Perspectives on the system-level design of a safe autonomous driving stack

  • Majd Hawasly*
  • , Jonathan Sadeghi
  • , Morris Antonello
  • , Stefano V. Albrecht
  • , John Redford
  • , Subramanian Ramamoorthy
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Achieving safe and robust autonomy is the key bottleneck on the path towards broader adoption of autonomous vehicles technology. This motivates going beyond extrinsic metrics such as miles between disengagement, and calls for approaches that embody safety by design. In this paper, we address some aspects of this challenge, with emphasis on issues of motion planning and prediction. We do this through description of novel approaches taken to solving selected sub-problems within an autonomous driving stack, in the process introducing the design philosophy being adopted within Five. This includes safe-by-design planning, interpretable as well as verifiable prediction, and modelling of perception errors to enable effective sim-to-real and real-to-sim transfer within the testing pipeline of a realistic autonomous system.

Original languageEnglish
Pages (from-to)285-294
Number of pages10
JournalAI Communications
Volume35
Issue number4
DOIs
Publication statusPublished - 2 Sept 2022
Externally publishedYes

Keywords

  • Autonomous driving
  • assurance
  • explainability
  • motion planning and prediction
  • safety

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