Computing Multimodal Journeys in Practice

We study the problem of finding multimodal journeys intransportation networks, including unrestricted walking, driving, cycling,and schedule-based public transportation. A natural solution to thisproblem is to use multicriteria search, but it tends to be slow and toproduce too many journeys, several of which are of little value. We pro-pose algorithms to compute a full Pareto set and then score the solu-tions in a postprocessing step using techniques from fuzzy logic, quicklyidentifying the most significant journeys. We also propose several (stillmulticriteria) heuristics to find similar journeys much faster, making theapproach practical even for large metropolitan areas.