IEEE - Institute of Electrical and Electronics Engineers, Inc. - Multiple Model Unscented Kalman Filtering in Dynamic Bayesian Networks for Intention Estimation and Trajectory Prediction

2018 IEEE International Conference on Intelligent Transportation Systems (ITSC)

Author(s): Jens Schulz ; Constantin Hubmann ; Julian Lochner ; Darius Burschka
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Publication Date: 1 November 2018
Conference Location: Maui, HI, USA, USA
Conference Date: 4 November 2018
Page(s): 1,467 - 1,474
ISBN (Electronic): 978-1-7281-0323-5
ISBN (USB): 978-1-7281-0322-8
ISBN (Paper): 978-1-7281-0321-1
ISSN (Electronic): 2153-0017
DOI: 10.1109/ITSC.2018.8569932
Regular:

Dynamic Bayesian networks (DBNs) are a popular method for driver intention estimation and trajectory prediction. To account for hybrid state spaces and non-linear system dynamics, sequential Monte... View More

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