Automated Inventory and Analysis of Highway Assets

Gong, Weiguo; Hou, Zhiqiong; Wang, Kelvin C. P.; University of Arkansas, Fayetteville. Dept. of Civil Engineering

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Automated Inventory and Analysis of Highway Assets

2007-03-13
By Gong, Weiguo ; Hou, Zhiqiong ; Wang, Kelvin C. P.

[PDF-799.34 KB]

English

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Creators:

Gong, Weiguo ; Hou, Zhiqiong ; Wang, Kelvin C. P.

Gong, Weiguo ; Hou, Zhiqiong ; Wang, Kelvin C. P. Less -
Corporate Creators:

University of Arkansas, Fayetteville. Dept. of Civil Engineering
Subject/TRT Terms:

[+]

Asset Management Databases Data Collection Detectors By Object Of Detection Freight Transportation Highway Facilities Highways I61: Equipment And Maintenance Methods Image Processing Maintenance And Preservation Object Tracking Right Of Way (Traffic) Speed Traffic Signs Transportation, Hydraulic And Utility Facilities
Publication/ Report Number:

MBTC 2065 Project
Resource Type:

Tech Report
Geographical Coverage:

United States ; Arkansas

United States ; Arkansas Less -
TRIS Online Accession Number:

01049506
Edition:

Final Report
Corporate Publisher:

University of Arkansas, Fayetteville. Dept. of Civil Engineering
Abstract:

The goal of this project is to develop a system which can automatically detect and localize the traffic signs along the roads, in order to provide a comprehensive sign database for sign inventory purpose. The project work focuses on systems integration of existing technologies to create reliable applications for high performance road data asset inventory. The fundamental methods used for feature extraction, object tracking and retrieval in these applications are well-established. Exploration of the advanced, state-of-the-art or experimental algorithmic development was also made during the project. The work also addresses the issue of incorporating parallel computing in order to achieve the real-time characteristics of the system. This report describes the research work on system design, data acquisition, image processing, object tracking, feature extraction, and database recording. The system developed in this project is capable of reliably capturing the Right-Of-Way (ROW) images. The software developed in this project can detect and recognize most of the commonly used road signs with a 99% accuracy rate in a driving speed up to 60 mph.
Format:

PDF
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:6ee42bcc38047369fbf0ec818f00310dde574a89edbe710cc287ef9d4608b75e
Download URL:

https://rosap.ntl.bts.gov/view/dot/38887/dot_38887_DS1.pdf
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Automated Inventory and Analysis of Highway Assets

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