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Towards a Driver Model: Preliminary Study of Lane Change Behavior

  • The presented work formulates an framework in which early prediction of drivers lane change behavior is realized. We aim to build a representation of drivers lane change behavior in order to recognize and to predict driver's intentions as a first step towards a realistic driver model. In the test bed of the Institute of Neuroinformatik, based on the traffic simulator NISYS TRS 1, 10 individuals have driven in the experiments and they performed more then 150 lane change maneuvers. Lane-offset, distance to the front car and time to contact, were recorded. The acquired data was used to train - in parallel- a recurrent neural network, a feed forward neural network and a set of support vector machines. In the followed test drives the system was able of performing a lane change prediction time of 1.5 sec beforehand. The proposed approach describes a framework for lane-change detection and prediction, which will serve as a prerequisite for a successful driver model.

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Metadaten
Author:Ürün Dogan, Hannes Edelbrunner, Ioannis Iossifidis
URL:https://ieeexplore.ieee.org/abstract/document/4732700
DOI:https://doi.org/10.1109/ITSC.2008.4732700
ISSN:2153-0009
Parent Title (English):2008 11th International IEEE Conference on Intelligent Transportation Systems
Document Type:Article
Language:English
Year of Completion:2008
Release Date:2019/04/29
Volume:2008
Issue:12.-15.Oct
Institutes:Fachbereich 1 - Institut Informatik
DDC class:000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):License LogoNo Creative Commons