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Research on the Relationship between the Individual Characteristics of Electric Bike Riders and Illegal Speeding Behavior: A Questionnaire-Based Study

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  • Changxi Ma

    (School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Jibiao Zhou

    (College of Transportation Engineering, Tongji University, Shanghai 200092, China
    Intelligent Transport System (ITS) R & D Center, Shanghai Urban Construction Design and Research Institute (Group) Co., Ltd., Shanghai 200125, China)

  • Dong Yang

    (School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Yuanyuan Fan

    (School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China)

Abstract

To examine the relationship between electric bike riders’ individual characteristics and their riding speed, this paper obtained 350 valid survey responses from e-bike riders using an on-site sampling survey method. Using the non-aggregate theory, we take the individual attributes of the rider’s age, driving age, personality, and corrective vision as potential influencing factors. The metric model of the influencing factors of the rider’s personal characteristics on riding speed is established, and we analyze the sensitivity of many influencing factors by using the theory of elasticity. The results show that the absolute value of the elasticity value corresponding to the rider’s gender, age, corrected visual acuity, and other factors is less than 1, which indicates that the above factors have no flexibility regarding the rider’s riding speed selection behavior. However, in four selection intervals, the elasticity values of the rider’s education level are 1.577, 2.484, 1.810, and 1.667; those of their driving age are −1.537, −2.061, −1.547, and −1.606, and those of their riding proficiency are 3.302, 12.038, 10.370, and 11.177, which indicate that the three factors of rider’s education level, driving age, and riding proficiency have a significant impact on the riding speed choice behavior. The finding of the study is helpful for the relevant government departments to formulate more accurate classified intervention measures, and effectively prevent the occurrence of illegal speeding behavior.

Suggested Citation

  • Changxi Ma & Jibiao Zhou & Dong Yang & Yuanyuan Fan, 2020. "Research on the Relationship between the Individual Characteristics of Electric Bike Riders and Illegal Speeding Behavior: A Questionnaire-Based Study," Sustainability, MDPI, Open Access Journal, vol. 12(3), pages 1-12, January.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:799-:d:311752
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    References listed on IDEAS

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    1. Cherry, Christopher R. & Yang, Hongtai & Jones, Luke R. & He, Min, 2016. "Dynamics of electric bike ownership and use in Kunming, China," Transport Policy, Elsevier, vol. 45(C), pages 127-135.
    2. Yanyong Guo & Yao Wu & Jian Lu & Jibiao Zhou, 2019. "Modeling the Unobserved Heterogeneity in E-bike Collision Severity Using Full Bayesian Random Parameters Multinomial Logit Regression," Sustainability, MDPI, Open Access Journal, vol. 11(7), pages 1-12, April.
    3. Cherry, Christopher & Cervero, Robert, 2007. "Use characteristics and mode choice behavior of electric bike users in China," Transport Policy, Elsevier, vol. 14(3), pages 247-257, May.
    4. Shen, Qing & Chen, Peng & Pan, Haixiao, 2016. "Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 31-44.
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