Real-time Highway Traffic Accident Prediction Based on the k-Nearest Neighbor Method

被引：35
|
作者：
Lv, Yisheng [1 ]
Tang, Shuming [2 ]
Zhao, Hongxia [1 ,3 ]
机构：
[1] Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
[2] Shandong Univ Sci & Technol, Qingdao, Peoples R China
[3] Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, VOL III | 2009年
关键词：
real-time accident prediction; highway accident prediction; k-nearest neighbor method; real-time traffic data; pattern classification;
D O I：
10.1109/ICMTMA.2009.657
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The occurrence of a highway traffic accident is associated with the short-term turbulence of traffic flow. In this paper, we investigate how to identify the traffic accident potential by using the k-nearest neighbor method with real-time traffic data. This is the first time the k-nearest neighbor method is applied in real-time highway traffic accident prediction. Traffic accident precursors and their calculation time slice duration are determined before classifying traffic patterns. The experimental results show the k-nearest neighbor method outperforming the conventional C-means clustering method.
引用
收藏
页码：547 / +
页数：2
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