Driving safety is considered to have a strong relationship with traffic flow characteristics. However, very few studies have addressed the safety impacts in the three-phase traffic theory that has been demonstrated to be an advancement in explaining the empirical features of traffic flow. Another important issue affecting safety is driver experience heterogeneity, especially in developing countries experiencing a dramatic growth in the number of novice drivers. Thus, the primary objective of the current study is to develop a microsimulation environment for evaluating safety performance considering the presence of novice drivers in the framework of three-phase theory. First, a car-following model is developed by incorporating human physiological factors into the classical Intelligent Driver Model (IDM). Moreover, a surrogate safety measure based on the integration concept is modified to evaluate rear-end crashes in terms of probability and severity simultaneously. Based on a vehicle-mounted experiment, the field data of car-following behavior are collected by dividing the subjects into a novice group and an experienced group. These data are used to calibrate the proposed car-following model to explain driver experience heterogeneity. The results indicate that our simulation environment is capable of reproducing the three-phase theory, and the changes in the modified surrogate safety measure are highly correlated with traffic phases. We also discover that the presence of novice drivers leads to different safety performance outcomes across various traffic phases. The effect of driver experience heterogeneity is found to increase the probability of the rear-end crashes as well as the corresponding severity. The results of this study are expected to provide a scientific understanding of the mechanisms of crash occurrences and to provide application suggestions for improving traffic safety performance.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Simulation Study of Rear-End Crash Evaluation considering Driver Experience Heterogeneity in the Framework of Three-Phase Traffic Theory


    Beteiligte:
    Haifei Yang (Autor:in) / Yao Wu (Autor:in) / Huihui Xiao (Autor:in) / Yi Zhao (Autor:in)


    Erscheinungsdatum :

    2021




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt






    Characterising driver heterogeneity within stochastic traffic simulation

    Makridis, Michail A. / Anesiadou, Aikaterini / Mattas, Konstantinos et al. | Taylor & Francis Verlag | 2023

    Freier Zugriff

    Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types

    Qiang Luo / Xinqiang Chen / Jie Yuan et al. | DOAJ | 2020

    Freier Zugriff

    Impact of heterogeneity of car-following behavior on rear-end crash risk

    Zhang, Junjie / Wang, Yunpeng / Lu, Guangquan | Elsevier | 2019