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Title:

Remote Traffic Sign Retro-reflectivity Assessment in a Daytime Using High Dynamic Range Images

Accession Number:

01622728

Record Type:

Component

Abstract:

One of the most effective and low cost ways for improving night time driving safety of transportation systems is maintaining the traffic signs retro-reflectivity condition. The U.S. Federal Highway Administration (FHWA) has enacted new rules on minimum level of retro-reflectivity which compel agencies to measure the current levels of retro-reflectivity of traffic signs and develop plans for replacing or improving their condition. The current practices in assessing and measuring the retro-reflectivity of traffic signs including handheld retro-reflectometer and mobile technologies are financially and practically infeasible because of their constraints. This paper explores the possibility and presents an inexpensive computer vision method for remotely measuring the retro-reflectivity of traffic signs during daytime using High Dynamic Range (HDR) images. By capturing two images simultaneously in a daytime, the method simulates nighttime visibility for each sign and measures retro-reflectivity at a level of accuracy that is mandated by FHWA guidelines. An experimental test was conducted on different types of traffic signs with different levels of retro-reflectivity which are located at different distances in real-world conditions to validate the performance of the method. The results – compared with data collected from a standard retro-reflectometer– demonstrate the potential of the method in lowering the cost, improving the safety, performing in the daytime, and shortening the time needed for retro-reflectivity data collection.

Supplemental Notes:

This paper was sponsored by TRB committee ABJ50 Standing Committee on Information Systems and Technology.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-00477

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Balali, Vahid
Sadeghi, Mohammad Amin
Golparvar-Fard, Mani

Pagination:

15p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Data and Information Technology; Highways; Maintenance and Preservation

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-00477

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 10:05AM