Using APC-AVL Data to Improve Transit Reliability and Accessibility Analysis

Abstract

Real-world transit service often deviates substantially from schedules, leading to variability in route-choice behaviors and experienced travel times that are not adequately reflected in existing accessibility analyses based on general transit feed specification (GTFS) schedule data alone. This study presents a methodology for more accurately assessing origin–destination (OD) transit reliability and accessibility by using GTFS data to generate candidate itineraries, then using automatic passenger counting and automatic vehicle location (APC-AVL) data to determine which routes are selected in real time and calculate the experienced travel time. The methodology is applied across March 2016–2020 from the perspectives of two groups in Allegheny County, Pennsylvania: residents in origins of high socioeconomic need traveling to opportunity employment hotspots, and prospective employers looking to establish a transit-accessible worksite. The worst OD pairs in practice achieved less than 15% of the accessibility captured by 95% of scheduled trips. At the 90-min threshold, the lowest observed accessibility corresponded to a realized loss of 17% of the eligible workforce due to service unreliability. These findings reveal the need to incorporate APC-AVL data to accurately model the route choice process and evaluate rider experiences.