Conditional Transit Signal Priority for Connected Transit Vehicles. Issue 2 (February 2022)

• Record Type: Journal Article
• Authors: Cvijovic, Zorica; Zlatkovic, Milan; Stevanovic, Aleksandar; Song, Yu
• Is Part Of: Transportation research record. Volume 2676:Issue 2(2022)
• Page Start: 490
• Page End: 503
• Publication Date: 2022-02
• Subjects: operations -- traffic simulation -- automated/autonomous/connected vehicles -- microscopic traffic simulation -- traffic signal systems -- intersection performance -- multimodal -- optimization -- signal priority -- signalized intersection -- V2I -- V2V -- public transportation -- bus transit systems -- bus rapid transit -- public transportation -- traffic signal priority; Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981211044459
• Languages: English
• ISSNs: 0361-1981

Abstract

Connected vehicle (CV) technologies enable safe and interoperable wireless communication among vehicles and the infrastructure with the possibility to run many applications that can improve safety, and enhance mobility. This paper develops CV-based algorithms which use transit vehicle speed and the estimated time that the vehicle needs to arrive at an intersection to trigger transit signal priority (TSP) initiation. This information is updated each second based on the traffic conditions such as speed, a current distance of a transit vehicle to the intersection, and queue conditions. The algorithm uses the actual speed of a transit vehicle and its latitude/longitude (lat/lon) coordinates to compute the time that the vehicle needs to reach the stop line. It was tested on a real-world network using VISSIM traffic simulation, but can easily be implemented in the field, since it is using world coordinates. The upgraded algorithm was applied to a future bus rapid transit (BRT) scenario, and included different levels of conditional TSP, which depend on three combined conditions: the time that a transit vehicle needs to reach the stop line, the number of passengers on board, and the lateness that the transit vehicle experiences. The test-case network used for model building is a corridor consisting of ten signalized intersections along State Street in Salt Lake City, UT. The CV algorithms coupled with TSP can yield notable delay reductions for both the regular bus and the BRT of 33% and 12%, respectively.