@inproceedings {pub2898,
	title = {The Foresighted Driver Model},
	author = {Julian Eggert AND Florian Damerow AND Stefan Klingelschmitt},
	year = {2015},
	month = {June},
	abstract = {The Intelligent Driver Model (IDM) is a mesoscopic, time continuous car following model for the simulation of freeway and urban traffic. Its popularity is grounded in its simplicity (it consists of a single differential equation) and its capacity to describe from single vehicle to traffic jam behavior. Nevertheless, it lacks a series of properties that would be desirable for more realistic agent models. In this paper, we propose 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.). Introducing 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 that such a model can be used to simulate driving behavior which approximates that of the full behavior planning models and which generalizes and reaches beyond the IDM modeling scenarios.},
	publisher = {IEEE},
	booktitle = {Intelligent Vehicles Symposium (IV) 2015},
	city = {Seoul, Korea}
}