Compacting Massive Public Transport Data

Abstract

In this work, we present a compact method for storing and indexing users’ trips across transport networks. This research is part of a larger project focused on providing transportation managers with the tools to analyze the need for improvements in public transportation networks. Specifically, we focus on addressing the problem of grouping the massive amount of data from the records of traveller cards as coherent trips that describe the trajectory of users from one origin stop to a destination using the transport network, and the efficient storage and querying of those trips. We propose two alternative methods capable of achieving a space reduction between 60 to 80% with respect to storing the raw trip data. In addition, our proposed methods are auto-indexed, allowing fast querying of the trip data to answer relevant questions for public transport administrators, such as how many trips have been made from an origin to a destination or how many trips made a transfer in a certain station.

This work was partially supported by the CITIC research center funded by Xunta de Galicia, FEDER Galicia 2014-2020 80%, SXU 20% [CSI: ED431G 2019/01]; MCIN/ AEI/10.13039/501100011033 ([EXTRA-Compact: PID2020-114635RB-I00]; “NextGenerationEU”/PRTR [SIGTRANS: PDC2021-120917-C21], [PLAGEMIS: TED2021-129245B-C21]; EU/ERDF A way of making Europe [OASSIS-UDC: PID2021-122554OB-C3]); by GAIN/Xunta de Galicia [GRC: ED431C 2021/53]; by UE FEDER [CO3: IN852D 2021/3]; by Xunta de Galicia [ED481A/2021-183], and by the Fondecyt grant #11221029 of Universidad Austral de Chile.