Dynamic Transfer Patterns for Fast Multi-modal Route Planning

Route planning makes direct use of geographic data and provides beneficial recommendations to the public. In real-world the schedule of transit vehicles is dynamic and delays in the schedules occur. Incorporation of these dynamic schedule changes in multi-modal route computation is difficult and requires a lot of computational resources. Our approach extends the state-of-the-art for static transit schedules, Transfer Patterns, for the dynamic case. Therefore, we amend the patterns by additional edges that cover the dynamics. Our approach is implemented in the open-source routing framework OpenTripPlanner and compared to existing methods in the city of Warsaw. Our results are an order of magnitude faster then existing methods.