Determining Optimum Transit Signal Priority Implementation Locations on a Network

Murat Bayrak, S. Ilgin Guler

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Transit signal priority (TSP) can be used to improve bus operations at intersections. However, implementing TSP can often increase the delay of non-transit modes. Therefore, it is necessary to evaluate the effects of TSP both on car and bus operations to determine optimal locations to equip with TSP to improve network operations. To do so, the link transmission model is used to evaluate the travel times of both cars and buses on the network while accounting for dynamic queuing and queue spillover. This method is then used to evaluate different combinations of locations for TSP implementation and to determine the optimal configuration that can minimize the total travel time of network users, including bus and car passengers. The sensitivity of the proposed algorithm to demand level, changes in transit network, implementation strategy, and solution method are also evaluated. For all tested scenarios, the TSP configurations found to be optimum achieve a significant reduction of total bus passenger travel time while creating minimal effect on total car travel time. The results reveal that in general, not all intersections should be equipped with TSP, and intersections that carry high demand within a network are promising locations for TSP implementation to reduce the total travel time of network users. Additionally, it is found that the total travel time of network users can be further decreased by only activating TSP for buses with more than a certain number of on-board passengers.

Original languageEnglish (US)
Pages (from-to)387-400
Number of pages14
JournalTransportation Research Record
Issue number10
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mechanical Engineering


Dive into the research topics of 'Determining Optimum Transit Signal Priority Implementation Locations on a Network'. Together they form a unique fingerprint.

Cite this