Passenger Occupancy Estimation in Vehicles: A Review of Current Methods and Research Challenges

Passenger detection and occupancy estimation are vital tasks in many fields. The existing literature emphasises that the increasing demand for such systems will continue to grow. This paper reviews the existing literature specializing in the field of transportation safety and efficiency concerning o...

Full description

Saved in:
Bibliographic Details
Published in:Sustainability 2023-01, Vol.15 (2), p.1332
Main Authors: Kuchár, Pavol, Pirník, Rastislav, Janota, Aleš, Malobický, Branislav, Kubík, Jozef, Šišmišová, Dana
Format: Article
Language:English
Subjects:
Accuracy
Air bags
Buses (vehicles)
Cameras
Comparative analysis
High occupancy vehicle lanes
Literature reviews
Methods
Motorcycles
Neural networks
Occupancy
Passengers
Public transportation
Sensors
Surveillance
Sustainability
Tinting
Trucks
Windshields
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Passenger detection and occupancy estimation are vital tasks in many fields. The existing literature emphasises that the increasing demand for such systems will continue to grow. This paper reviews the existing literature specializing in the field of transportation safety and efficiency concerning occupancy estimation in vehicles and passenger detection at public transport stations. A comparison between different approaches to passenger estimation is presented. Discussion on the advantages and disadvantages is highlighted. Hence, this paper provides an analysis of 146 papers on the current state of the field. This review paper concludes that invasive methods provide high accuracy with relatively cheap implementation, while noninvasive systems do not violate passenger privacy but lack state-of-the-art accuracy. Future work will include a systematic literature review and a comparative analysis of systems considering the existing window tinting and solar windshields heavily blocking certain parts of the electromagnetic spectrum. Moreover, future work will investigate the critical challenges of noninvasive passenger estimation in different types of vehicles: trucks, buses, or even motorcycles.
ISSN:2071-1050
2071-1050
DOI:10.3390/su15021332