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LI Cong-ying, SHAO Zhuang-zhuang, FENG Shao-shuai, WANG Xiao-kun, JIA Jin-xiu, TAN Qian. Physiology, psychology and comprehensive loading perception models of cyclists[J]. Journal of Traffic and Transportation Engineering, 2020, 20(1): 181-191. doi: 10.19818/j.cnki.1671-1637.2020.01.015
Citation: LI Cong-ying, SHAO Zhuang-zhuang, FENG Shao-shuai, WANG Xiao-kun, JIA Jin-xiu, TAN Qian. Physiology, psychology and comprehensive loading perception models of cyclists[J]. Journal of Traffic and Transportation Engineering, 2020, 20(1): 181-191. doi: 10.19818/j.cnki.1671-1637.2020.01.015
shu

Physiology, psychology and comprehensive loading perception models of cyclists

doi: 10.19818/j.cnki.1671-1637.2020.01.015
  • 1.

    School of Civil Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, Shaanxi, China

  • 2.

    MOE key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China

  • 3.

    Department of Civil and Environment Engineering, Rensselaer Polytechnic Institute, Albany 12180, New York State, USA

  • 4.

    Xi'an Municipal Engineering Design and Research Institute Co., Ltd.Xi'an 710068, Shaanxi, China

More Information
  • Author Bio:

    LI Cong-ying(1977-), female, associate professor, PhD, licongying@126.com

  • Corresponding author: JIA Jin-xiu(1977-), female, senior engineer, PhD, 313848588@qq.com
  • Received Date: 2019-07-21
  • Publish Date: 2020-02-25
    Abstract
  • In order to explore the influence mechanisms of cyclists' physiological and psychological states on the individual attributes, cycling intensity and environment during the cycling process, the cycling experiment was designed and implemented. The relative metabolism rate, mood state, self-induced fatigue and task load index were selected to analyze the features and mechanisms of the cyclists' physiological, psychological and comprehensive loading perception. Based on the cycling experiment data, the physiological, psychological and comprehensive loading perception models were established by partial least-squares regression method, and the forecasting abilities of the models were also tested. Analysis result shows that cyclists' individual attributes, cycling intensity and environment all have impacts on cyclists' loading perception. Body mass index and basal metabolic rate play significant roles in individual attribute factors of cyclists, the average influence factors in the loading perception model are 0.121 and 0.112, respectively. Cycling time has the largest influence on loading perception among the cycling intensity factors, with an average influence factor of 0.139. Among the cycling environmental factors, the number of intersections has the most significant influence on cycling loading perception, with an average influence factor of 0.137. Each variable has the same influence tendency on psychological load and comprehensive load perception, but has different influence tendency on physiological load and comprehensive load. Therefore, paying more attention to some factors and the psychological load of cyclists has certain effects on improving the service level of cycles, and the research results can be applied to improve the environment of cycling facilities.

     

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