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Optimizing Traffic Signals in Smart Cities Based on Genetic Algorithm

Nagham A. Al-Madi*, Adnan A. Hnaif

Al-Zaytoonah University of Jordan, Faculty of Science and Information Technology, Amman, 11733, Jordan

* Corresponding Author: Nagham A. Al-Madi. Email: email

Computer Systems Science and Engineering 2022, 40(1), 65-74. https://doi.org/10.32604/csse.2022.016730

Abstract

Current traffic signals in Jordan suffer from severe congestion due to many factors, such as the considerable increase in the number of vehicles and the use of fixed timers, which still control existing traffic signals. This condition affects travel demand on the streets of Jordan. This study aims to improve an intelligent road traffic management system (IRTMS) derived from the human community-based genetic algorithm (HCBGA) to mitigate traffic signal congestion in Amman, Jordan’s capital city. The parameters considered for IRTMS are total time and waiting time, and fixed timers are still used for control. By contrast, the enhanced system, called enhanced-IRTMS (E-IRTMS), considers additional important parameters, namely, the speed performance index (SPI), speed reduction index (SRI), road congestion index (Ri), and congestion period, to enhance IRTMS decision. A significant reduction in congestion period was measured using E-IRTMS, improving by 13% compared with that measured using IRTMS. Meanwhile, the IRTMS result surpasses that of the current traffic signal system by approximately 83%. This finding demonstrates that the E-IRTMS based on HCBGA and with unfixed timers achieves shorter congestion period in terms of SPI, SRI, and Ri compared with IRTMS.

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APA Style
Al-Madi, N.A., Hnaif, A.A. (2022). Optimizing traffic signals in smart cities based on genetic algorithm. Computer Systems Science and Engineering, 40(1), 65-74. https://doi.org/10.32604/csse.2022.016730
Vancouver Style
Al-Madi NA, Hnaif AA. Optimizing traffic signals in smart cities based on genetic algorithm. Comput Syst Sci Eng. 2022;40(1):65-74 https://doi.org/10.32604/csse.2022.016730
IEEE Style
N.A. Al-Madi and A.A. Hnaif, “Optimizing Traffic Signals in Smart Cities Based on Genetic Algorithm,” Comput. Syst. Sci. Eng., vol. 40, no. 1, pp. 65-74, 2022. https://doi.org/10.32604/csse.2022.016730

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cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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