Use of Public Transport Smartcard Data for Understanding Travel Behaviour

Use of Public Transport Smartcard Data for Understanding Travel Behaviour


M Bagchi, Steer Davies Gleave; P White, TSG, University of Westminster, UK



Background to paper:

This paper will show how public transport smart card data can be used to investigate and understand travel behaviour. However, critical to the quality and utility of this new data source is the way in which the smart card scheme is designed and implemented, including consideration of the fare environment and composition of the public transport market into which smart cards are introduced. The paper will be based on results that have been obtained from a PhD research project that is nearing completion.

Smart card data constitute a new transport data source that can be analysed to investigate and understand travel behaviour. These data are generated from the use of smart cards, as replacement for traditional fare media such as magnetic stripe cards and paper tickets, for travel on public transport. Of central significance is that smart card journey data can be linked to the use of a particular card, as each card has a unique serial number. These journey data can then be linked to the cardholder if name/address details are known or the card is personalised with a photo. This is a clear advantage over certain existing transport data sources, such as electronic ticket machine data from buses. The critical attribute of being able to link the data to the card or individual, combined with other attributes that smart card data possess, mean that transport service providers can undertake a range of analyses they may have previously been unable to do, or found difficult to do because of some of the deficiencies of existing transport data sources (such as electronic ticket machine data and sample surveys).

However, there are many factors which can impact on the quality and utility of smart card data for understanding travel behaviour, not least the parameters of the smart card scheme, the fare environment and the composition of the passenger market in which schemes are introduced.

Structure of paper:

In order to examine and illustrate the potential of smart card data, analyses of two sample smart card datasets from bus-based schemes in the United Kingdom (UK) were undertaken, and these results will be presented. Smart card data, as noted above, have advantages over existing transport data sources, such as bus electronic ticket machine (ETM) data. With ETMs, when a passenger boards a bus, a 'boarding' is registered on the machine. However, this boarding cannot be tied to any given individual or card. With smart card data, boardings can be tied to the individual or individual card, and this information can be used to 'construct' passenger journeys made over the course of a day or longer. Subject to quality constraints, a transport service provider will also have a continuous record of journeys made using a particular smart card. Therefore, it is possible to examine level of card usage over particular time periods (trip rates) and to examine patterns of interchange, where boardings can be grouped and 'rules' applied in processing. Other travel behaviours can also be examined. For this research, two analyses, of inferring trip rates and bus-to-bus interchange were chosen, and results of those analyses will be presented.

The findings of the analyses indicated the importance of the main parameters of a smart card scheme, in addition to a range of other factors, in both the explanation of analysis results, and more generically for the quality and utility of smart card data. The generic stages of the design and implementation of a smart card scheme will be presented, highlighting the stages where influence on the end smart card data is greatest, including discussion of the individual components of those relevant stages.

The examination of the nature of smart card data, the findings of the analysis and the examination of the wider components of smart card development and implementation allowed a set of factors affecting quality and utility of smart card data to be identified, and these will be presented. These factors can be used as a useful checklist that smart card industry practitioners can incorporate into the design, implementation and evaluation stages of their public transport smart card schemes. This will help to ensure that the smart card data produced are of relatively good quality, and are useful for a range of applications.

The Rees Jeffreys Trustees and the UK Department for Transport (DfT) funded the research on which this paper will be based.


Association for European Transport