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Identification of Lane-Change Maneuvers in Real-World Drivings with Hidden Markov Model and Dynamic Time Warping

Klitzke, Lars and Koch, Carsten and Köster, Frank (2020) Identification of Lane-Change Maneuvers in Real-World Drivings with Hidden Markov Model and Dynamic Time Warping. In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. 23rd Intelligent Transportation Systems Conference (IEEE ITSC 2020), 20.-23. Sep. 2020, online Konferenz (urpsrgl. Griechenland).

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Official URL: https://www.ieee-itsc2020.org/

Abstract

For the introduction of new automated driving functions, the systems need to be verified extensively. A scenario-driven approach has become an accepted method for this task. But to verify the functionality of an automated vehicle in the simulation in a certain scenario such as a lane change, relevant characteristics of scenarios need to be identified. This, however, requires to extract these scenarios from real-world drivings accurately. For that purpose, this work proposes a novel framework based on a set of unsupervised learning methods to identify lane-changes on motorways. To represent various types of lane changes, the maneuver is split up into primitive driving actions with an Hidden Markov Model and Divisive Hierarchical Clustering. Based on this, lane change maneuvers are identified using Dynamic-Time-Warping. The presented framework is evaluated with a real-world test drive and compared to other baseline methods. With a f1 score of 98.01\% in lane-change identification, the presented approach shows promising results.

Item URL in elib:https://elib.dlr.de/135748/
Document Type:Conference or Workshop Item (Speech)
Title:Identification of Lane-Change Maneuvers in Real-World Drivings with Hidden Markov Model and Dynamic Time Warping
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Klitzke, LarsLars.Klitzke (at) dlr.dehttps://orcid.org/0000-0001-9362-707X
Koch, CarstenCarsten.Koch (at) hs-emden-leer.deUNSPECIFIED
Köster, FrankFrank.Koester (at) dlr.deUNSPECIFIED
Date:2020
Journal or Publication Title:IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Lane-change Maneuver, Hidden Markov Model, Dynamic Time Warping, Divisive Hierarchical Clustering, Automated Driving
Event Title:23rd Intelligent Transportation Systems Conference (IEEE ITSC 2020)
Event Location:online Konferenz (urpsrgl. Griechenland)
Event Type:international Conference
Event Dates:20.-23. Sep. 2020
Organizer:Institute of Electrical and Electronics Engineers (IEEE)
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Data Management and Knowledge Discovery
Deposited By: Klitzke, Lars
Deposited On:28 Aug 2020 12:33
Last Modified:27 Jan 2021 19:51

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