• Transportation Research Board

      TRB 98th Annual Meeting

      January 13–17, 2019

    • Interactive Program

2019

Annual Meeting Event Detail




Poster Session 1565

Application of Machine Learning Methods for Operation and Maintenance of Transportation Systems (Part 1)

Tuesday 1:30 PM- 3:15 PM
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Poster
Adrian Burde, Leidos, Inc., presiding
Sponsored by:
Standing Committee on Maintenance and Operations Management (AHD10)
Section - Maintenance and Preservation (AHD00)

Recent advances in machine and statistical learning have the potential to unveil deep correlations and patterns across different variables affecting roadway assets. The emergence of advanced vision sensing methods has considerably increased the amount of research in the field of video analytics and image processing, opening the door to fast and inexpensive roadway asset classification and defect detection. This session explores relevant topics such as incorporating advanced machine learning tools in operations & maintenance, predictive analytics for highway asset management, application of machine learning for reducing life-cycle costs of maintenance, and visual analytics for automated asset classification and condition assessment.



No agenda available

Title Presentation Number
A Scalable Machine Learning Framework for Predictive Road Maintenance and Management
Arash Karimzadeh, UNCC, CHARLOTTE
Adrian Burde, Leidos, Inc.
Hamed Tabkhi, University of North Carolina, Charlotte
Omidreza Shoghli, University of North Carolina, Charlotte
Show Abstract
P19-20553
Deep Learning-in-the-loop for Road Asset Classification
Sadegh Nouri Gooshki, University of North Carolina, Charlotte
Mayuri Deshpande, University of North Carolina, Charlotte
Adrian Burde, Leidos, Inc.
Omidreza Shoghli, University of North Carolina, Charlotte
Hamed Tabkhi, University of North Carolina, Charlotte
Show Abstract
P19-20554
Supporting Bridge Management with Advanced Analysis and Machine Learning
Fayaz Sofi, University of Nebraska, Lincoln
Xinyu Lin, University of Connecticut
Joshua Steelman, University of Nebraska, Lincoln
FRANCISCO JOSE GARCIA
Show Abstract
P19-20555
Application of Machine-Learning Methods in Pavement Management and Evaluation
Momen Ragab Mousa, Louisiana State University
Mostafa Elseifi, Louisiana State University
Omar Elbagalati, Louisiana State University
Show Abstract
P19-20556
Evaluation of Alternative Pre-trained Convolutional Neural Networks for Winter Road Surface Condition Monitoring
Guangyuan Pan, University of Waterloo
Liping Fu, University of Waterloo
Ruifan Yu, University of Waterloo
Matthew Muresan, University of Waterloo
Tae Kwon, University of Alberta
Show Abstract
P19-20690
Deep Learning and Traffic Signal Control: A Comparative Analysis of Current State-of-the-Art Methods
Matthew Muresan, University of Waterloo
Guangyuan Pan, University of Waterloo
Liping Fu, University of Waterloo
Show Abstract
P19-20692