Abstract
The purpose of this paper was to present an empirical inquiry into the categorization of collision types based on contributing factors and severity distribution. This study used Connecticut crash data from selected two-lane roads originated from police reports from 1996 to 2001. K-means cluster analysis methodology was conducted to categorize 10 collision types into 4 groups according to the similar pattern of their contributing factors. The severity distribution of the collision types was then considered to further divide up or combine the categories. The result of this analysis offers an analytical way at categorizing collisions to relate crash risk to causalities and driver’s misbehaviors. It also provides a crash categorization that can lead to more accurate and specific severity prediction.
Original language | English |
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Title of host publication | Proceedings of the 86th Annual meeting of TRB, CD-ROM |
Publisher | Transportation Research Board, Washington DC, USA |
Number of pages | 21 |
Publication status | Published - 2007 |
Event | 86th annual meeting of the Transportation Research Board - Washington DC, United States Duration: 2007 Jan 21 → 2007 Jan 25 |
Conference
Conference | 86th annual meeting of the Transportation Research Board |
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Country/Territory | United States |
City | Washington DC |
Period | 2007/01/21 → 2007/01/25 |
Subject classification (UKÄ)
- Civil Engineering
Free keywords
- modelling
- severity
- crash
- accident
- safety
- road
- modeling
- traffic
- causality