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Investigation of Contributing Factors to Traffic Crashes and Violations: A Random Parameter Multinomial Logit Approach
Author(s) -
Jaeyoung Lee,
Xing Li,
Suyi Mao,
Wen Fu
Publication year - 2021
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1155/2021/2836657
Subject(s) - seriousness , multinomial logistic regression , minor (academic) , commit , crash , poison control , human factors and ergonomics , affect (linguistics) , psychology , computer security , transport engineering , statistics , engineering , computer science , mathematics , environmental health , medicine , political science , programming language , communication , database , law
This study investigates contributing factors to traffic violations by seriousness. The traffic violations are divided into four categories by seriousness (unintentional violation, minor violation, serious violation, and crash with violation). The results of the random parameter multinomial logit model indicate that various factors potentially affect the severity of traffic violations. The key findings include the following: (1) female drivers are more likely to commit minor violations; (2) drivers from an area with a longer travel time to work and a higher proportion of driving to work are more likely to have minor violations and serious violations, while those from the high-income area are less likely; (3) drivers are more likely to be associated with a more minor infraction during the afternoon peak (4 p.m.–6 p.m.). The results from this study are expected to be beneficial for policymakers and traffic police to comprehend the factors affecting violations and implement effective strategies to minimize the number and seriousness of traffic violations.

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