Collision Type Categorization Based on Crash Causality and Severity Analysis
(2007) 86th annual meeting of the Transportation Research Board- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/838785
- author
- Zhang, Chen ; Ivan, John N. and Jonsson, Thomas LU
- organization
- publishing date
- 2007
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- modelling, severity, crash, accident, safety, road, modeling, traffic, causality
- host publication
- Proceedings of the 86th Annual meeting of TRB, CD-ROM
- pages
- 21 pages
- publisher
- Transportation Research Board, Washington DC, USA
- conference name
- 86th annual meeting of the Transportation Research Board
- conference location
- Washington DC, United States
- conference dates
- 2007-01-21 - 2007-01-25
- language
- English
- LU publication?
- yes
- id
- fcc64ebc-a6af-438a-82de-941ae86ffe30 (old id 838785)
- date added to LUP
- 2016-04-04 11:18:12
- date last changed
- 2018-11-21 21:03:57
@inproceedings{fcc64ebc-a6af-438a-82de-941ae86ffe30, 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.}}, author = {{Zhang, Chen and Ivan, John N. and Jonsson, Thomas}}, booktitle = {{Proceedings of the 86th Annual meeting of TRB, CD-ROM}}, keywords = {{modelling; severity; crash; accident; safety; road; modeling; traffic; causality}}, language = {{eng}}, publisher = {{Transportation Research Board, Washington DC, USA}}, title = {{Collision Type Categorization Based on Crash Causality and Severity Analysis}}, year = {{2007}}, }