NDLI: Vehicle departure pattern and queue length prediction at an isolated intersection with automatic vehicle identity detection

Content Provider	IET Digital Library
Author	Li, Bo Yu, Zhi Huang, Liuhong Guo, Bowen
Abstract	Queue length is more likely to be affected by inefficient departure behaviour near the stop line at an intersection because of the prohibition of lane changes. The inefficient departure behaviour and its influence on the evolution of queue discharging in specific lanes have significant research value. In the past few years, the deployment of automatic vehicle identification (AVI) systems has made it possible to acquire information on vehicles’ passing through an intersection. Researchers can obtain individual driving information more accurately and effectively based on an analysis of AVI data. These high-resolution data have enabled the reconstruction and quantitative analysis of the influence of microscopic traffic behaviour. This study aims to model the departure of vehicle platoon and predict the queue length at isolated intersections. They propose a multi-layer gated recurrent unit (GRU) network to understand the mechanism of queue length evolution. A case study of vehicle departure pattern and queue length prediction is presented with AVI data obtained from an isolated intersection in Xuancheng, Anhui province, China for the first quarter of 2018. The results of the case study indicate that their work has good application prospects. The proposed multi-layer GRU network has potential to guide the signal scheme optimisation.
Starting Page	1804
Ending Page	1813
Page Count	10
ISSN	1751956X
Volume Number	13
e-ISSN	17519578
Issue Number	Issue 12, Dec (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/13/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2019.0117
Journal	IET Intelligent Transport Systems
Publisher Date	2019-09-25
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Vehicle Identification System Automatic Vehicle Identity Detection AVI Data Computer Vision And Image Processing Technique High-resolution Data Individual Driving Information Isolated Intersection Lane Changes Microscopic Traffic Behaviour Multilayer Gated Recurrent Unit Network Multilayer GRU Network Neural Computing Technique Object Detection Optical, Image And Video Signal Processing Queue Discharging Queue Length Prediction Queueing Theory Recurrent Neural Nets Road Traffic Road Vehicle Signal Scheme Optimisation Stop Line Traffic Engineering Computing Vehicle Departure Pattern Vehicle Platoon
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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