Continuous Road Surface Distress Detection

Mertz, Christoph; Hebert, Martial; Jose, Sobhagya; Sharma, Karan; Varadharajan, Srivatsan; Wander, Lars; Wang, Jinhang; Carnegie-Mellon University. Robotics Institute; Technologies for Safe and Efficient Transportation. University Transportation Center

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Continuous Road Surface Distress Detection

2014-01-01
By Mertz, Christoph ; Hebert, Martial ; Jose, Sobhagya ; ...

[PDF-1.53 MB]

English

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Details:

Creators:

Mertz, Christoph ; Hebert, Martial ; Jose, Sobhagya ; Sharma, Karan ; Varadharajan, Srivatsan ; ... More +

Mertz, Christoph ; Hebert, Martial ; Jose, Sobhagya ; Sharma, Karan ; Varadharajan, Srivatsan ; Wander, Lars ; Wang, Jinhang Less -
Corporate Creators:

Carnegie-Mellon University. Robotics Institute ; Technologies for Safe and Efficient Transportation. University Transportation Center

Carnegie-Mellon University. Robotics Institute ; Technologies for Safe and Efficient Transportation. University Transportation Center Less -
Corporate Contributors:

United States. Dept. of Transportation. Research and Innovative Technology Administration
Subject/TRT Terms:

[+]

Algorithms Data And Information Technology Detection And Identification Devices Highways Image Processing Inspection Machine Vision Maintenance And Preservation Pavement Distress Smartphones Urban Areas
Resource Type:

Tech Report
Geographical Coverage:

Pittsburgh (Pennsylvania) ; United States

Pittsburgh (Pennsylvania) ; United States Less -
TRIS Online Accession Number:

01668814
Corporate Publisher:

Carnegie-Mellon University
NTL Classification:

NTL-HIGHWAY/ROAD TRANSPORTATION-Pavement Management and Performance
Abstract:

State and local maintenance departments are tasked with keeping roads in good repair. One part of this task is to monitor the degradation of road surfaces, which manifests itself with the presence of cracks, potholes, and other distress. The approach of the road inspection system developed in this project is to use images or videos collected by commodity devices such as smartphones. The devices are mounted in vehicle that travels the roads for other purposes and therefore no dedicated vehicles or drivers are needed. The captured images are analyzed automatically with machine vision algorithms and the resulting distress scores are passed to the asset management system.
Format:

PDF
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:2bf0a9e555c86bdd8e1056cd1aeb59a5a7adeeac971463ab86ae73fb38aeaf7d
Download URL:

https://rosap.ntl.bts.gov/view/dot/36795/dot_36795_DS1.pdf
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Continuous Road Surface Distress Detection

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