Development of Pavement Performance Models for MDOT: A Neural Network Approach

Yasarer, Hakan; Najjar, Yacoub M.; University of Mississippi

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Development of Pavement Performance Models for MDOT: A Neural Network Approach

2024-06-26
By Yasarer, Hakan ; Najjar, Yacoub M.

[PDF-3.54 MB]

English

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Creators:

Yasarer, Hakan ; Najjar, Yacoub M.

Yasarer, Hakan ; Najjar, Yacoub M. Less -
Corporate Creators:

University of Mississippi
Corporate Contributors:

Mississippi Department of Transportation
Subject/TRT Terms:

[+]

Artificial Neural Networks Composite Pavements Flexible Pavements Neural Networks Pavement Management Systems Pavement Performance Pavement Performance Modeling Rigid Pavements
Publication/ Report Number:

FHWA/MDOT-RD-22-298 ; 12019-00(004)/107895-101000

FHWA/MDOT-RD-22-298 ; 12019-00(004)/107895-101000 Less -
Resource Type:

Tech Report
Geographical Coverage:

Mississippi ; United States

Mississippi ; United States Less -
Edition:

2/28/19 – 12/31/2023
Corporate Publisher:

Mississippi. Dept. of Transportation
Abstract:

The continuous investigation into the mechanical properties and rehabilitation management of existing pavements is vital for the sustainability and efficiency of transportation systems. The Mississippi Department of Transportation (MDOT) database, containing over 40 million records, necessitates modernized decision-making models that align with current design methods and materials. In collaboration with the University of Mississippi, MDOT's pavement management program aimed to update outdated Markov transition matrices with advanced Artificial Neural Networks (ANNs). This four-year project focuses on dynamic sequential ANNs to develop performance prediction models for flexible, rigid, and composite pavements, utilizing extensive distress data. Initial results for flexible pavements showed promising outcomes, with robust statistical accuracy measures for rigid pavements (JCP and CRCP) and composite pavements, although further data and calibration are recommended. The developed models, accessible through a user-friendly interface, are expected to improve the prioritization of maintenance and rehabilitation resources, achieving significant time and cost savings while enhancing the overall efficiency of MDOT's pavement management practices.
Format:

PDF
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha-512:b918c7ce03465a43b8a64c303ea60459f81348ebca51591d4fa34236aa55b652922632889bf38c71d66cd2e7a2ad507325a8a3737bcca37197d9708abf711def
Download URL:

https://rosap.ntl.bts.gov/view/dot/75840/dot_75840_DS1.pdf
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Development of Pavement Performance Models for MDOT: A Neural Network Approach

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