Influence of Pavement Conditions on Commercial Motor Vehicle Crashes [Research Brief]

Arhin, Stephen; Manandhar, Babin; Gatiba, Adam; San Jose State University. College of Business. Mineta Transportation Institute

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Influence of Pavement Conditions on Commercial Motor Vehicle Crashes [Research Brief]

2023-11-01
By Arhin, Stephen ; Manandhar, Babin ; Gatiba, Adam

[PDF-262.66 KB]

English

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Creators:

Arhin, Stephen ; Manandhar, Babin ; Gatiba, Adam

Arhin, Stephen ; Manandhar, Babin ; Gatiba, Adam Less -
Corporate Creators:

San Jose State University. College of Business. Mineta Transportation Institute
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Artificial Neural Network Commercial Vehicles Confusion Matrix Highways Motor Carriers Neural Networks Pavement Condition Pavements Public Transit Road Safety Traffic Safety
Publication/ Report Number:

2343
Resource Type:

Brief
Geographical Coverage:

Washington (District of Columbia) ; United States

Washington (District of Columbia) ; United States Less -
Edition:

Final Report
Corporate Publisher:

San Jose State University. College of Business. Mineta Transportation Institute
Abstract:

The study examined traffic crash data obtained from the Traffic Accident Reporting and Analysis Systems Version 2.0 (TARAS2) database and pavement condition data maintained by the District Department of Transportation (DDOT) in the District of Columbia. CMV crash data was specifically collected for crashes occurring on designated CMV routes between the years 2016 to 2020. Recent measurements of International Roughness Index (IRI) and Pavement Condition Index (PCI) data for the years 2016, 2017, 2019, and 2021 were acquired from the DDOT to correlate the crash data with the pavement’s condition. The research team used QGIS, a robust open-source geographic information system, to effectively manage data integration and analysis.
Format:

PDF
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:5c8ea4a26efac8111005a56fd76d688378e115b0d7414f946508ff0df55225c0
Download URL:

https://rosap.ntl.bts.gov/view/dot/73108/dot_73108_DS1.pdf
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Influence of Pavement Conditions on Commercial Motor Vehicle Crashes [Research Brief]

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