[1] Cai Yingfeng, Wang Hai, Zhang Weigong,. Video-based urban expressway traffic measurementand performance monitoring [J]. Journal of Southeast University (English Edition), 2011, 27 (2): 164-168. [doi:10.3969/j.issn.1003-7985.2011.02.010]
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Video-based urban expressway traffic measurementand performance monitoring(
)
基于视频的城市快速路交通流检测及车辆行为监控
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 27
- Issue:
- 2011 2
- Page:
- 164-168
- Research Field:
- Traffic and Transportation Engineering
- Publishing date:
- 2011-06-30
Info
- Title:
- Video-based urban expressway traffic measurementand performance monitoring
- 基于视频的城市快速路交通流检测及车辆行为监控
- Author(s):
- Cai Yingfeng; Wang Hai; Zhang Weigong
- School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
- Keywords:
- multi-vehicle tracking; flow analysis; anomaly detection; behavior understanding; video surveillance and monitoring(VSAM)
- PACS:
- U491
- DOI:
- 10.3969/j.issn.1003-7985.2011.02.010
- Abstract:
- This paper presents an urban expressway video surveillance and monitoring system for traffic flow measurement and abnormal performances detection. The proposed flow detection module collects traffic flow statistics in real time by leveraging multi-vehicle tracking information. Based on these online statistics, road operating situations can be easily obtained. Using spatiotemporal trajectories, vehicle motion paths are encoded by hidden Markov models. With path division and parameter matching, abnormal performance containing extra low or high speed driving, illegal stopping and turning are detected in real scenes. The traffic surveillance approach is implemented and evaluated on a DM642 DSP-based embedded platform. Experimental results demonstrate that the proposed system is feasible for the detection of vehicle speed, vehicle counts and road efficiency, and it is effective for the monitoring of the aforementioned anomalies with low computational costs.
- 提出一种针对城市快速路的视频监控系统, 完成交通流及道路异常行为检测.流量检测模块对车辆进行实时跟踪获得各类交通流统计数据, 实现快速路车辆运行状况的全面掌控.异常监控模块运用隐马尔科夫模型, 对带有时间和空间信息的车辆轨迹进行训练, 获得路径划分后对道路车辆轨迹进行参数匹配, 提取诸如超低(高)速行驶、违章停车、违规掉头等异常行为.所提监控算法在基于DSP的嵌入式DM642平台上得到应用和测试, 试验结果表明:系统能够完成包括车速、车流量、道路利用率等信息的检测, 并能对上述异常行为实施有效监控, 算法运算量低、鲁棒性好.
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Memo
- Memo:
-
Biographies: Cai Yingfeng(1985—), female, graduate; Zhang Weigong(corresponding author), male, doctor, professor, zhangwg@seu.edu.cn.
Foundation items: The National Key Technology R& D Program of China during the 11th Five-Year Plan Period(No.2009BAG13A04); Jiangsu Transportation Science Research Program(No.08X09); Program of Suzhou Science and Technology(No.SG201076).
Citation: Cai Yingfeng, Wang Hai, Zhang Weigong.Video-based urban expressway traffic measurement and performance monitoring[J].Journal of Southeast University(English Edition), 2011, 27(2):164-168.[doi:10.3969/j.issn.1003-7985.2011.02.010]