Investigating into public transport fare noninteractions using large-scale automatically collected data

Abstract

Fare card data provides an unprecedented opportunity to monitor day-to-day variability of travel demand and its responses to service disruptions and special events. However, when passengers take public transport without interacting with the fare system, demand is usually underestimated, which may cause problems for performance measurement and revenue collection. This research aims to investigate the fare noninteractions phenomena of the tram network in Melbourne, Australia. According to a prior evaluation, only 37% of boarding passengers validate tickets. This study utilizes large-scale automatically collated data to measure fare noninteractions, including data collected by Automatic Passeng..