Sensitivity analysis of driver's behavior and psychophysical conditions

•Visibility and Alcohol/Drugs variables are biased due to data collection procedure.•Bayesian Network has been used to quantify the overall accident severity.•Drugs/alcohol use will likely increase the probability of F/SI up to 5%.•Alcohol consumption significantly impairs the performance of drivers...

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Veröffentlicht in:Safety science 2020-05, Vol.125, p.104586, Article 104586
Hauptverfasser: García-Herrero, Susana, Gutiérrez, J.M., Herrera, Sixto, Azimian, Amin, Mariscal, M.A.
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Sprache:eng
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Zusammenfassung:•Visibility and Alcohol/Drugs variables are biased due to data collection procedure.•Bayesian Network has been used to quantify the overall accident severity.•Drugs/alcohol use will likely increase the probability of F/SI up to 5%.•Alcohol consumption significantly impairs the performance of drivers under 25. To reduce traffic accidents, an accurately estimated model is needed to capture the true relationships between the injury severity and risk factors. This study aims to propose a robust procedure to address the biases in police-reported accident data and subsequently to conduct sensitivity analyzes in order to estimate the variations in injury severity and distraction probability based on drivers’ behaviors/characteristics and psychophysical conditions. The results show that: (i) the excess speed will likely increase the probability of serious/fatal injury for drivers of all age groups by 10%; (ii) distraction and driver’ errors will likely increase the probability of serious/fatal injury in all drivers driving at a proper speed up to 1.5%; (iii) alcohol and drug consumption can significantly increase the probability of being distracted and making errors by 28.5% and 33.5% respectively; (iv) Alcohol consumption reduces the probability of driving at an appropriate speed in drivers under 25 by 40%. However, the results for drugs consumption are not as significant as the ones for alcohol consumption.
ISSN:0925-7535
1879-1042
DOI:10.1016/j.ssci.2019.104586