Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender

► Mixed logit models capture population heterogeneity in injury severity. ► Age and gender lead to important population heterogeneity effects. ► Transportation policy must account for increased aging-related population variance. ► Population move towards newer safer vehicles can have a significant s...

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Veröffentlicht in:	Accident analysis and prevention 2013-01, Vol.50, p.1073-1081
Hauptverfasser:	Kim, Joon-Ki, Ulfarsson, Gudmundur F., Kim, Sungyop, Shankar, Venkataraman N.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accidents, Traffic - statistics & numerical data Adult Age Age Factors Aged Automobile Driving Biological and medical sciences California - epidemiology Female Gender Heterogeneity Humans Injury severity Injury Severity Score Logistic Models Male Medical sciences Middle Aged Miscellaneous Mixed logit Prevention and actions Public health. Hygiene Public health. Hygiene-occupational medicine Risk Factors Sex Factors Single-vehicle
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