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Issue title: Multi-agent systems research in the United Kingdom
Guest editors: Stefano V. Albrecht and Michael Woolridge
Article type: Research Article
Authors: Hawasly, Majda; * | Sadeghi, Jonathana | Antonello, Morrisa | Albrecht, Stefano V.a; b | Redford, Johna | Ramamoorthy, Subramaniana; b
Affiliations: [a] Five AI Ltd., United Kingdom | [b] School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
Correspondence: [*] Corresponding author. E-mail: majd.hawasly@five.ai.
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.
Keywords: Autonomous driving, motion planning and prediction, safety, assurance, explainability
DOI: 10.3233/AIC-220148
Journal: AI Communications, vol. 35, no. 4, pp. 285-294, 2022
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