Transit Signal Priority Fine-Tuning – How to Get More from Your System
R Stewart, Michael Corby
Abstract
R Stewart, Michael Corby
Abstract
The purpose of this paper is to describe the developments of the transit signal priority (TSP) fine-tuning process and the lessons learned from the application of the guidelines for the four transit systems. Although many TSP systems have been implemented, there have been few studies to examine the fine tuning process of individual TSP situations. The objective of fine tuning TSP systems is to verify that the systems are operating properly and that the TSP parameters are appropriate for the various intersections. In order to assess this, a methodology was created compiling field observations, data analysis of transit and signal log data as well as video recordings of the actual transit operations. When it was necessary, changes were proposed to individual systems, therefore making them more equivalent.
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The purpose of this paper is to describe the developments of the transit signal priority (TSP) fine-tuning process and the lessons learned from the application of the guidelines for the four transit systems. Although many TSP systems have been implemented, there have been few studies to examine the fine tuning process of individual TSP situations. The objective of fine tuning TSP systems is to verify that the systems are operating properly and that the TSP parameters are appropriate for the various intersections. In order to assess this, a methodology was created compiling field observations, data analysis of transit and signal log data as well as video recordings of the actual transit operations. When it was necessary, changes were proposed to individual systems, therefore making them more equivalent.
Key concepts: Transit (satellite), Process (computing), Computer science, SIGNAL (programming language), Real-time computing, Field (mathematics), Signal timing, Public transport