DocumentCode :
757085
Title :
Making driver modeling attractive
Author :
Pellecchia, Antonio ; Igel, Christian ; Edelbrunner, Johann ; Schöner, Gregor
Author_Institution :
Inst. fur Neuroinformatik, Ruhr-Univ., Bochum, Germany
Volume :
20
Issue :
2
fYear :
2005
Firstpage :
8
Lastpage :
12
Abstract :
Automobile industry and academic researchers expend considerable effort to develop driver assistance systems. DASs are aware of certain driving situations and support drivers through information, warnings, or even intervention. Many DAS applications are safety oriented, such as lane departure warning systems. Some are comfort oriented, such as automated parking assistants. Moreover, DAS human-machine interfaces must support careful communication with potentially taxed drivers. Driver models support DAS design in several ways. Our work focuses on modeling the tactical level of driving decisions, such as when to brake and whether to accelerate and pass another vehicle. Such decisions are based on local, instantaneously available environmental information about the road and other cars in the same or an adjacent lane.
Keywords :
behavioural sciences computing; driver information systems; evolutionary computation; human computer interaction; knowledge based systems; learning (artificial intelligence); mobile robots; DAS human-machine interfaces; automated parking assistant; automobile industry; driver assistance systems; lane departure warning systems; road information; Acceleration; Evolutionary computation; Intelligent systems; Intelligent vehicles; Permission; Road vehicles; Safety; Traffic control; Vehicle driving; Vehicle dynamics; driver assistance systems; driver models; dynamical systems; evolutionary algorithms;
fLanguage :
English
Journal_Title :
Intelligent Systems, IEEE
Publisher :
ieee
ISSN :
1541-1672
Type :
jour
DOI :
10.1109/MIS.2005.31
Filename :
1413165
Link To Document :
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