructure options and interventions available to support active travel is presented below. The majority of these options are associated with the road network where road crossing facilities and interactions at intersections are of significant importance.

B.1 Roads and Streets

Pedestrian streets are pedestrian only areas created by restricting traffic access or closing street to traffic eg Brisbane’s Queen Street mall shown in the following Figure.

Figure B6 Pedestrian street

Shared zone is a street that has been designed to give priority to pedestrians by significantly reducing the dominance of the motorised transport through the road environment and speed reduction eg Duporth Avenue, Maroochydore shown in the following Figure

Figure B7 Shared zone

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Traffic calming measures are interventions that impact motorised transport aiming to improve the active transport network, with some schematic diagrams shown in the following Figure, and include;

– road closure

– half closure

– build outs

– gateway or entry treatment

– chicanes

– raised intersections

– speed humps

Figure B8 Traffic control devices

B.2 Pathways within the road corridor

Footpaths running adjacent to the road/carriageway

Sealed road shoulders (mainly relevant to rural roads)

Wide kerb-side lanes are widening traffic lanes adjacent to the kerb giving more space for cyclists

Shared bus or parking lanes with cyclists

Peak period cycle lanes

Exclusive on-road cycle lanes can take the form of either green surface treatment and road markings, white line marking and bicycle symbol or bicycle awareness zones (BAZ) with bicycle symbols in the traffic lane. Examples are shown in the following Figure.

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Figure B9 On-road cycle lane facilities

Segregated on-road cycle lanes – see following Figure.

Figure 10 Segregated bike lane within road corridor

B.3 Pathways separate to the road corridor

Exclusive pedestrian path

Shared pedestrian and bicycle path – see following Figure

Segregated pedestrian and cycle path – see following Figure

Exclusive cycle path

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Figure B11 Shared pedestrian/cycle path and segregated pedestrian/cycle path

B.4 Path upgrades or retrofitting

Widening of an existing path

Resurfacing of an existing path

Ramps to improve the movement along an active travel route for cyclists and pedestrians

Steps to improve pedestrian movements along a pathway.

B.5 Ancillary Infrastructure

Lighting along pedestrian and cyclist routes will improve safety, security and the likelihood of the facility being used particular at night time

Seating provided at appropriate locations will improve the amenity of a facility, particularly for walkers – see following Figure

Figure B12 Improve amenity of footpaths

Pedestrian

Path

Cycle Path SHARED PED/CYCLE PATH

SEGREGATED PED/CYCLE PATH

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Water points eg water fountains sited at appropriate locations along an active travel route

Landscaping eg shade planting along an active travel path or at rest areas – see following Figure

Handrails and guiderails at appropriate locations to assist users of active travel facilities – see following Figure

Security cameras eg CCTV surveillance to improve personal security

Emergency help points to improve personal security

Wayfinding signage to inform people of the location and distance to the land uses in the area – see following Figure

Lifts or escalators at grade separated crossing will promote use of the crossing facility

Non-slip surface treatments for pedestrian will improve safety of the path.

Figure B13 Wayfinding signage and guardrail

B.6 Crossings

Dropped kerb eg pram ramps, is where part of the path along the kerb is lowered to the same level of the adjacent carriageway to allow easier use

Blended kerb crossings is where the path and road are at the same level, these usually are formed in shared zones or by raised pedestrian crossing platforms – see following Figure.

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Figure B14 Blended crossing across side street

Refuge island treatments eg medians, will enhance safety for active travellers crossing at that point

Pedestrian platforms eg raised crossing, remove the level difference making crossing easier for pedestrians

Zebra crossing is marked with longitudinal road markings with traffic required to give way to pedestrians

Mid-block pedestrian signals are traffic signals not at an intersection that stop traffic to allow crossing

Grade separated crossing eg overpass or bridge, underpass or tunnel which separates active travel users from motorised transport improving safety, connectivity and promoting active travel – see Figure below

Figure B15 Active travel bridge crossing over a river

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School patrol crossing usually involves a parent/guardian who control the traffic to allow children to cross without conflict, sometimes they incorporate markers and swing signs

Gate controlled crossing are usually found at railway crossing points to enhance safety.

