Robert Thomson Chalmers University of Technology Division of Vehicle Safety/SAFER

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http://[email protected]

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sustainable surface transportsixthframework programme

Robert Thomson Chalmers University of TechnologyDivision of Vehicle Safety/SAFER

Rankers Field Studies of Infrastructure Performance

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2http://[email protected]

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28 / 06 / 07

Outline

Motivation for Field Studies Partners Field Study Objectives

▫ Infrastructure Monitoring▫ Countermeasure Effectiveness

Methods Results Future Activities

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Motivation

What approach do we need for improving traffic safety?1) Identify locations with traffic safety problems What indicators can we use to predict safety problems? Do we need to wait for fatal accidents to accumulate before we identify

problem areas?

2) Identify suitable candidate solutions Identify potential solutions for review Conduct field evaluations of selected countermeasures Provide information for ranking suggested countermeasures

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Motivation

Road Safety Index Use existing road information to find signals of safety problems

▫ Traffic data▫ Accident data▫ Maintenance data▫ Road Surface properties▫ Road Geometry▫ Roadside layout

Identify important indicators for monitoring trends in road safety▫ Eliminate need for Black Spot developments

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Motivation

Safety Countermeasures must be evaluated and compared with the following considerations: What type of safety problem is of most concern? What are the installation / implementation costs? What are the maintenance and operations costs? What is the effectiveness of the countermeasure? How will this affect future safety / traffic conditions?

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RANKERS Scenarios

A review of a detailed database developed in RANKERS identified several accident types Main accident types

1. Run off road without driver reaction 2. Run off road with driver reaction3. Rear end impacts 15%4. Lane change accidents 13%5. Wild life 3%6. Pedestrians7. Wrong way entrance to motorway / Tunnels

46%

RANKERS Field Studies primarily focus on items 1-4

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Partners

Five partners are involved in the Infrastructure field studies: Chalmers University of Technology (Sweden) Swedish Road Administration Helsinki University of Technology (Finland) Autostrade (Italy) CETE (France) DARS (Slovenia)

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Objectives

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Field Study Objectives

The Infrastructure Field Studies can be divided into two groups based on the type of activity Monitoring: What are the relationships between road characteristics and

accidents (numbers and types) Countermeasure Performance: How does a given countermeasure

perform in real world conditions

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Objectives: Monitoring

Studies related to accident analysis and contributions of the road infrastructure focus on the following variables: Road Geometry (vertical and horizontal alignment, width, cross slope,

etc.) Road Surface (roughness, wheel ruts) Speed

Analysis requires accident and infrastructure databases, common for road operators but not necessarily combined Link accident information and road information by accident location

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Objectives: Countermeasure Performance

Different countermeasures in before-after studies were evaluated Countermeasures were selected which have a connection to the

main accident scenarios presented earlier

Specific topics comprise: Curves Aquaplaning Rear end / lane change Passive Safety Devices Wildlife Speed reduction Sign/Lighting

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Methods

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Methods: Safety Monitoring A linked dataset to analyze the contibution of road characterisics to safety

A national accident database Road network database Pavement Management System (PMS)

Accident locations were connected to road sections with a 200 m accuracy

Swedish data included all accident types, Finnish data included only Run-off-Road accidents

Swedish road sections were physically divided (median barrier) and were 2+1, 2+2, motorway designations

Finnish data covered motorways with different construction dates (old/new designs)

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Sketch of the 17 laser measurement points

Road data: Laser RST

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Methods

PMS (Pavement Management System)

Speed limit

Grade

Measuring date Measuring direction

Unevenness

Link ID

Wheel rut

Curvature Carriageway width

Traffic volume Road type

Super elevation

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Methods: Period of Investigation

Sweden: Six-year period, from 2000 to 2005 accidents with personal

injury. No property damage reported to the accident databases. 2912 accidents collected including 54 fatal, 29 severe and

3877 light injuries. Finland:

Six-year period, from 2000 to 2005 accidents with personal injury

437 accidents been collected including 31 fatal, 406 personal injuries.

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Mehtods: Statistical Analysis

Accident and Infrastructure data were analyzed using a regression analysis to identify the relationships between different parameters

Accident data were expressed in Accident Rates (AR):

Where: N=number of accidents; AADT= Annual Average Daily Traffic; L=Length of section;L=Length of investigation period (km), T=period of study (years)

This allowed a normalised value for comparing different infrastructure elements Road sections with similar characteristics were lumped together

LTAADT

NAR

365

106

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Methods: Countermeasure Evaluation

Countermeasures studied were implemented and investigated in the period 2000-2007.

