TRB 2016 Blue Ribbon Committee
16th National Transportation Planning Applications Conference

A deeper insight into ridership and travel behaviour from smart card technology

Corresponding Author: Fearghal King, TransLink

Presented By: Fearghal King, Graeme Brown, TransLink


Traditionally, methods of estimating transit ridership have relied upon analysis of ticket sales data and periodic fare audit surveys. Survey data tends to be derived from small samples where there are concerns about how representative it is of system-wide travel behaviour. Assumptions are often made on the usage of monthly passes and transfer rates, as well as cyclical fluctuations, and expansion factors. All of these factors contribute to ensure that ridership estimation has historically been achieved using ‘black box’ methods. Furthermore, in terms of potential insights and applications, little is known regarding the granular patterns from these data sources such as boardings by station or bus line, the time of travel, the distance or duration of travel, the origins and destinations, as well as the fare products used to make these trips. Transit planners often must rely on expensive and infrequent surveys to help reveal the complete picture of travel patterns and behaviour. The arrival of smart card technology into the transit world has brought with it a range of new and exciting opportunities to help understand ridership, travel behaviour, and system performance. This presentation offers an insight into the capabilities and implications that the Compass Card offers TransLink since general population launch in 2016. Methods of estimating ridership have vastly improved in terms of accuracy, reliability, granularity, and timeliness. Furthermore, the sheer volume of transactional data linked to attributes such as day/date/time, transit service, location, and fare products allows for an almost infinite combination of custom queries to be addressed. The availability of such rich information offers vast implications for planning and policy, from network and service planning, to research and analytics, to transit operations, and even transit security. Such transparent methods and approaches to transit planning easily enable greater usage and understanding of the data, and pave the way towards open data policies and improving customer experiences and relationships.


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