This study provides potential safety considerations and infrastructure needs that will support the mass adoption of autonomous vehicle (AV) and connected vehicle (CV) technologies in the motor carrier industry. Using large truck crash data from 2013 through 2015 obtained from the Missouri State Highway Patrol, chi-square automatic interaction detection (CHAID) decision trees were estimated to examine the effect of AV and CV technologies on motor carrier crash severity. Results suggest that the greatest contributory predictors of crash severity outcomes are driving too fast for conditions, distracted/inattentive driving, overcorrecting, and driving under the influence of alcohol. If these circumstances are altered by AV and CV technologies, it is suggested that between 117 and 193 severe crashes involving large trucks could be prevented annually in Missouri alone. To render such safety benefits, key vehicle needs include autonomously controlling acceleration and steering, monitoring of the environment, and responding to dynamic driving environments without the need for human intervention. Importantly, the safe operations of a system that can perform such AV and CV tasks require readable lane markings, traffic signals and signs, managed or dedicated lane usage, and dedicated refueling and/or recharging facilities.


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    Titel :

    Paving the Way for Autonomous and Connected Vehicle Technologies in the Motor Carrier Industry


    Beteiligte:
    J. M. B. Bracy (Autor:in) / K. Bao (Autor:in) / R. A. Mundy (Autor:in)

    Erscheinungsdatum :

    2018


    Format / Umfang :

    26 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch