User-Constrained Multi-Modal Route Planning

In the multi-modal route planning problem we are given multiple transportation networks (e.\,g., pedestrian, road, public transit) and ask for a best \emph{integrated} journey between two points. The main challenge is that a seemingly optimal journey may have changes between networks that do not reflect the user's modal preferences. In fact, quickly computing reasonable multi-modal routes remains a challenging problem: Previous approaches either suffer from poor query performance or their available choices of modal preferences during query time is limited. % In this work we focus on computing exact multi-modal journeys that can be restricted by specifying arbitrary modal sequences at query time. For example, a user can say whether he wants to only use public transit, or also prefers to use a taxi or walking at the beginning or end of the journey; or if he has no restrictions at all. % By carefully adapting node contraction, a common ingredient to many speedup techniques on road networks, we are able to compute point-to-point queries on a continental network combined of cars, railroads and flights several orders of magnitude faster than Dijkstra's algorithm. Thereby, we require little space overhead and obtain fast preprocessing times.