Article | Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016 | Situation Awareness and Early Recognition of Traffic Maneuvers Linköping University Electronic Press Conference Proceedings
Göm menyn

Title:
Situation Awareness and Early Recognition of Traffic Maneuvers
Author:
Galia Weidl: Department of Driving Automation, Daimler AG, Group Research & AE, 71034 Böblingen, Germany Anders L. Madsen: HUGIN EXPERT A/S, Denmark / Department of Computer Science, Aalborg University, Denmark Viacheslav Tereshchenko: Department of Driving Automation, Daimler AG, Group Research & AE, 71034 Böblingen, Germany / University of Stuttgart, Germany Wei Zhang: Department of Driving Automation, Daimler AG, Group Research & AE, 71034 Böblingen, Germany / University of Stuttgart, Germany Stevens Wang: Department of Driving Automation, Daimler AG, Group Research & AE, 71034 Böblingen, Germany / University of Stuttgart, Germany Dietmar Kasper: Department of Driving Automation, Daimler AG, Group Research & AE, 71034 Böblingen, Germany
DOI:
10.3384/ecp171428
Download:
Full text (pdf)
Year:
2018
Conference:
Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
Issue:
142
Article no.:
002
Pages:
8-18
No. of pages:
11
Publication type:
Abstract and Fulltext
Published:
2018-12-19
ISBN:
978-91-7685-399-3
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


Export in BibTex, RIS or text

We outline the challenges of situation awareness with early and accurate recognition of traffic maneuvers and how to assess them. This includes also an overview of the available data and derived situation features, handling of data uncertainties, modelling and the approach for maneuver recognition. An efficient and effective solution, meeting the automotive requirements, is successfully deployed and tested on a prototype car. Test driving results show that earlier recognition of intended maneuver is feasible on average 1 second (and up to 6.72 s) before the actual lane marking crossing. The even earlier maneuver recognition is dependent on the earlier recognition of surrounding vehicles.

Keywords: Bayesian networks, massive data streams

Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016

Author:
Galia Weidl, Anders L. Madsen, Viacheslav Tereshchenko, Wei Zhang, Stevens Wang, Dietmar Kasper
Title:
Situation Awareness and Early Recognition of Traffic Maneuvers
DOI:
http://dx.doi.org/10.3384/ecp171428
References:
No references available

Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016

Author:
Galia Weidl, Anders L. Madsen, Viacheslav Tereshchenko, Wei Zhang, Stevens Wang, Dietmar Kasper
Title:
Situation Awareness and Early Recognition of Traffic Maneuvers
DOI:
https://doi.org10.3384/ecp171428
Note: the following are taken directly from CrossRef
Citations:
No citations available at the moment


Responsible for this page: Peter Berkesand
Last updated: 2019-10-02