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Computer vision-guided intelligent traffic signaling for isolated intersections

Authors
Kumaran S.K.Mohapatra S.Dogra D.P.Roy P.P.Kim B.-G.
Issue Date
Nov-2019
Publisher
Elsevier Ltd
Keywords
Dirichlet process mixture model; Isolated intersections; Traffic signal timing; Unsupervised machine learning; Visual surveillance
Citation
Expert Systems with Applications, v.134, pp.267 - 278
Journal Title
Expert Systems with Applications
Volume
134
Start Page
267
End Page
278
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/2751
DOI
10.1016/j.eswa.2019.05.049
ISSN
0957-4174
Abstract
Computer vision-guided traffic management is an emerging area of research. Intelligent traffic signal control using computer vision is a less explored area of research. In this paper, we propose a new approach of traffic flow-based intelligent signal timing by temporally clustering optical flow features of moving vehicles using Temporal Unknown Incremental Clustering (TUIC) model. First, we propose a new inference scheme that works approximately 5-times faster as compared to the one originally proposed in TUIC in a dense traffic intersection. The new inference scheme can trace clusters representing moving objects that may be occluded while being tracked. Cluster counts of approach roads have been used for signal timing for traffic intersections. It is done by detecting cluster motion inside the regions-of-interest (ROI) marked at the entry and exit locations of intersection approaches. Departure rates are learned using Gaussian regression to parameterize traffic variations. Using the learned parameters as a function of cluster count, an adaptive signal timing algorithm, namely Throughput and Average Waiting Time Optimization (TAWTO) has been proposed. Experimental results reveal that the proposed method can achieve better average waiting time and throughput as compared to the state-of-the-art signal timing algorithms. We intend to publish two datasets as part of this work for enabling the research community to explore computer vision aided solutions for typical problems such as intelligent traffic controlling, violation detection in chaotic road intersections, etc. © 2019 Elsevier Ltd
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