In Dallas, Texas, simulation found that transit signal priority reduced bus travel time up to 11 percent during peak periods, reduced car travel times up to 16 percent, vehicle delay up to 4 percent and person delay up to 6 percent.
Field data were used to check the accuracy of simulated baseline traffic conditions generated by the VISSIM model prior to simulating the following TSP scenarios.
Enhanced Software Scheme – This scenario calculated the impacts of implementing enhanced software logic on existing type 170 signal controllers already deployed on Harry Hines Boulevard. The model simulated bus priority by extending the priority phase by 10 seconds. Each subsequent phase following an extension phase was decreased by a calculated percentage of the cycle length until normal timing was recovered. This technique allowed all intersections on the corridor to remain in sync.
Advanced Priority Logic Scheme – This scenario allowed more advanced logic to be implemented for signal priority, however, the advanced priority logic implemented required more precise bus location information than required for the enhanced software logic scenario above. The Advanced Priority Logic model was able to simulate the effects of adding additional or more advanced vehicle detectors on Harry Hines Boulevard.
Advanced Priority Logic with Modifications Scheme - This scenario used advanced priority logic in conjunction with modified operations at the intersection of Harry Hines Boulevard and Motor Street. Modifications consisted of removing signal priority at this intersection and reconfiguring bus stop locations to minimize delay. The bus stop reconfiguration was estimated to have limited impacts on rider access to bus services.
Ten simulation runs were made for each TSP scenario and the following measures of effectiveness were used to gauge corridor performance.
- Bus travel time,
- Car travel time,
- Delay time per vehicle, and
- Delay time per person.
The impact of bus travel and delay times weighed heavily in the results. Each DART bus was assumed to have at least 20 people on-board.
Enhanced Software Scheme
- Bus travel time savings ranged from -2 to 6 percent during the AM and PM peaks.
- Car travel time savings ranged from -1 to 16 percent during the AM and PM peaks.
- Overall vehicle delay (including side street approaches) decreased 3.7 percent.
- Overall person delay (including side street approaches) decreased 4.1 percent.
Advanced Priority Logic Scheme
- The results of this scenario were used to determine if modifications were necessary to accommodate congestion on cross street traffic. Heavy congestion on Motor Street was addressed using the Advanced Priority Logic with Modifications Scheme.
Advanced Priority Logic with Modifications Scheme
- Bus travel time savings ranged from -2 to 11 percent during the AM and PM peaks.
- Car travel time savings ranged from -5 to 6 percent during the AM and PM peaks.
- Overall vehicle delay (including side street approaches) decreased 2.8 percent.
- Overall person delay (including side street approaches) decreased 6.1 percent.
The author noted that the shortness of the test corridor, the long cycle lengths, and the varied bus dwell times increased the variance of the car and bus travel time data.
The extent to which signals were optimized in the base case of this study was not reported. A high degree of optimization in baseline scenarios may limit achievable benefits and vice versa.
Transit Signal Priority on a Fully-Actuated Signalized Corridor Utilizing Advanced Priority Logic and Detection Systems
Author: Ivanovic, M. et al.
Published By: Paper presented at the 9th World Congress Conference on ITS. Chicago, Illinois
Source Date: 14-17 October 2002
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bus priority, traffic signals, TSP