In light of the environmental and energy crisis, the use of public transport is a crucial step closer to carbon-neutrality. Unlike a car, however, traveling by public transport requires a significant amount of planning, which discourages many people from using it more. The goal of this thesis is to make route planning easier for passengers by introducing an intelligent route planner that automatically finds optimal transportation routes using any combination of buses, trains, car sharing and city bikes.
We intend to reach this goal in three steps: (1) develop a unified data model and aggregation system for public transit and micromobility data from all providers in Slovenia; (2) set up the open source trip planning engine OpenTripPlanner using this data and (3) develop a hybrid web and mobile application that displays this data to users and allows them to use the trip planner to plan their journeys.
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