Modeling the Effects of Transit Preferential Treatments on the Transit Reliability Index

Transit reliability is a crucial level-of-service (LOS) indicator to improve the service quality as it consequently increases ridership and revenue. This study investigates the effects of alternative transit preferential treatments on transit reliability index. Reliability can be defined as the deviation between the runtime and scheduled time. In this study a traffic microsimulation model for a congested urban corridor is developed for PM, AM, and mid-day peak periods. All models are calibrated and validated against multiple criteria including traffic volume, queue length and travel time of transit and auto. In calibration, GEH values < 5 are achieved in 100% cases and for queue length validation error ranges of 0%-17% are achieved which is quite satisfactory. Following the development of the base scenario in the microsimulation platform, four transit preferential treatments such as transit signal priority (TSP), queue jump lane (QJL), transit lane (TrLane) and combination of TSP+QJL are tested and corresponding reliability index is generated. In this study reliability is defined as the absolute value of deviation between the runtime and scheduled time within a segment of the corridor. Using the deviations as a dependent variable a random parameter regression (RPR) model is developed. The model results suggest that TSP+QJL is the most effective compared to other alternatives since it shows a higher likelihood to reduce deviation and does not reveal any variations. All other treatments show variation with a higher standard deviation value, suggesting that their effects are variable during a given peak period.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Maps; References; Tables;
  • Pagination: 10p

Subject/Index Terms

Filing Info

  • Accession Number: 01764095
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-04288
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:19AM