2009Journal of Public TransportationOpen access

Calculation of Transit Performance Measures Using Smartcard Data

Martin Trépanier, Catherine Morency, Bruno Agard

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Abstract

Smartcard automated fare collection systems (SCAFC) for transit have been considered primarily for their administrative function of controlling access to the service and for revenue management. However, it is likely that data from these systems also can be used to describe both transport supply and demand. This article illustrates the use of smartcard data to estimate various transit performance measures. Combined with well-established evaluation processes, such measures can help operators monitor their networks in greater detail. The performance of the network supply (vehicle-kilometers, vehicle-hours, commercial speed, etc.) and the statistics on passenger service (passenger-kilometers, passenger-hours, average trip length, etc.) can be calculated from these datasets for any spatial or temporal level of resolution, including route and bus stop levels.

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What this paper is about

Smartcard automated fare collection systems (SCAFC) for transit have been considered primarily for their administrative function of controlling access to the service and for revenue management. However, it is likely that data from these systems also can be used to describe both transport supply and demand. This article illustrates the use of smartcard data to estimate various transit performance measures. Combined with well-established evaluation processes, such measures can help operators monitor their networks in greater detail. The performance of the network supply (vehicle-kilometers, vehicle-hours, commercial speed, etc.) and the statistics on passenger service (passenger-kilometers, passenger-hours, average trip length, etc.) can be calculated from these datasets for any spatial or temporal level of resolution, including route and bus stop levels.

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Available abstract

Smartcard automated fare collection systems (SCAFC) for transit have been considered primarily for their administrative function of controlling access to the service and for revenue management. However, it is likely that data from these systems also can be used to describe both transport supply and demand. This article illustrates the use of smartcard data to estimate various transit performance measures. Combined with well-established evaluation processes, such measures can help operators monitor their networks in greater detail. The performance of the network supply (vehicle-kilometers, vehicle-hours, commercial speed, etc.) and the statistics on passenger service (passenger-kilometers, passenger-hours, average trip length, etc.) can be calculated from these datasets for any spatial or temporal level of resolution, including route and bus stop levels.

Key concepts: Smart card, Transit (satellite), Revenue, Public transport, Computer science, Service (business), Data collection, Transport engineering

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