Validation of surrogate traffic safety indicators Carl Johnsson, PhD - - PowerPoint PPT Presentation

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Validation of surrogate traffic safety indicators Carl Johnsson, PhD - - PowerPoint PPT Presentation

Validation of surrogate traffic safety indicators Carl Johnsson, PhD student, Lund University ICTCT Workshop 2016, Lund Outline Part 1 What do we mean by validation? Product validation Previous product validation Process


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SLIDE 1

Validation of surrogate traffic safety indicators

ICTCT Workshop 2016, Lund Carl Johnsson, PhD student, Lund University

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SLIDE 2

– Part 1

  • What do we mean by validation?
  • Product validation

– Previous product validation

  • Process validation

– Previous process validation – Part 2

  • Product validation in InDeV

Outline

27/10/2016

  • No. 2

www.indev‐project.eu

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SLIDE 3

What do we mean by validation?

27/10/2016

  • No. 3

www.indev‐project.eu

  • Does an indicator actually “measure” the property you

want to measure

  • Validity of an indicator means to what extent it

describes (un)safety

  • Relation between accidents and conflicts
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SLIDE 4

Product validation

27/10/2016

  • No. 4

www.indev‐project.eu

  • Correlation between conflicts and accidents
  • Number of observed or expected conflicts
  • Number of recorded or expected accidents
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SLIDE 5
  • Linear correlation
  • Number of reported accidents
  • Number of observed conflicts

Previous product validation

27/10/2016

  • No. 5

www.indev‐project.eu (TRRL, 1980)

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SLIDE 6

Previous product validation

27/10/2016

  • No. 6

www.indev‐project.eu

  • Hauer and Gårder (1986)
  • Variance of the Accident‐to‐conflict ratio, VAR()
  • “a technique (method, device) for the estimation of

safety is “valid” if it produces unbiased estimates, the variance of which is deemed to be satisfactory.”

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SLIDE 7
  • Focusing on the variance of the Accident‐to‐conflict ratio

Previous product validation

27/10/2016

  • No. 7

www.indev‐project.eu (Hydén, 1977)

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SLIDE 8
  • Linear correlation

– Lord (1996)

  • Estimate the expected number of accidents using an accident

prediction model

  • Number of observed conflicts

Previous product validation

27/10/2016

  • No. 8

www.indev‐project.eu

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SLIDE 9
  • El‐Basyouny & Sayed (2013)

– Two‐phase model

  • Predict expected conflict rate using traffic volume, area type

etc.

  • Predicted conflict rate used as input for negative binomial

safety performance function

Previous product validation

27/10/2016

  • No. 9

www.indev‐project.eu

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SLIDE 10
  • Before‐after approach

– Autey et al. (2012)

  • Before‐after conflict study

– Sacchi et al. (2016)

  • Collision‐based full Bayes

before–after safety evaluation

Previous product validation

27/10/2016

  • No. 10

www.indev‐project.eu (Autey et al., 2012)

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SLIDE 11
  • Indicates the extent to which safety indicators can be used for

describing the process that leads to accidents

Process validation

27/10/2016

  • No. 11

www.indev‐project.eu

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SLIDE 12
  • In‐depth accident studies or accident investigations by the

police

– Brake‐marks measured – interviews with involved road users and witnesses

  • Compare ”process” between accidents and conflicts

Process validation

27/10/2016

  • No. 12

www.indev‐project.eu

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SLIDE 13

Previous process validation

27/10/2016

  • No. 13

www.indev‐project.eu (Hydén, 1987) (Hydén, 1987)

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SLIDE 14
  • Video recorded accidents
  • Compare event leading to accidents compared to events

leading to conflicts

Previous process validation

27/10/2016

  • No. 14

www.indev‐project.eu

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SLIDE 15

Previous process validation

27/10/2016

  • No. 15

www.indev‐project.eu (Saunier et al., 2011) (Saunier et al., 2011)

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SLIDE 16

Part 2

Product validation in InDeV

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SLIDE 17
  • 21 signalized intersections in 6 countries

– Spain, Sweden, Denmark, Belgium, the Netherlands and Poland – 3 weeks of filming

  • Focus on pedestrians and bicyclists
  • Manoeuvre specific

– Low number of recorded accidents

Product validation in InDeV

27/10/2016

  • No. 17

www.indev‐project.eu

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SLIDE 18

– Similar approach to Lord (1996)

  • Expected number of accidents

– Adapt safety performance function (SPF) – Nation and manoeuvre specific

  • Expected the number of conflicts

– Based on observed conflicts

  • Focus on the variance of the Accident‐to‐conflict ratio

Product validation in InDeV

27/10/2016

  • No. 18

www.indev‐project.eu

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SLIDE 19

Product validation in InDeV

27/10/2016

  • No. 19

www.indev‐project.eu

Expected number of accidents Expected number of conflicts

  • Comparison of two different

methods to estimate safety.

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SLIDE 20

Thank you very much for your attention!

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 635895

Visit us on www.indev‐project.eu

Carl Johnsson, PhD student, Lund University

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SLIDE 21
  • Suggested accident model in InDeV

– ∗

  • 1 & 2 will be estimated based on literature

Product validation in InDeV

27/10/2016

  • No. 21

www.indev‐project.eu

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SLIDE 22
  • Güttinger (1979)

– The relation between serious conflicts and accidents must be stronger than the relation between traffic volume and accidents. – The relation between serious conflicts and accidents must be stronger than the relation between people’s opinion regarding road safety and accidents.

Satisfactory validation

27/10/2016

  • No. 22

www.indev‐project.eu