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Comparative analysis & modelling for riders’ conflict avoidance behavior of E-bikes and bicycles at un-signalized intersections

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journal contribution
posted on 2020-02-17, 13:18 authored by Ling Huang, Jianping Wu, Ronghui Zhang, Dezong Zhao, Yinhai Wang
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.

Funding

Autonomous Optimization of Powertrain Systems using Cloud-Aided Learning : EP/S001956/1

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Intelligent Transportation Systems Magazine

Volume

13

Issue

4

Pages

131 - 145

Publisher

IEEE

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Publication date

2020-01-31

Copyright date

2021

ISSN

1939-1390

eISSN

1941-1197

Language

  • en

Depositor

Dr Dezong Zhao Deposit date: 15 February 2020

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