Safety Toolkit for Automated Vehicle Shuttle -Practical Implementation of Digital Twin

Sell, Raivo; Malayjerdi, Ehsan; Malayjerdi, Mohsen; Baykara, Baris Cem

doi:10.1109/iccve52871.2022.9742881

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…The architecture of the proposed combined testing methodology is presented in Figure 3. This method takes advantage of a high-fidelity software in the loop (SiL) simulation [16] approach to validate and verify the performance of a AD software under critical cyber security conditions. This method consists of three main following elements:…”

Section: Combined Safety and Cybersecurity Testing Methodology For Ad...mentioning

confidence: 99%

Combined Safety and Cybersecurity Testing Methodology for Autonomous Driving Algorithms

Roberts

Malayjerdi

et al. 2022

Computer Science in Cars Symposium

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Combined safety and cybersecurity testing are critical for assessing the reliability and optimisation of autonomous driving (AD) algorithms. However, safety and cybersecurity testing is often conducted in isolation, leading to a lack of evaluation of the complex system-of-system interactions which impact the reliability and optimisation of the AD algorithm. Concurrently, practical limitations of testing include resource usage and time. This paper proposes a methodology for combined safety and cybersecurity testing and applies it to a real-world AV shuttle using digital twin, softwarein-the-loop (SiL) simulation and a real-world Autonomous Vehicle (AV) test environment. The results of the safety and cybersecurity tests and feedback from the AD algorithm designers demonstrate that the methodology developed is useful for assessing the reliability and optimisation of an AD algorithm in the development phase. Furthermore, from the observed system-of-system interactions, key relationships such as speed and attack parameters can be used to optimise testing.

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Section: Combined Safety and Cybersecurity Testing Methodology For Ad...mentioning

confidence: 99%

Combined Safety and Cybersecurity Testing Methodology for Autonomous Driving Algorithms

Roberts

Malayjerdi

et al. 2022

Computer Science in Cars Symposium

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“…Using the PolyVerif Framework partner teams addressed their specific V&V research challenges. Current ongoing active projects with the PolyVerif include: 1) Digital Twin Model of AV route in Tallinn, Estonia with an Autoware engine [34], [39], [40]. 2) Digital Twin Model of AV route in Jacksonville, Florida with a non Autoware engine [41].…”

Section: Polyverif Projectsmentioning

confidence: 99%

“…In the first step, the TalTech team built a digital twin of the TalTech campus test track. A virtual copy of the vehicle was created and defined with the same sensor configuration as the actual vehicle [39] (see Fig. 8).…”

Section: Polyverif Projectsmentioning

confidence: 99%

PolyVerif: An Open-Source Environment for Autonomous Vehicle Validation and Verification Research Acceleration

et al. 2023

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Validation and Verification (V&V) of Artificial Intelligence (AI) based cyber physical systems such as Autonomous Vehicles (AVs) is currently a vexing and unsolved problem. AVs integrate subsystems in areas such as detection, sensor fusion, localization, perception, and path planning. Each of these subsystems contains significant AI content integrated with traditional hardware and software components. The complexity for validating even a subsystem is daunting and the task of validating the whole system is nearly impossible. Fundamental research in advancing the state-of-the-art for AV V&V is required. However, for V&V researchers, it is exceedingly difficult to make progress because of the massive infrastructure requirements to demonstrate the viability of any solution. This paper presents PolyVerif, the world's first open-source solution focused on V&V researchers with the objective of accelerating the state-of-the-art for AV V&V research. PolyVerif provides an AI design and verification framework consisting of a digital twin creation process, an open-source AV engine, access to several open-source physics based simulators, and open-source symbolic test generation engines.PolyVerif's objective is to arm V&V researchers with a framework which extends the state-of-the-art on any one of the many major axes of interest and use the remainder of the infrastructure to quickly demonstrate the viability of their solution. Given its open-source nature, researchers can also contribute their innovations to the project. Using this critical property of open-source environments, the innovation rate of the whole research community to solve these vexing issues can be greatly accelerated. Finally, the paper also presents results from several projects which have used PolyVerif.

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Digital Twins for Autonomous Driving: A Comprehensive Implementation and Demonstration

Wang,

Yu,

et al. 2024

2024 International Conference on Information Networking (ICOIN)

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Safety Toolkit for Automated Vehicle Shuttle -Practical Implementation of Digital Twin

Cited by 4 publications

References 20 publications

Combined Safety and Cybersecurity Testing Methodology for Autonomous Driving Algorithms

Combined Safety and Cybersecurity Testing Methodology for Autonomous Driving Algorithms

PolyVerif: An Open-Source Environment for Autonomous Vehicle Validation and Verification Research Acceleration

Digital Twins for Autonomous Driving: A Comprehensive Implementation and Demonstration

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