This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Highway safety is a major priority for the public and for transportation agencies. Pavement distresses directly affect ride quality, and indirectly contribute to driver distraction, vehicle operation, and accidents. In this study, analysis was performed on highways in the states of Arizona, North Carolina and Maryland for years…
Highway safety is a major priority for the public and for transportation agencies. Pavement distresses directly affect ride quality, and indirectly contribute to driver distraction, vehicle operation, and accidents. In this study, analysis was performed on highways in the states of Arizona, North Carolina and Maryland for years between 2013 and 2015 in order to investigate the relationship between accident rate and pavement roughness and rutting. Two main types of data were collected: crash data from the accident records and roughness and rut depth data from the pavement management system database in each state. Crash rates were calculated using the U.S. Department of Transportation method, which is the number of accidents per vehicle per mile per year multiplied by 100,000,000. The variations of crash rate with both International Roughness Index (IRI) and rut depth were investigated. Linear regression analysis was performed to study the correlation between parameters. The analysis showed positive correlations between road roughness and rut depth in all cases irrespective of crash severity level. The crash rate data points were high for IRI values above 250-300 inches/mile in several cases. Crash road segments represent 37-48 percent of the total length of the network using 1-mile segments. Roughness and rut depth values for crash and non-crash segments were close to each other, suggesting that roughness and rutting are not the only factors affecting number of crashes but possibly in combination with other factors such as traffic volume, human factors, etc. In summary, it can be concluded that both roughness and rut depth affect crash rate and highway maintenance authorities should maintain good pavement condition in order to reduce crash occurrences.
