To answer the impact of traffic flow around the bottleneck of the expressway on the transition time of human-machine takeover, and to ensure that drivers can safely takeover the vehicle, it is necessary to analyze the mechanism of different traffic flows on the transition time of taking over. Based on UC-win/road, the bottleneck of the expressway was designed, and a driving simulator was used to conduct a man-machine switching test. A total of 47 people participated in the experiment (33 males and 14 females). The average age of the participants was 23.91 years, the standard deviation was 1.09 years, and the average driving experience was 2.43 years. Participants observed the surrounding traffic conditions after receiving the takeover request from the intelligent car and then took over the vehicle. The results of the study show that different volumes and speeds have a significant impact on the transition time of takeover $(\mathrm{F}\ (8,407) =6.314,\ \mathrm{p} < 0.05)$. When the magnitude of the expressway's bottleneck increases, the takeover's transition time increases, but the growth of the driving speed will reduce the transition time of the takeover. At the same time, the surrounding vehicles of the ego vehicle have a significant impact on the transition time of the takeover. The specific manifestation is that when the longitudinal distance between the front and rear of the ego vehicle in the left lane is less than 50 meters, the transition time of the takeover is significantly increased. As the longitudinal distance from the front and rear of the ego vehicle in the left lane increases, the takeover transition time decreases. This study provides theoretical support for the transition time of conditional autonomous vehicles.


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    Title :

    Influence of Traffic Flow Around the Intelligent Vehicle on Takeover Time in a Bottleneck of the Expressway


    Contributors:
    Liu, Qingchao (author) / Xu, Tianyu (author) / Cai, Yingfeng (author) / Chen, Long (author)


    Publication date :

    2021-10-15


    Size :

    5427290 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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