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Title:

Road Slipperiness Detection Using Digital Tachograph Data

Accession Number:

01763586

Record Type:

Component

Abstract:

Faced with high rates of traffic accidents on slippery roads, it is recommended that road managers promptly identify the slippery spots, remove the slipperiness and inform drivers of the location of the dangerous spots on the route ahead, to allow them to prepare for the slipperiness. In this paper, the wheel slip-based and wheel acceleration-based approaches are suggested for detecting road slipperiness using sensor data from a digital tachograph (DTG), which is mandatory in commercial vehicles. Support vector machine algorithms were employed to categorize slippery and non-slippery states. The performances were outstanding (with accuracy more than 98%) when evaluated using experimental data, collected on a road weather-proving ground. Considering a large number of commercial vehicles equipped with DTG devices which are connected via celluar communications, the suggested methods could be practically applied to real-world DTG-based fleet management systems.

Supplemental Notes:

This paper was sponsored by TRB committee AKR50 Standing Committee on Road Weather.

Report/Paper Numbers:

TRBAM-21-00168

Language:

English

Corporate Authors:

Transportation Research Board

Authors:

Jang, Jinhwan

Pagination:

14p

Publication Date:

2021

Conference:

Transportation Research Board 100th Annual Meeting

Location: Washington DC, United States
Date: 2021-1-5 to 2021-1-29
Sponsors: Transportation Research Board; Transportation Research Board

Media Type:

Web

Features:

Glossary; References; Tables

Subject Areas:

Data and Information Technology; Highways

Source Data:

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-00168

Files:

TRIS, TRB, ATRI

Created Date:

Dec 23 2020 11:06AM