NDLI: Probabilistic trajectory prediction with Gaussian mixture models

Content Provider	IEEE Xplore Digital Library
Author	Wiest, J. Hoffken, M. Kresel, U. Dietmayer, K.
Copyright Year	2012
Description	Author affiliation: Institute of Measurement, Control an Microtechnology, Ulm University, 89081 Ulm, Germany (Wiest, J.; Hoffken, M.; Dietmayer, K.) \|\| Daimler AG, Ulm, Germany (Kresel, U.)
Abstract	In the context of driver assistance, an accurate and reliable prediction of the vehicle's trajectory is beneficial. This can be useful either to increase the flexibility of comfort systems or, in the more interesting case, to detect potentially dangerous situations as early as possible. In this contribution, a novel approach for trajectory prediction is proposed which has the capability to predict the vehicle's trajectory several seconds in advance, the so called long-term prediction. To achieve this, previously observed motion patterns are used to infer a joint probability distribution as motion model. Using this distribution, a trajectory can be predicted by calculating the probability for the future motion, conditioned on the current observed history motion pattern. The advantage of the probabilistic modeling is that the result is not only a prediction, but rather a whole distribution over the future trajectories and a specific prediction can be made by the evaluation of the statistical properties, e.g. the mean of this conditioned distribution. Additionally, an evaluation of the variance can be used to examine the reliability of the prediction.
Starting Page	141
Ending Page	146
File Size	477602
Page Count	6
File Format	PDF
ISBN	9781467321198
ISSN	19310587
e-ISBN	9781467321181
DOI	10.1109/IVS.2012.6232277
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Trajectory Chebyshev approximation Predictive models Vehicles History Probabilistic logic
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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