Use of Transit Signal Priority systems for Bus Rapid Transit can reduce transit time by 9 percent, with minimal impact to non-transit traffic.

The Salt Lake City based simulation study found that GPS-based systems in particular were flexible, effective, and unlikely to be expensive.

Date Posted

Improving Efficiency and Reliability of Bus Rapid Transit

Summary Information

Bus Rapid Transit (BRT) systems, which typically run in exclusive lanes with specially designed rail-like features, are popular for their effectiveness in promoting urban mobility. They have high capacity and low operational cost, which may be augmented by certain operational strategies to improve travel times and headway adherence. The most effective of these strategies is Transit Signal Priority (TSP), which is enabled by GPS-based technology and which provides data that may be further used to improve a BRT system's reliability.

The researchers, sponsored by the United States Department of Transportation, sought to analyze the effectiveness of both TSP and off-board fare collection. Several varieties of both operational strategies were reviewed. For the analysis, the study performed a microscopic simulation to test the TSP scenarios and implemented a data-driven optimization method to understand the contributing factor of off-board fare collection systems. The researchers also performed a literature review to understand the state of the practice.


VSSIM, a microscopic, time-step and behavior-based simulation platform, was used for network modeling. Eight different scenarios were investigated, each with different variations of BRT implementation, GPS or traditional TSP, and further sophisticated varieties of TSP systems. The study corridor examined was an urban principal arterial in Salt Lake County. Findings were analyzed from the perspectives of transit operation, other non-transit operations along the corridor, and non-transit operations along side streets.

To understand the impact of fare collection systems, the researchers performed a heuristic optimization search over a number of variables. Passengers could be considered to board with or without needing to make a smart card payment, representing fare collection systems that relied on on-board fare collection and station-based fare collection respectively.


The implementation of TSP and GPS-enabled TSP systems decreased transit travel time by approximately 8.5 percent and 9 percent, respectively. These time savings held even in scenarios in which TSP algorithms were restricted to sometimes emphasize non-transit traffic flow. Non-transit traffic travel time increased by up to 1 percent along the corridor, indicating a small overall impact. This difference was broadly similar across all scenarios. Scenarios in which TSP systems were implemented did lead to increases in side-street traffic time of up to 6 percent, though these could be mitigated by use of conditional TSP systems. In cases with such algorithms, the side-street traffic delay was approximately the same as in the base model.

The final boarding model was found to exhibit good statistical fit, with an R-squared value of .90. It found that idling time could be reduced by up to 30 minutes per day by eliminating on-board cash fares.

The study concluded that GPS-based TSP strategies are more effective than traditional TSP tools because of their flexibility and lower equipment costs. However, both methods are broadly effective.

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