标题： 具有人工智能驱动的数字孪生的车辆在环模拟器，用于测试自动驾驶控制器 显示英文标题

标题： A Vehicle-in-the-Loop Simulator with AI-Powered Digital Twins for Testing Automated Driving Controllers

摘要： 模拟器是测试自动驾驶控制器的有用工具。 车辆在环（ViL）测试和数字孪生（DTs）是广泛使用的仿真技术，以促进控制器顺利部署到实际车辆中。 然而，传统的ViL测试依赖于全尺寸车辆，需要较大的空间和高昂的费用。 此外，基于物理模型的DT存在由于建模不精确而导致的真实感差距。 本文开发了一个全面且实用的模拟器，用于测试由缩比物理汽车和人工智能驱动的DT模型增强的自动驾驶控制器。 缩比汽车可以节省模拟测试的空间和费用。 人工智能驱动的DT模型确保了卓越的仿真保真度。 此外，该模拟器与现成的软件和控制算法集成良好，使其易于扩展。 我们使用了一个经过过滤的控制基准并具有形式化安全保证，以展示模拟器在验证自动驾驶控制器方面的能力。 进行了实验研究以展示模拟器的有效性，表明其在验证自动驾驶车辆和智能交通控制解决方案方面的巨大潜力。 显示英文摘要

摘要： Simulators are useful tools for testing automated driving controllers. Vehicle-in-the-loop (ViL) tests and digital twins (DTs) are widely used simulation technologies to facilitate the smooth deployment of controllers to physical vehicles. However, conventional ViL tests rely on full-size vehicles, requiring large space and high expenses. Also, physical-model-based DT suffers from the reality gap caused by modeling imprecision. This paper develops a comprehensive and practical simulator for testing automated driving controllers enhanced by scaled physical cars and AI-powered DT models. The scaled cars allow for saving space and expenses of simulation tests. The AI-powered DT models ensure superior simulation fidelity. Moreover, the simulator integrates well with off-the-shelf software and control algorithms, making it easy to extend. We use a filtered control benchmark with formal safety guarantees to showcase the capability of the simulator in validating automated driving controllers. Experimental studies are performed to showcase the efficacy of the simulator, implying its great potential in validating control solutions for autonomous vehicles and intelligent traffic.