Detection and Characterization of Road Accident Clusters in Texas Counties
2017
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Advisor: Mehmet Metin Kunt
Abstract (EN)
Traffic accidents count for one of the main causes of life losses globally as well as heavy burden of their consequents on societies, a matter which prompts researchers to discover the reasons of accidents occurrence and factors affect their severity. Therefore, in this study k-means clustering method is applied to analyze traffic accident data to identify the counties with the highest relatively severe accidents, considering all levels of crash severity, due to driver-related risk factors in Texas State. It analyzes recorded data of the statewide accidents occurred within 2013 to 2015, available from Texas Department of Transportation official website. As a result of this research the counties with similar status of crash severity were identified among which the counties in the most critical situation were distinguished, an outcome that can be useful for authorities such as transportation planners to make appropriate decisions in safety planning. Furthermore, some of the contributor factors that may intensify accidents were addressed. Keywords: Traffic safety, Accident, Severity, K-Means, Clustering
Author
Dr. Zaniar Babaei
How to Cite
Zaniar Babaei (Master Thesis). Detection and Characterization of Road Accident Clusters in Texas Counties, 2017, Eastern Mediterranean University, Department of Civil Engineering.
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