Planning Transport Systems

Geetam Tiwari

Department of Civil Engineering &

Transportation Research and Injury Prevention Program (TRIPP)

Indian Institute of Technology Delhi(IITD)

New Delhi, India

What is Transport Planning?

• Spatial and temporal spread of activities; where we live, work, how long we travel

• Travel demand estimation and design of facilities to meet the present and future demand; how do we travel

• Long range plans for multi-modal transportation systems; roads, metro, bus system, bicycle and pedestrian facilities

Travel demand model

Existing Landuse (2001)

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2000

DESIRE LINES FOR

BASE YEAR: TWO

WHEELER TRIPS

(PCU)

4000

6000

8000

10000

Volume Scale (PCU)

Infrastructure Improvement

8 Bridges Across River Sabarmati (3

Proposed)

8 Underpass/ flyovers (11 proposed)

Problem AnalysisSolution??

• Analysis in terms of PCU (NMV, pedestrians

ignored)

• Focus on inter zonal trips, short intra zonal trips

ignored

• Focus on travel time(speed)

• Conventional method designed to promote

personal motorised trips

Planning for safe Urban transport: a multi

sector task

City systems

Landuse plans

Transportation System

Infrastructure

Technology

outcome Flows

Congestion

Pollution

Accidents

Contiguous development of low-density, high

income and high-density, low-income colonies

(enclosed within red boundary) in southern

part of Delhi

Traffic risk and urban sprawl

Authors Main Findings

(Lovegrove and

Sayed 2007)

Related number of crashes to amount of travel within

geographic unit

(Galster et al. 2001) Accounted for multifaceted nature of design and

density and their relationship to sprawl.

(Ewing et al. 2003) Created a sprawl index and examined the relationship

between this index and traffic crashes. The main

findings include sprawling areas that are associated

with more traffic and pedestrian fatalities.

(Trowbridge et al.

2009;Trowbridge

and McDonald 2008)

Constructed sprawl indices to show that sprawl is

associated with more teen driving and longer

ambulance arrival times. In both papers the authors

conclude that sprawl can lead to more traffic fatalities.

(Lambert and Meyer

2006;Lucy 2003)

Used another index of sprawl and found that sprawl is

associated with more crashes.

Table 1

Urban Density and traffic risk

• Dense urban areas are safer than lower density

suburban environments. This is because per capita

lower vehicle miles are travelled in denser areas at lower

speed as compared to low density sub urban

environments.

• Development with lower vehicle mile travelled is likely to

have lower crash rate. This is related to density,

diversity, design, and destination.

• Density in urban areas and design treatments like

narrower streets, street trees, and traffic calming

measures appear to enhance a roadway safety.

Major recommendations

• Increase density, diversity, destinations and design in

urban environments. It is expected that this promotes

narrower, shorter, more enclosed and interconnected

streets leading to safer travels.

• Density is measured by number of people, households

or jobs per unit area(acre or km2) ,

• diversity refers to mixing of commercial, residential and

industrial areas.

• involves street typology of a community which can vary

from straight interconnected streets to loops of

curvilinear streets. Design also involves sidewalks,

pedestrian crossings road side trees.

Travel patterns in different city size

0%

20%

40%

60%

80%

100%

120%

>5 mill 2-5 mill 1-2 mill .5-1 mill .1-.5mill

Chart Title

On foot Bicycle

Moped/Scooter/Motor Cycle Car/Jeep/Van

Tempo/Autorickshaw/Taxi Bus

Train Water transport

Any other No travel

Travel mode share cities1 million-> 5 million population

0% 20% 40% 60% 80% 100% 120%

North Twenty Four Parganas

Pune

Ahmadabad

Thane

Bangalore

Mumbai Suburban

Modal Share( Above 5million popn size districts)

0% 20% 40% 60% 80% 100% 120%

Haora

Surat

Gurdaspur

Coimbatore

Hyderabad

Modal Share( 2 million-5million popn size districts)

0% 20% 40% 60% 80% 100% 120%

Sambalpur

Erode

Kolhapur

East Godavari

Kendrapara

Kalahandi

Meerut

Bhopal

Modal Share( 1million-2million popn size districts)

Travel mode shares in cities (.1 million -2 million population)

0% 20% 40% 60% 80% 100% 120%

Sambalpur

Erode

Kolhapur

East Godavari

Kendrapara

Kalahandi

Meerut

Bhopal

Modal Share( 1million-2million popn size districts)

