Evaluation of Injury Severity for Pedestrian–Vehicle Crashes in Jordan Using Extracted Rules
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 145, Issue 7
Abstract
Pedestrian safety is a major concern throughout the world because pedestrians are considered to be the most vulnerable roadway users. This paper sought to identify the main factors in pedestrian-vehicle crashes that increase the risk of a fatality or severe injury. Pedestrian-vehicle crashes which occurred in urban and suburban areas in Jordan between 2009 and 2011 were investigated. Extracted rules from Bayesian networks were used to identify factors related to severity of pedestrian-vehicle crashes. To obtain as much information as possible about these factors, three subsets were used. The first and second subsets contain all types of collisions (pedestrian and nonpedestrian), in which the first subset used collision type as a class variable and the second subset used injury severity. The third subset contains pedestrian collisions only and used injury severity as the class variable. The results indicate that when using collision type as the class variable, better performance was obtained and that the following variables increase the risk of fatality or severe injury: roadway type, number of lanes, speed limit, lighting, and adverse weather conditions.
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Acknowledgments
The authors are grateful to the Police Traffic Department in Jordan for providing the necessary data for this research. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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©2019 American Society of Civil Engineers.
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Received: Nov 30, 2017
Accepted: Nov 26, 2018
Published online: Apr 30, 2019
Published in print: Jul 1, 2019
Discussion open until: Sep 30, 2019
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