Modeling of individual differences in car-following behaviour of drivers

摘要

Car-following models microscopically express acceleration behavior of an individual driver. There are many car-following models each with its own assumptions. Among these car-following models, Intelligent Driver Model (IDM) has been used and cited extensively by research community. All the models including IDM have been developed with engineering perspective i.e. to reproduce perfect acceleration behavior. This study focuses on development of a humanistic car-following model. We have identified humanistic parameters that have been modeled in IDM from mathematical formulation of the model. In its existing form, parameters of IDM could be assigned arbitrary values from a prescribed range to define different driver profiles. This way, theoretically, infinite driver profiles could be created many of which does not exist in real. Literature of traffic psychology suggests that there are few dominant classes of drivers, which exhibit certain behavioral patterns. These dominant classes are characterized with the help of human personality. In our study, we have modeled a relationship between model of human's personality profile namely Big Five Factors (BFF) and parameters of IDM. The enhanced model let us reproduce individual differences in driving behaviors. The proposed model has been verified using computer simulation to investigate whether proposed humanistic car-following model produce desirable results or not. The proposed car-following model would be able to help in simulating driving behavior of an individual given that personality profile of that individual is known.