@inproceedings{b1f957af2a1d44358aab7ab5cd6b9df3,
title = "Integrated modular safety system design for intelligent autonomous vehicles",
abstract = "This paper presents an approach to specifying a modularised safety system which comprehensively addresses the safety requirements for highly autonomous (SAE Level 3+) road vehicles featuring advanced sensing and automated navigation. As these requirements are often overlooked in similar autonomous driving system proposals, we present a method of hazard and risk analysis which investigates hardware failures, environmental perception limitations, human interaction and functional requirements for artificial intelligence. We then define a system design which implements the required safeguards and examines the application on two electric autonomous vehicle testbeds: a race car and a shuttle bus. The close-coupling of a safety-oriented architecture and multi-regime Hazard and Risk Assessment process was tested to measure the system's ability to detect and react to pedestrian stimuli, resulting in accurate detections and reactions, thereby confirming its ability to design safety systems for autonomous research vehicles in a scalable and easily assured fashion.",
author = "Thomas Drage and Lim, {Kai Li} and {Hai Koh}, {Joey En} and David Gregory and Craig Brogle and Thomas Braunl",
year = "2021",
month = jul,
day = "11",
doi = "10.1109/IV48863.2021.9575662",
language = "English",
series = "IEEE Intelligent Vehicles Symposium, Proceedings",
publisher = "IEEE, Institute of Electrical and Electronics Engineers",
pages = "258--265",
booktitle = "32nd IEEE Intelligent Vehicles Symposium, IV 2021",
address = "United States",
note = "32nd IEEE Intelligent Vehicles Symposium, IV 2021 ; Conference date: 11-07-2021 Through 17-07-2021",
}