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Title: Dynamic transit signal priority
Author: Ekeila, Wael
Degree Master of Applied Science - MASc
Program Civil Engineering
Copyright Date: 2006
Abstract: Transit Signal Priority (TSP) is a popular Traffic Demand Management strategy used to enhance the performance of transit systems by modifying the signal control logic to give transit signal priority through signalized intersections. Conventional TSP strategies used in most cities have been shown to offer significant benefits in minimizing the delays of transit vehicles. However, there have been several concerns about the shortcomings of conventional TSP strategies which limited their applications. The main concern is the potential negative impact on the cross street traffic. Another concern is the static nature of conventional TSP strategies and the lack of responsiveness to real-time traffic and transit conditions. This thesis describes the development and evaluation of a dynamic Transit Signal Priority (TSP) control system which has the ability to provide signal priority in response to real-time traffic and transit conditions. The dynamic TSP system consists of three main components: a virtual detection system, a dynamic arrival prediction model, and a dynamic TSP algorithm. The methodology followed to develop the system consisted of three main steps. The first was to develop a microsimulation model that would be used to test and evaluate the performance of the dynamic TSP system. In the model, Automatic Vehicle location (AVL) was used as the virtual detection system. The second step was the development of several bus arrival prediction models using linear regression and neuro-fuzzy methods. Techniques such as Kalman and Bayes filters were used to refine the prediction. The last step was the development of a dynamic TSP algorithm that would decide what TSP strategy to use and when to apply it. The dynamic TSP system was tested and compared to the conventional TSP system using the microsimulation model. Scenarios with varying simulation parameters and traffic volumes were tested. Results showed that when an accurate prediction model was used, the dynamic TSP system outperformed the conventional one. The dynamic TSP system could be further enhanced if better arrival prediction models are used, more TSP strategies are evaluated, and a larger scale of implementation is studied.
URI: http://hdl.handle.net/2429/17633
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]

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