Dynamic Collaborative Path Planning for Remote Assistance of Highly-Automated Vehicles

Domagoj Majstorovic, Frank Diermeyer

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

3 Zitate (Scopus)

Abstract

Given its increasing popularity in recent years, teleoperation technology is now recognized as a robust fallback solution for Automated Driving (AD). Remote Assistance (RA) represents an event-driven class of teleoperation with a distinct division of tasks between the Autonomous Vehicle (AV) and the remote human operator. This paper presents a novel approach for RA of AVs in urban environments. The concept draws in-spiration from the potential synergy between highly-automated systems and human operators to collaboratively solve complex driving situations. Utilizing a hybrid algorithm that makes use of the Operational Design Domain (ODD) modification idea, it considers actions that go beyond the nominal operational space. Combined with the advanced cognitive reasoning of the human remote operator the concept offers features that hold potential to significantly improve both RA and AD user experiences.

OriginalspracheEnglisch
TitelIAVVC 2023 - IEEE International Automated Vehicle Validation Conference, Proceedings
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9798350322538
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung2023 IEEE International Automated Vehicle Validation Conference, IAVVC 2023 - Austin, USA/Vereinigte Staaten
Dauer: 16 Okt. 202318 Okt. 2023

Publikationsreihe

NameIAVVC 2023 - IEEE International Automated Vehicle Validation Conference, Proceedings

Konferenz

Konferenz2023 IEEE International Automated Vehicle Validation Conference, IAVVC 2023
Land/GebietUSA/Vereinigte Staaten
OrtAustin
Zeitraum16/10/2318/10/23

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