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Overcoming Challenges of Validation Automated Driving and Identification of Critical Scenarios

Wang, Cheng ; Winner, Hermann
Hrsg.: IEEE (2019)
Overcoming Challenges of Validation Automated Driving and Identification of Critical Scenarios.
2019 IEEE Intelligent Transportation Systems Conference (ITSC). (27-30 October 2019)
doi: 10.1109/ITSC.2019.8917045
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Automated driving has arisen more and more attention both in traditional automobile industries and in IT companies. Rapid development and significant results have been achieved. However, there are few effective and satisfying methods to prove that Highly Automated Driving (HAD) is currently at least as safe as a human driver. In this paper, a novel validation method named Virtual Assessment of Automation in Field Operation (VAAFO) is introduced in detail. In VAAFO, HAD system has no access to actuators but runs in parallel while human driver drives the vehicle. Behavior comparison between human-driven vehicle and HAD in same scenario is a main new feature in VAAFO to validate automated driving and find out potential critical scenarios. Combined with correction of world model and criticality metrics, potential critical scenarios are filtered further to identify real critical scenarios. Different modules of VAAFO are explained elaborately based on these working principles. In principle, the proposed method could accelerate testing and validation of HAD a lot without bringing additional risks. Moreover, critical scenarios will be identified as well.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2019
Autor(en): Wang, Cheng ; Winner, Hermann
Art des Eintrags: Bibliographie
Titel: Overcoming Challenges of Validation Automated Driving and Identification of Critical Scenarios
Sprache: Englisch
Publikationsjahr: 28 November 2019
Ort: Auckland, New Zealand
Veranstaltungstitel: 2019 IEEE Intelligent Transportation Systems Conference (ITSC)
Veranstaltungsdatum: 27-30 October 2019
DOI: 10.1109/ITSC.2019.8917045
Kurzbeschreibung (Abstract):

Automated driving has arisen more and more attention both in traditional automobile industries and in IT companies. Rapid development and significant results have been achieved. However, there are few effective and satisfying methods to prove that Highly Automated Driving (HAD) is currently at least as safe as a human driver. In this paper, a novel validation method named Virtual Assessment of Automation in Field Operation (VAAFO) is introduced in detail. In VAAFO, HAD system has no access to actuators but runs in parallel while human driver drives the vehicle. Behavior comparison between human-driven vehicle and HAD in same scenario is a main new feature in VAAFO to validate automated driving and find out potential critical scenarios. Combined with correction of world model and criticality metrics, potential critical scenarios are filtered further to identify real critical scenarios. Different modules of VAAFO are explained elaborately based on these working principles. In principle, the proposed method could accelerate testing and validation of HAD a lot without bringing additional risks. Moreover, critical scenarios will be identified as well.

Freie Schlagworte: Highly automated driving;Validation;Testing;Safety;Critical Scenarios;Measurement
Zusätzliche Informationen:

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Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD)
16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD) > Fahrerassistenzssysteme
16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD) > Sicherheit
Hinterlegungsdatum: 13 Okt 2020 05:31
Letzte Änderung: 13 Okt 2020 05:31
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