The importance of using adaptive traffic signal control for figuring out the unpredictable traffic congestion in today’s metropolitan life cannot be overemphasized. The vehicular ad hoc network (VANET), as an integral component of intelligent transportation systems (ITSs), is a new potent technology that has recently gained the attention of academics to replace traditional instruments for providing information for adaptive traffic signal controlling systems (TSCSs). Meanwhile, the suggestions of VANET-based TSCS approaches have some weaknesses: (1) imperfect compatibility of signal timing algorithms with the obtained VANET-based data types, and (2) inefficient process of gathering and transmitting vehicle density information from the perspective of network quality of service (QoS). This paper proposes an approach that reduces the aforementioned problems and improves the performance of TSCS by decreasing the vehicle waiting time, and subsequently their pollutant emissions at intersections. To achieve these goals, a combination of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications is used. The V2V communication scheme incorporates the procedure of density calculation of vehicles in clusters, and V2I communication is employed to transfer the computed density information and prioritized movements information to the road side traffic controller. The main traffic input for applying traffic assessment in this approach is the queue length of vehicle clusters at the intersections. The proposed approach is compared with one of the popular VANET-based related approaches called MC-DRIVE in addition to the traditional simple adaptive TSCS that uses the Webster method. The evaluation results show the superiority of the proposed approach based on both traffic and network QoS criteria.
Original Version 
(at publishers web site)
BibTeX 
Erfan Shaghaghi
Mohammad Reza Jabbarpour
Rafidah Md Noor
Hwasoo Yeo
Jason J. Jung
@article{shaghaghi2017adaptive,
author = {Shaghaghi, Erfan and Jabbarpour, Mohammad Reza and Md Noor, Rafidah and Yeo, Hwasoo and Jung, Jason J.},
doi = {10.1631/FITEE.1500355},
issn = {2095-9230},
journal = {Frontiers of Information Technology & Electronic Engineering},
month = {3},
number = {3},
pages = {373--393},
publisher = {Springer},
title = {{Adaptive green traffic signal controlling using vehicular communication}},
volume = {18},
year = {2017},
}
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