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Attribute Development of Active Lane Departure Warning Systems

  • The proposed contribution addresses the growing need for systematic and efficient development methods for assisted and automated driving features. Active Lane Departure Warning (ALDW) systems with correcting steering interventions are the specific object of this research. Due to NCAP requirements ALDW systems are widespread in modern cars, but often lack drivers’ approval, as several related studies have shown. Causes are assumed to lie in unspecified attribute requirement metrics and missing target values. Based on typical ALDW usage scenarios on different road types, such as freeway, highway and country road, an advanced catalogue of subjective evaluation criteria was developed and deployed in a comprehensive proband study with experts involving four distinct ALDW equipped passenger cars. Characteristic driving maneuvers with the intention to provoke controlled ALDW interventions complemented the subjective assessment with objective data. Statistically correlating derived objective key performance indicators with the respectiveThe proposed contribution addresses the growing need for systematic and efficient development methods for assisted and automated driving features. Active Lane Departure Warning (ALDW) systems with correcting steering interventions are the specific object of this research. Due to NCAP requirements ALDW systems are widespread in modern cars, but often lack drivers’ approval, as several related studies have shown. Causes are assumed to lie in unspecified attribute requirement metrics and missing target values. Based on typical ALDW usage scenarios on different road types, such as freeway, highway and country road, an advanced catalogue of subjective evaluation criteria was developed and deployed in a comprehensive proband study with experts involving four distinct ALDW equipped passenger cars. Characteristic driving maneuvers with the intention to provoke controlled ALDW interventions complemented the subjective assessment with objective data. Statistically correlating derived objective key performance indicators with the respective subjective ratings established a link between drivers’ impressions and measurable system behavior. These dependencies allowed the conclusion of target values for a certain range of desired subjective ALDW characteristics fulfilling the initial requisites.show moreshow less

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Metadaten
Author:Matthias BeckerORCiD, Micha Niklas Balzer, Karin Riedlmüller, Bernhard SchickORCiD, Daniel Neidlein
Identifier:978-3-981-69717-9 OPAC HS OPAC extern
Parent Title (English):International Symposium on Development Methodology
Publisher:AVL Deutschland
Place of publication:Wiesbaden
Editor:Christian Beidl
Document Type:conference proceeding (article)
Conference:9th International Symposium on Development Methodology, 9.-10. November 2021, Wiesbaden, Germany
Language:English
Date of Publication (online):2021/11/09
Year of first Publication:2021
Tag:METAVI
Advanced Driver Assistance Systems; Attribute; Automated Driving; Objective Evaluation
Number of pages:10 Seiten
First Page:1
Last Page:10
Institutes:IFM - Institut für Fahrerassistenz und vernetzte Mobilität
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik
6 Technik, Medizin, angewandte Wissenschaften
Research focus:FSP2: Mobilität
FSP4: Soziale Innovationen
Publication Lists:Becker, Matthias
Schick, Bernhard
Riedlmüller, Karin
Research Project:METAVI - Menschenzentrierte Technologien und Entwicklungsmethoden für das automatisierte Fahren mittels Digitalisierung und Virtualisierung
Publication reviewed:begutachtet
Release Date:2022/03/29
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