Conference Schedule

Title:
Speaker(s):	Session Speakers

Monday, Feb 20, 2023	Monday, Feb 20, 2023 2:30 PM - 3:00 PM MST		Advanced Machine-Learning Algorithms for Monitoring the Degradation of Pavement Markings Most U.S. transportation agencies restripe their pavement markings based on visual inspection or a fixed schedule, instead of monitoring the retroreflectivity of their markings and restriping when the retroreflectivity drops to a specified threshold. These restriping strategies are not optimum in terms of both efficiency and economy, because on many occasions, markings are restriped before or after the end of their service life, wasting monetary resources and presenting safety issues. Explore a new tool based on advanced machine learning algorithms that can predict the future retroreflectivity of pavement markings without the need for taking regular measurements. Find out how implementation of this tool by state agencies can ensure that pavement markings are restriped timely, while minimizing the potential of under-striping and over-striping. Speaker(s): Momen Mousa, Sam Houston State University Location: ATSSA Showcase, Phoenix Convention Center Advanced Machine-Learning Algorithms.pdf	Location: ATSSA Showcase, Phoenix Convention Center	2023022014:3015:00 001	MON, FEB 20	54841B52-B648-ED11-80F3-8418D0FDE056 85E8D3EE-0CD2-EC11-80F2-AFC32350B496 86E8D3EE-0CD2-EC11-80F2-AFC32350B496 87E8D3EE-0CD2-EC11-80F2-AFC32350B496 75E8D3EE-0CD2-EC11-80F2-AFC32350B496

Monday, Feb 20, 2023

Monday, Feb 20, 2023 2:30 PM - 3:00 PM MST

Advanced Machine-Learning Algorithms for Monitoring the Degradation of Pavement Markings

Most U.S. transportation agencies restripe their pavement markings based on visual inspection or a fixed schedule, instead of monitoring the retroreflectivity of their markings and restriping when the retroreflectivity drops to a specified threshold. These restriping strategies are not optimum in terms of both efficiency and economy, because on many occasions, markings are restriped before or after the end of their service life, wasting monetary resources and presenting safety issues. Explore a new tool based on advanced machine learning algorithms that can predict the future retroreflectivity of pavement markings without the need for taking regular measurements. Find out how implementation of this tool by state agencies can ensure that pavement markings are restriped timely, while minimizing the potential of under-striping and over-striping.

Speaker(s):

Momen Mousa, Sam Houston State University

Location: ATSSA Showcase, Phoenix Convention Center

Advanced Machine-Learning Algorithms.pdf

Location: ATSSA Showcase, Phoenix Convention Center

2023022014:3015:00 001

MON, FEB 20

54841B52-B648-ED11-80F3-8418D0FDE056
85E8D3EE-0CD2-EC11-80F2-AFC32350B496
86E8D3EE-0CD2-EC11-80F2-AFC32350B496
87E8D3EE-0CD2-EC11-80F2-AFC32350B496
75E8D3EE-0CD2-EC11-80F2-AFC32350B496

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