Transit Signal Priority (TSP) is an operational strategy that can speed the movement of in-service transit vehicles (typically bus, light rail, or streetcar) through traffic signals. By reducing control delay at signalized intersections, TSP can improve schedule adherence and travel time efficiency while minimizing impacts to normal traffic operations. These benefits improve the quality of service thereby making it more attractive to choice riders. A TSP system can also allow for fewer buses on the same due to travel time reductions and increased reliability, thus reducing transit operating costs.
Much of the previous research on TSP has focused on signal control strategies and bus stop placement with little of it analyzing the effectiveness of the system using actual data. This study aims to evaluate the effectiveness of the system using a bus route corridor in Portland, Oregon through real-time Automatic Vehicle Locator data. Key measures that TSP is promoted to improve are evaluated, including travel time, schedule adherence and variability. The TSP system on data was collected for two weeks and is compared to an adjacent two weeks of bus data with the TSP system turned off such that there is no skewing of data due to changes in traffic volumes or transit ridership.
This research has shown, that on certain corridors there may be little to no benefit towards TSP implementation and may possibly provide some disbenefit. The direct comparison for TSP on and off scenarios completed for this research yielded no significant differences in reduction in travel time or schedule adherence performance. An additional interesting result was that the standard deviation of the results did not have any specific tendencies with the TSP on or off. Based on these findings, recommendations are made to increase the effectiveness of the system.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/22660 |
Date | 01 April 2008 |
Creators | Sundstrom, Carl Andrew |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Thesis |
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