Modelling the potential effect of shared bicycles on public transport travel times in Greater Helsinki: An open data approach

Document Type

Journal Article

Publication Date


Subject Area

mode - bike, mode - mass transit, place - europe, policy - environment, policy - sustainable


Bicycle sharing system, public transport, cyclilng, open data, accessibility, daily mobility


In many European cities, support for public transport and cycling in daily mobility is considered an efficient means to reduce air pollution, traffic jams, and carbon emissions. Shared bicycle systems have turned out effective in increasing cycling in many urban areas, particularly when combined with public transportation. In this study, we make an effort to model a hypothetical shared bike system and quantify its spatial effect on public transport travel times. The study area is one of the fastest growing urban agglomerations in Europe, the Greater Helsinki area in Finland. We model the travel times between the population and 16 important destinations in the city centre of Helsinki by public transportation and by public transportation extended with shared bikes. We use open route and timetable databases and tools developed in-house to perform extensive data mining through application programming interfaces (APIs). We show 1) that open transport information interfaces can provide a new effective means to evaluate multimodal accessibility patterns in urban areas and 2) that the launch of a bicycle sharing system could reduce public transportation travel times in the study area on average by more than 10%, meaning some 6 min per each individual trip. We conclude that bicycle sharing systems complementing the traditional public transport system could potentially increase the competitiveness and attractiveness of sustainable modes of urban transport and thus help cities to promote sustainable daily mobility. Finally, we emphasize that the availability of open data sources on urban transport information – such as the public transport data in our case – is vital for analysis of multimodal urban mobility patterns.


Permission to publish the abstract has been given by Elsevier, copyright remains with Elsevier.


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