Many worldwide implementations of transit signal priority (TSP) in cities, such as Los Angeles, Portland, Vancouver, and Zurich, have demonstrated that it can significantly improve the operation state of transit vehicles without affecting other users of traffic networks. As a result, a number of researchers and practitioners proposed to expand the implementation of TSP. However, with an increasing number of prioritized transit lines within the same network, the probability of having two or more conflicting requests simultaneously is also increasing. Existing TSP methods cannot provide a good solution for this conflicting problem. Therefore, this study is developed and it is sponsored by the National High Technology Research and Development Program 863 (No. 2014AA110303), the Key Project of National Science Foundation of China (No. 51338003), and the Postgraduate Research and Innovation Plan Project in Jiangsu Province (No. KYLX15_0156). This thesis aims at seeking the methods to resolve the conflicts among multiple TSP requests and enhance the efficiency of TSP from three perspectives (i.e., intersections, urban arterials, and traffic network). In this way, the optimization of TSP will be achieved and this will then provide theory, methods, and technical support for the application of TSP in the reality.
This thesis is mainly composed of the following three aspects: the optimization of the TSP at intersections, the optimization of the TSP at urban arterials, and the optimization of the TSP at traffic network. Additionally, it is necessary to note that since urban rail transit (e.g., light rail and metro) cannot be influenced by signal control sysem this study is mainly conduced on surface bus system, including tramcar, bus rapid system, and routine bus.
(1) At intersections, this study explores the interaction among multiple TSP requests within the same phase on basis of the operation characteristics of transit vehicles and the generation mechanism of TSP requests. Then the in-bus passengers’ delay and the waiting delay of bus passengers at the downstream bus stops are selected as the indices to measure the priority level of a TSP request. Following that, an evaluation model for the priority level is developed and it will grant priority to the buses with the highest priority level. In this way, the conflicts among different TSP requests will be effectively resolved and thus improves the implementation of TSP, i.e., the optimization on TSP is achieved.
(2) Based on the bi-level programming method, the optimization method of the TSP at urban arterials is presented. The upper level aims at conducting the coordination control at the arterials. Firstly, since the deficiency of existing integral green wave, based on the buses’ operation characteristics this thesis chooses the bus stops as the nodes to divide the arterial intersections into different groups. A stop-to-stop green band will generate within one group. The MAXBAND model is then modified to optimize the width of the stop-to-stop band. The lower level is used to optimize TSP method. Taking the upper and lower limits on the width of stop-to-stop green band as the constraints, the TSP is executed under the premise of not disturbing the coordination at urban arterials. Meanwhile, an evaluation model for priority requests is established to solve their conflicts to enhance the efficiency of TSP.
(3) Given the complicated distributed characteristic of urban traffic network, an optimization approach of the TSP in traffic network is proposed in this thesis by using the multi-agent technology (MAT) and fuzzy control theory. Here each agent controls one intersection and the TSP is realized by the fuzzy reasoning. It utilizes the multi-level fuzzy logic controller to achieve TSP. With respect to the conflicting TSP requests, this study will determine the priority level of TSP request based on the priority level of buses and traffic flow necessitious in the corresponding approaching. Since a number of variables will be involved, a multi-leve fuzzy controller developed to resolve the conflicting TSP requests by the coorperation among multiple fuzzy controllers. Finally, the consultation fuzzy logic controller is applied to obtain the coordination control among the arterial intersections to guarantee the continuity of the vehicles at arterials.