Can we estimate accurately fare evasion without a survey? Results from a data comparison approach in Lyon using fare collection data, fare inspection data and counting data

Document Type

Journal Article

Publication Date


Subject Area

place - urban, place - europe, planning - methods, planning - surveys, technology - passenger information


Public transport, Smart card, Fare evasion, Survey, Data collection, Lyon


In a context of worldwide urbanization and increasing awareness for environmental issues, it is undeniable that public transport will play an important role in the cities of the future. This will require increased attractiveness of public transit and adequate funding. In this regard, fare evasion could be considered as a threat that needs to be quantified accurately. To do this, transit operators often rely on on-site surveys that are limited in terms of spatiotemporal coverage. Yet, new data sources such as farebox transactions, fare inspection logs and automated passenger counter are now available and little research examines how they could help in estimating the fare irregularity rate. In this paper, we initiate research in this direction. To do this, we followed the operator’s viewpoint and used a comparative approach to analyse the potential of those new data sources. We introduced a classification of fare irregularities and then applied data fusion methods to derive two fare irregularity rates. Results are then compared to a survey and the area of relevance of each data source is discussed. The research is done with data from the public transport network of Lyon which is an interesting case study because different access control types coexist (open and closed environment). The research results suggest that the fare inspection logs might have significant limitations to measure accurately the level of fare evasion. They also suggest that the merging of automated count and farebox transactions is a more promising direction of research. Still, it will probably not be enough to completely replace on-site manual survey. These findings can help operators in identifying the pros and cons of all data sources and implement new measurement methods.


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