0% 20% 40% 60% 80% 100% 120%

Bhilwara

Bikaner

Kottayam

Bagalkot

Bhagalpur

Gautam Buddha Nagar

Modal Share( .5 million-1 million popn size districts)

On foot Bicycle

Moped/Scooter/Motor Cycle Car/Jeep/Van

Tempo/Autorickshaw/Taxi Bus

Train Water transport

Any other No travel

0% 20% 40% 60% 80% 100% 120%

Rajgarh

Sonitpur

Muzaffarpur

Bhiwani

Ghazipur

Modal Share( .1million-.5million popn size districts)

sustainable safe traffic system

a road environment with an infrastructure adapted to the

limitations of the road user;

vehicles equipped with technology to simplify the driving task and

provided with features that protect vulnerable and other road

users; and

road users that are well informed and adequately educated.

Fifth Annual TRIPP Lecture

Discussion on a paradigm shift

Relative contribution

Driver failures:

‘excess’

18

Safe Urban Transport

• Interaction at three levels:

Landuse planning(mode choice & exposure)

Transport infrastructure(mode choice, risk to

captive users)

Urban design( mode choice)

1. Landuse planning

Urban poor in Delhi Symbiosis between formal

and informal sectors~90% people are employed in

unorganised sector( 2002)

48% unorganised sector is

dependent on “own business”-

vendors etc.

50% women have daily wage

jobs

Women are either domestic

workers, self employed, or

street vendors.

52% women walk to work

Women have longer work days

than men

Cities within cities

Converting walking

trips tp motorised

trips- buses, RTVs,

LCVs

Long cycling trips

Time poverty of

women increases

Opportunity for

“self employed”

business reduces

Large numer of people relocated for metro

and other development projects

Planned landuse has lead to ~40,000

households relocation in 4 years

Site

Numbe

r

No. of

Househ

olds

Distanc

e from

original

site

1 8000 8 km

2 4000 7 km

3 5000 18 km

4 3000 10 km

5 2300 12 km

6 50 5 km

7 500 18 km

8 5500 23 km

9 4500 20 km

10 1000 15 km

11 4000 18 km

12 50 8 km

13 65 35 km

14 20 40 km

15 1200 25 km

Distance to main road after relocation

0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Site NumbersD

ista

nce (

mts

)

Original

Relocated

Distance to bus-stop after relocation

0

250

500

750

1000

1250

1500

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Site Numbers

Dis

tan

ce (

mts

)

Original

Relocated

•Rehabilitation of slums results in converting nmv trips to mv trips

• avg. distance to main road

before relocation< .5 km.

•avg. distance to main road after

relocation>2 kmn

•Avg. distance to bus stop 200

m before relocation

•Avg. distance to bus stop 1

km after relocation

•Minimum distance to bus stop

before 10m, after 1km

Location of informal settlements

Informal settlements relocated by planners in Delhi 2001-2006 15-20 kms

away from the original location

self planned -

expert planned-

Captive and potential NMV usersLow income households (slums/ JJ colonies, LIG Colonies, urban villages)

• 10% - 50% households in Indian cities with Household income 100-180 USD/month

• Motorized public transport (bus)- not an affordable option

CAPTIVE RIDER GROUP

School and College students

High density (planned and unplanned)And mixed land use – Short Trip Maker

• High ownership of bicycle, low car ownership

POTENTIAL RIDER GROUP

Impact on safety

• The probability of a specific threat-victim crash = total “at-risk” kms travelled by road users in the victim’s travel mode (Uvictim× dvictim) X total distance travelled by the vehicles that pose the threat (Mthreat× dthreat).

• The mobility indicators for travel to work – distance, time and cost –have increased for 83%, 82% and 61% of the households respectively.

• The relocated households are travelling longer distances than before on arterial or national highways coming to the city. These roads do not have dedicated facilities for pedestrian, bicycles or buses.

• Aggregate data of fatal crash from 2001-2009 shows the increase in fatal crashes involving pedestrians and bicyclists

Transport Market & Latent Demand

• Changing demand

Volume/ Demand

s

er

vi

c

e

V1 V2

T1

T2

Investment in car infrastructure leads to higher

speeds(short term), increased accidents, more cars,

congestion!!!

