Digital Twins for Autonomous Driving: A Comprehensive Implementation and Demonstration
CoRR(2023)
摘要
The concept of a digital twin (DT) plays a pivotal role in the ongoing
digital transformation and has achieved significant strides for various
wireless applications in recent years. In particular, the field of autonomous
vehicles is a domain that is ripe for exploiting the concept of DT.
Nevertheless, there are many challenges that include holistic consideration and
integration of hardware, software, communication methods, and collaboration of
edge/cloud computing. In this paper, an end-to-end (E2E) real-world smart
mobility DT is designed and implemented for the purpose of autonomous driving.
The proposed system utilizes roadside units (RSUs) and edge computing to
capture real-world traffic information, which is then processed in the cloud to
create a DT model. This DT model is then exploited to enable route planning
services for the autonomous vehicle to avoid heavy traffic. Real-world
experimental results show that the system reliability can reach 99.53
achieving a latency that is 3.36
for autonomous driving. These results clearly validate the effectiveness of the
system according to practical 3GPP standards for sensor and state map sharing
(SSMS) and information sharing.
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