Trip-Based Public Transit Routing

TL;DR

This paper introduces a trip-based algorithm for efficiently computing Pareto-optimal public transit journeys considering arrival time and transfers, enabling rapid 24-hour profile queries in large networks.

Contribution

It presents a novel trip-focused approach that significantly improves query speed for multi-criteria public transit routing compared to existing methods.

Findings

Computes full 24-hour profiles in 70 ms after 30 s preprocessing

Handles dynamic scenarios efficiently

Demonstrates effectiveness on London's metropolitan network

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. We take a novel approach, focusing on trips and transfers between them, allowing fine-grained modeling. Our experiments on the metropolitan network of London show that the algorithm computes full 24-hour profiles in 70 ms after a preprocessing phase of 30 s, allowing fast queries in dynamic scenarios.