Optimal cycle for a signalized intersection using Global Optimization and Complementarity

Ribeiro, Isabel M.; Simões, M. Lurdes

doi:10.1007/s11750-010-0167-3

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…Note that many publications such as Ribeiro and Simões [57]; Simões and Ribeiro [58]; Simões and Ribeiro [59]; and Ribeiro and Simões [60] assumed that the arrival rates obey Poisson distribution. e memoryless is one of the characteristics of Poisson distribution, that is, the arrival rates of the cycle k are never influenced to the former several cycles.…”

Section: Mtgplp Algorithmmentioning

confidence: 99%

“…Furthermore, note that some similar works (eg., Ribeiro and Simões [57]; Simões and Ribeiro [58]; Simões and Ribeiro [59]; and Simões and Ribeiro [60] studied the urban traffic light control and, however, some complementarity constraints are contained in the systems, which are very hard to solve because of their exceeding nonconvexity and combinatorial construction. In this paper, some ways are utilized to overcome the 0-1 variables in the model.…”

Section: Introductionmentioning

confidence: 99%

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MTGPLP Approach for Traffic Signal Intelligent Control

Liu

Zou

et al. 2020

Mathematical Problems in Engineering

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In this paper, we state a combining programming approach to optimize traffic signal control problem. The objective of the model is to minimize the total queue length with weight factors at the end of each phase. Then, modified Twin Gaussian Process (MTGP) is employed to predict the arrival rates for the traffic signal control problem. For achieving automatic control of the traffic signal, an intelligent control method of the traffic signal is proposed in view of the combining method, that is to say, the combining method of MTGP and LP, called MTGPLP, is embraced in the intelligent control system. Furthermore, some numerical experiments are proposed to test the validity of the model and the MTGPLP approach. In particular, the results of numerical experiments show that the model is effective with different arrival rates, departure rates, and weight factors and the combining method is successful.

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Section: Mtgplp Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MTGPLP Approach for Traffic Signal Intelligent Control

Liu

Zou

et al. 2020

Mathematical Problems in Engineering

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“…In this section, we briefly describe the traffic model and present the MPCC formulation-further details could be consulted in the work of Ribeiro and Simões [17]. The traffic model considers an intersection with four traffic streams: 1 , 2 , 3 , and 4 which are controlled by a traffic signal: 1 , 2 , 3 , and 4 , respectively.…”

Section: Traffic Model Formulationmentioning

confidence: 99%

Solving a Signalized Traffic Intersection Problem with NLP Solvers

Melo

Matias

Monteiro

2013

Conference Papers in Mathematics

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Mathematical Programs with Complementarity Constraints (MPCC) finds many applications in areas such as engineering design, economic equilibrium, and mathematical theory itself. In this work, we consider a queuing system model resulting from a single signalized traffic intersection regulated by pretimed control in an urban traffic network. The model is formulated as an MPCC problem and may be used to ascertain the optimal cycle and the green split allocation. This MPCC problem is also formulated as its NLP equivalent reformulation. The goal of this work is to solve the problem, using both MPCC and NLP formulations, minimizing two objective functions: the average queue length over all queues and the average waiting time over the worst queue. The problem was codified in AMPL and solved using some optimization software packages.

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Signal adaptive cooperative control of two adjacent traffic intersections using a two-stage algorithm

Zou

Liu

et al. 2021

Expert Systems with Applications

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Optimal cycle for a signalized intersection using Global Optimization and Complementarity

Cited by 6 publications

References 8 publications

MTGPLP Approach for Traffic Signal Intelligent Control

MTGPLP Approach for Traffic Signal Intelligent Control

Solving a Signalized Traffic Intersection Problem with NLP Solvers

Signal adaptive cooperative control of two adjacent traffic intersections using a two-stage algorithm

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