NDLI: Fast video-based queue length detection approach for self-organising traffic control

Content Provider	IET Digital Library
Author	Jiang, Tao Cai, Mingdai Zhang, Yulong Jia, Xiaojie
Abstract	With the development of traffic control theory, self-organising control has become one of the most promising techniques for traffic control. Among the various parameters of self-organising control, the queue length (number of vehicles) is a key one. Compared to the approaches using other detectors, vision-based approaches have a greater potential in queue length detection. However, the complicated traffic conditions (such as the changeable weather and the vehicle occlusion) and the large calculation of image processing have posed great challenges to the real-time application. Here, a fast video-based queue length detection approach is proposed. For each lane, according to the level of traffic congestion evaluated by the foreground area ratio, the corresponding vehicle counting method is adopted. When the traffic is determined congested, a fast area-based method for estimating the number of vehicles is adopted. Otherwise, a fast vehicle detection and counting method combining background difference and Adaboost classifier is adopted. The experiment results demonstrate that the proposed approach can handle actual traffic environment and has great potential for real-time application.
Starting Page	670
Ending Page	676
Page Count	7
ISSN	1751956X
Volume Number	13
e-ISSN	17519578
Issue Number	Issue 4, Apr (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/13/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2018.5073
Journal	IET Intelligent Transport Systems
Publisher Date	2018-12-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaboost Classifier Background Difference Complicated Traffic Condition Computer Vision And Image Processing Technique Fast Area-based Method Fast Vehicle Detection Fast Video-based Queue Length Detection Approach Image Classification Image Recognition Knowledge Engineering Technique Learning in AI Road Traffic Control Road Traffic System Control Self-organising Traffic Control Traffic Congestion Traffic Engineering Computing Vehicle Counting Method Video Signal Processing Vision-based Approach
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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