Severity Analyses of Single-Vehicle Crashes Based on Rough Set Theory

被引：2
|
作者：
Wu, Chaozhong [1 ]
Lei, Hu [1 ]
Ma, Ming [1 ]
Yan, Xinping [1 ]
机构：
[1] Wuhan Univ Technol, MOE, Engn Res Ctr Transportat Safety, Wuhan 430070, Peoples R China
来源：
PROCEEDINGS OF THE 2009 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND NATURAL COMPUTING, VOL II | 2009年
关键词：
rough sets; single-vehicle crash; severity; cross-validation; transportation safety; FIXED ROADSIDE OBJECTS; COLLISIONS; DRIVERS;
D O I：
10.1109/CINC.2009.185
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A single-vehicle crash is a typical pattern of traffic accidents and tends to cause heavy loss. The purpose of this study is to identify the factors significantly influencing single-vehicle crash injury severity, using a data selected from Beijing city for a 4-year period. Rough set theory was applied to complete the injury severity analysis, and followed by applying cross-validation method to estimate the prediction accuracy of extraction rules. Results show that it is effective for analyzing the severity of Single-vehicle crashes with rough set theory.
引用
收藏
页码：59 / 62
页数：4
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