Cited by 24Video Surveillance and Tracking MethodsAdvanced Neural Network ApplicationsTransportation Planning and Optimization

Evaluating the Performance of Video-Based Automated Passenger Counting Systems in Real-World Conditions: A Comparative Study

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Pronello, Cristina, Garzón Ruiz, Ximena Rocio·2023·Sensors

Abstract

Automatic passenger counting (APC) systems in public transport are useful in collecting information that can help improve the efficiency of transport networks. Focusing on video-based passenger counting, the aim of this study was to evaluate and compare an existing APC system, claimed by its manufacturer to be highly accurate (98%), with a newly developed low-cost APC system operating under the same real-world conditions. For this comparison, a low-cost APC system using a Raspberry Pi with a camera and a YOLOv5 object detection algorithm was developed, and an in-field experiment was performed in collaboration with the public transport companies operating in the cities of Turin and Asti in Italy. The experiment shows that the low-cost system was able to achieve an accuracy of 72.27% and 74.59%, respectively, for boarding and alighting, while the tested commercial APC system had an accuracy, respectively, of 53.11% and 55.29%. These findings suggest that current APC systems might not meet expectations under real-world conditions, while low-cost systems could potentially perform at the same level of accuracy or even better than very expensive commercial systems.

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  1. [13]Hensher D.A. Chapter 23—A Review of Objective and Subjective Measures of Crowding in Public Transport Bus Transport Elsevier Amsterdam, The Netherlands 2020 281 294 978-0-12-820132-9
  2. [16]Liciotti D. Cenci A. Frontoni E. Mancini A. Zingaretti P. An Intelligent RGB-D Video System for Bus Passenger Counting Intelligent Autonomous Systems 14 Chen W. Hosoda K. Menegatti E. Shimizu M. Wang H. Springer International Publishing Cham, Switzerland 2017 473 484

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Authors
Pronello, C., & Garzón Ruiz, X. R.
Affiliations
  • Politecnico di Torino (IT)
  • Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, 10125 Turin, Italy
Corresponding author
Pronello, Cristina
Venue
Sensors
Publisher
MDPI AG
Published
2023-09-07
Volume
23
Issue
18
Pages
7719
ISSN
1424-8220 (ISSN-L)
OpenAlex
W4386498394
Cited by
24
References
56
Citations by year
2026: 6 · 2025: 10 · 2024: 8
FWCI
2.18
Type
journal article
Language
en
Open access
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PORTO@Iris (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
  • Social Sciences › Transportation › Transportation Planning and Optimization
Keywords
automatic passenger counting, public transport, Raspberry Pi, YOLOv5, object detection, passenger flow monitoring

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