An Intelligent Video Analysis Method for Abnormal Event Detection in Intelligent Transportation Systems

Author(s):  
Shaohua Wan ◽  
Xiaolong Xu ◽  
Tian Wang ◽  
Zonghua Gu
2014 ◽  
Vol 926-930 ◽  
pp. 1314-1317 ◽  
Author(s):  
Li Yang

To solve the demand of real-time event detection in the RFID-based Intelligent Transportation Systems , using Complex Event Processing technology to establish a rule model to detect events.The model allows users to customize the Basic Events and Complex Events, using the rule files describe the complex events modes, clearly expressed the timing and gradation relationships between RFID events, meeting the needs of real-time event detection in the Intelligent Transportation System ,achieving the appropriate rules engine,. Finally, test and verify the effectiveness of the rules file and the rules engine model by experiments.


2012 ◽  
Vol 198-199 ◽  
pp. 1225-1230
Author(s):  
Jin Hui Lan ◽  
Min Guo ◽  
Xiao Jie Liu

Video event detection technology has become a hot issue in the Intelligent Transportation Systems(ITS) research. It mainly uses in highways, tunnels, urban roads and other video surveillance systems. This paper makes a brief overview on the development of video detection technology at home and abroad. It describes the working principles and key technologies of the two kinds of incident detection technology based on virtual detection loop and video vehicle tracking, compare above two technology to sum up their advantages and disadvantages. At last it introduces the typical products of the domestic and foreign video event detection technology, their applications and performance index.


2020 ◽  
Vol 19 (11) ◽  
pp. 2116-2135
Author(s):  
G.V. Savin

Subject. The article considers functioning and development of process flows of transportation and logistics system of a smart city. Objectives. The study identifies factors and dependencies of the quality of human life on the organization and management of stream processes. Methods. I perform a comparative analysis of previous studies, taking into account the uniquely designed results, and the econometric analysis. Results. The study builds multiple regression models that are associated with stream processes, highlights interdependent indicators of temporary traffic and pollution that affect the indicator of life quality. However, the identified congestion indicator enables to predict the time spent in traffic jams per year for all participants of stream processes. Conclusions. The introduction of modern intelligent transportation systems as a component of the transportation and logistics system of a smart city does not fully solve the problems of congestion in cities at the current rate of urbanization and motorization. A viable solution is to develop cooperative and autonomous intelligent transportation systems based on the logistics approach. This will ensure control over congestion, the reduction of which will contribute to improving the life quality of people in urban areas.


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