Journal ArticleDOI
Grouped random parameters bivariate probit analysis of perceived and observed aggressive driving behavior: A driving simulation study
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In this paper, the authors used driving simulation data and surveys conducted in 2014 and 2015 in Buffalo, NY, to study the factors that affect perceived (self-reported, based on surveys) and observed (as measured based on driving simulation experiments) aggressive driving behavior.About:
This article is published in Analytic Methods in Accident Research.The article was published on 2017-03-01. It has received 84 citations till now. The article focuses on the topics: Multivariate probit model & Probit model.read more
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Occupant injury severities in hybrid-vehicle involved crashes: A random parameters approach with heterogeneity in means and variances
Puttipan Seraneeprakarn,Shuaiqi Huang,Venkataraman N. Shankar,Fred L. Mannering,Narayan Venkataraman,John Milton +5 more
TL;DR: In this article, the authors used a sample of hybrid-vehicle-involved crashes and estimates a mixed logit model of the resulting injury level of the most severely injured occupant in the crash, while accounting for possible heterogeneity in the means and variances of model parameters.
Journal ArticleDOI
Analysis of accident injury-severities using a correlated random parameters ordered probit approach with time variant covariates
TL;DR: A correlated random parameters ordered probit modeling framework is employed to explore time-variant and time-invariant factors affecting injury-severity outcomes in single-vehicle accidents and shows that accounting for the unobserved heterogeneity interactions results in superior statistical performance.
Journal ArticleDOI
A statistical assessment of temporal instability in the factors determining motorcyclist injury severities
TL;DR: The results show significant temporal instability in motorcyclist-injury severity models, which likely result from changes in motorcycle technology and performance, changes in macroeconomic conditions, changes induced by how riders respond to the changing behavior of other road users, and the changes in riders’ behavior and skills over time.
Journal ArticleDOI
The effects of driver fatigue, gender, and distracted driving on perceived and observed aggressive driving behavior: A correlated grouped random parameters bivariate probit approach
TL;DR: In this article, the effect of the socio-demographic and behavioral factors on perceived and observed aggressive driving behavior was analyzed for fatigued and non-fatigued, distracted and not-distracted, male and female drivers.
Journal ArticleDOI
A Temporal Analysis of Driver-Injury Severities in Crashes Involving Aggressive and Non-aggressive Driving
TL;DR: In this article, the authors investigated differences between resulting crash-injury severities when aggressive and non-aggressive driving behavior is observed, and how these differences changed over time using three years of crash data from 2015 to 2017.
References
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Statistical and econometric methods for transportation data analysis
TL;DR: In this paper, the authors proposed a sampling-based approach for estimating Elasticities in time series regression models, which can be used to estimate a single Beta Parameter for m - 1 of the m Levels of a Variable Checking Regression Assumptions Regression Outliers Regression Model GOF Measures Multicollinearity in the Regression Regression model-Building Strategies Estimating Elasticities Censored Dependent Variables-Tobit Model Box-Cox Regression Violations of Regression this paper
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On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals
TL;DR: In this paper, the efficiency of such an integration formula can be measured by considering how it fares when the indicator function of the hyperbrick is defined by an arbitrary point in the unit hypercube.
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Analytic methods in accident research: Methodological frontier and future directions
TL;DR: A review of the evolution of methodological applications and available data in highway-accident research can be found in this article, where fruitful directions for future methodological developments are identified and the role that new data sources will play in defining these directions is discussed.
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Unobserved heterogeneity and the statistical analysis of highway accident data
TL;DR: In this article, a detailed discussion of the unobserved heterogeneity in highway accident data and analysis is presented along with their strengths and weaknesses, as well as a summary of the fundamental issues and directions for future methodological work that address this problem.
Book
Modeling Ordered Choices: A Primer
TL;DR: Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives as discussed by the authors, and have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance.