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Public Transport

, Volume 10, Issue 2, pp 257–289 | Cite as

Automatic recognition of “low-quality” vehicles and bus stops in bus services

  • Benedetto Barabino
Original Paper
  • 60 Downloads

Abstract

A recent interest in transit service analysis resulted in advances in the monitoring of public transport quality from the passenger’s viewpoint. Several frameworks were proposed to show where and when different quality levels occur, but there has been no focus on determining which vehicles and bus stops lead to low-quality performance in bus services. This paper proposes a framework that: (i) performs a simple data collection on selected parameters on passenger activities at bus stops (e.g., consulting posted information) and in-vehicle (e.g., validating the ticket). This data collection is performed by Secret Shoppers on Origin-Destination pairs representing paths travelled by passengers, (ii) proposes two new algorithms detecting criticalities for each route and parameter, and (iii) shows the vehicles and bus stops for which some targets are not met. These steps result in the first framework that can help build operational plans guiding the correction of criticalities arising in the delivered bus services. This framework is deeply investigated and discussed in a real-life Italian case.

Keywords

Transit service quality monitoring Low-quality in bus stops Low-quality in vehicles Automatic detection Secret Shopper 

Abbreviations

AHP

Analytical hierarchy process

AT

Alert threshold

CSS

Customer Satisfaction Surveys

HAN

Handling algorithm

OD

Origin-destination

OUT

Output algorithm

PTCs

Public transport companies

SSS

Secret Shopper Surveys

TT

Target threshold

Notes

Acknowledgements

This work has been partially supported by the Italian Ministry of University and Research (MIUR), within the Smart City framework (project: PON04a2_00381 “CAGLIARI2020”). The author is very grateful to the Editor-in-Chief Prof. Stefan Voß and two anonymous referees for their very helpful suggestions. The author is very grateful to the CTM senior management for its support of this work and the opportunity to illustrate the results.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.CTM SpACagliariItaly
  2. 2.Department of Civil Engineering, Environment and ArchitectureUniversity of CagliariCagliariItaly

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