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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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/ |
work_keys_str_mv |
AT timstahl onlineverificationenablingapprovalofdrivingfunctionsx2014implementationforaplannerofanautonomousracevehicle AT frankdiermeyer onlineverificationenablingapprovalofdrivingfunctionsx2014implementationforaplannerofanautonomousracevehicle |
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