摘要
海量动态交通流中,经常出现结伴而行的车辆.特定区域内,当结伴车辆出现的概率较大时,即可将其视为伴随车辆,这类车辆具有相互掩护和团伙作案的重大嫌疑.及早检测和识别伴随车辆,能有效降低道路交通安全系统中的危险因素,对预防和减少与道路有关的治安和刑事案件,也具有十分重要的意义.本文在车牌自动识别数据库基础上,应用数据挖掘技术,提出伴随车辆检测和识别算法,并进行了实地测试.实验结果表明:应用数据挖掘技术对伴随车辆进行分析检测,具有检测效率高、检测误差小、应用范围广的特点,完全可以满足刑侦等部门对伴随嫌疑车辆进一步排查的需要.
In massive dynamic traffic flows, it is very common to see the cars moving in a queue. In some scenarios, these cars are regarded as accompanying cars and suspected of gang crime support each other when that condition occurs in a high rate. It is very important to identify the accompanying vehicles as early as possible and to reduce potential risks of road traffic system and to reduce road-related public security cases and criminal cases. Based on the automatic license plate recognition database and data mining technology, this paper proposes a set of algorithms in identifying accompanying cars and a field test is conducted. The results demonstrate the performance of the algorithm with effectiveness, low detection error, wide application and capability for further investigation.
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2012年第3期36-40,共5页
Journal of Transportation Systems Engineering and Information Technology
基金
'十一五'国家科技支撑计划项目(2009BAG13A06)
关键词
交通工程
车辆识别
数据挖掘
伴随车辆
traffic engineering
vehicle recognition
data mining
accompanying cars
