Estimation of bus connection risk with the use of open bus data
Rose, Elena (2016)
MDP in Software Development
Informaatiotieteiden yksikkö - School of Information Sciences
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Bus connection risk estimation has not been studied well despite its potential impact on travellers decisions about the choice of transportation mode and loyalty to public transportation. We aim to develop a framework to estimate and visualize bus connection chance with the use of open bus data. This thesis presents two original models for estimation of bus connection risk based on probability distributions. The first model refers to Bayesian analysis and beta distribution functions. This model depends on the possibility of calculating parameters for all possible bus connections, which is problematic since such data are not stored but rather generated during actual planning of the itinerary. The second model allows us to calculate distribution parameters for arrivals of each feeder bus at the alighting stop and departures of each connecting bus from the boarding stop. It is possible to aggregate historical open bus data to the list of distribution parameters on a regular basis, which only requires setting automatic jobs of preparing and processing data, calculating distribution parameters, and loading them to a planning graph of a trip planner. The framework consists of the theoretical description and practical application, which makes it useful for transportation systems decision-makers, developers, researchers, and end users. The framework has been applied successfully in the city of Tampere, Finland. As a result, the web trip planner with estimation of bus connection chance is ready to use by the public.