Conflict between safety and

mobility• Higher level of service implies

higher speeds-i.e. higher

probability of fatality

0

20

40

60

80

100

0 10 20 30 40 50 60 70

Impact speed km/h

Probability of

pedestrian

fatalityPercent

Planning for safe Urban transport: a multi

sector task

City systems

Heterogeneity, Informal economy,

squatter settlements

Transportation System

Pedestrians,

Non motorised vehicles,

para transit

outcome Flows

Congestion

Pollution

Accidents

Contrasting Approaches to

Transport PlanningThe Conventional Approach:

Transport Planning and Engineering

Physical dimensions

Mobility

Traffic focus, particularly on the car

Large in scale

Street as a road

Motorised transport

Forecasting traffic

Modelling approaches

Economic evaluation

Travel as a derived demand

Demand based

Speeding up traffic

Travel time minimisation

An Alternative ApproachSustainable Mobility

• Social dimensions

• Accessibility

• People focus, either in (or on) a vehicle or on foot

• Local in scale

• Street as a space

• All modes of transport often in a hierarchy with pedestrian and cyclist at the top and car users at the bottom

• Visioning on cities

• Scenario development and modelling

• Multicriteria analysis to take account of environmental and social concerns

• Travel as a valued activity as well as a derived demand

• Management based

• Slowing movement down

• Reasonable travel times and travel time reliability

• Integration of people and traffic

IIT Delhi 2007

Seoul

Restoration of Cheonggyecheon

Decrease of car-traffic volume : 125,000 veh/day

Before After(Sep. 2005)

Infrastructure and Travel Characteristics

• Before and after the introduction of Metro system, negligible change in congestion index.

• Curitiba planned high density along the corridor, PT infrastructure has resulted in high use of PT despite high car ownership

• Bogota NMV ridership increased from .8% to 4% after NMV infrastructure

• NMV ridership increased in The Netherlands after improvement in NMV infrastructure.

SDGs

• Universal, integrated and transformative

2030 Agenda for Sustainable Development

17 Sustainable Development Goals and 169

associated targets.

• Sustainable transport has been included in 7

of the 17 goals and is covered directly by 5

targets and indirectly by 7 targets.

Transport related issued in specific targets

• Target 3.6. By 2020, halve the number of global

deaths and injuries from road traffic accidents.

• Target 7.3. By 2030, double the global rate of

improvement in energy efficiency.

• Target 9.1. Develop quality, reliable, sustainable,

and resilient infrastructure, including regional and

trans-border infrastructure, to support economic

development and human well-being, with a focus

on affordable and equitable access for all.

Transport related issued in specific targets..

• Target 11.2. By 2030, provide access to safe,

affordable, accessible, and sustainable transport

systems for all, improving road safety, notably by

expanding public transport, with special attention

to the needs of those in vulnerable situations,

women, children, persons with disabilities, and

older persons.

• Target 11.6 by 2030, reduce the adverse per

capita environmental impact of cities, including by

paying special attention to air quality, municipal

and other waste management

Transport related issued in specific targets…

• Target 12.c. Rationalize inefficient fossil-fuel

subsidies that encourage wasteful consumption by

removing market distortions, in accordance with

national circumstances, including by restructuring

taxation and phasing out those harmful subsidies,

where they exist, to reflect their environmental

impacts, taking fully into account the specific

needs and conditions of developing countries and

minimizing the possible adverse impacts on their

development in a manner that protects the poor

and the affected communities

Impact on Public Health of Reducing

Greenhouse Gas Emissions from Urban

Land Transport

Based on :Public health benefits of strategies to reduce greenhouse-gas emissions: urban

land transport. Woodcock J, Edwards P, Tonne C. et al. The Lancet: Published Online November 25, 2009DOI:10.1016/S0140-

6736(09)61714-1 39

0

10

20

30

40

50

60

70

80

90

100

Bus Motorcycle Car Bicycle Rail Walk

km p

er p

erso

n p

er w

eek

Delhi travel patterns

Baseline

2030: Lower Carbon Driving

2030: Increased Active Travel

40

Change in disease burden Change in premature

deaths

Ischaemic heart

disease11-25% 2490-7140

Cerebrovascular

disease11-25% 1270-3650

Road traffic crashes 27-69% 1170-2990

Diabetes 6-17% 180-460

Depression 2-7% NA

Delhi: Health impacts by cause

41

0

1000

2000

3000

4000

5000

6000

7000

8000

Physical activity Air pollution Road traffic collisions

DA

LYs

per

mill

ion

po

pu

lati

on

in o

ne

year

Delhi: Health impacts by pathway

42

Landuse-Transport integration for

sustainable cities

• Integrating diverse socio economic

households in master plan

• Street designs and transport system to

ensure current and potential walking and

bicycling trips

• Lessons- indicators and methods from self

organising cities.