云计算
计算机科学
避障
障碍物
模拟
半实物仿真
场景测试
实时计算
智能交通系统
工程类
人工智能
移动机器人
机器人
运输工程
多样性(控制论)
政治学
法学
操作系统
作者
Li Shuguang,Luo Zhonglin,Wei Wenbo,Zhao Yang,Hu Jierui,Cheng Hong
标识
DOI:10.1109/itsc55140.2022.9922190
摘要
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.
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