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Improving the Credibility of, and Compliance with, Speed Limits:

a Real-World ApproachN. Hautière1, P. Charbonnier2,

E. Dumont1, S. Glaser1, E. Violette3

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1 LCPC, Paris2 LRPC de Strasbourg, ERA 27, Strasbourg3 CETE Normandie-Centre, ERA 34, Rouen

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Presentation Outline

IntroductionIntroduction Rough pointsRough points Our positionOur position

Speed limits computation: state of the artSpeed limits computation: state of the art How to improve drivers’ compliance with speed How to improve drivers’ compliance with speed

limits? limits? ProcessProcess ExamplesExamples

On-board solution: On-board solution: ARCOSARCOS Roadside solution: Roadside solution: SARISARI Cooperative solution: Cooperative solution: DIVASDIVAS

PerspectivesPerspectives

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Introduction

FactFactThere is a strong link between accidentology and speed.There is a strong link between accidentology and speed.

Problem Problem PermanentPermanent speed limits (signs) do not help road users speed limits (signs) do not help road users

to adapt their speed in case of to adapt their speed in case of transienttransient difficulties difficulties - Meteorology: rain, fog, wet road, ice on the road- Meteorology: rain, fog, wet road, ice on the road

- Traffic, road works, lack of maintenance…- Traffic, road works, lack of maintenance…

SolutionSolutionAdaptiveAdaptive and and customizedcustomized speed limits. speed limits.

110 light rain110 light rain90 strong rain90 strong rain

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Introduction: Rough Spots(at least in France)

The duality of speed limitsThe duality of speed limits Speed limits have different functionsSpeed limits have different functions, e.g.:, e.g.:

• to ensure homogeneous behaviours,to ensure homogeneous behaviours,

• to ensure coherence with road related to ensure coherence with road related risksrisks..

To comply with speed limits, road users must be aware To comply with speed limits, road users must be aware that that speed limits are related to the riskspeed limits are related to the risk and not only to speed enforcement.and not only to speed enforcement.

Problem: do we communicate on the speed Problem: do we communicate on the speed or on the risk?or on the risk?

ComplianceCompliance Prior to the introduction of automatic speed enforcement, Prior to the introduction of automatic speed enforcement, speed speed

limits were designed knowing that they would not be respectedlimits were designed knowing that they would not be respected.. Today, Today, posted speed limits are no longer suitableposted speed limits are no longer suitable because they are because they are

complied with.complied with.

LiabilityLiability LegalLegal issues are problematic for adaptive speed limits. issues are problematic for adaptive speed limits.

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Introduction: Our Position

We focus on the We focus on the scientificscientific aspect of the problem.aspect of the problem.

We seek to We seek to compute credible compute credible safe* speed limits.safe* speed limits.(*) i.e. risk-related(*) i.e. risk-related

We consider We consider isolatedisolated vehicles, only interacting with vehicles, only interacting with the infrastructure.the infrastructure.

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Speed Limits Computation: State of the Art

Empirical approach Actual speeds are

measured in nominal conditions all the parameters are integrated

Problem: only appliesin nominal conditions not adaptive not credible

Computational approach Based on physical models

for specific situations many parametersare omitted: driver, car, visibility...

Problem: not customized needs to be pessimistic not credible

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How to Improve Drivers’ Compliance with Speed Limits?

HypothesisHypothesisCredible speed limits Credible speed limits

are better complied with.are better complied with.

QuestionQuestionHow to make speed limits credible?How to make speed limits credible?

AnswerAnswerBy making them By making them adaptiveadaptive and and customizedcustomized..

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Process

Combine Combine empiricalempirical and and computationalcomputational approaches approaches

Usual approach:

Our approach:

with with SLSL = Speed Limit = Speed LimitMSLMSL = Mandatory Speed Limit = Mandatory Speed LimitNSLNSL = Nominal Speed Limit = Nominal Speed Limit empirical modelempirical modelf(pf(pii)) = speed decrement needed to maintain nominal risk level = speed decrement needed to maintain nominal risk levelppii = transient risk factor = transient risk factor computational approachcomputational approach

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iipfMSLSL

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ipfNSLSL

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ExamplesOn-board solution

We make it We make it customizedcustomized(on-board = more credible), (on-board = more credible),

ARCOSARCOS Project Project First use of First use of risk functionsrisk functions Example: the Example: the SAVV (speed SAVV (speed

warning in curves)warning in curves)

Website: http://www.arcos2004.com/

Source: ARCOS Project

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We make it adaptive SARI / IRCAD (roadside = addresses all drivers)

Problem: drivers are not aware of the risk in bad conditions (particularly with skid resistance)

We must set a warning threshold in the speed distribution.

