计算机科学与探索Issue(1)：111-120,10.DOI:10.3778/j.issn.1673-9418.1306016
离群点挖掘技术在交通事件检测中的应用
Research on Traffic Incident Detection with Outlier Mining Technology
摘要
Abstract
Traffic incident detection and confirmation is the primary problem in traffic incident management, but detection method based on loop detector and video data is restricted in practical applications due to the high cost and inefficiency. This paper proposes a traffic incident detection algorithm based on outlier mining by use of feature vector related to traffic incident. The feature vector is obtained from the traffic information processed by the float car technology. The algorithm is simple, efficient, and easy to deploy. The experimental results show that the algorithm has higher accuracy than the pattern recognition method, and can effectively distinguish between the conventional congestion and traffic incident.关键词
交通事件/浮动车/特征分析/离群检测Key words
traffic incident/floating car data/feature analysis/outlier mining分类
信息技术与安全科学引用本文复制引用
诸彤宇,王奇,高梦丹..离群点挖掘技术在交通事件检测中的应用[J].计算机科学与探索,2014,(1):111-120,10.基金项目
The National High Technology Research and Development Program of China under Grant No.2012AA12A207(国家高技术研究发展计划(863计划)) （国家高技术研究发展计划(863计划）
