Incident Duration Model on Urban Freeways Based on Classification and Regression Tree

摘要：

Effective incident management requires accurate prediction of incident duration. In this paper, Classification and Regression Tree (CART) 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％. it shows that the reliability of the model is quite satisfactory. The average relative error of the prediction on different ring roads of Beijing is approximately the same.

关键词： Decision tree Classification and regression tree Incident duration Mutiple linear regression

作者: Zhao Xiaoqiang Li Ruimin YU Xinxin

作者单位: Institute of Transportation Engineering, Tsinghua University Beijing, China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 2551-2554

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）