From Code to Road: A Vehicle-in-the-Loop and Digital Twin-Based Framework for Central Car Server Testing in Autonomous Driving
🤖 AI Summary
This work addresses the limitations of existing virtual simulation in faithfully replicating real-world dynamics and the high cost and inefficiency of conventional testing approaches that require separate validation of individual physical ECUs and their communication protocols. The authors propose an integrated testing framework that combines Vehicle-in-the-Loop (ViL) with digital twin technology, coupling a real vehicle on a dynamometer with its synchronized virtual counterpart and executing the full autonomous driving software stack directly on the vehicle’s onboard hardware. This approach enables, for the first time under a centralized electronic/electrical architecture, an end-to-end deployment without firmware flashing or intermediate middleware, seamlessly unifying physical and virtual test environments to support early-stage hybrid validation. Experimental results demonstrate that the framework substantially reduces development and integration testing costs while enhancing safety, reproducibility, and fidelity.
Application Category
📝 Abstract
Simulation is one of the most essential parts in the development stage of automotive software. However, purely virtual simulations often struggle to accurately capture all real-world factors due to limitations in modeling. To address this challenge, this work presents a test framework for automotive software on the centralized E/E architecture, which is a central car server in our case, based on Vehicle-in-the-Loop (ViL) and digital twin technology. The framework couples a physical test vehicle on a dynamometer test bench with its synchronized virtual counterpart in a simulation environment. Our approach provides a safe, reproducible, realistic, and cost-effective platform for validating autonomous driving algorithms with a centralized architecture. This test method eliminates the need to test individual physical ECUs and their communication protocols separately. In contrast to traditional ViL methods, the proposed framework runs the full autonomous driving software directly on the vehicle hardware after the simulation process, eliminating flashing and intermediate layers while enabling seamless virtual-physical integration and accurately reflecting centralized E/E behavior. In addition, incorporating mixed testing in both simulated and physical environments reduces the need for full hardware integration during the early stages of automotive development. Experimental case studies demonstrate the effectiveness of the framework in different test scenarios. These findings highlight the potential to reduce development and integration efforts for testing autonomous driving pipelines in the future.
Problem
Research questions and friction points this paper is trying to address.
autonomous driving
centralized E/E architecture
simulation validation
Vehicle-in-the-Loop
digital twin
Innovation
Methods, ideas, or system contributions that make the work stand out.
Vehicle-in-the-Loop
Digital Twin
Centralized E/E Architecture
Autonomous Driving Testing
Hardware-in-the-Loop Simulation
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