Comparative analysis & modelling for riders’ conflict avoidance behavior of E-bikes and bicycles at un-signalized intersections
journal contributionposted on 17.02.2020 by Ling Huang, Jianping Wu, Ronghui Zhang, Dezong Zhao, Yinhai Wang
Any type of content formally published in an academic journal, usually following a peer-review process.
With the increasing popularity of electric-assist bikes (E-bikes) in China, U.S. and Europe, the corresponding safety issues at intersections have attracted the attention of researchers. Understanding the microscopic behavior of E-bike riders during conflicts with other road users is fundamental for safety improvement and simulation modeling of E-bikes at intersections. This study compared the conflict avoidance behaviors of E-bike and conventional bicycle riders using field data extracted from video recordings of different intersections. The impact of conflicting road user type and gender on E-bikes and bicycles were analyzed. Compared with bicycles, E-bikes appeared to enable more flexibility in conflict avoidance behavior. For example, E-bikes would behave like bicycles when conflicting with motor vehicles/Ebikes, and behave more like motor vehicles when conflicting with bicycles/pedestrians. Based on this, we built an Extended Cyclist Conflict Avoidance Movement (ECCAM) model, which can represent the conflict avoidance behavior of E-bikes/bicycles at mixed traffic flow un-signalized intersections. Field data were applied to validate the proposed model, and the results are promising.
Autonomous Optimization of Powertrain Systems using Cloud-Aided Learning : EP/S001956/1
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering