Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race Vehicle

Safety guarantees and regulatory approval for autonomous vehicles remain an ongoing challenge. In particular, software that is frequently adapted or contains complex, non-transparent components, such as artificial intelligence, is exceeding the limits of safety standards. This paper presents a detai...

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Main Authors: Tim Stahl, Frank Diermeyer
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of Intelligent Transportation Systems
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9424710/
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spelling doaj-af7aa6f7b16d433e8df0ab4ca67a4fed2021-05-27T23:05:24ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132021-01-0129711010.1109/OJITS.2021.30781219424710Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race VehicleTim Stahl0https://orcid.org/0000-0002-4924-6090Frank Diermeyer1Chair of Automotive Technology, Technical University of Munich, Munich, GermanyChair of Automotive Technology, Technical University of Munich, Munich, GermanySafety guarantees and regulatory approval for autonomous vehicles remain an ongoing challenge. In particular, software that is frequently adapted or contains complex, non-transparent components, such as artificial intelligence, is exceeding the limits of safety standards. This paper presents a detailed implementation of an online verification module – the Supervisor – that copes with these challenges. The presented implementation focuses on autonomous race vehicles without loss of generality. Following an identified holistic list of safety-relevant requirements for a trajectory, metrics are developed to monitor whether the trajectory can safely be executed. To evaluate safety with respect to dynamic objects in a semi-structured and highly dynamic racing environment, rule-based reachable sets are presented. As a result, the pure reachable set is further constrained by applicable regulations. Real-time capability and effectiveness are demonstrated in fault-injected scenario-based tests and on real-world run data. The implemented Supervisor will be publicly available on GitHub.https://ieeexplore.ieee.org/document/9424710/Autonomous vehiclesformal verificationruntime environmentsoftware safetyvehicle safety
collection DOAJ
language English
format Article
sources DOAJ
author Tim Stahl
Frank Diermeyer
spellingShingle Tim Stahl
Frank Diermeyer
Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race Vehicle
IEEE Open Journal of Intelligent Transportation Systems
Autonomous vehicles
formal verification
runtime environment
software safety
vehicle safety
author_facet Tim Stahl
Frank Diermeyer
author_sort Tim Stahl
title Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race Vehicle
title_short Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race Vehicle
title_full Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race Vehicle
title_fullStr Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race Vehicle
title_full_unstemmed Online Verification Enabling Approval of Driving Functions—Implementation for a Planner of an Autonomous Race Vehicle
title_sort online verification enabling approval of driving functions—implementation for a planner of an autonomous race vehicle
publisher IEEE
series IEEE Open Journal of Intelligent Transportation Systems
issn 2687-7813
publishDate 2021-01-01
description Safety guarantees and regulatory approval for autonomous vehicles remain an ongoing challenge. In particular, software that is frequently adapted or contains complex, non-transparent components, such as artificial intelligence, is exceeding the limits of safety standards. This paper presents a detailed implementation of an online verification module – the Supervisor – that copes with these challenges. The presented implementation focuses on autonomous race vehicles without loss of generality. Following an identified holistic list of safety-relevant requirements for a trajectory, metrics are developed to monitor whether the trajectory can safely be executed. To evaluate safety with respect to dynamic objects in a semi-structured and highly dynamic racing environment, rule-based reachable sets are presented. As a result, the pure reachable set is further constrained by applicable regulations. Real-time capability and effectiveness are demonstrated in fault-injected scenario-based tests and on real-world run data. The implemented Supervisor will be publicly available on GitHub.
topic Autonomous vehicles
formal verification
runtime environment
software safety
vehicle safety
url https://ieeexplore.ieee.org/document/9424710/
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