Note: This project completed the work begun under project A-16 with the University of Arizona.

Traffic congestion and traffic signals cause significant delay and increase operating costs for on-street transit service. Signal priority has been a promising method to improve transit operations and service quality, but it has not seen widespread deployment in North America. The resistance to implementation has often been based on a concern that overall traffic performance may be unduly compromised when signal timing intended to optimize traffic flow is overridden to provide a travel advantage to transit vehicles.

Traditional traffic signal systems have had limited capabilities, resulting in simplistic transit priority strategies, such as extending the green phase. Recent advancements in the field of Intelligent Transportation Systems (ITS) have created new capabilities to support transit priority in traffic signal systems. These advancements cover a wide range of features including smart buses, detection, communications, control hardware, optimization algorithms, and simulation modeling.

Traffic signal priority for transit must contribute to the objectives set for operation of the transportation system. Some of these objectives (e.g., reducing emissions) will be attractive to both the transit agency and the agency responsible for the signal system. Other objectives (e.g., reducing transit operating costs) will be principally attractive to the transit agency. Some objectives may be partially conflicting (e.g., reducing vehicle delay and reducing person delay). In designing transit priority for a traffic signal system, operating objectives must be determined and, if needed, a balance found between conflicting objectives.

The objective of this project was to develop and test improved transit priority algorithms for traffic signal controllers and systems taking into account various levels of hardware sophistication, operating characteristics, and transportation management strategies. The major products of this project will be a description of the algorithms, an evaluation of their associated benefits and effects, and a detailed implementation plan.

Status:   This project has been completed.  The  final report is available for loan from the TCRP.