Neal Lathia
ABSTRACT
The widespread adoption of automated fare collection (AFC) systems by public transport authorities around the world means that, increasingly, people carry and use passive sensors (embedded inside of public transit tickets) to record their daily movements. Unlike mobile phones, the records held by AFC systems provide a rich and detailed source of data about peoples' transport habits: times of travel, modalities, destinations, trip durations, and fares paid. In this work, we explore the extent that this data offers the possibility to both build and measure future of travel-based ubiquitous computing applications. We focus on two potential end-users: first, how travellers may be aided by feedback mechanisms in order to re-align misperceptions of their travel behaviour and leverage this data to change their habits. In particular, we analyse differences between 85 travellers' surveyed perceptions of their public transport habits and their actual usage of the system. Second, how transport authorities can use this data to measure and implement incentive mechanisms that produce the expected impact. We use anonymised AFC data to measure the extent that financial incentives implemented by London's transport authority (such as peak-hour fares and student discounts) correlate with measurable changes in millions of travellers' behaviours.
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Index Terms
- How smart is your smartcard?: measuring travel behaviours, perceptions, and incentives
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