交通运输系统工程与信息

交通运输系统工程与信息 ›› 2012, Vol. 12 ›› Issue (3): 36-40.

• 智能交通系统与信息技术 • 上一篇    下一篇

伴随车检测技术应用研究

赵新勇，安实*   

  1. 哈尔滨工业大学 交通科学与工程学院，哈尔滨 150001
  • 收稿日期:2012-03-14 修回日期:2012-04-28 出版日期:2012-06-24 发布日期:2012-07-03
  • 作者简介:赵新勇（1968- ），男，江苏南通人，研究员，博士生.
  • 基金资助:

    “十一五”国家科技支撑计划项目（2009BAG13A06）.

Research on Accompanying Cars Recognition in Practical Application

ZHAO Xin-Yong, AN Shi   

  1. School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
  • Received:2012-03-14 Revised:2012-04-28 Online:2012-06-24 Published:2012-07-03

PDF

被引次数

9

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.

关键词: 交通工程, 车辆识别, 数据挖掘, 伴随车辆

Abstract:

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.

Key words: traffic engineering, vehicle recognition, data mining, accompanying cars

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