Tri-level programming model for combined urban traffic signal control and traffic flow guidance

Sun, Zengqi; Lu, Huapu; Qu, Wen-cong

doi:10.1007/s11771-016-3303-x

Cited by 9 publications

(2 citation statements)

References 7 publications

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“…In fact, the algorithm developed in this study seeks to minimize the total waiting time of traveling vehicles in the intersection. Sun et al [12] in a recent study developed a tri-level programming model for combined urban traffic signal control in which the lower level model refers to the intersection delay, the middle-level model concerns about the traffic signal control optimization and the tide lane management is controlled with the upper level of the model. Finally, they solved the model using a heuristic iterative optimization algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Traffic Light Signal Timing Using Simulation

Kamran¹,

Ramezani²,

Masoumzadeh³

et al. 2017

Communications on Advanced Computational Science with Applicati

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Increasing trend in the number of vehicles and consequently intensifying the traffic volume, traffic lights optimum timing plays a vital role in congestion mitigation in the critical intersections of urban areas. This paper gives an insight into traffic light timing using simulation modeling methods. In fact, this study aims at minimizing the average time that entities (vehicles) spend in the system (intersection). First, real data including vehicles arrive and leave times, and the time spent waiting at a red light etc. is collected through monitoring an intersection in downtown Urmia, Iran. Then, a simulation model is developed using Arena Simulation Software. The most important feature of the proposed model is the replacement a four-stroke traffic light with the current three-stroke one. After model validation, several alternatives are considered for traffic light timing and the one which resulted the minimum average time spent in the system is selected. According to the simulation results, the four-stroke traffic light yielded a better performance compared to the three-stroke one.

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Section: Literature Reviewmentioning

confidence: 99%

Traffic Light Signal Timing Using Simulation

Kamran¹,

Ramezani²,

Masoumzadeh³

et al. 2017

Communications on Advanced Computational Science with Applicati

View full text Add to dashboard Cite

show abstract

“…In order to solve pedestrian phase patterns, a GA was proposed to obtain solutions for signal settings by Ma et al 18 Sabar et al 19 developed a memetic algorithm to optimize signal timings and solve traffic signal optimization problems. The algorithm adopted a local search algorithm to improve the exploitation power of GA. To collaborate intersection signal control and traffic flow, Sun et al 20 established a tri-level programming model, and non-dominated sorting genetic algorithm II (NSGA II) was applied to solve phase. In this article, a metaheuristic approach combining difference operator, based on Particle Swarm Optimization (PSO) Algorithm, is developed.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of urban road intersection signal timing based on particle swarm optimization algorithm

Jia

Lin

Luo

et al. 2019

Advances in Mechanical Engineering

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Currently, signal control mode is the main control method of urban road intersections. Given that the traffic efficiency of road intersections is mainly affected by signal timing schemes, it is important to optimize signal timing at road intersections. Therefore, signal timing optimization methods of urban road intersections are explored in this work. When optimizing the timing of the signal at the intersections, the selection of optimization targets play an important role. At present, there are multiple objectives considered while designing signal timing scheme, including capacity, delays, and automobile exhaust. However, from the perspective of the traveler, they are more concerned about their own delay while passing intersections. In this work, we propose a novel multi-objective signal timing optimization model with goals of per capita delay, vehicle emissions, and intersection capacity. Considering the problem characteristics of the target problem, a meta-heuristic algorithm combining difference operator, which is based on Particle Swarm Optimization Algorithm, is developed. To test the validity of proposed approach, we applied it to real-world intersection signal timing problems in China. The results show that the optimized signal timing scheme obtained by the proposed algorithm is better than the realistic one. Also, the effectiveness of the developed algorithm is demonstrated by comparing it with other efficient algorithms.

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Adaptive flow abnormity identification based on information entropy

Liu

Fan

Wang

2018

Concurrency and Computation

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SummaryAlong with the normal network flow, abnormal flow follows, threatening the security and normal use of the computer. Under the impact of the massive network flow, researchers were prompted to study identification methods based on machine learning. Currently, the existing identification methods based on machine learning still have deficiencies, ie, feature redundancy and deficiency in classifier. In order to deal with these problems, this paper proposes an adaptive approach (AEDs) to identify abnormal network flow. The AEDs utilizes the feature extraction algorithm proposed in this paper, which is based on information entropy to filter features and reduce the size of features. Then, a weight construction method based on rough set theory is implemented to construct the weights of given‐case‐based ensemble classifiers, and only the sub‐classifier with weight that is higher than the given threshold will be reserved. On this basis, in order to keep the effectiveness of the classifier, we utilize new flow data to update weights. Moreover, an adaptive detection algorithm is proposed to adaptively monitor the change of entropy of abnormal flow and enable the update of classifier. Finally, experiments have been conducted to illustrate the effectiveness and the feasibility of the approach.

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Tri-level programming model for combined urban traffic signal control and traffic flow guidance

Cited by 9 publications

References 7 publications

Traffic Light Signal Timing Using Simulation

Traffic Light Signal Timing Using Simulation

Multi-objective optimization of urban road intersection signal timing based on particle swarm optimization algorithm

Adaptive flow abnormity identification based on information entropy

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