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Impact of methodological choices on road safety ranking

Impact of methodological choices on road safety ranking. SAMO conference: 20/06/07 Elke Hermans: elke.hermans@uhasselt.be Transportation Research Institute - Hasselt University (Belgium). Overview. 1. Introduction to indicators 2. Introduction to road safety

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Impact of methodological choices on road safety ranking

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  1. Impact of methodological choices on road safety ranking SAMO conference: 20/06/07 Elke Hermans: elke.hermans@uhasselt.be Transportation Research Institute - Hasselt University (Belgium)

  2. Overview 1. Introduction to indicators 2. Introduction to road safety 3. The road safety index process 4. Study design 5. Method: UA & SA 6. Results 7. Conclusions

  3. 1. Introduction to indicators • Popular concept • Represent large amount of information • Communicate simplified, clear message • Use: trends, bottlenecks, policy targets and priorities, communication, … • # indicators <-> aggregation in 1 index (e.g. TAI, IMI) • Road safety index = new, challenging and necessary matter!

  4. 2. Introduction to road safety • Causes of accidents and casualties: human-vehicle-environment • International literature defines risk domains: • Alcohol and drugs • Speed • Protective systems • Vehicle park • Infrastructure • Trauma management • Others: youth, VRUs, DRL, tiredness, … • Country-specific factors (low policy impact)

  5. General framework Billions of EUROs 49.286 injury acc. 1.089 fatalities 7.253 seriously inj. 58.057 slightly inj. Social cost - Final outcomes + Safety Performance Indicators Belgium, 2005 Safety measures and safety programs

  6. 3. The road safety index process • A methodologically sound road safety index (RSI) will be developed • Objective: • Comprehensive presentation of information • Better understanding of accident process • Comparing RS performance of regions • Measuring progress to objectives • Supporting policy by means of specific actions

  7. The RSI framework Index process Road Fatality Ranking Road unsafety Indicators Indicator selection Alcohol & drugs  % road users < BAC limit Imputation Speed  % road users < speed limit Normalisation C A S U A L T I E S A C C I D E N T S Weighting Protective systems  seatbelt wearing % in front Aggregation Visibility  daytime running lights law Uncertainty and sensitivity analysis Vehicle  % cars < 6 years Infrastructure  network density Road Safety Index Trauma management  health expenditure as GDP%

  8. 4. Study design • 3 methodological aspects • Weighting method: AHP or BA • Expert: 9 RS experts assigned weights • Indicator set: 7 or 6 RS indicators • RSI = ∑ stand. ind.values x weights • Output = avg. Δ in country ranking based on RSI compared to RFR

  9. Dataset • 7 road safety indicators • Data available for 18 European countries (≠ sources) Zwitserl.

  10. 5. Method: UA & SA • UA & SA are essential for indexes • Several subjective choices are made • Focus on ranking and 1 position • Offer correct and robust results • UA estimates uncertainty in output taking into account uncertainty in input • SA studies how uncertainty in output can be apportioned to different sources of uncertainty • Global variance based sensitivity method • Factors prioritisation setting • SIMLAB

  11. Step-by-step analysis(Saltelli et al., 2004) • Output = average shift in rank • 3 input factors: weighting, exp., ind. • Uniform distributions • Extended FAST method • Generation of 10,000 x 3 sample • Calculation of 10,000 output values • Analysis of the output • Conclusions

  12. Determining the output F11 F12 F13 F21 F22 F23 … … … FN1 FN2 FN3 e.g. F21 = BA F22 = expert 2 F23 = all 7 indicators M = W = [0.286; 0.429; 0.071; 0.000; 0.071; 0.071; 0.071] ZAT = [0.14; 0.62; -0.17; 1.30; -0.21; -0.32; 1.35] … ZUK = [0.99; -0.05; 0.97; -1.46; 0.58; -0.96; -1.31] for row 2

  13. 6. Results • UA: output distribution • μ = 5.64 • σ = 0.75 • Large ≠: • More and better ind. • Small EU data set BA; exp. 6; 6 indic. (no infrastr.)

  14. Results (2) • SA: first order and total effect index for each input factor

  15. 7. Conclusions • Importance and usefulness of UA & SA has been shown  essential part in the RSI development process • Set of indicators is most influencing input factor  focus on theoretical framework and indicator selection • Expert selection and weighting method had an impact mostly by interaction effects • Weighting method BA or AHP had the least impact but they have some similarities • These three aspects proved important in other studies as well

  16. Further research • Incorporate more methodological aspects: normalisation, imputation, aggregation and more possible weighting techniques in UA & SA • Other output of interest: country level • Methodological adaptations

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