Various disruptions such as natural disasters, malevolent attacks, and emergencies are still inevitably posing threats on road networks in the driverless environment. However, most studies have focused on the impacts of micro mixed traffic flow characteristics, which cannot explicitly measure road network vulnerability in driverless environment. This paper develops a bi-objective framework to construct driverless environment based on travel demand. An improved accessibility-based methodology integrating traffic flow and driverless conditions evaluates the vulnerability of road network under disruptions. The proposed methodology was applied to the highway network in Florida, USA. Results demonstrate that the vulnerability of road network would be decreased with the increase of the penetration rate of autonomous vehicles. When the penetration rate gets in the range of 40%–80%, network vulnerability would significantly reduce, and they show linear relationship. Findings of this study could provide new sights into managing and planning driverless road network in future.


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    Title :

    An Assessment of Driverless-Oriented Road Network Vulnerability under Disruptions


    Contributors:
    Yan, Ke (author) / Xu, Peng-Cheng (author) / Zhang, Lei (author) / Lu, Qing-Chang (author) / Cui, Xin (author) / Qin, Han (author)

    Conference:

    22nd COTA International Conference of Transportation Professionals ; 2022 ; Changsha, Hunan Province, China


    Published in:

    CICTP 2022 ; 2410-2422


    Publication date :

    2022-09-08




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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