B.7 Cycle path crossing treatments of side roads at priority intersections

Bent-out treatment where off-road cycle path bends away from the road if there is sufficient space in the road reserve with priority given to cyclists over the traffic on the side road as shown in the following Figure

Straight crossing treatment allows the straight movements across the side road – see Figure below

Bent-in treatment provides for a one-way off-road cycle lane transitions into an on-road cycle lane thereby enabling cyclists to have priority over the side street as shown in Figure below

Figure B16 Cycle path crossing side road

BENT-OUT STRAIGHT BENT-IN

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Refuge treatment within an intersection to accommodate cycle crossing while restricting vehicles to left turn movements only as shown in following Figure

Figure B17 Refuge treatment within an intersection

B.8 Further crossing treatments at Roundabouts

On-road cycle facilities with the traffic lane can take the form of the cycle lane facilities listed above ie BAZ, green colour and line marking with a significant concern being the speed of traffic approaching the roundabout with a mixed cycle and traffic lane roundabout shown in the following Figure

Figure B18 Mixed cycle lanes with traffic at roundabout

Physically separated cycle lanes at grade minimise bicycle and vehicle interaction on the roadway with cyclists crossing the arms of the roundabout similar to pedestrians with an example shown in the following Figure.

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Figure B19 Separated cycle lanes at grade at roundabout

B.9 Further crossing treatments at signalised intersections

Single stage signalised pedestrian crossing

Head-start or expanded storage areas ie advanced cycle stop lines are used at signalised intersections to facilitate stacking of cyclists allowing them to stop and wait ahead of the vehicular traffic improving safety, shown in the following Figure

Hook turn storage boxes are used as an alternative to right turn movements from the centre of the road where cyclists go straight through and wait at the corner the intersection and make the right turn manoeuvre when it is safe to do so or with through movement on the other arm – see Figure B20.

Figure B20 Expanded storage and hook turn at signalised intersection

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Left-turn treatments for cyclists are often required as part of channelized left turn treatment or left turn slip lanes for the vehicular traffic which can involve cyclists sharing the left turn lane vehicles or a free-flow or bypass treatment

Bypass of T-intersection for the through movement opposite discontinuing arm will limit delay to cyclists and be incorporated as a separated lane as shown in the following Figure or provide for cyclists on the adjacent path

Figure B21 Bypass of T-intersection

Bicycle loop detectors with sensitive detection arrangements should be provided at separate bicycle lane

Push button bicycle signalised crossing should be provided where cyclists share the intersection with vehicles as detection is not always possible due to their small electromagnetic footprint.

B.10 Other strategies

Pedestrian signals co-ordination can be useful in a city centre area with significant commuter movements to improve pedestrian travel time along the route

Count-down timers at signalised crossings promote safety for pedestrians and give them greater knowledge of the waiting and crossing times

Scramble crossings involve an all red signal phase for vehicles to allow pedestrian crossings in all directions at the intersection.

B.11 End-of-trip Facilities

Showers should be provided at all end-of-trip locations for cyclists

Changing rooms should also be available for cyclists

Lockers to store clothing and bike equipment should also be provided if the cyclist does not have space to store their items.

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B.12 Bike Parking

Bike stands or racks to allow cyclists to lock their bike frame and wheels as required – see following Figure

Shared gated parking areas ie lockable enclosure/shelter with bike stands or racks enclosed as in following Figure

Individual secure bike parking lockers are the most secure bike parking facility available – see Figure below.

Figure B22 Bike racks at public transport interchange

Figure B23 Bike enclosure and locker

SHARED GATED PARKING AREA INDIVIDUAL SECURE LOCKERS

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Appendix C Assessment of interventions

Interventions / Options Health

Physical Safety

Personal Security

Pedestrian Amenity

Cycle Amenity

Encouraging Mode Shift

Capacity Active Travel Time Saving

Installation Cost

Maintenance Cost

Roads and streets

Pedestrian Street (eg mall) ✓ ✓✓✓ ✓✓✓ ✓ ✓ ✓ Low-High (see Note 1)

Low-High (See Note 1)

Shared zone

(eg Duporth Avenue) ✓ ✓✓ ✓✓ ✓✓ ✓ ✓

Medium-High (see Note 1)

Medium-High (See Note 1)

Traffic calming measures

Road closure (See Note 2) ✓✓ ✓ ✓ Low-Medium Low

Half closure (See Note 2) ✓ ✓ ✓ Low-Medium Low

Build-outs (eg kerb extensions)

✓ ✓ Low Low

Gateway treatment ✓ (See

Note 3) Low Low

Chicanes ✓ ✓ Low Low

Raised intersections ✓ Low Low

Pathways within road corridor

Footpath adjacent to road ✓ ✓ ✓✓ ✓ ✓ ✓ ✓ Low Low

Sealed shoulder

✓ ✓ ✓ ✓ ✓ ✓ ✓

Low-Medium (See Note 4)

Low

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Interventions / Options Health

Physical Safety

Personal Security

Pedestrian Amenity

Cycle Amenity

Encouraging Mode Shift

Capacity Active Travel Time Saving

Installation Cost

Maintenance Cost

Wide kerb-side lanes ✓ ✓ ✓ ✓ ✓ ✓ ✓ Low-Medium (See Note 4)

Low

Shared bus / cycle lanes ✓ ✓ ✓ ✓ ✓ ✓ ✓ Low-Medium (See Note 4)

Low

Peak period cycle lanes ✓✓ ✓ ✓ ✓ ✓✓ ✓ ✓ Low-Medium (See Note 4)

Low

Exclusive on- road cycle lanes

✓✓✓ ✓✓ ✓ ✓ ✓✓✓ ✓ ✓ Low-Medium (See Note 4)

Low

Segregated on- road cycle lane

✓✓✓ ✓✓✓ ✓ ✓ ✓✓✓ ✓ ✓ Low-Medium (See Note 4)

Low

Pathways separate to road corridor

Exclusive pedestrian path ✓✓✓ ✓✓✓ ✓✓✓ ✓✓✓ ✓✓✓ ✓✓ Low-Medium Low

Shared ped/cycle path ✓✓✓ ✓✓ ✓✓ ✓✓ ✓✓✓ ✓✓ ✓✓ Low-Medium Low

Segregated ped/cycle path ✓✓✓ ✓✓✓ ✓✓✓ ✓✓✓ ✓✓✓ ✓✓✓ ✓✓ Low-Medium Low

Exclusive cycle path ✓✓✓ ✓✓✓ ✓✓✓ ✓✓✓ ✓✓✓ ✓✓ Low-Medium Low

Path upgrades or retrofitting

Widening ✓ ✓ ✓ ✓ ✓ ✓ Low Low

Resurfacing ✓ ✓ ✓ ✓ ✓ N/A Low

Ramps ✓ ✓ ✓ ✓ Low Low

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Interventions / Options Health

Physical Safety

Personal Security

Pedestrian Amenity

Cycle Amenity

Encouraging Mode Shift

Capacity Active Travel Time Saving

Installation Cost

Maintenance Cost

Steps ✓ ✓ ✓ Low Low

Ancillary infrastructure

Lighting ✓✓ ✓✓ ✓✓ ✓✓ ✓ Medium Low

Seating ✓ ✓✓✓ ✓ Low Low

Water points ✓ ✓✓ ✓✓ Low Low

Landscaping (eg shade planting)

