Intra-driver heterogeneity is defined as transition of driver’s behavior between usual and unusual, which is an intrinsic feature of drivers while yet to be extensively explored. This study used a large-scale naturalistic driving data set to investigate intra-driver heterogeneity in car-following. We constructed an IDM-based baseline model to represent a driver’s usual behavior; by measuring difference between observed behavior with baseline, unusual behavior was identified. Then, multi-level logit model with random effects was fitted to uncover contributing factors. Among 41 drivers’ 1356 trips, intra-driver heterogeneity was identified in 3194 episodes, which accounts for 15% of the time. Within investigated 24 factors, we found that intra-driver heterogeneity was statistically related with vehicle kinematic features, then traffic flow and surrounding environment, but not driver sociodemographics. Being cut in is the most prominent trigger for intra-driver heterogeneity. These findings garner some remarkable insights into improvement of car-following modeling and many other engineering practices.


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    Title :

    Investigating the intra-driver heterogeneity in car following behaviour based on large-scale naturalistic driving study


    Contributors:
    Rao, Hongyu (author) / Zhang, Duo (author) / Qin, Guoyang (author) / Yue, Lishengsa (author) / Sun, Jian (author)

    Published in:

    Publication date :

    2023-12-31


    Size :

    21 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown








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    Sangster, John / Rakha, Hesham / Du, Jianhe | Transportation Research Record | 2013