A Comprehensive Analysis of Passenger Alighting and Boarding Rates

Abstract

AbstractThe understanding and management of station stops continues to be a key issue in the operation of urban railways. This paper reports a statistical meta-analysis of passenger alighting and boarding rates from an expansion of a real-life worldwide data set which includes 34 different variables reflecting characteristics of passenger flow, rolling stock design, infrastructure and management actions. This has enabled the authors to identify, test hypotheses about, and quantify the impact of, previously-untested variables. A stepwise regression method using the R statistical package was proposed and developed into a more tractable model with fewer variables. This process eliminated those variables shown to provide no statistical explanation (including the presence of platform edge doors). Of the remaining 18 hypothesised variables, all provided some form of statistical explanation at the 90% level (or more) in one model or another. The results will help railways and transport authorities around the world manage station stops, through timetabling and appropriate investment.