会议专题

Incident Duration Model on Urban Freeways Using Three Different Algorithms of Decision Tree

Effective incident management requires accurate prediction of incident duration. In this paper, Classification and Regression Tree (CART), CHAID and Exhaustive CHAID is employed to model the incident duration. All 65000 incident records from Beijing Transportation Management Bureau are used for model establishment and another 8000 records for validation. The average relative error of the CART model is 29.5197% while CHAID is 30.78%; Exhaustive CHAID is 31.23%.1t shows that the reliability of the three models is quite satisfactory. The average relative error of the prediction on different ring roads of Beijing is approximately the same.

Decision tree Classification and regression tree Incident duration CHAID Exhaustive CHAID

Li Ruimin Zhao Xiaoqiang YU Xinxin Li Junwei Cheng Nan Zhang Jie

Institute of Transportation Engineering, Tsinghua University Beijing, China

国际会议

2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

长沙

英文

1696-1698

2010-05-11(万方平台首次上网日期,不代表论文的发表时间)