Automated Pavement Condition Survey Field Manual

Automated Pavement Condition Survey Field Manual
Author: Pennsylvania. Department of Transportation. Roadway Management Division
Publisher:
Total Pages: 70
Release: 2015
Genre: Pavements
ISBN:

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Automated Pavement Condition Survey Field Manual

Automated Pavement Condition Survey Field Manual
Author: Pennsylvania. Department of Transportation. Bureau of Maintenance and Operations. Roadway Management Division
Publisher:
Total Pages: 66
Release: 2005
Genre: Pavements
ISBN:

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Automated Pavement Condition Surveys

Automated Pavement Condition Surveys
Author: Linda M. Pierce
Publisher:
Total Pages: 124
Release: 2019
Genre: Pavements
ISBN: 9780309480482

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TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 531 documents agency practices, challenges, and successes in conducting automated pavement condition surveys. The report also includes three case examples that provide additional information on agency practices for conducting automated pavement surveys. Pavement condition data is a critical component for pavement management systems in state departments of transportation (DOTs). The data is used to establish budget needs, support asset management, select projects for maintenance and preservation, and more. Data collection technology has advanced rapidly over the last decade and many DOTs now use automated data collection systems.

Development of Automated Pavement Condition Score and Decision Logic

Development of Automated Pavement Condition Score and Decision Logic
Author: Joseph A. Stefanski
Publisher:
Total Pages: 0
Release: 2022
Genre: Pavements
ISBN:

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The Ohio Department of Transportation (ODOT) has been collecting 3D digital data on their pavement network since 2014. This data contains a variety of information derived from 3d laser scans of the pavement. While ODOT has been using the data to meet federal HPMS reporting requirements of pavement condition, the agency wished to leverage this wealth of data to aid their pavement management system and transition from a manual pavement condition survey to an automated one. This research aims to provide ODOT a means to interpret the data and use it to make the same decisions as the existing pavement management system. Topics include analysis and development of a new rating methodology for automated distress detection and classification as well as deterioration models and decision trees for the new rating methodology. The rating system was developed using comparisons with existing manual ratings and automated data collected from 2014 through 2018. Additionally, the report covers how to implement this methodology and how it impacts pavement management decisions.