Reproducing Longitudinal In-Vehicle Traveler Experience and the Impact of a Service Reduction with Public Transit Smart Card Data

Abstract

In-vehicle traveler experience is an influencing factor in the mode choice and satisfaction of public transit users. Vehicle load is an operator-centric indicator used as a level-of-service standard. This indicator considers crowding an isolated and deterministic event generalizable to all travelers. It has been argued that this indicator does not reflect the actual perception from the user perspective. This paper proposes a more comprehensive approach to measure in-vehicle experience by introducing an individual-based indicator that encompasses multiple days. The rationale is that the traveler’s perception is not determined by a single trip but by multiple events over time within a specific trip pattern. Multiday public transit smart card transaction data from an express bus route were used to demonstrate the concept. First, a data processing technique was developed to enrich the data with operations and vehicle capacity information. These data were used to reproduce the longitudinal in-vehicle experience of each traveler. The individual results were then summarized and analyzed according to trip and user attributes. Noticeable differences in the in-vehicle experience were found between fare groups and also were found associated with trip direction. Through the analysis of data before and after an actual service reduction, it was revealed that the level of impact on individual in-vehicle experience also varied according to fare group and trip direction. The traveler-based indicators complement traditional measures and could be integrated into operational planning, such as service reduction and increase studies, to anticipate the impact on traveler experience and customer satisfaction.