Transit Signal Priority (TSP) is an operational strategy that can speed the movement of in-service transit vehicles (typically bus, light rail, or streetcar) through traffic signals. By reducing control delay at signalized intersections, TSP can improve schedule adherence and travel time efficiency while minimizing impacts to normal traffic operations. These benefits improve the quality of service thereby making it more attractive to choice riders. A TSP system can also allow for fewer buses on the same due to travel time reductions and increased reliability, thus reducing transit operating costs. Much of the previous research on TSP has focused on signal control strategies and bus stop placement with little of it analyzing the effectiveness of the system using actual data. This study aims to evaluate the effectiveness of the system using a bus route corridor in Portland, Oregon through real-time Automatic Vehicle Locator data. Key measures that TSP is promoted to improve are evaluated, including travel time, schedule adherence and variability. The TSP system on data was collected for two weeks and is compared to an adjacent two weeks of bus data with the TSP system turned off such that there is no skewing of data due to changes in traffic volumes or transit ridership. This research has shown, that on certain corridors there may be little to no benefit towards TSP implementation and may possibly provide some disbenefit. The direct comparison for TSP on and off scenarios completed for this research yielded no significant differences in reduction in travel time or schedule adherence performance. An additional interesting result was that the standard deviation of the results did not have any specific tendencies with the TSP on or off. Based on these findings, recommendations are made to increase the effectiveness of the system.

Dedicated short-range communication (DSRC) systems, a form of vehicle-to-everything (V2X) systems, were placed on Utah Department of Transportation (UDOT) snowplows to request signal preemption. The study took place along five state routes in the Salt Lake City metropolitan area. Snowplows and intersections were equipped with the technology to communicate and process requests for signal preemption. Signal performance and vehicle performance analysis were performed to understand the impacts that snowplows requesting signal preemption had. Signal performance analysis was done to determine how snowplows with V2X systems using DSRC affected signals. Vehicle performance analysis was done to see if plowing and traffic efficiency and performance were improved, as well as evaluating safety implications of signal preemption. To perform the signal performance analysis, V2X data were collected to understand how often signal preemption was requested by snowplows, how often it was granted by signal controllers, and how long preemption requests affected signal controller timing. Snowplows requested preemption over 50 percent of the time they approached a signalized intersection. Of messages that requested signal preemption, over 80 percent were granted. On average, signal controllers are affected by preemption processing for less than 5 minutes. This shows that the system works as designed, is used often, and does not have adverse effects on signal controller. Data for vehicle performance analysis included analysis of snowplow speed data, general travel speed data, and crash data. These were collected to analyze the effects of snowplows requesting signal preemption on vehicle performance. The analysis showed that snowplow speeds are not changed due to the signal preemption system, but the number of times snowplows stopped was reduced. General travel speeds on equipped routes were more consistently closer to the speed limits than not equipped routes. Crash data showed a greater negative decrease on equipped routes than on not equipped routes. These findings showed minimal changes or impacts to vehicle performance, but anecdotal evidence from snowplow drivers indicates benefits from the system overall. There were various limitations in the analysis. Data granularity differed among datasets, making comparison between the different datasets difficult without reducing data integrity. Some datasets did not have much data, making statistical significance unclear. With these data limitations, conclusions were drawn, but do not fully describe all the potential benefits and impacts of snowplows with V2X systems that use DSRC to request signal preemption. Additional research is needed to better understand the impacts that snowplows requesting signal preemption has on different maintenance metrics, such as fuel usage and time spent plowing. It is also recommended that data used is explored for ways to improve the granularity.

Transit travel time is affected by many factors including traffic signals and traffic condition. Transit agencies have implemented strategies such as transit signal priority (TSP) to reduce transit travel time and improve service reliability. However, due to the lack of empirical data, the joint impact of these factors and improvement strategies on bus travel time has not been studied at the stop-to-stop segment level. This study utilizes and integrates three databases available along an urban arterial corridor in Portland, Oregon. Data sources include stop-level bus automatic vehicle location (AVL) and automatic passenger count (APC) data provided by the Tri-County Metropolitan Transportation District of Oregon (TriMet), the Sydney Coordinated Adaptive Traffic System (SCATS) signal phase log data, and intersection vehicle count data provided by the City of Portland. Based on the unique collection and integration of these fine granularity empirical data, this research utilizes multiple linear regression models to understand and quantify the joint impact of intersection signal delay, traffic conditions and bus stop location on bus travel time and its variability at stop-to-stop segments. Results indicate that intersection signal delay is the key factor that affects bus travel time variability. The amount of signal delay is nearly linearly associated with intersection red phase duration. Results show that the effect of traffic conditions (volumes) on bus travel time varies significantly by intersection and time of day. This study also proposed new and useful performance measures for evaluating the effectiveness of TSP systems. Relationships between TSP requests (when buses are late) and TSP phases were studied by comparing TSP phase start and end times with bus arrival times at intersections. Results show that green extension phases were rarely used by buses that requested TSP and that most green extension phases were granted too late. Early green effectiveness (percent of effective early green phases) is much higher than green extension effectiveness. The estimated average bus and passenger time savings from an early green phase are also greater compared to the average time savings from a green extension phase. On average, the estimated delay for vehicles on the side street due to a TSP phase is less than the time saved for buses and automobiles on the major street. Results from this study can be used to inform cities and transit agencies on how to improve transit operations. Developing appropriate strategies, such as adjusting bus stop consolidation near intersections and optimizing bus operating schedules according to intersection signal timing characteristics, can further reduce bus travel time delay and improve TSP effectiveness.