Passenger incidence (station arrival) behavior has been studied primarily to understandhow changes to a transit service will affect passenger waiting times. The impact of oneintervention (i.e. increasing frequency) could be overestimated compared to another (i.e.improving reliability), depending on the assumption of incidence behavior. It is important tounderstand passenger incidence so that management decisions will be based on realisticbehavioral assumptions. Prior studies on passenger incidence chose their data samples fromstations with a single service pattern such that the linking of passengers to services wasstraightforward. This simplifies the analysis but heavily limits the stations that can be studied. Inany moderately complex network, many stations may have more than one service patterns. Thislimitation prevents it from being systematically applied to the whole network and limits its use inpractice.This paper concerns with incidence behavior in stations with heterogeneous services. Itproposes a method to estimate incidence headway and waiting time by integrating disaggregatesmartcard data with published timetables using schedule-based assignment. We apply thismethod to stations in the entire London Overground to demonstrate its practicality and observethat incidence behavior varies across the network and across times of day, reflecting the differentheadways and reliability. Incidence is much less timetable-dependent on the North London Linethan on the other lines because of shorter headways and poorer reliability. Where incidence istimetable-dependent, passengers reduce their mean scheduled waiting time by over 3 minutescompared with random incidence.
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