Mixed Test Environment-based Vehicle-in-the-loop Validation - A New Testing Approach for Autonomous Vehicles

Abstract

The current test of autonomous driving technology requires extensive experimental verification, whether in simulation or on real roads. Netherthless, how to test autonomous vehicles thoroughly in a safe and comprehensive manner remains a major challenge. To achieve safer and more effective autonomous driving testing, this paper proposes a novel mixed test environment-based validation method with vehicle in the loop(ViL) : (1) our method supports more realistic drive safety tests in mixed scenarios which integrate the synthetic and the real-world scenarios. Synthetic scenarios offer complex traffic simulation with diverse road conditions. The real-world scenarios introduce the real autonomous driving vehicle, the real sensor suite as well as the test field to the test loop, having further bridged the gap between Hardware-in-the-Loop(HiL) testing and real road tests than ViL; (2) virtual perceptional results are simulated directly and delivered to the real vehicle in Unified Fusion Data Format(UFDF), without rendering virtual detection data for reduced resource consumption; (3) diverse test scenarios are configurable and reproducible with OSM-based High Definition(HD) map, enabling the simulation to be decoupled from a specific test filed or traffic facilities. A series of experiments on the application of our method have been demonstrated, and our approach is proved to be a promising drive safety testing technique before actual road testing.