A remote sensing and GIS-enabled highway asset management system : final report.

Tsai, Yichang (James); Wang, Zhaohua; Georgia Institute of Technology

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A remote sensing and GIS-enabled highway asset management system : final report.

2016-04-01
By Tsai, Yichang (James) ; Wang, Zhaohua

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English

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Details:

Creators:

Tsai, Yichang (James) ; Wang, Zhaohua

Tsai, Yichang (James) ; Wang, Zhaohua Less -
Corporate Creators:

Georgia Institute of Technology
Corporate Contributors:

Georgia. Dept. of Transportation. Office of Research ; United States. Federal Highway Administration

Georgia. Dept. of Transportation. Office of Research ; United States. Federal Highway Administration Less -
Subject/TRT Terms:

[+]

3D Laser Asset Management Case Studies Cracking Data Collection Flaw Detection Geographic Information Systems Global Positioning System Image Processing Laser Radar Mobile LiDAR Pavement Cracking Pavement Maintenance Remote Sensing Retroreflectivity Rutting Traffic Sign Traffic Signs
Publication/ Report Number:

GA-15-1008
Resource Type:

Tech Report
Geographical Coverage:

United States ; Georgia

United States ; Georgia Less -
Edition:

Final report
Corporate Publisher:

Georgia. Dept. of Transportation. Office of Research
Abstract:

The objective of this project is to validate the use of commercial remote sensing and spatial information

(CRS&SI) technologies, including emerging 3D line laser imaging technology, mobile LiDAR, image

processing algorithms, and GPS/GIS technologies, to improve the transportation asset data collection,

condition assessment, and management. Traffic sign asset and pavement asset were used for validation. For

sign asset, an enhanced procedure for sign inventory was proposed; a large-scale case study was conducted on

I-285; a preliminary study has been done to evaluate sign retroreflectivity using mobile LiDAR; and a

prototype GIS-based sign management system was developed. The research results show that using the

automatic image-processing-based sign detection and recognition algorithms and the LiDAR-based sign

detection can improve the current time-consuming image-based traffic sign data collection process. For

pavement asset, comprehensive validation has been done on network-level rutting measurement and isolated

rutting detection; an innovative method was developed to evaluate the performance of an automatic crack

detection algorithm; comprehensive lab and field tests have been done to validate the capability of 3D laser

data for asphalt pavement crack detection; and a crack propagation study has also been done using the long-term

monitoring data. Based on the research results, conclusions were made and recommendations were

suggested.
Format:

PDF
Funding:

RP 10-08
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:b2bf89be02b770a2fc1f75dd2c6437726d03f11dc46f5cd1dc6d320c3b12d7ca
Download URL:

https://rosap.ntl.bts.gov/view/dot/31105/dot_31105_DS1.pdf
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A remote sensing and GIS-enabled highway asset management system : final report.

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