The before – after period of interest varied depending on date of implementation

The number of accidents in the before period were often limited to a limited road segment length (1-5 km). May involve only 1-2 accidents for a given location Higher accident rate than network average

Results are the influence of countermeasure at the area of implementation and may not represent their global performance

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Mehtods: Countermeasure Types

The countermeasure types can be grouped in the following categories and partners

No Objectives Organisations

1 Investigation of accidents in curves – influence of resurfacing

CETE

2 Investigation of accidents in curves – influence of speed control

CETE

3 Aquaplaning accidents in curves – influence of resurfacing

CETE, DARS

4 Influence of hills on rear end collisions CETE

5 Countermeasures for wildlife accidents DARS

6 Effectiveness of Crash Cushions DARS

7 Influence of Speed control (Type of Measurement)

Autostrade

8 Road signs and Lighting Autostrade

This presentation will only discuss 4 countermeasures

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Results

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Results: Monitoring

Most interesting results related to curvature, cross slope, road surface

Accident rate increases with decreasing radius, below 400 dealing with ramps and urban sections of motorway (lower speeds)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

≤ 250 400 700 1000 >1000

Curve Radius [m]

Acc

iden

t R

ate

Left Curves

Right Curves

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Results: Monitoring

Accident distribution changes with curvature, overtaking accidents increase significantly in right curves with curve radii 700-1000mRight curves have higher risk for overtaking accidents

RR

R

R R

Rear End

Run-off-Road

Overtaking

L

LL L

L

0.00

20.00

40.00

60.00

80.00

100.00

< 250 400 700 1000 >1000

Curve Radius [m]

Acc

iden

t T

ype

Co

ntr

ibu

tio

n (

%)

L=LeftR=Right

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Results: Monitoring

Higher risk for negative 3%-4%

0.00

0.20

0.40

0.60

0.80

0-1.5 1.5-2.5 2.5-3 3-4. 4-5. >5

Cross Slope (%)

Acc

iden

t R

ate

Positive Cross-slope

Negative Cross-slope

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Positive cross slope is twice as safe as negative in left curves.

Explanation needed for higher risk for negative cross slope in right curves

Results : Super elevation

Accident rate for (3-4)% cross slopes for left and right curves

0

0,1

0,2

0,3

0,4

0,5

0,6

Left curves Left curves Right curves

Acc

iden

t ra

te

+

-

-

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Results: Monitoring

Road Condition

Both IRI and Rut depthaffect accident rate, almostdoubling in the first 2 intervals

0

0.2

0.4

0.6

0.8

1

<1,5 1,5-2,5 2.5-3.5 >3,5IRI Value

Acc

iden

t R

ate

0

0.2

0.4

0.6

0.8

1

<3,1mm 3,1-10 mm 10-15 mm >15 mmRut Depth [mm]

Acc

iden

t R

ate

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Results: Monitoring

Other Results: Relationship between carriageway width and accident rate Average curvature of a road network appears to influence the accident

rate▫ Old motorways had higher accident rate▫ Average curve radius under 3000 m(old) compared to 4000 m (new)

Relationship between speed and accident rate

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Results: Safety in Curves

Two studies on safety in curves and countermeasures A: Speed Cameras B: Adjust crossfall

Both sites are characterised by 400 m radius curves counter-acting crossfall (ie –ve slope for left curves)

Both curves are preceded by curves R>500m and the driver is “surprised” with a tighter curve

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Results: Safety in Curves

Countermeasures investigated Speed Cameras mounted at the site with information signs Reconstruction of crossfall in left curve (-2.5% changed to +2.5%)

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Results: Speed Cameras

Paris -> Rouen Slow lane (nearside lane)

Fast lane (outside lane) Rouen -> Paris Fast lane

(outside lane) Slow lane

(nearside lane) Average speed 88 km/h 103 km/h Average speed 102 km/h 86 km/h

V85 101 km/h 113 km/h V85 114 km/h 98 km/h

Before

Paris -> Rouen Slow lane (nearside lane)

Fast lane (outside lane) Rouen -> Paris Fast lane

(outside lane) Slow lane

(nearside lane) Average speed 79 km/h 87 km/h Average speed 82 km/h 75 km/h

V85 90 km/h 104 km/h V85 104 km/h 87 km/h

After

Posted Speed90 km/h

Case A

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Safety in Curves

Case A: Speed Cameras Installed

Before After Effectiveness ratio

Injury accidents

6 in 20 months

0 in 1 year 100%

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Results: Crossfall Change

Case B

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Accident follow-up 9 months later:- 0 injury accident- 1 non-injury accident

Effectiveness on accidents Case A


Non-injury accidents

20 in 1 year 1 in 9 months 93%

Injury accidents 5 in 2 years 0 in 1 year 100%

Video footages 6 in 2 months 0 in 4 months 100%

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Results: Reconstruction of Curve

BeforeAfter

Reconstruction of road shiftedtraffic left

Vehicle motionbefore

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Aquaplaning

Two aquaplaning issues were identified in France and Slovenia Two different countermeasures investigated

