A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem

2020 ◽  
pp. 1-16
Author(s):  
Palwasha W. Shaikh ◽  
Mohammed El-Abd ◽  
Mounib Khanafer ◽  
Kaizhou Gao
Keyword(s):  
Evolutionary Algorithms ◽  
Control Problem ◽  
Swarm Intelligence ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control

scholarly journals MTGPLP Approach for Traffic Signal Intelligent Control

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Ya Li ◽  
Renhuai Liu ◽  
Yuanyang Zou ◽  
Yingshuang Ma ◽  
Guoxin Wang
Keyword(s):  
Control Problem ◽  
Intelligent Control ◽  
Numerical Experiments ◽  
Control Method ◽  
Traffic Signal ◽  
Programming Approach ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Intelligent Control System ◽  
Weight Factors

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.

scholarly journals The traffic signal control problem for intersections: a review

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Myungeun Eom ◽  
Byung-In Kim
Keyword(s):  
Control Problem ◽  
Traffic Congestion ◽  
Citation Network ◽  
Traffic Signal ◽  
Future Research ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Practical Implementation ◽  
Entire Body ◽  
Traffic Systems

Abstract Background The intersection traffic signal control problem (ITSCP) has become even more important as traffic congestion has been more intractable. The ITSCP seeks an efficient schedule for traffic signal settings at intersections with the goal of maximizing traffic flow while considering various factors such as real-time strategies, signal timing constraints, rapid developments in traffic systems, and practical implementation. Since the factors constituting the ITSCP exhibit stochastically complicated interactions, it is essential to identify these factors to propose solution methods that can address this complexity and still be practically implemented. Objective The objective of this review is to provide a survey of problems, methods, and practices in the evaluation of the ITSCP. In this paper, a unified terminology for the ITSCP and a citation network of the current body of relevant research are accordingly presented, and various assumptions, constraints, and solution approaches are summarized. A review across the entire body of knowledge throughout the history of the ITSCP is therefore provided. This review also highlights open issues and challenges that remain to be addressed by future research.

scholarly journals Applying Genetic Programming with Substructure Discovery to a Traffic Signal Control Problem

2007 ◽  
Vol 22 ◽  
pp. 127-139 ◽  
Author(s):  
Juncichi Kumagai ◽  
Yasuo Ojima ◽  
Souichi Takashige ◽  
Yoshitaka Kameya ◽  
Taisuke Sato
Keyword(s):  
Genetic Programming ◽  
Control Problem ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control
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