TL;DR
This paper introduces ULTRA, a preprocessing technique that enables efficient multimodal route planning with unlimited transfers, significantly improving query speed across various transportation modes.
Contribution
ULTRA provides a novel method to incorporate unlimited transfer graphs into public transit algorithms, enabling faster and more flexible multimodal journey planning.
Findings
ULTRA achieves an order of magnitude speedup over existing methods.
It supports various transfer modes including walking, cycling, and driving.
The approach maintains query efficiency even with unlimited transfers.
Abstract
We study a multimodal journey planning scenario consisting of a public transit network and a transfer graph which represents a secondary transportation mode (e.g., walking, cycling, e-scooter). The objective is to compute Pareto-optimal journeys with respect to arrival time and the number of used public transit trips. While various existing algorithms can efficiently compute optimal journeys in either a pure public transit network or a pure transfer graph, combining the two increases running times significantly. Existing approaches therefore typically only support limited walking between stops, either by imposing a maximum transfer distance or by requiring the transfer graph to be transitively closed. To overcome these shortcomings, we propose a novel preprocessing technique called ULTRA (UnLimited TRAnsfers): Given an unlimited transfer graph, which may represent any non-schedule-based…
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