American Society of Civil Engineers


Urban Road Traffic Incident Auto-Detecting Based on Decision Fusion


by Changjiang Zheng, (College of Civil and Transportation Engineering Hohai University, Xi Kang Road #1, Nanjing, China, 210098. E-mail: zhenghhu@sina.com), Qiang Zhou, (College of Civil and Transportation Engineering Hohai University, Xi Kang Road #1, Nanjing, China 210098. E-mail: 304907836@qq.com), Shuyan Chen, (School of Transportation, Southeast University, Si Pai Lou #2, Nanjing, China, 210096. E-mail: chenshuyan@seu.edu.cn), and Zhangxiao Yu, (College of Civil and Transportation Engineering, Hohai University, Xi Kang Road #1, Nanjing, China, 210098. E-mail: yzx_jiafeimao@163.com)
Section: Intelligent Transportation Systems, pp. 1348-1359, (doi:  http://dx.doi.org/10.1061/41186(421)134)

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Document type: Conference Proceeding Paper
Part of: ICCTP 2011: Towards Sustainable Transportation Systems
Abstract: The objective of this study is to improve the performance of traffic incident detection algorithms on urban roads. The concept of algorithm performance reliability is introduced to make decision fusion which combines the results of the automatic incident detection algorithm based on floating car data and inductive loop detector data. The decision fusion algorithm in this article includes three modules: 1) Detection algorithm module based on inductive loop detector data; 2) Detection algorithm module based on floating car data; 3) Module of decision fusion, introduce the concept of algorithm reliability, calculate the weights of module, and use the weighted average method to make decision fusion. Finally, VISSIM simulation system was used to get the traffic flow data, and implement the algorithm using MATLAB. The simulation results show the algorithm of decision fusion is better than automatic incident detection algorithm of single data-source.


ASCE Subject Headings:
Traffic accidents
Urban areas