Heavy-Vehicle Driver Injury Severity Analysis by Time of Week :

announce the Highway Safety Information Systems (HSIS) Excellence in Highway Safety Data Awards Program, a competition designed to encourage university students to use HSIS data to investigate a topic that advances highway safety and to develop a paper to document the original research, as well as introduce potential future highway safety professionals to good quality safety data, the application of appropriate research methods to derive recommendations, and the practice of using data to make decisions.

[1]  Samantha Islam,et al.  Comprehensive analysis of single- and multi-vehicle large truck at-fault crashes on rural and urban roadways in Alabama. , 2014, Accident; analysis and prevention.

[2]  Gudmundur F. Ulfarsson,et al.  A note on modeling pedestrian-injury severity in motor-vehicle crashes with the mixed logit model. , 2010, Accident; analysis and prevention.

[3]  Kirolos Haleem,et al.  Effect of driver's age and side of impact on crash severity along urban freeways: a mixed logit approach. , 2013, Journal of safety research.

[4]  Matthew G Karlaftis,et al.  Vehicle occupant injury severity on highways: an empirical investigation. , 2010, Accident; analysis and prevention.

[5]  Gudmundur F. Ulfarsson,et al.  Differences in male and female injury severities in sport-utility vehicle, minivan, pickup and passenger car accidents. , 2004, Accident; analysis and prevention.

[6]  Fred L Mannering,et al.  Highway accident severities and the mixed logit model: an exploratory empirical analysis. , 2008, Accident; analysis and prevention.

[7]  Avinash Unnikrishnan,et al.  Analysis of large truck crash severity using heteroskedastic ordered probit models. , 2011, Accident; analysis and prevention.

[8]  Kai Wang,et al.  Logistic Regression Models of the Safety of Large Trucks , 2013 .

[9]  Dominique Lord,et al.  Comparing Three Commonly Used Crash Severity Models on Sample Size Requirements: Multinomial Logit, Ordered Probit, and Mixed Logit Models , 2014 .

[10]  А.В. Голяшев.  Общие особенности межрегиональных торговых потоков в США в 2007 г. (по данным Commodity Flow Survey) , 2013 .

[11]  J Carson,et al.  The effect of ice warning signs on ice-accident frequencies and severities. , 2001, Accident; analysis and prevention.

[12]  Chandra R. Bhat,et al.  Unobserved heterogeneity and the statistical analysis of highway accident data , 2016 .

[13]  Konstantina Gkritza,et al.  A comparison of the mixed logit and latent class methods for crash severity analysis , 2014 .

[14]  Sunil Patil,et al.  Analysis of Motorcycle Crashes in Texas with Multinomial Logit Model , 2011 .

[15]  Salvador Hernandez,et al.  Modeling Injury Outcomes of Crashes Involving Heavy Vehicles on Texas Highways , 2013 .

[16]  F. Mannering,et al.  Differences in rural and urban driver-injury severities in accidents involving large-trucks: an exploratory analysis. , 2005, Accident; analysis and prevention.

[17]  Li-Yen Chang,et al.  Analysis of driver injury severity in truck-involved accidents using a non-parametric classification tree model , 2013 .

[18]  Suren Chen,et al.  Injury severities of truck drivers in single- and multi-vehicle accidents on rural highways. , 2011, Accident; analysis and prevention.

[19]  Xiaoyu Zhu,et al.  A comprehensive analysis of factors influencing the injury severity of large-truck crashes. , 2011, Accident; analysis and prevention.

[20]  Jasmine Pahukula,et al.  A time of day analysis of crashes involving large trucks in urban areas. , 2015, Accident; analysis and prevention.

[21]  D. McFadden.  Econometric Models of Probabilistic Choice , 1981 .

[22]  F. Mannering,et al.  The effects of road-surface conditions, age, and gender on driver-injury severities. , 2011, Accident; analysis and prevention.

[23]  Gudmundur F. Ulfarsson,et al.  Driver-injury severity in single-vehicle crashes in California: A mixed logit analysis of heterogeneity due to age and gender. , 2013, Accident; analysis and prevention.