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Pedestrian monitoring techniques for crowd-flow prediction

Published version
Peer-reviewed

Type

Article

Change log

Authors

Martani, C 
Stent, S 
Acikgoz, S 
Soga, K 
Bain, D 

Abstract

The high concentration and flow rate of people in train stations during rush hours can pose a prominent risk to passenger safety and comfort. In situ counting systems are a critical element for predicting pedestrian flows in real time, and their capabilities must be rigorously tested in live environments. The focus of this paper is on evaluating the reliability of two alternative counting systems, the first using an array of infrared depth sensors and the second a visible light (RGB) camera. Both proposed systems were installed at a busy walkway in London Bridge station. The data were collected over a period of 2 months, after which, portions of the data set were labelled for quantitative evaluation against ground truth. In this paper, the implementation of the two different counting technologies is described, and the accuracy and limitations of both approaches under different conditions are discussed. The results show that the developed RGB-based system performs reliably across a wide range of conditions, while the depth-based approach proves to be a useful complement in conditions without significant ambient sunlight, such as underground passageways.

Description

Keywords

4005 Civil Engineering, 46 Information and Computing Sciences, 40 Engineering

Journal Title

Smart Infrastructure and Construction

Conference Name

Journal ISSN

2397-8759
2397-8759

Volume Title

170

Publisher

ICE Pulbishing
Sponsorship
Engineering and Physical Sciences Research Council (EP/K000314/1)
Engineering and Physical Sciences Research Council (EP/I019308/1)
Engineering and Physical Sciences Research Council (EP/N021614/1)
EPSRC
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