The Foresighted Driver Model

Abstract

The Intelligent Driver Model (IDM) is a microscopic, time continuous car following model for the simulation of freeway and urban traffic. Its popularity is grounded in its simplicity and its capacity to describe both single vehicle velocity profiles as well as collective traffic behavior. Nevertheless, it lacks a series of properties that would be desirable for more realistic agent models. In this paper, as an alternative and improvement to the IDM, we propose the Foresighted Driver Model (FDM), which assumes that a driver acts in a way that balances predictive risk (e.g. due to possible collisions along its route) with utility (e.g. the time required to travel, smoothness of ride, etc.). Based on a risk concept developed for full behavior planning, we introduce driver model equations from the assumption that a driver will mainly try to avoid risk maxima in time and space. We show how such a model can be used to simulate driving behavior similar to full behavior planning models and which generalizes and reaches beyond the IDM modeling scenarios.