Connection Scan Algorithm

TL;DR

The paper presents the Connection Scan Algorithm (CSA), an efficient method for timetable query problems that adapts to timetable changes, incorporates delay uncertainties, and scales to nationwide networks.

Contribution

It introduces CSA and its variants for optimizing timetable queries, including handling delays and the MEAT problem, with extensions for large-scale networks.

Findings

CSA efficiently solves timetable queries with minimal delays.

CSA variants optimize arrival time and transfer count.

The approach scales to nationwide transportation networks.

Abstract

We introduce the Connection Scan Algorithm (CSA) to efficiently answer queries to timetable information systems. The input consists, in the simplest setting, of a source position and a desired target position. The output consist is a sequence of vehicles such as trains or buses that a traveler should take to get from the source to the target. We study several problem variations such as the earliest arrival and profile problems. We present algorithm variants that only optimize the arrival time or additionally optimize the number of transfers in the Pareto sense. An advantage of CSA is that is can easily adjust to changes in the timetable, allowing the easy incorporation of known vehicle delays. We additionally introduce the Minimum Expected Arrival Time (MEAT) problem to handle possible, uncertain, future vehicle delays. We present a solution to the MEAT problem that is based upon CSA. Finally, we extend CSA using the multilevel overlay paradigm to answer complex queries on nation-wide integrated timetables with trains and buses.