DocumentCode :
1517980
Title :
Highly Automated Driving on Freeways in Real Traffic Using a Probabilistic Framework
Author :
Ardelt, Michael ; Coester, Constantin ; Kaempchen, Nico
Author_Institution :
BMW Group Res. & Technol., Munich, Germany
Volume :
13
Issue :
4
fYear :
2012
Firstpage :
1576
Lastpage :
1585
Abstract :
A system, particularly a decision-making concept, that facilitates highly automated driving on freeways in real traffic is presented. The system is capable of conducting fully automated lane change (LC) maneuvers with no need for driver approval. Due to the application in real traffic, a robust functionality and the general safety of all traffic participants are among the main requirements. Regarding these requirements, the consideration of measurement uncertainties demonstrates a major challenge. For this reason, a fully integrated probabilistic concept is developed. By means of this approach, uncertainties are regarded in the entire process of determining driving maneuvers. While this also includes perception tasks, this contribution puts a focus on the driving strategy and the decision-making process for the execution of driving maneuvers. With this approach, the BMW Group Research and Technology managed to drive 100% automated in real traffic on the freeway A9 from Munich to Ingolstadt, showing a robust, comfortable, and safe driving behavior, even during multiple automated LC maneuvers.
Keywords :
decision making; driver information systems; probability; road safety; road traffic; BMW Group Research and Technology; Ingolstadt; LC maneuvers; Munich; automated lane change maneuvers; decision-making concept; driving strategy; freeways; highly automated driving; measurement uncertainty; perception tasks; probabilistic framework; real traffic; traffic participant general safety; traffic participant robust functionality; Decision making; Probabilistic logic; Robustness; Safety; Traffic control; Uncertainty; Advanced driver-assistance systems (ADASs); highly automated driving; lateral vehicle guidance; probabilistic decision making;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2012.2196273
Filename :
6200871
Link To Document :
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