During the A.M. peak period, transit signal priority on an arterial route in Arlington, Virginia could reduce bus travel time by 4.0 to 9.1 percent, decrease person delay of bus passengers by 6.5 to 14.2 percent, and reduce transit vehicle stops by 1.5 to 2.9 percent.

13-17 January 2002
Arlington,Virginia,United States

Summary Information

This study used the INTEGRATION simulation model to estimate the impact of implementing transit signal priority (TSP) on a 3.95 mile section Columbia Pike in Arlington, Virginia. Baseline corridor and cross street traffic flows were determined from field data collected between June 12 and 14, 2000. Saturated traffic flow parameters were estimated based on corridor geometry.

The model was designed to reflect the geometric location and configuration of multiple bus stops and intersections on the corridor. The transit signal priority scheme gave priority to buses traveling on Columbia Pike or entering the corridor from major cross streets. The signal priority logic enhanced the existing optimized fixed-time signal control system by enabling transit vehicles to receive a five second green extension if approaching an intersection at the end of a green cycle. The model considered vehicle movements only, and did not account for pedestrian clearance intervals or the impact of emergency vehicle signal preemption. In addition, if two transit vehicles called for priority simultaneous at the same intersection, no priority was given.

The simulation model was run to determine the impacts of TSP on AM peak and midday traffic flows. Peak period person delays were calculated based on the assumption that passenger cars carried 1.2 persons per vehicle, and transit vehicles carried 23 persons per vehicle. During non-peak hours, transit vehicle were assumed to carry 16 persons per vehicle.


In general, transit vehicles benefited from transit signal priority at the expense of all other traffic on cross streets.

At congested intersections there was little spare green time, therefore, small changes in the signal timing easily increased delay for a large number of vehicles. The author noted that adaptive signal control systems may help reduce this delay if transit signal priority can be denied at times when traffic sensors detect heavy congestion on side streets. However, adaptive signal control systems were not evaluated during this study.

The list below shows the range of mobility impacts transit signal priority had on prioritized vehicles during AM peak periods for five different scenarios (Express buses, Regular buses, Express with Regular buses, Cross Street Buses, and All buses)
  • Travel times decreased between 4.0 percent (Express buses scenario) and 9.1 percent (Cross street buses scenario)
  • Person delays decreased between 6.5 percent (Express buses scenario) and 14.2 percent (Cross street buses scenario)
  • Vehicle stops decreased between 1.5 percent (Express buses scenario) and 2.9 percent (Express with Regular buses scenario).

The list below shows the range of mobility impacts transit signal priority had on all traffic during the AM peak period for five different scenarios (Express buses, Regular buses, Express with Regular buses, Cross Street Buses, and All buses)
  • Travel times increased between 0.6 percent (Express buses scenario) and 7.2 percent (All buses scenario)
  • Person delays increased between 0.6 percent (Express buses scenario) and 8.8 percent (All buses scenario)
  • Vehicle stops increased between 0.4 percent (Express buses scenario) and 3.0 percent (Regular buses scenario).

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Evaluation of Transit Signal Priority Benefits Along A Fixed-Time Signalized Arterial

Author: Dion, Francois, et al.

Published By: Paper presented at the 81st Annual Transportation Research Board Meeting. Washington, District of Columbia

Source Date: 13-17 January 2002


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Goal Areas


Typical Deployment Locations

Metropolitan Areas


bus priority, traffic signals, TSP, pre-timed, pretimed, time-of-day signal timing, fixed-time

Benefit ID: 2007-00348