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A platform for research: civil engineering, architecture and urbanism
Multiagent Control Approach with Multiple Traffic Signal Priority and Coordination
In this paper, a multiagent-based control method is proposed to design a transit signal priority (TSP) scheme at urban traffic networks. One agent controls an intersection. Coordination among different intersection agents is deployed to guarantee the benefits from TSP at upstream intersections. At one intersection there are usually many bus routes, and thus multiple TSP requests and coordination requests can occur at one phase simultaneously. Therefore, the proposed method also aims at resolving conflicting TSP or coordination requests. A multilevel fuzzy controller consisting of a transit signal priority controller, Green Time Adjustment Controller 1, fuzzy negotiation controller, and Green Time Adjustment Controller 2 is then introduced to realize these objectives. Following that, fuzzy inference decisions and algorithms are provided for describing the control process of the proposed multiagent method. An urban traffic network with 25 intersections is selected to conduct a case study to evaluate the proposed method by comparison and sensitivity analysis. The proposed method performed better than the other three methods under different scenarios in accordance with the simulation results.
Multiagent Control Approach with Multiple Traffic Signal Priority and Coordination
In this paper, a multiagent-based control method is proposed to design a transit signal priority (TSP) scheme at urban traffic networks. One agent controls an intersection. Coordination among different intersection agents is deployed to guarantee the benefits from TSP at upstream intersections. At one intersection there are usually many bus routes, and thus multiple TSP requests and coordination requests can occur at one phase simultaneously. Therefore, the proposed method also aims at resolving conflicting TSP or coordination requests. A multilevel fuzzy controller consisting of a transit signal priority controller, Green Time Adjustment Controller 1, fuzzy negotiation controller, and Green Time Adjustment Controller 2 is then introduced to realize these objectives. Following that, fuzzy inference decisions and algorithms are provided for describing the control process of the proposed multiagent method. An urban traffic network with 25 intersections is selected to conduct a case study to evaluate the proposed method by comparison and sensitivity analysis. The proposed method performed better than the other three methods under different scenarios in accordance with the simulation results.
Multiagent Control Approach with Multiple Traffic Signal Priority and Coordination
J. Transp. Eng., Part A: Systems
Xu, Mingtao (author) / Zhai, Xiaoqi (author) / Sun, Zhongyu (author) / Zhou, Xuan (author) / Chen, Yunxing (author)
2023-01-01
Article (Journal)
Electronic Resource
English
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