Modeling and optimizing bus transit priority along an arterial: A moving bottleneck approach

Kan Wu, Muyang Lu, S. Ilgin Guler

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Bus operations on arterials are often hindered by traffic signals and car queues. Transit signal priority (TSP) strategies can be used to improve bus operations on arterials. Analytically quantifying the impacts of TSP in mixed traffic, where cars and buses share lanes, is challenging since car queues can slow down buses, while slow-moving buses can create bottlenecks for cars. Furthermore, computational costs increase significantly when considering an arterial with multiple intersections. To tackle these challenges, this paper first develops a dynamic programming framework to model and evaluate TSP along an arterial. Next, the algorithm is utilized to determine the changes to car and bus delays as a result of TSP implementation along an arterial, and the sensitivity of the algorithm to the signal timing plan, bus stop locations and dwell durations, and the bus headway is evaluated. Next, a bi-level optimization framework is proposed to determine the optimal location of TSP implementation along arterials. Finally, the results of integrating TSP with dedicated bus lanes is evaluated. The results suggest that the benefits of TSP largely depend on the signal setting, and bus stop location, and that as the bus headway decreases, the marginal benefit of providing TSP also decreases. Additionally, the results suggest that the specific intersection at which TSP is implemented can play a large role on its operational impacts. Finally, it is found that in some scenarios, the benefits of implementing TSP alone can be larger than implementing dedicated bus lanes alone.

Original languageEnglish (US)
Article number102873
JournalTransportation Research Part C: Emerging Technologies
StatePublished - Dec 2020

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Management Science and Operations Research


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