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Boids Flocking Algorithm for Situation Assessment of Driver Assistance Systems

  • Driver assistance systems are increasingly becoming part of the standard equipment of vehicles and thus contribute to road safety. However, as they become more widespread, the requirements for cost efficiency are also increasing, and so few and inexpensive sensors are used in these systems. Especially in challenging situations, this leads to the fact that target discrimination cannot be ensured which may lead to false reactions of the driver assistance system. In this paper, the Boids flocking algorithm is used to generate semantic neighborhood information between tracked objects which in turn can significantly improve the overall performance. Two different variants were developed: First, a free-moving flock whereby a separate flock is generated per tracked object and second, a formation-controlled flock where boids of a single flock move along the future road course in a pre-defined formation. In the first approach, the interaction between the flocks as well as the interaction between the boids within a flock is used to generate additional information, which in turn can be used to improve, for example, lane change detection. For the latter approach, new behavioral rules have been developed, so that the boids can reliably identify control-relevant objects to a driver assistance system. Finally, the performance of the presented methods is verified through extensive simulations.

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Metadaten
Author:Christopher KnievelORCiD, Aldin PejicORCiD, Lars KrügerORCiD, Christoph ZieglerORCiD, Jürgen AdamyORCiD
URN:urn:nbn:de:bsz:kon4-opus4-34307
DOI:https://doi.org/10.1109/OJITS.2023.3236985
ISSN:2687-7813
Parent Title (English):IEEE Open Journal of Intelligent Transportation Systems
Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Document Type:Article
Language:English
Year of Publication:2023
Release Date:2023/01/19
Tag:Driver Assistance Systems; Lane Association; Target Discrimination; Boids Flocking Algorithm
First Page:71
Last Page:82
Note:
Corresponding author: Christopher Knievel
Open Access?:Ja
Relevance:Peer reviewed Publikation in Master Journal List
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International