Website: http://www.sari.prd.fr/

ExamplesRoadside solution

Source: Lacroix Traffic

Alert threshold

Risk function

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ExamplesCooperative Solution

We make SLs both We make SLs both adaptiveadaptive and and customizedcustomized..

We generalizeWe generalize road-related road-related risks byrisks by adding adding meteorological risksmeteorological risks, and , and by by combining risk factorscombining risk factors (with ranking, rather than (with ranking, rather than simply decrementing).simply decrementing).

This is one objective of the This is one objective of the DIVASDIVAS ProjectProject..

Source: PReVENT Maps&Adas

Source: ARCOS Project

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Type of project: French ANR 2006

Promoted by PREDIT GO9 Timeframe: May 2007-May 2010 Cost budget: 4 M€

(ANR funding 1.3M€) Coordinator: LCPC

Philippe Lepert Nicolas Hautière

Consortium: 15 partners

Industrials

Research institutes

Local actors

Universities

Competitiveness clusters

DIVAS: Dialog between Infrastructure and Vehicles to Improve the Road Safety (1)

Source: LARA (ENSMP/INRIA)

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The DIVAS project is building a global a vehicles – infrastructure information exchange system

It aims at preparing its implementation, in terms of: technology, acceptability, credibility.

The project is focussed on the role of: the infrastructure characteristics the role of the road operators in the deployment of such systems.

It aims at providing each vehicle with an individualized safety indicator along a route,

It mainly takes into account the road geometry, the road surface conditions and the visibility conditions.

Web site: http://or.lcpc.fr/divas-fr/ Reference:

N. Hautière, P. Lepert. “Infrastructure - Vehicles Dialogue to Improve Road Safety: The DIVAS Approach”. To appear in Transport Research Arena (TRA), Ljubljana, Slovenia, April 21 – 25, 2008

DIVAS: Dialog between Infrastructure and Vehicles to Improve the Road Safety (2)

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DIVASMeasuring Actual Speeds

(empirical approach)

“Reference” drivers with instructions, in nominal conditions.

Record the speed profile along the road (and other information also) with an instrumented vehicle.

Calibrate speed profiles using roadside speed measurements at different spots.

Build a nominal speed profile. Infer nominal risk for a specific situation

(e.g. “brick wall”)

Source: LAVIA Project

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1st Level Application:Consolidation of Vertical Signalling

Signs provide the permanent speed limits, posted by the road operator (or police).

Posted speed should be coherent with nominal speed in order to be credible Discrepancies should be studied, baring in mind the duality of posted speed limits.

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2nd Level Application: Adaptation of Speed Limits to Keep

Constant Risks (computational approach)

Risk models are chosen with respect to the studied risk factor The V is computed to have a constant risk (R) compared to the nominal risk (RN) Example: brick wall risk model and wet road

Nominal risk: we compute the gravity of an accident at impact speed SN into a wall at t=2s

SN AN EESN* RN

Wet road leads to a reduction of skid resistance

S A EES R > RN

Knowing the actual road surface conditions, we can compute

S / S’=S-S R’=RN

Assumption: computing S’=S-S is more credible than computing S’=f(skid resistance), which was used for example in ALZIRA project.

*EES = Equivalent Energy Speed (cf. LAB PSA/RENAULT)

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Perspectives

We argue that We argue that crediblecredible risk-relatedrisk-related speed limits speed limits would be better complied with.would be better complied with.

We proposed an approach to computeWe proposed an approach to compute credible speed credible speed limits by making them limits by making them adaptiveadaptive and and customizedcustomized..

We are testing the approach in the framework of We are testing the approach in the framework of DIVAS DIVAS project dealing with cooperative systems.project dealing with cooperative systems.

In the coming next months, we will see if our In the coming next months, we will see if our approach is relevant or not.approach is relevant or not.

May 2010November 2008Mid-term seminarMid-term seminar

Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12

TimeTime(Quarter)(Quarter)

May 2007

DIVAS agenda

Today