CarDroid: Container-Based Architecture for Graphic-Intensive Tasks in Automotive Cockpits

The automotive industry has widely adopted GPUs for In-Vehicle Infotainment (IVI) systems, which support applications ranging from navigation to graphics-intensive gaming. However, current automotive GPU virtualization solutions often lack the efficiency, flexibility, and low overhead required in vehicle cockpits. Insufficient isolation under dynamic workloads can cause performance fluctuations and delays, including in latency-sensitive tasks such as route planning. To address these limitations, we introduce CarDroid, a GPU virtualization solution for in-vehicle systems. CarDroid has three main components: (1) a lightweight container runtime that offloads graphics tasks and minimizes interference, (2) cross-OS buffer projection that shares a rendering buffer with the Android host to eliminate redundant cross-OS copies, and (3) a PMU-guided predictor for real-time resource adjustment. Across the tested workload combinations, these mechanisms reduce the arithmetic-mean interference ratio by 31.83%, with a virtualization-overhead premium of 9.19 percentage points over a GPU-passthrough baseline. CarDroid was piloted and validated on production cockpit platforms across 10 vehicle models at 9 automotive companies.