Complete Estimation Approach for Characterizing Passenger Travel Time Distributions at Rail Transit Stations

Abstract

Route choice behavior of a rail transit passenger is not directly observable and it may be affected by the route travel time to a large extent. Compared to the on-train time, travel times at stations, including walking time and waiting time, have been receiving less attention and therefore become more difficult to analyze. A common method to analyze the travel time at a rail transit station is to directly assume a distribution function and to further fit the distribution. However, most distribution functions in the prior literature were used without validation and/or conclusive decision on the best fit. In such context, this paper develops a complete approach to estimating both the walking and waiting times at stations (including origin stations, destination stations, and transfer stations) by mining automatic fare collection (AFC) and automatic train supervision (ATS) data, and their distributions are further discussed and characterized in detail. An initial case study of the Beijing subway network shows that it can deduce passengers’ walking and waiting times in sequence, and consequently obtain and depict their distributions with high performance.