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
Ladda ner artikel
http://dx.doi.org/10.3384/ecp171428Ingår i: Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
Linköping Electronic Conference Proceedings 142:2, s. 8-18
Publicerad: 2018-12-19
ISBN: 978-91-7685-399-3
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
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.
Inga referenser tillgängliga
