Impact of Employer-based Programs on Transit System Ridership and Transportation System Performance

This document reports on a National Center for Transit Research (a program at CUTR) study that established a direct quantitative relationship between employer-based Transportation Demand Management (TDM) strategies and the performance of a transportation system. The study objectives were to develop a methodology for measuring the impacts of employer-based TDM programs on the performance of a traffic network using measures universal to traffic operations staff, transportation planners, and decision-makers. The study used a micro-simulation traffic model to simulate the effects of Washington State Commute Trip Reduction (CTR) programs implemented by 189 employers in an 8.6 miles segment of I-5 in the Seattle downtown area. The current performance of the selected network with the actual volumes provided by the Washington State Department of Transportation (Scenario With TDM) was compared to that of a scenario with vehicle trips actually reduced by CTR programs at the worksites added onto the network (Scenario Without TDM). Performance measures analyzed included the spatial and temporal extent of congestion, recurring delay, speed, and travel time. On the segment of I-5 in the study area, savings in AM peak delay due to CTR programs were 152,489 vehicle minutes and 17,297 vehicle miles of travel were reduced. Savings in PM peak delay were 169,486 vehicle minutes and 14,510 vehicle miles were reduced. Fuel saved in the AM and PM peak were 3,489 and 4,314 gallons, respectively. The study proved that TDM programs have a significant impact on the operation of the transportation network. Further sensitivity analysis proved that even a small reduction in vehicle trips at worksites (assuming as little as 4 percent with non-regulatory programs) had a significant impact on the performance of the transportation network decreasing delay in vehicle-minutes by as much as 21.9 and 32.3 percent during the AM and PM peak periods, respectively.

Final report (pdf) (3MB)