Highlights A duration modeling approach of accumulated distances between crashes is used to evaluate automated vehicle safety. Conventional vehicle crashes sourced from the naturalistic driving study are considered as the benchmark. Statistical tests are conducted to statistically assess differences between automated and conventional vehicles. The existing level 3 of automation is shown to be safer than conventional vehicles with 95 % confidence. Automated vehicles have roughly 27 % more miles bewteen crashes than conventional.

    Abstract Ideally, the evaluation of automated vehicles would involve the careful tracking of individual vehicles and recording of observed crash events. Unfortunately, due to the low frequency of crash events, such data would require many years to acquire, and potentially place the motorized public at risk if defective automated technologies were present. To acquire information on the safety effectiveness of automated vehicles more quickly, this paper uses the collective crash histories of a group of automated vehicles, and applies a duration modeling approach to the accumulated distances between crashes. To demonstrate the applicability of this approach as a method compare automated and conventional vehicles (human drivers), an empirical assessment was undertaken using two comparable sources of data. For conventional vehicles, police and non-police-reportable crashes were collected from the Second Strategic Highway Research Program’s naturalistic driving study, and for automated vehicles, data from the California Department of Motor Vehicles Autonomous Vehicle Tester program were used (105 crashes from 59 permit holders driving ∼2.8 million miles were used for the analysis). The results of the empirical study showed that automated driving was safer at the 95% confidence level, with a higher number of miles between crashes, relative to their conventional vehicle counterparts. The findings indicate that the number of miles between crashes would be increased by roughly 27% when switching from conventional vehicles to automated vehicles. Despite limited data which mandated a group-vehicle approach, this study can be considered a reasonable initial approximation of automated vehicle safety.


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    Titel :

    Assessing the collective safety of automated vehicle groups: A duration modeling approach of accumulated distances between crashes


    Beteiligte:
    Sohrabi, Soheil (Autor:in) / Lord, Dominique (Autor:in) / Dadashova, Bahar (Autor:in) / Mannering, Fred (Autor:in)


    Erscheinungsdatum :

    2023-12-29




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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