Deploying transit signal priority systems may reduce transit bus delay in Burlington, Vermont by 14.2 to 16.5 percent on Route 15 and by 2.5 to 7 percent on the Old North Route, without producing delays for non-priority traffic.
Mobility benefits of transit priority in a medium-sized city without affecting travel time of non-priority traffic.
Made Public Date
01/30/2012

604

Burlington
Vermont
United States
Identifier
2011-00683
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Planning and Deploying Transit Signal Priority in Small and Medium-Sized Cities: Burlington, Vermont, Case Study

Summary Information

Transit signal priority (TSP) improves transit quality of service by facilitating the movement of in-service buses through traffic-signal controlled intersections. However, prior to deployment it is important to consider the impact TSP may have on all road users including cross-traffic, pedestrians, emergency vehicles that may also have priority, and transit vehicles without priority (i.e., those moving in a different direction from priority vehicles).

Researchers assessed the impact of TSP on the travel time of priority and non-priority vehicles with VISSIM, a micro-simulation tool. The research examined TSP strategies for Route 15 and the Old North Route in Burlington, Vermont, a medium-sized city with a population of 105,365 (in 2000). The analysis estimated priority bus travel time and side-street queue lengths.
METHODOLOGY

VISSIM, a micro-simulation modeling tool, was used by researchers to evaluate the impact of TSP on bus travel time in Burlington, Vermont. The research assessed the impacts of transit priority on traffic on Route 15, which is a four-lane arterial connecting the suburbs to the city of Burlington, and on the Old North Route, which is a loop in the downtown area. The research compared bus travel time and delay per vehicle during operations without TSP (baseline condition) to operations with TSP. Performance measures are averages of the measures obtained over the course of multiple simulated runs. The simulations included baseline operations (i.e., without TSP) and two TSP scenarios, as summarized below.

Route 15
  • Scenario 1 consisted of a 10 second green extension and 30 minute headway. Scenario 1 was run twenty times in VISSIM.
  • Scenario 2 consisted of a 10 second green extension and 15 minute headway. The 15 minute headway was included to take into account stakeholders' interest in increasing the frequency of bus service in the downtown area. Scenario 2 was run eight times in VISSIM.
Old North Route
  • Scenario 1: 10 second green extension with bus stops located on the nearside (i.e., before the intersection).
  • Scenario 2: 10 second green extension with bus stops relocated from the nearside to the farside (i.e., the far side of the intersection)
FINDINGS
In general, the results show that TSP improved priority bus level of service without impacting other traffic.

Route 15 for Scenario 1 Performance
Baseline
Scenario 1
Outcome
Bus Travel Time (sec)
828.44
790.35
5% reduction in travel time
Vehicle Travel Time
538.08
536.59
<0.5% reduction in vehicle travel time
Bus Delay
268.09
229.92
14.2% reduction in delay for priority buses
Vehicle Delay
304.08
300.64
1% reduction in delay for vehicles traveling in the same direction as priority buses
Bus Waiting Time - Inbound Buses
129.03
93.1
27.9% reduction in the rate of change in bus waiting time
Bus Waiting Time - Outbound Buses
31.55
35.45
12.4% increase in bus waiting time

Route 15 for Scenario 2 Performance
Baseline
Scenario 2
Outcome
Bus Travel Time (sec)
836.76
788.49
6% reduction in travel time
Vehicle Travel Time
586.56
549.35
6% reduction in vehicle travel time
Bus Delay
295.61
246.73
16.5% reduction for delay for priority buses
Vehicle Delay
352.96
319.48
9.5% reduction in delay for vehicles traveling in the same direction as priority buses
Bus Waiting Time - Inbound Buses
121.22
88.13
27.3% reduction in the rate of change in bus waiting time
Bus Waiting Time - Outbound Buses
29.28
30.48
4% increase in bus waiting time


Old North Route for Scenarios 1 and 2 Performance
Baseline
Scenario 1
Scenario 2
Outcome
Bus Travel Time (sec)
1420.3
1321.4
1285.9
Scenario 1 reduced travel time by 7% relative to Baseline.
Scenario 2 reduced travel time by 2.5% relative to Scenario 1 (not statistically significant).
Total Vehicle Delay (hours)
(Delay to Non-transit Vehicles)
79.61
80.09
80.68
Scenario 1 decreased vehicle delay by <1% relative to baseline (not statistically significant).
Scenario 2 decreased vehicle delay by <1% relative to Scenario 1 (not statistically significant).

SUMMARY

TSP reduced average travel time for priority buses by 2.5 to 7 percent, reduced average delay for priority buses by 14.2 to 16.5 percent, reduced the average waiting time for priority buses by about 27 percent, and had a statistically non-significant impact on delay for other vehicles of less than 1 percent.

The findings indicate that TSP may increase transit bus level of service while also having a minimal impact on non-transit traffic. Considering that previous evaluations of TSP have found improvements in bus travel time, these findings are not entirely unexpected. However, the results are noteworthy because Burlington is smaller compared to other cities with TSP.

Planning and Deploying Transit Signal Priority in Small and Medium-Sized Cities: Burlington, Vermont, Case Study

Planning and Deploying Transit Signal Priority in Small and Medium-Sized Cities: Burlington, Vermont, Case Study
Publication Sort Date
07/01/2010
Author
Vlachou, K., Collura, J., & Mermelstein, A.
Publisher
Journal of Public Transportation, Vol. 13, No. 3, 2010, National Center for Transit Research, Center for Urban Transportation Research (CUTR), University of South Florida

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