A hi-fidelity driving simulator with the 300 degree screen and an actual vehicle cabin on hexapod motion platform has been developed in order to measure driving behavior, including visual behavior, in town environment. For measuring the driving behavior, various driving parameters were recorded. The eye glancing direction was detected by combining the eyetracking system and the head-tracking sy...

Drivers’ individual difference is one of the key factors to influence the accuracy of driving behavior model. The accuracy of model should include the effect characteristics of individual difference on driving behavior. The overtaking process was the research object to study the individual characteristics of driving behavior. The operation data of accelerator and steering wheel of each driver w...

In the present study, we examined a bidimensional model of acculturation (which includes both heritage and U.S. practices, values, and identifications) in relation to hazardous alcohol use, illicit drug use, unsafe sexual behavior, and impaired driving. A sample of 3,251 first- and second-generation immigrant students from 30 U.S. colleges and universities completed measures of behavioral accul...

OBJECTIVES The aim of the work was the analysis of personality traits of men serving a custodial sentence for driving under the influence of alcohol. METHODS The study included 44 males serving a custodial sentence for drink driving, 45 males serving a custodial sentence for assault and robbery as well as 32 men with no criminal record, who had never driven a motor vehicle under the influence...

This paper presents a stochastic driver behavior modeling framework which takes into account both individual and general driving characteristics as one aggregate model. Patterns of individual driving styles are modeled using a Dirichlet process mixture model, as a non-parametric Bayesian approach which automatically selects the optimal number of model components to fit sparse observations of ea...

In this era of active development autonomous vehicles, it becomes crucial to provide driving systems with the capacity explain their decisions. work, we focus on generating high-level explanations as vehicle drives. We present BEEF, for BEhavior Explanation Fusion, a deep architecture which explains behavior trajectory prediction model. Supervised by annotations human decisions justifications, ...