Traffic Signaling optimization for Intelligent and Green Transportation in Smart Cities

Balta, Musa; Özçeli̇k, İbrahim

doi:10.1109/ubmk.2018.8566333

Cited by 6 publications

(1 citation statement)

References 15 publications

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“…Real-time DRLE decreases the convergence time by 65.66% compared to PPO and training steps by 79.44% compared to ARS and ES. [20] Ant Colony Optimization, SUMO, VANET Real-time 20-25% improvement in delays. Decrease of 14-18% in CO emissions, 15-21% fuel consumption, 7-9% noise rate.…”

Section: Discussionmentioning

confidence: 99%

A Bibliometric Review and Analysis of Traffic Lights Optimization

Witeck

Rocha

Silva

et al. 2022

Computational Science and Its Applications – ICCSA 2022 Workshops

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The significant increase in the number of vehicles in urban areas emerges the challenge of urban mobility. Researchers in this area suggest that most daily delays in urban travel times are caused by intersections, which could be reduced if the traffic lights at these intersections were more efficient. The use of simulation for real intersections can be effective in optimizing the cycle times and improving the traffic light timing to coordinate vehicles passing through intersections. From these themes emerge the research questions: How are the existing approaches (optimization techniques and simulation) to managing traffic lights smartly? What kind of data (offline and online) are used for traffic lights optimization? How beneficial is it to propose an optimization approach to the traffic system? This paper aims to answer these questions, carried out through a bibliometric literature review. In total, 93 articles were analyzed. The main findings revealed that the United States and China are the countries with the most studies published in the last ten years. Moreover, Particle Swarm Optimization is a frequently used approach, and there is a tendency for studies to perform optimization of real cases by real-time data, showing that the praxis of smart cities has resorted to smart traffic lights.

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Section: Discussionmentioning

confidence: 99%