Highlights Driving errors and violations can lead to safety–critical events (SCEs). A safe system path analysis approach is applied to account for vehicle instability and unobserved factors. Path analysis decomposes complex mechanisms leading to SCEs by analyzing naturalistic driving data. Driving errors and violations are positively associated directly with SCEs and indirectly through vehicle instability. To mitigate driving errors, violations, and driving instability, promising countermeasures are discussed.

    Abstract This study explores how different driving errors, violations, and roadway environments contribute to safety–critical events through instability in driving speed. We harness a subsample (N = 9239) of the naturalistic driving study (NDS) data collected through the Second Strategic Highway Research Program (SHRP2). From a methodological standpoint, we use the safe systems approach relying on path analysis to jointly model outcomes. This accounts for the potential correlation between unobserved factors associated with both instability in driving speed and epoch (video stream) outcomes, i.e., baseline or event-free driving, near-crashes, and crashes. Tobit and ordered Probit regressions are estimated to model the coefficient of variation (COV) of speed and epoch outcomes, respectively. Results from the Tobit model indicate that driving errors and violations are associated with instability in the driving speed of the subject driver (COV of speed). The Probit model reveals that driving errors, violations, and instability in driving speed are associated with higher chances of crashes and near-crashes. Our key finding is that driving errors and violations not only induce event risk directly but also indirectly through instability in driving speed. For instance, recognition errors associate with higher crash risk by 6.78 % but this error is accompanied by instability in driving speed, which further increases event risk by 4.73 %, bringing the total increase in risk to 11.51 %. Moreover, significant correlations were found between unobserved factors reflected in the error terms of the two models. Ignoring such correlations can lead to inefficient parameter estimates. Based on the findings, practical implications are discussed, which can lead to effective countermeasures that effectively reduce crash risk.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Exploring pathways from driving errors and violations to crashes: The role of instability in driving


    Beteiligte:
    Ahmad, Numan (Autor:in) / Arvin, Ramin (Autor:in) / Khattak, Asad J. (Autor:in)


    Erscheinungsdatum :

    2022-10-17




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Built environment, driving errors and violations, and crashes in naturalistic driving environment

    Ahmad, Numan / Wali, Behram / Khattak, Asad J. et al. | Elsevier | 2021


    Driving errors, driving violations and accident involvement

    Parker, D. / Reason, J.T. / Manstead, A.S.R. et al. | Tema Archiv | 1995


    A taxonomy of driving errors and violations: Evidence from the naturalistic driving study

    Khattak, Asad J. / Ahmad, Numan / Wali, Behram et al. | Elsevier | 2020


    Normal Behavior and Traffic Safety: Violations, Errors, Lapses and Crashes

    Stradling, S. G. | British Library Conference Proceedings | 2000


    Cognitive failures as predictors of driving errors, lapses, and violations

    Wickens, Christine M. / Toplak, Maggie E. / Wiesenthal, David L. | Elsevier | 2008