Integration of Automated Vehicle Location, Fare Control, and Schedule Data for Improved Public Transport Trip Definition

Juan Benavente,Andres Rodriguez,Jose Luis Moura,Borja Alonso

doi:10.1109/access.2021.3107833

Juan Benavente, Andres Rodriguez + Show 2 more

Open Access

https://doi.org/10.1109/access.2021.3107833

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Journal: IEEE Access	Publication Date: Jan 1, 2021
Citations: 1	License type: CC BY 4.0

Affiliation: Universidad de Cantabria

Abstract

This paper proposes a flexible methodology to improve the definition of each distinct trip carried out in a transport system, integrating the information provided by stop-level events from its automated vehicle location and fare collection systems, and scheduling subsystem information at the initial stop of planned trips. The data are structured; and then corrected and completed utilizing several criteria, including a probabilistic approach based on the distributions of travel and dwell times, aiming to minimize the distortions that appear due to the nature of the available sources. The case study data encompass one year of records from the automated vehicle location, fare collection, and scheduling subsystems in Santander City, Spain. The results are discussed with captures from an interactive web visualization tool that has been developed for this work.

Highlights

Multiple opportunities for research and development stem from the analysis of the current implementations and future possibilities of intelligent public transportation systems (IPTSs), being the integration of data from different subsystems to create better models one of them [1, 2]
This paper proposes a flexible methodology to improve the definition of each distinct trip carried out in a transport system, integrating the information provided by stop-level events from its automated vehicle location and fare collection systems, and scheduling subsystem information at the initial stop of planned trips
The methodology described in this paper combines automated fare control (AFC), automated vehicle location (AVL), and scheduling subsystem information to provide a better characterization of the trips of the routes offered in a public transport system; ameliorating the problems that commonly occur when working with IPTS data: ambiguous ids for some elements of the system; missing or multiple entries related to the same AVL event; inconsistent trip ids between the different subsystems, which impedes identifying their respective records related to the same trip; AFC events with wrong information; and uncertainty regarding whether a programmed trip took place

Summary

Introduction

Multiple opportunities for research and development stem from the analysis of the current implementations and future possibilities of intelligent public transportation systems (IPTSs), being the integration of data from different subsystems to create better models one of them [1, 2]. VOLUME -, 2021 separate source, others to the fusion process. These include missing, redundant or erroneous entries; fragmentation of the sequences of stops that are part of a single trip; clocks of different devices not synchronized; or inconsistent ids for the same elements along different tables. They are carried out during day-to-day operations. The datasets which are useful to build this transportation offer model may, in most cases, be obtained from the IPTSs

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