Extending the Time Horizon: Efficient Public Transit Routing on Arbitrary-Length Timetables

TL;DR

This paper introduces an extension to trip-based public transit routing algorithms that efficiently handles arbitrarily long timetables, enabling fast queries and quick updates over year-spanning networks.

Contribution

It extends existing routing methods to support long-term timetable planning, improving scalability and update responsiveness for large, long-duration transit networks.

Findings

Fast query performance on year-spanning timetables

Efficient handling of timetable updates like delays or route changes

Scalability demonstrated on large networks spanning multiple years

Abstract

We study the problem of computing all Pareto-optimal journeys in a public transit network regarding the two criteria of arrival time and number of transfers taken. In recent years, great advances have been made in making public transit network routing more scalable to larger networks. However, most approaches are silent on scalability in another dimension: Time. Experimental evaluations are often done on slices of timetables spanning a couple of days, when in reality, the planning horizon is much longer. We introduce an extension to trip-based public transit routing, proposed in [12], that allows efficient handling of arbitrarily long timetables. Our experimental evaluation shows that the resulting algorithm achieves fast queries on year-spanning timetables, and can incorporate updates such as delays or changed routes quickly even on large networks.