This study aimed to reveal the potential relationship between personal characteristics of e-bike riders and illegal occupation of motor vehicle lane. To this end, a questionnaire survey was conducted and 350 valid copies of responses were retrieved from the e-bike riders. Depending on the number of motor vehicle lanes occupied, the risky behavior of illegal occupation was divided into four intervals: intervals A, B, C, and D. The disaggregate theory has high adaptability to the analysis of individual traffic behavior. In this study, the multinomial logit model was used, and eight personal characteristics of e-bike riders were selected. The aforementioned four intervals were the four selection limbs, and a measurement model calculating the influence of personal characteristics on the behavior of illegal occupation was built. The theory of elasticity was employed to analyze the sensitivity degree of each influence factor. The results showed that the absolute values of elasticity of all tested influence factors, including age, educational level, and eye vision, were less than 1.000. However, on the four intervals, the elasticity of riders’ temperament was 1.203, 1.656, 1.554, and 1.355, respectively, and elasticity of riding proficiency was 2.782, 3.883, 3.453, and 2.932, respectively.


    Access

    Download


    Export, share and cite



    Title :

    Personal Characteristics of e-Bike Riders and Illegal Lane Occupation Behavior


    Contributors:
    Changxi Ma (author) / Jibiao Zhou (author) / Dong Yang (author) / Fuquan Pan (author) / Yuanyuan Fan (author)


    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    Riders' Control Behavior of Lane Change

    Nishimi, T. / Katayama, T. / Okayama, T. et al. | British Library Conference Proceedings | 1996


    Self-powered device for detecting illegal occupation of bus lane

    HE SHITONG / WANG HONGDE / WANG YAN | European Patent Office | 2021

    Free access

    Traffic Safety for Electric Bike Riders in China

    Yao, Lin / Wu, Changxu | Transportation Research Record | 2012