Towards Cooperative Perception Services for ITS: Digital Twin in the Automotive Edge Cloud

We demonstrate a working functional prototype of a cooperative perception system that maintains a real-time digital twin of the traffic environment, providing a more accurate and more reliable model than any of the participant subsystems-in this case, smart vehicles and infrastructure stations-would manage individually. The importance of such technology is that it can facilitate a spectrum of new derivative services, including cloud-assisted and cloud-controlled ADAS functions, dynamic map generation with analytics for traffic control and road infrastructure monitoring, a digital framework for operating vehicle testing grounds, logistics facilities, etc. In this paper, we constrain our discussion on the viability of the core concept and implement a system that provides a single service: the live visualization of our digital twin in a 3D simulation, which instantly and reliably matches the state of the real-world environment and showcases the advantages of real-time fusion of sensory data from various traffic participants. We envision this prototype system as part of a larger network of local information processing and integration nodes, i.e., the logically centralized digital twin is maintained in a physically distributed edge cloud.

Automated summary

The paper presents a working prototype of a cooperative perception system that maintains a real-time digital twin of the traffic environment, providing a more accurate model than individual subsystems could. This technology enables new derivative services such as cloud-assisted ADAS functions and dynamic map generation for traffic control. The prototype system is envisioned as part of a larger network of local information processing and integration nodes, showcasing the advantages of real-time fusion of sensory data.