Rehabilitation (France+Slovenia) Grooving (Slovenia)

Both cases involve low crosslopes values with low grades Identify a monitoring condition:

▫ -1% <crossfall<1% and -1% <grade<1%

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Results Aquaplaning

Results – Reconstruction France


Injury accidents

12 in 7 months

0 in 4 years 100%

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Aquaplaning

Aquaplaning: accident before / after: Slovenia

Roar numberSection number

location

Type of measure

Date of implementation

Traffic accidents

beginning m

length m

One year before implementation

After implementation

A1 55 2.500 100 G 22.9.2006 6 0

A1 659 1.215 130 G 23.10.2005 2 0

A1 60 2.736 129 G 23.10.2005 2 0

A1 660 2.870 120 G 23.10.2005 1 0

A1 58 0.080 100 G 23.10.2005 1 0

A3 69 0.650 120 G 23.10.2005 0 0

A3 669 0.760 115 G 23.10.2005 0 0

A1 41 3.700 100 R 22.9.2006 6 0

A1 644 13.416 84 G 11.6.2006 2 0

A1 644 12.172 124 G 11.6.2006 9 0

A1 631 4.800 300 G 11.6.2006 4 2

LEGEND:

Type of measure G - Grooving R - reconstruction

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Speed Control – Influence of System

Speed Measurement Identification of road sections suitable for improvements (scenario definition), Identification of the PISM and collection of the accidents data in the period 1999-

2005 of the A14 motorway sections, Case study A

▫ Installation of safety tutor, ▫ Data collection,▫ Analysis of the performance in terms of real average speed reduction.

Case study B▫ Installation of a combined safety system (camera and inductive loops), ▫ Data collection,▫ Analysis of the performance in terms of real average speed reduction.

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Case study A In the eight-month period September 2006 - April 2007, the accident rate and the

consequences for persons on sections covered by Tutor registered a decline. This can be attributed to the following factors:

Average speeds on the sample day were in constant reduction (-16 km/h) An even greater reduction concerned the top speeds (-23 km/h on the average of the ten top speeds) This favourable trend in driving behaviour is reflected in the tickets issued by the constantly operating

system, which also recorded a reduction (Highway Police data)

∆Six-month periodSeptember 2006

April 2007

Six-month period September 2005

April 2006

0.71

20.76

52.35

Death rate

Injury rate

Accident rate -22.2 %40.73

-23.2 %15.94

0.44 -38.1 %

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Case study B Data have been acquired for the following two monthly periods by a speed

monitoring systems including loop system and camera box October 2nd-29th, 2006 (without camera box) January 29th-February 25th, 2007 (with camera box)

In order to verify the influence on vehicle speed of put off effect of speed monitoring system by camera box, more than 9,000 data of average speed (km/h) on a 5 min base, box have been acquired.

From data analysis appears that the average speeds on the sample month are in constant reduction on both carriageway (of -10 km/h on right and of -5 km/h on left).

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Summary

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Summary

Accident Data provides some possibilities to identify critical infrastructure conditions Sufficient data needed for analysis New motorway designs may have sufficiently high standard limiting

black spot analysis An alternative to black spot analysis - critical infrastucture properties -

may be useful for monitoring road safety Countermeasures

Several countermeasures were investigated addressing run-off road accidents, rear-end, and lane change accidents

Speed control was shown to be an effective approach in 3 different studies

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Future Work

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Connections between Infrastructure and Human Factors Studies

Behaviour in Curves Influence of curve direction on overtaking accident risk (right curves

more dangerous) Influence of cross fall (-ve cross slope more dangerous, even for right

curves) Lane keeping tendencies in smaller radius curves (400-500)

Speed Control What is the mechanism to reduce accident risk

▫ Speed distribution (V15-V85)▫ Lateral handling capacity (skid resistance)

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Future Work

Data from the field studies needs to be analysed and presented in a form to Develop a set of recommendations for a safety problem

▫ Cost (Benefit) information▫ Maintenance information▫ Influence on traffic

Develop a diagnostic tool (Road Safety Index)▫ Help point put critical infrastructure elements▫ Support ongoing monitoring of traffic safety

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Further Information

Results of the RANKERS project will be implemented into an “e-Book” that will provide information on countermeasures for a variety of road safety issues

Further information on the field studies can be found at the RANKERS website

www.rankers-project.com

(Or contact the indiviudal partners)

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Acknowledgements

The RANKERS project is thankful for the support of the European Commission (DG-TREN)

Partners are also indebted to national and regional road authorities for their support and assistance in the project

Robert Thomson Chalmers University of Technology Division of Vehicle Safety/SAFER

Documents

Transcript of Robert Thomson Chalmers University of Technology Division of Vehicle Safety/SAFER