Fuzzy Traffic Control with Vehicle-to-Everything Communication
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Department of Information Systems, College of Computer Sciences and Information Technology, University of Anbar, 55431 Baghdad, 55 Ramadi, Anbar, Iraq
2
Computer Engineering Department, Ankara Yildirim Beyazit University, 06010 Ankara, Turkey
3
Computer Engineering Department, Gazi University, 06570 Ankara, Turkey
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(2), 368; https://doi.org/10.3390/s18020368
Received: 30 November 2017
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Revised: 4 January 2018
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Accepted: 19 January 2018
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Published: 27 January 2018
(This article belongs to the Special Issue Sensor Networks for Smart Roads)
Traffic signal control (TSC) with vehicle-to everything (V2X) communication can be a very efficient solution to traffic congestion problem. Ratio of vehicles equipped with V2X communication capability in the traffic to the total number of vehicles (called penetration rate PR) is still low, thus V2X based TSC systems need to be supported by some other mechanisms. PR is the major factor that affects the quality of TSC process along with the evaluation interval. Quality of the TSC in each direction is a function of overall TSC quality of an intersection. Hence, quality evaluation of each direction should follow the evaluation of the overall intersection. Computational intelligence, more specifically swarm algorithm, has been recently used in this field in a European Framework Program FP7 supported project called COLOMBO. In this paper, using COLOMBO framework, further investigations have been done and two new methodologies using simple and fuzzy logic have been proposed. To evaluate the performance of our proposed methods, a comparison with COLOMBOs approach has been realized. The results reveal that TSC problem can be solved as a logical problem rather than an optimization problem. Performance of the proposed approaches is good enough to be suggested for future work under realistic scenarios even under low PR.
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Keywords:
traffic signal control; V2X communication; intersection; fuzzy system; acceleration and stopped delay; traffic policy
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MDPI and ACS Style
Salman, M.A.; Ozdemir, S.; Celebi, F.V. Fuzzy Traffic Control with Vehicle-to-Everything Communication. Sensors 2018, 18, 368. https://doi.org/10.3390/s18020368
AMA Style
Salman MA, Ozdemir S, Celebi FV. Fuzzy Traffic Control with Vehicle-to-Everything Communication. Sensors. 2018; 18(2):368. https://doi.org/10.3390/s18020368
Chicago/Turabian StyleSalman, Muntaser A., Suat Ozdemir, and Fatih V. Celebi. 2018. "Fuzzy Traffic Control with Vehicle-to-Everything Communication" Sensors 18, no. 2: 368. https://doi.org/10.3390/s18020368
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