Digital Twin Test Method With LTE-V2X for Autonomous Vehicle Safety Test | IEEE Journals & Magazine | IEEE Xplore

Digital Twin Test Method With LTE-V2X for Autonomous Vehicle Safety Test


Abstract:

The development of test method is essential for assessing autonomous vehicle safety. How to ensure real vehicle dynamic performance and create more critical scenarios is ...Show More

Abstract:

The development of test method is essential for assessing autonomous vehicle safety. How to ensure real vehicle dynamic performance and create more critical scenarios is the challenge for safety test. Therefore, the novel method for autonomous vehicle safety test is necessary. The contribution of this article is twofold. First, the digital twin test method with Internet of Things (IoT) technique is purposed, which seamlessly integrates real test vehicle with virtual environment. We use Vehicle to Everything (V2X) technique to communicate the physical world and virtual environment. The real test vehicle can undergo within the virtual environment, which can create complex critical scenarios conveniently and ensure high-test confidence level. Second, we employ the fault tree analysis method to identify critical scenario element. The identified critical scenario elements can be combined to create various critical scenarios. Furthermore, the case study of autonomous emergency braking (AEB) system in pedestrian crossing collision scenario is implemented with the purposed method. A comparison of the purposed method with traditional methods shows that the purposed method has higher test confidence and more critical scenarios. This study addresses the challenge of safety test with the IoT technique and offers valuable insights for improving autonomous vehicle safety.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 18, 15 September 2024)
Page(s): 30161 - 30171
Date of Publication: 05 June 2024

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I. Introduction

The rapid development of artificial intelligence has significantly accelerated the development and deployment of autonomous vehicles, and autonomous vehicles has great potential in alleviating traffic congestion and avoiding collisions. Despite significant advancements in autonomous driving technology, there are some challenges for practical applications, including functional defects and substantial safety risk [1], [2], [3]. For autonomous driving system, deployment without adequate test and evaluation could take potential risks to drivers, passengers, and other road users. Therefore, it is imperative to conduct rigorous tests and evaluate system safety before deployment to ensure the system effectiveness, reliability, and safety [4], [5], [6].

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References

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