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Improve Urban Pavement Roughness Measures to Meet Customer Expectations
Cities and Counties: See how the City of Austin, Texas is improving pavement data quality and delivering smoother streets. In this interactive 1-hour webinar, Ed Poppitt, P.E., PWLF, explains how better data drives better decisions, improves maintenance outcomes, and helps agencies meet customer expectations for riding comfort on local streets.

Key takeaways: 

• Why city and county streets require unique data collection methods vs. a highway-centric approach
• How riding comfort and surface distress data help you assess road condition to better meet customer expectations
• What actions you can take to improve the quality of your pavement roughness data
• How one city government is benefiting from robust data analysis—and how your agency can, too

Jul 15, 2020 10:00 AM in Central Time (US and Canada)

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Edward Poppitt, III, P.E., PWLF
Consulting Engineer @City of Austin
Ed is a 34-year veteran of the Office of Public Works at the City of Austin, Texas, where he currently serves as Consulting Engineer for the City’s Infrastructure Management Group. He provides general engineering support for issues affecting Austin’s streets, bridges, sidewalks, pavement design programs and criteria, and asset management. He is also assisting the City in developing its newly formed Asset Management Office. He has designed pavements, street reconstruction and rehabilitation, and has collaborated with pavement and bridge management teams since 1993.
Chris Newson
Senior Consultant @AgileAssets
Chris is an asset management expert with more than 25 years of experience in conducting, managing, and analyzing asset condition surveys to improve roadway performance. He has led survey operations for large international consultancies and specialist data collectors and was the pavement data lead at Highways England, a national road authority. Since 2018, he has served as Senior Consultant at AgileAssets, helping agencies improve their asset management strategies and outcomes.