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 order to process multitasking driver behavior effectively, an improved driver cognitive behavior modeling method of ACT-R is proposed in this paper. The manual and visual modules of ACT-R are concatenated directly to cope with human subconscious/unconscious behavior. A parallel processing method is also proposed to mimic the parallel reaction style of a given cerebral area of human brain's r...

human driver or control the vehicle autonomously, they usually must make these decisions in real time with only incomplete information. So, human drivers still must maintain control over the vehicle. Advanced in-vehicle information systems (IVISs) endow vehicles with different types and levels of intelligence to complement the driver.2 Their introduction has allowed an almost symbiotic relation...

Driver behavior plays an important role in modeling vehicle dynamics in a traffic simulation environment. To study one element of the general driver behavior, that of car following, an advanced instrumented vehicle has been applied in dynamic data collection in real traffic flow on Swedish roads. This paper briefly introduces our car following data collection and smoothing methods. Moreover, we...