Nowadays, many machine learning (ML) solutions to improve the wireless standard IEEE802.11p for Vehicular Adhoc Network (VANET) are commonly evaluated in the simulated world. At the same time, this approach could be cost-effective compared to real-world testing due to the high cost of vehicles. There is a risk of unexpected outcomes when these solutions are implemented in the real world, potentially leading to wasted resources. To mitigate this challenge, the hardware-in-the-loop is the way to move forward as it enables the opportunity to test in the real world and simulated worlds together. Therefore, we have developed what we believe is the pioneering hardware-in-the-loop for testing artificial intelligence, multiple services, and HD map data (LiDAR), in both simulated and real-world settings.

翻译：当前，针对车载自组织网络（VANET）中无线标准IEEE802.11p的改进，众多机器学习（ML）解决方案通常仅在仿真环境中进行评估。与此同时，由于车辆成本高昂，相较于真实世界测试，仿真方法可能更具成本效益。然而，当这些解决方案部署于真实环境时，存在产生意外结果的风险，可能导致资源浪费。为应对这一挑战，硬件在环技术是可行的发展路径，它为实现真实世界与仿真世界的联合测试提供了可能。因此，我们开发了据信为首创的硬件在环系统，用于在仿真与真实世界环境中，对人工智能、多类服务及高精地图数据（LiDAR）进行测试。