Nebraska Data Collection
Keyvan Zare Rami, Yong‐Rak Kim
Abstract
Keyvan Zare Rami, Yong‐Rak Kim
Abstract
Automated pavement performance data collection is a method that uses advanced technology to collect detailed road surface distress information at traffic speed. Agencies are driven to use automated survey techniques to enhance or replace their current manual distress survey because of the advantages of objective measurements, safety benefits, and reduced measurement time. As agencies move toward the transition to fully automated data collection methods, there are common concerns regarding how the output of the new method will match the current manual survey ratings and how they will be adopted into the existing Pavement Management System (PMS). This study evaluates the newly implemented automated distress survey technique and its implementation into the Nebraska Pavement Management System (NPMS). To meet the objectives, a user-friendly program was developed to convert the automated distress ratings into the current manual distress ratings format. Then, a data set that includes more than 7,000 miles of distress data collected by the automated method was converted to the manual data format and compared to the most recent manual rating data of those sections to assess the agreement between the two data formats after the conversion process. The results show that the automated pavement survey slightly overrates bituminous pavement distresses with only a few distress types that could not be properly detected. Finally, a regression analysis of a core pavement performance indicator, Nebraska Serviceability Index (NSI), was conducted to examine how the new automated performance measurement system will ultimately affect NPMS decisions if implemented into Nebraska’s pavement management system.
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Automated pavement performance data collection is a method that uses advanced technology to collect detailed road surface distress information at traffic speed. Agencies are driven to use automated survey techniques to enhance or replace their current manual distress survey because of the advantages of objective measurements, safety benefits, and reduced measurement time. As agencies move toward the transition to fully automated data collection methods, there are common concerns regarding how the output of the new method will match the current manual survey ratings and how they will be adopted into the existing Pavement Management System (PMS). This study evaluates the newly implemented automated distress survey technique and its implementation into the Nebraska Pavement Management System (NPMS). To meet the objectives, a user-friendly program was developed to convert the automated distress ratings into the current manual distress ratings format. Then, a data set that includes more than 7,000 miles of distress data collected by the automated method was converted to the manual data format and compared to the most recent manual rating data of those sections to assess the agreement between the two data formats after the conversion process. The results show that the automated pavement survey slightly overrates bituminous pavement distresses with only a few distress types that could not be properly detected. Finally, a regression analysis of a core pavement performance indicator, Nebraska Serviceability Index (NSI), was conducted to examine how the new automated performance measurement system will ultimately affect NPMS decisions if implemented into Nebraska’s pavement management system.
Key concepts: Data collection, Serviceability (structure), Pavement management, Distress, Engineering, Computer science, Transport engineering, Civil engineering