Issue 5
Oct.  2016
Turn off MathJax
Article Contents
BAO Xu, CHEN Jinwen. Identification of Overspeed Vehicles in Broadside Collision with Electric Bicycles[J]. Journal of Transport Information and Safety, 2016, 34(5): 31-37,67. doi: 10.3963/j.issn1674-4861.2016.05.005
Citation: BAO Xu, CHEN Jinwen. Identification of Overspeed Vehicles in Broadside Collision with Electric Bicycles[J]. Journal of Transport Information and Safety, 2016, 34(5): 31-37,67. doi: 10.3963/j.issn1674-4861.2016.05.005

Identification of Overspeed Vehicles in Broadside Collision with Electric Bicycles

doi: 10.3963/j.issn1674-4861.2016.05.005
  • Publish Date: 2016-10-28
  • In order to identify whether a vehicle is overspeed at braking moment in broadside collision with an electronic bicycle, a case study at one urban intersection is used to develop a method to identify the speed of a vehicle in a broadside side collision with an electric bicycle.According to the moment of a collision, it is divided into two stages: pre-collision and post-collision.Use the method for reverse reduction of accidents, the thrown distance and empirical formula of impact velocity are combined to propose a model to compute vehicles′ speed in collisions.The model of vehicles′ speed at braking moment is proposed by using the Work Energy Theorem based on the length of the brake trace.The simulations in PC-Crash software indicate that when the speed of vehicles at braking moment is 34-38 km/h, the error of identification is 1.47%;when the speed is 42-70 km/h, the error is less than 1.3%.The accuracy of identification is improved by 15.94% in the maximum when use the proposed method.Compare with GIDAS, this method can accurately analyze broadside collisions between vehicles and electronic bicycles, and identify whether the vehicle is overspeed or not.However, it is still necessary to improve the accuracy of identification when the speed of vehicle is 34-38 km/h.

     

  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (251) PDF downloads(0) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return