Vehicle-in-the-Loop Intelligent Connected Vehicle Simulation System Based on Vehicle-Road-Cloud Collaboration

Abstract

Autonomous driving test technology is an important guarantee for the large-scale commercialization of autonomous vehicles(AV). The existing test methods are mainly based roads and simulations. Traditional vehicle road test has real traffic environment, but the diversity of test scenarios is limited. It is difficult to customize corner case scenarios safely and efficiently. Simulation testing is flexible and efficient, but the lack of a real traffic flow test environment separates the strong coupling relationship between the vehicle and the environment in practical application scenarios. In view of above, a novel Vehicle-in-the- Loop(ViL) verification method based on vehicle-road-cloud collaboration is proposed in this paper. (1) On the roadside, we propose a road real-time traffic flow element perception method based on monocular camera, and apply the real traffic flow to autonomous driving simulation testing. (2) On cloud platform, we independently develop a simulation platform based on Open- SceneGraph(OSG), which can quickly simulate different weather, lighting and other disturbance factors such as virtual pedestrians and vehicles based on real scenes. (3) On the vehicle, we build a closed-loop test system that combine intelligent connected vehicle(ICV) and mixed environments. This paper takes the autonomous driving obstacle avoidance algorithm in the campus road scene as an example, and completes the system test in the mixed scene. Experiments show that our proposed method can be used as a safer and more efficient test method before autonomous vehicle road test.