Intelligence, Informatics and Infrastructure
Online ISSN : 2758-5816
A Road Narrowing Condition Estimation from In-vehicle Camera Videos via Late-Fusion based on Confidence Level Integration of Multiple Classifiers
Hiroki KINOSHITAMasahiro YAGISho TAKAHASHIToru HAGIWARA
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2024 Volume 5 Issue 1 Pages 80-88

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Abstract

In snowy and cold regions, piled snow on road shoulders may cause traffic congestion and even traffic accidents. Maintaining the functionality of urban transportation can be a severe problem. In order to maintain the effective width of roads during the winter, piled snow on the road shoulders is removed and cleared. However, getting road information requires a great deal of time and workforce. In this paper, we propose a novel method for classifying the effective road width, narrowed by piled snow on road shoulders, based on videos captured from in-vehicle cameras using features focused on piled snow. Estimating road narrowing conditions from in-vehicle cameras will enable ordinary vehicles to collect road information and create an environment that does not require much time or workforce to gather road information.

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© 2024 Japan Society of Civil Engineers
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