Development and Experimental Validation of High Performance Embedded Intelligence and Fail-Operational Urban Surround Perception Solutions of the PRYSTINE Project

Rihards Novickis, Aleksandrs Levinskis, Vitalijs Fescenko, Roberts Kadikis, Kaspars Ozols, Anna Ryabokon, Rupert Schorn, Jochen Koszescha, Selim Solmaz, Georg Stettinger, Akwasi Adu-Kyere, Lauri Halla-aho*, Ethiopia Nigussie, Jouni Isoaho

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Automated Driving Systems (ADSs) commend a substantial reduction of human-caused road accidents while simultaneously lowering emissions, mitigating congestion, decreasing energy consumption and increasing overall productivity. However, achieving higher SAE levels of driving automation and complying with ISO26262 C and D Automotive Safety Integrity Levels (ASILs) is a multi-disciplinary challenge that requires insights into safety-critical architectures, multi-modal
perception and real-time control. This paper presents an assorted effort carried out in the European H2020 ECSEL project—PRYSTINE. In this paper, we (1) investigate Simplex, 1oo2d and hybrid fail-operational computing architectures, (2) devise a multi-modal perception system with fail-safety mechanisms, (3) present a passenger vehicle-based demonstrator for low-speed autonomy and (4) suggest a trust-based fusion approach validated on a heavy-duty truck.
Original languageEnglish
Article number168
JournalApplied Sciences
Volume12
Issue number1
DOIs
Publication statusPublished - Jan 2022

Keywords

  • Architecture
  • Autonomous driving
  • Fail-operational
  • Parking
  • Perception
  • Trust

ASJC Scopus subject areas

  • Engineering(all)
  • Instrumentation
  • Materials Science(all)
  • Fluid Flow and Transfer Processes
  • Process Chemistry and Technology
  • Computer Science Applications

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