01658007

Component

Highway safety laws aim to influence driver behavior so as to reduce the frequency and severity of crashes, and their outcomes. There are 11 types of highway safety laws in the United States. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT model to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as explanatory variables and socio-demographic and traffic factors are used as control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher speeding fines, older licensing age, and stronger graduated licensing provisions. Injury and property damage only (PDO) crashes would be significantly reduced with stricter laws prohibiting the use of hand-held communication devices and higher fines for drunk driving.

This paper was sponsored by TRB committee ANB10 Standing Committee on Transportation Safety Management.

18-01455

English

24p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Crash rates; Crash severity; Evaluation and assessment; Highway law; Highway safety; Multivariate analysis; State laws

United States

Highways; Law; Safety and Human Factors

Transportation Research Board Annual Meeting 2018 Paper #18-01455

TRIS, TRB, ATRI

Jan 8 2018 10:22AM