Improving anytime behavior for traffic signal control optimization based on NSGA-II and local search

Nguyen, Peter H.; Passow, Benjamin N.; Yang, Yingjie

doi:10.1109/ijcnn.2016.7727804

Cited by 12 publications

(11 citation statements)

References 25 publications

(23 reference statements)

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“…Nguyen et al [36], Hatri and Boumhidi [37], Zheng et al [38] are the only papers that employ a multiobjective simulation-optimization approach. Although a relevant approach, there seems to be a research void in implementing multi-objective SimOpt for the TST problem.…”

Section: Multi-objective Based Approachesmentioning

confidence: 99%

“…Nguyen et al [36] integrated a local search (LS) algorithm with the iterations of NSGA-II in a way that the output of LS was becoming the next generation's parents in their study. Results of the proposed NSGA-II-LS were compared with NSGA-II and multi-objective differential evolutionary algorithms and found that the proposed algorithm was better than the other two approaches and good simulation results were achievable in the early phase of the optimization procedure.…”

Section: Multi-objective Based Approachesmentioning

confidence: 99%

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

Qadri

Gökçe

Öner

2020

Eur. Transp. Res. Rev.

104

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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.

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Section: Multi-objective Based Approachesmentioning

confidence: 99%

Section: Multi-objective Based Approachesmentioning

confidence: 99%

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

Qadri

Gökçe

Öner

2020

Eur. Transp. Res. Rev.

104

View full text Add to dashboard Cite

show abstract

“…More recently, two works by Nguyen et al [12] and Bravo et al [13] used for the first time SUMO in connection with EAs to perform traffic light optimization. In fact, these two papers inspired our work.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, these two papers inspired our work. In particular, in [12] SUMO was coupled with a memetic version of NSGA-II (including a local search algorithm) to improve the anytime behavior of the evolutionary algorithm. The main difference w.r.t.…”

Section: Introductionmentioning

confidence: 99%

Simulation-Driven Multi-objective Evolution for Traffic Light Optimization

Cacco

Iacca

2020

Applications of Evolutionary Computation

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The constant growth of vehicles circulating in urban environments poses a number of challenges in terms of city planning and traffic regulation. A key aspect that affects the safety and efficiency of urban traffic is the configuration of traffic lights and junctions. Here, we propose a general framework, based on a realistic urban traffic simulator, SUMO, to aid city planners to optimize traffic lights, based on a customized version of NSGA-II. We show how different metrics -such as number of accidents, average speed of vehicles, and number of traffic jams-can be taken into account in a multi-objective fashion to obtain a number of Pareto-optimal light configurations. Our experiments, conducted on two city scenarios in Italy and different combinations of fitness functions, demonstrate the validity of this approach and show how evolutionary optimization is an effective tool for traffic light optimization.

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“…Signalized intersections are essential traffic control treatments that provide safe and efficient control of traffic congestion (Nguyen et al 2016). Due to the complexity of intersections, high traffic volumes and densities, the interactions of vehicle-to-vehicle and bicycle-to-vehicle are steadily increased.…”

Section: Introduction and Objectivesmentioning

confidence: 99%

Cycling at Intersections: A Multi-Objective Assessment for Traffic, Emissions and Safety

2019

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This paper evaluated in an integrated manner the traffic performance, pollutant emissions and road conflicts between bicycles and motor vehicles at a signalized intersection. Two alternative scenarios were examined: (1) bicycles increment and motor vehicles replacement within the cycle-fixed traffic signal; (2) replacing the existing traffic control by a conventional two-lane roundabout and evaluating the impacts of bicycles increment. For each scenario, bicycle demand was varied from 9 to 270 bicycles per hour (bph). Traffic flow and vehicle dynamic data were collected from a three-leg signalized intersection in Aveiro (Portugal). The microscopic traffic model (VISSIM) paired with an emission (Vehicle Specific Power – VSP) methodology and safety (Surrogate Safety Assessment Methodology – SSAM) model were used to assess intersection-specific operations. The fast Non-Dominated Sorting Genetic Algorithm (NSGA-II) was used to find the optimal bicycle demands. The results showed that two-lane roundabout outperformed the existing traffic control, namely in highest bicycle demand scenario (number of stops and travel time reduced in 78 and 14%, respectively; CO2, NOx, and HC decreased 9, 7, and 12%, respectively). It was also found that the number of conflicts was significantly reduced (–49%) with this latter layout even in maximum bicycle demand scenario (270 bph). However, roundabout layout lead to more severe conflicts and potential crashes. The analysis showed that bicycle demands of 75, 95 and 110 bph delivered good environmental and safety outcomes for the intersection.

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Improving anytime behavior for traffic signal control optimization based on NSGA-II and local search

Cited by 12 publications

References 25 publications

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

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

Simulation-Driven Multi-objective Evolution for Traffic Light Optimization

Cycling at Intersections: A Multi-Objective Assessment for Traffic, Emissions and Safety

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