Traffic signal optimization with Particle Swarm Optimization for signalized roundabouts

Gökçe, Mahmut Ali; Öner, Erdinç; Işık, Gül

doi:10.1177/0037549715581473

Cited by 34 publications

(12 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The algorithms performed well both for undersaturated and oversaturated traffic conditions. Gokcxe and Isxık proposed a microscopic traffic simulator VISSIM-based PSO model for optimizing vehicle delay and traffic throughput using field data from28 signalized roundabout in Izmir, Turkey [64]. The simulation tool was used to evaluate the solutions obtained by PSO.…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Metaheuristics for Traffic Control and Optimization: Current Challenges and Prospects

Jamal¹,

Al-Ahmadi²,

Butt³

et al. 2023

Search Algorithm - Essence of Optimization

View full text Add to dashboard Cite

Intelligent traffic control at signalized intersections in urban areas is vital for mitigating congestion and ensuring sustainable traffic operations. Poor traffic management at road intersections may lead to numerous issues such as increased fuel consumption, high emissions, low travel speeds, excessive delays, and vehicular stops. The methods employed for traffic signal control play a crucial role in evaluating the quality of traffic operations. Existing literature is abundant, with studies focusing on applying regression and probability-based methods for traffic light control. However, these methods have several shortcomings and can not be relied on for heterogeneous traffic conditions in complex urban networks. With rapid advances in communication and information technologies in recent years, various metaheuristics-based techniques have emerged on the horizon of signal control optimization for real-time intelligent traffic management. This study critically reviews the latest advancements in swarm intelligence and evolutionary techniques applied to traffic control and optimization in urban networks. The surveyed literature is classified according to the nature of the metaheuristic used, considered optimization objectives, and signal control parameters. The pros and cons of each method are also highlighted. The study provides current challenges, prospects, and outlook for future research based on gaps identified through a comprehensive literature review.

show abstract

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Metaheuristics for Traffic Control and Optimization: Current Challenges and Prospects

Jamal¹,

Al-Ahmadi²,

Butt³

et al. 2023

Search Algorithm - Essence of Optimization

View full text Add to dashboard Cite

show abstract

“…A correta temporização dos semáforos ajuda a reduzir o congestionamento e a melhorar o fluxo de veículos. (Gökçe et al, 2015). Estratégias de controle de tráfego também podem ser classificadas como sendo de "tempo fixo" e de "tempo real".…”

Section: Revisão Da Literaturaunclassified

Aplicação de simulação de eventos discretos para melhorar o tráfego veicular numa região semaforizada do município de Uberaba – MG

Nascimento

Miranda

2022

Exacta

View full text Add to dashboard Cite

Este trabalho propõem um modelo de simulação para um conjunto de cruzamentos semaforizados de uma área localizada na região central de Uberaba-MG, com o objetivo de determinar valores para os tempos dos semáforos que permitam melhorar o fluxo de veículos. Para isto, descreve-se a dinâmica de funcionamento do sistema real, de modo a identificar as regras e comportamentos a serem incluídos no modelo de simulação, implementado via software Arena. Após a validação do modelo, realizou-se uma série de experimentos comparando diferentes cenários, incluindo experimentos fatorais; seguido por experimentos de otimização dos valores de tempo dos semáforos. O estudo de caso mostra que o tempo atual dos semáforos pode ser alterado de forma a permitir uma melhora de desempenho de até 24%; também se verifica que o Arena pode ser utilizado para a modelagem adequada de múltiplas vias, e que é possível ter uma solução prática, utilizável no mundo real.

show abstract

“…Reference numbers [29][30][31][32][33][34] employ meta-heuristic methods for optimization along with a microsimulation tool. Among the meta-heuristics implementations, population-based methods were mostly employed, where PSO, ACO, and GA are the most heavily utilized methods.…”

Section: Metaheuristics Based Approachesmentioning

confidence: 99%

“…Gökçe et al [29], Dabiri and Abbas [30], Panovski and Zaharia [31], Chuo et al [35] utilized PSO for the fulfillment of their objectives. Among them, [29] is the only study that has been carried out for the signalized roundabout containing 28 signal heads, whereas [30,31] worked on optimizing the arterial traffic signals having three intersections and the issues related with traffic flow management in the urban areas respectively. Jintamuttha, et al [33] proposed a finite-interval model to achieve the objective regarding TST.…”

Section: Metaheuristics Based Approachesmentioning

confidence: 99%

See 1 more Smart Citation

State-of-art review of traffic signal control methods: challenges and opportunities

Qadri

Gökçe

Öner

2020

Eur. Transp. Res. Rev.

117

View full text Add to dashboard Cite

Introduction Due to the menacing increase in the number of vehicles on a daily basis, abating road congestion is becoming a key challenge these years. To cope-up with the prevailing traffic scenarios and to meet the ever-increasing demand for traffic, the urban transportation system needs effective solution methodologies. Changes made in the urban infrastructure will take years, sometimes may not even be feasible. For this reason, traffic signal timing (TST) optimization is one of the fastest and most economical ways to curtail congestion at the intersections and improve traffic flow in the urban network. Purpose Researchers have been working on using a variety of approaches along with the exploitation of technology to improve TST. This article is intended to analyze the recent literature published between January 2015 and January 2020 for the computational intelligence (CI) based simulation approaches and CI-based approaches for optimizing TST and Traffic Signal Control (TSC) systems, provide insights, research gaps and possible directions for future work for researchers interested in the field. Methods In analyzing the complex dynamic behavior of traffic streams, simulation tools have a prominent place. Nowadays, microsimulation tools are frequently used in TST related researches. For this reason, a critical review of some of the widely used microsimulation packages is provided in this paper. Conclusion Our review also shows that approximately 77% of the papers included, utilizes a microsimulation tool in some form. Therefore, it seems useful to include a review, categorization, and comparison of the most commonly used microsimulation tools for future work. We conclude by providing insights into the future of research in these areas.

show abstract

Traffic signal optimization with Particle Swarm Optimization for signalized roundabouts

Cited by 34 publications

References 26 publications

Metaheuristics for Traffic Control and Optimization: Current Challenges and Prospects

Metaheuristics for Traffic Control and Optimization: Current Challenges and Prospects

Aplicação de simulação de eventos discretos para melhorar o tráfego veicular numa região semaforizada do município de Uberaba – MG

State-of-art review of traffic signal control methods: challenges and opportunities

Contact Info

Product

Resources

About