✓ ✓✓ ✓✓ Low Low

Handrails / guiderails ✓ ✓✓ ✓✓ Low Low

Security cameras ✓✓✓ ✓ Medium Low

Emergency points ✓✓✓ ✓ Medium Low

Wayfinding Signage ✓✓ ✓✓ ✓ Low Low

Lift or escalators (grade separated crossing)

✓ ✓ ✓ ✓ Medium Medium

Non-slip treatment ✓ ✓ ✓ Low Low

Crossings

Dropped kerb ✓ ✓ ✓ Low Low

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Interventions / Options Health

Physical Safety

Personal Security

Pedestrian Amenity

Cycle Amenity

Encouraging Mode Shift

Capacity Active Travel Time Saving

Installation Cost

Maintenance Cost

Blended or level kerb treatment

✓ ✓ ✓ Low-Medium Low

Refuge island ✓✓ Low Low

Ped platform (ie raised crossing)

✓ ✓ Low Low

Zebra crossing ✓ Low Low

Mid-block signals ✓✓✓ Medium Medium

Grade separated bridge or tunnel

✓ ✓✓✓ ✓ 5 ✓ (See

Note 5) ✓✓ ✓ ✓✓ High Medium

School patrol crossing (See Note 6)

✓✓ ✓✓ ✓ ✓ Low Low

Gate controlled (eg at rail line)

✓✓✓ Medium Low

Cycle path crossing treatments of side roads at priority intersections

Bent-out treatment ✓✓ ✓ ✓ ✓ Medium Low

Straight treatment ✓ ✓ ✓ ✓ Medium Low

Bent-in treatment ✓ ✓ ✓ ✓ Medium Low

Refuge in the intersection ✓✓ ✓ ✓ ✓ Medium Low

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Interventions / Options Health

Physical Safety

Personal Security

Pedestrian Amenity

Cycle Amenity

Encouraging Mode Shift

Capacity Active Travel Time Saving

Installation Cost

Maintenance Cost

Further crossing treatments at roundabouts

On-road with traffic ✓ ✓ ✓ Low Low

Physically separated lanes – at grade

✓✓✓ ✓✓ ✓ ✓ Low-Medium Low

Further crossing treatments at Signalised intersections

Single stage signalised ped crossing

✓ Low Low

Head-start storage ✓ ✓ ✓ Low Low

Hook turn storage box ✓ ✓ ✓ Low Low

Left-turn treatments ✓ ✓ ✓ Low Low

T-intersection bypass ✓✓ ✓ ✓ ✓ Low Low

Bicycle loop detectors ✓✓ ✓ ✓ Low Low

Push button cycle signals ✓✓ ✓ ✓ Low Low

Other strategies

Ped signal coordination ✓ ✓✓✓ Low Low

Count-down timers ✓✓ ✓ ✓ Low Low

Scramble signals – all movements

✓✓ ✓✓ ✓ ✓ Low Low

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Interventions / Options Health

Physical Safety

Personal Security

Pedestrian Amenity

Cycle Amenity

Encouraging Mode Shift

Capacity Active Travel Time Saving

Installation Cost

Maintenance Cost

End-of-trip facilities

Showers ✓ ✓✓✓ ✓✓ Low-Medium Low

Changing rooms ✓ ✓✓✓ ✓✓ Low-Medium Low

Bag Lockers ✓✓ ✓✓ ✓✓ ✓ Low Low

Bike parking

Stand or racks ✓ ✓ ✓ Low Low

Shared gated park area ✓✓ ✓ ✓ Low Low

Bike lockers ✓✓✓ ✓ ✓ Medium Low

Notes:

1. Dependent on the level of treatment used eg simple bollards or signage at the end of street to an overall street refurbishing

2. Allowing for cyclists through the intervention

3. If used in conjunction with other physical devices eg signage or line markings

4. Dependent on if road widening is required

5. Dependent on the design of the infrastructure

6. While in operation with patrol