Project. Integrating Transit Signal Priority and Adaptive Traffic Signal Control

Principal investigator. Hesham Rakha, Virginia Polytechnic Institute and State University, 540-231-1505, Rakha@vtti.vt.edu

Project objective. This project aims at evaluating the benefits of integrating transit signal priority logic within state-of-the-art adaptive traffic signal control systems, using Columbia Pike in Northern Virginia as a case study.

Project abstract. While the use of Transit Signal Priority (TSP) has been widely accepted at isolated intersections, there has been significant resistance to its use within coordinated signalized systems due to potential adverse impacts on general traffic. In particular, it has been argued that phase skipping and red truncation could confuse motorists, impact signal coordination, and cause significant delays to the general traffic, particularly on streets crossing the transit routes.

Up to this date apart from a single simulation study the benefits of integrating transit signal priority with adaptive signal control has not been investigated. The proposed study involves a field evaluation of the Split Cycle and Offset Optimization Tool (SCOOT) adaptive signal control system and the integration of adaptive signal control with TSP. This study will be conducted along a 20-signalized section of Columbia Pike that was simulated earlier Dion and Rakha (2004). The proposed study offers a unique opportunity to evaluate the potential benefits of integrating transit signal priority within an adaptive signal control system. The field study also provides an opportunity to validate the simulation study that was described earlier.

The study proposes the use of Global Positioning Systems (GPSs) to evaluate the impacts of transit signal priority within an adaptive signal control system on the Columbia Pike corridor. Five portable GPS units will be installed on a number of transit and passenger vehicles when transit priority is enabled and disabled. The study will consider the AM and PM peak periods (7:30-9:30AM and 3:30-5:30PM) and an off-peak period (12:00-1:00PM). Various Measures of Effectiveness (MOEs) will be considered in the study including vehicle travel time, vehicle delay, person travel time, person delay, vehicle stops, fuel consumption, and emissions of HC, CO, CO2, NOx, and PM. Statistical analyses will be conducted to investigate the impact of transit signal priority on the performance of transit vehicles and non-transit vehicles traveling along the mainline.

Tasks.
Task 1. Characterize typical travel time variability of buses and cars to estimate the number of samples required to achieve a desired level of confidence in the results.
Task 2. Install GPS units on five buses and five automobiles traveling along the corridor to second-by-second speed data.
Task 3. Develop emission models for transit vehicles.
Task 4. Analyze, reduce, and estimate different MOEs from the data.
Task 5. Conduct a statistical analysis of the aggregate data to quantify the impacts on TSP on the various MOEs.
Task 6. Produce a final report of the results

Milestones. Completion dates as follows:
Task 1, Sept. 2005.
Task 2, Dec. 2005.
Task 3, Feb. 2006.
Task 4, Apr. 2006.
Task 5, May 2006.
Task 6, June 2006.

Student involvement. One GRA

Budget. FY 06
Faculty $40,000
Match    55,000 (Arlington County)
                95,000

Relation to other research. This project builds on an earlier ITS Implementation Center project that focused on conducting a field evaluation of transit priority.

Technology Transfer. Technology transfer will be conducted via conference presentations and journal publications.

Potential Benefits. The proposed study offers a unique opportunity to evaluate the potential benefits of integrating transit signal priority within an adaptive signal control system. The study also provides an opportunity to validate a simulation study that was conducted earlier as part of the ITS Implementation Center.

TRB Keywords. Transit signal priority, traffic modeling, adaptive signal control.