Multiattribute Decision-Making Methods for Optimal Selection of Traffic Signal Control Parameters in Multimodal Analysis

2014 ◽  
Vol 2438 (1) ◽  
pp. 64-71 ◽  
Author(s):  
Juan C. Medina ◽  
Eric G. Lo ◽  
Rahim (Ray) F. Benekohal
Keyword(s):  
Decision Making ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Optimal Selection ◽  
Control Parameters ◽  
Multimodal Analysis ◽  
Selection Of

Consideration of 24-hr Volumes in Selection of Traffic Signal Control Strategies for Isolated Intersections

1996 ◽  
Vol 1553 (1) ◽  
pp. 18-27
Author(s):  
Stephen C. Lee ◽  
Joe Lee
Keyword(s):  
Control Strategy ◽  
Traffic Signal ◽  
Effective Control ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Universal Method ◽  
Effective Strategy ◽  
Traffic Volumes ◽  
Isolated Intersection ◽  
Selection Of

Selection of the most appropriate traffic signal control strategy for isolated intersections is a difficult and complicated process. TRAF-NETSIM was used to evaluate the operational performance of an isolated intersection under pretimed, semiactuated, and actuated control for continuous 24-hr traffic volumes. Guidelines were developed for selecting the most effective control strategy. Findings include the following: either pretimed or actuated control is the most effective strategy for isolated intersections without flashing for the 24-hr and peak 8-hr traffic volumes. The conventional three-dial pretimed controller is still a valuable control strategy and should not be eliminated from consideration. The most effective strategy for the peak 8-hr operation of an isolated intersection is probably the most effective one for overall 24-hr operation, as well. The combined control strategy (which consists of one or more of the pretimed, actuated, and semiactuated controls dependent on the hourly volumes) without flashing is the most effective strategy for the 24-hr and peak 8-hr traffic volumes. The signal flashing mode is very effective during the night when the total intersection critical lane volume falls below 500 vehicles per hour. Advanced pretimed controllers are generally more effective than conventional three-dial pretimed controllers. There is no direct, universal method to determine the most effective combined traffic signal control strategy for isolated intersections.

Research on Strategy Intelligent Control of Traffic Signal

2015 ◽  
Vol 713-715 ◽  
pp. 889-892
Author(s):  
Yan Min Zhang ◽  
Hai Bing Luo ◽  
Jian Qiang Wang
Keyword(s):  
Control System ◽  
Traffic Congestion ◽  
Fuzzy Inference ◽  
Control Method ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Control Parameters ◽  
Existing Problems ◽  
Vehicle Capacity

In order to make the traffic flow smoothly through the intersection, to minimize the delay time, must ensure that the control decision of the traffic signal is real-time and accuracy. Aiming at the existing problems of the traditional timing control method, analysis of traffic signal control parameters, performance indicators, put forward the fuzzy inference is applied to the traffic signal control system, puts forward an intelligent traffic signal control system based on fuzzy control; the vehicle queue length, inlet flow rate, green extension as the control parameters and simulation the results show that the proposed control method can effectively improve the traffic congestion, improve the vehicle capacity.

Stochastic Model of Traffic Jam and Traffic Signal Control

2011 ◽  
Vol 131 (2) ◽  
pp. 303-310
Author(s):  
Ji-Sun Shin ◽  
Cheng-You Cui ◽  
Tae-Hong Lee ◽  
Hee-hyol Lee
Keyword(s):  
Stochastic Model ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Traffic Jam

Recent Advances in Reinforcement Learning for Traffic Signal Control

2021 ◽  
Vol 22 (2) ◽  
pp. 12-18 ◽  
Author(s):  
Hua Wei ◽  
Guanjie Zheng ◽  
Vikash Gayah ◽  
Zhenhui Li
Keyword(s):  
Reinforcement Learning ◽  
Real World ◽  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Control Methods ◽  
Advantages And Disadvantages ◽  
Recent Advances

Traffic signal control is an important and challenging real-world problem that has recently received a large amount of interest from both transportation and computer science communities. In this survey, we focus on investigating the recent advances in using reinforcement learning (RL) techniques to solve the traffic signal control problem. We classify the known approaches based on the RL techniques they use and provide a review of existing models with analysis on their advantages and disadvantages. Moreover, we give an overview of the simulation environments and experimental settings that have been developed to evaluate the traffic signal control methods. Finally, we explore future directions in the area of RLbased traffic signal control methods. We hope this survey could provide insights to researchers dealing with real-world applications in intelligent transportation systems

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