Multi-Agent Fuzzy-Based Transit Signal Priority Control for Traffic Network Considering Conflicting Priority Requests

Journal article, 2022

The performance of transit signal priority (TSP) with conflicting priority requests highly depends on the serving sequence of multiple TSP requests. A series of existing methods have been developed to determine the priority level of requests. However, most of these methods focused on isolated intersections or a small number of intersections, which are not applicable to complex, dynamic and nonlinear urban traffic networks. In this regard, we propose a multi-agent TSP control method at the network level considering conflicting priority requests. Fuzzy inference is used to manage signal control. We further develop a specific control algorithm. The performance of the proposed method is verified by a case study with a sizeable traffic network with 20 intersections and 49 links. Simulation results demonstrate that the proposed method outperforms other three benchmarking methods under different traffic demands and bus departure frequencies. It is worth-noting that the improvement becomes more notable with the increase of traffic demands and the reduction of bus departure frequencies.