A Car Driver's Cognition Model. Krajzewicz, D.; Kühne, R.; and Wagner, P. In ITS Safety and Security Conference, volume CD, 2004.
A Car Driver's Cognition Model [link]Paper  abstract   bibtex   
There is a basic need in transportation planning and traffic engineering for developing and testing traffic models of different granularity. Although our major intrest is the replication of traffic within larger areas, both the current research on traffic safety and the desire to improve the quality of microscopic simulations makes it necessary to deal with the car driver?s cognition on a finer scale. This paper presents our model assumptions for such sub-microscopic simulations, which are based on results from cognitive psychology. Although some preliminary work of this type is available, most of these applications are not open to the public, which makes them useless for scientific purposes. the cognition simulations availabele up to now mostly deal withmemory processes and are not easily extendable by further structures such as vehickles with their dynamics or a representation of the simulated environment. These considerations motivated us to develop the above mentioned model from scratch. The design of the model described herein includes sub-models of a human being?s perception, visual attention, internal environment representation and decision making as well as the execution of actions in a simulated vehicle. Results both from cognitive psychology and the research on human-machine interaction are incorporated. This paper reveals our premises for a driver?s cognition model and describes the model itself, followed by a discussion of the model?s restrictions. As the implementation process is not yet closed, only some basic results are presented and a look into the furture of the model is given.
@inproceedings{ Krajzewicz2004a,
  author = {Daniel Krajzewicz and Reinhart Kühne and Peter Wagner},
  title = {A Car Driver's Cognition Model},
  booktitle = {ITS Safety and Security Conference},
  year = {2004},
  volume = {CD},
  abstract = {There is a basic need in transportation planning and traffic engineering
	for developing and testing traffic models of different granularity.
	Although our major intrest is the replication of traffic within larger
	areas, both the current research on traffic safety and the desire
	to improve the quality of microscopic simulations makes it necessary
	to deal with the car driver?s cognition on a finer scale. This paper
	presents our model assumptions for such sub-microscopic simulations,
	which are based on results from cognitive psychology. Although some
	preliminary work of this type is available, most of these applications
	are not open to the public, which makes them useless for scientific
	purposes. the cognition simulations availabele up to now mostly deal
	withmemory processes and are not easily extendable by further structures
	such as vehickles with their dynamics or a representation of the
	simulated environment. These considerations motivated us to develop
	the above mentioned model from scratch. The design of the model described
	herein includes sub-models of a human being?s perception, visual
	attention, internal environment representation and decision making
	as well as the execution of actions in a simulated vehicle. Results
	both from cognitive psychology and the research on human-machine
	interaction are incorporated. This paper reveals our premises for
	a driver?s cognition model and describes the model itself, followed
	by a discussion of the model?s restrictions. As the implementation
	process is not yet closed, only some basic results are presented
	and a look into the furture of the model is given.},
  file = {:http\://elib.dlr.de/6671/2/ITS_dkrajzew_ss25-29.pdf:URL},
  journal = {Proceedings of Intelligent Transportation Systems Safety and Security
	Conference},
  keywords = {driver modeling, cognition, sub-microscopic traffic flow modelling,
	model, lane-changing, Verkehrsmodellierung, Simulation, Anwendungen,
	Modelle, Programme, Verkehrssicherheit, Verkehrstr?ger Stra?e},
  owner = {Daniel},
  timestamp = {2011.12.02},
  url = {http://elib.dlr.de/6671/}
}
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