Estimation of Driver Reaction Time from Car-Following Data

Driver behavior plays an important role in modeling vehicle dynamics in a traffic simulation environment. To study one element of 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 the car-following data collection and smoothing methods. Moreover, spectrum analysis methods based on Fourier analysis of car-following data are introduced to estimate driver reaction times, a crucial parameter of driver behavior. A generalized general motor–type model was calibrated, an extension of the classic nonlinear general motor model, in a stable following regime based on estimated driver reaction times. The calibrated model was then evaluated by closed-loop simulations.