Autonomous Driving Research Facility (ADRF)

自动驾驶汽车（ADV），也被称为自动驾驶汽车或无人驾驶汽车，是一种能够感知其环境并在很少或没有人为输入的情况下安全行驶的车辆。自动驾驶汽车结合了各种传感器来感知周围环境，如雷达、激光雷达、声纳、GPS、里程计和惯性测量单元。先进的控制系统解释感官信息，以确定适当的导航路径，以及障碍物和相关标志。自动驾驶汽车的硬件能力已经接近优化ADV软件平稳运行所需的水平。然而，用于补充和充分利用自动驾驶汽车硬件潜力的软件（感知、规划、协调和人际互动）仍未开发出来。解决这些软件挑战不仅需要大量的前期研究和开发，还需要漫长的测试和验证期。因此，迫切需要适当的基础设施来支持关键自动驾驶技术的研究，特别是决策、传感器融合和优化策略，这些对于补充和充分利用自动驾驶汽车的潜力至关重要。所要求的基础设施，自动驾驶研究设施（ADRF），将在加拿大大学环境中建立一个独特的设施，能够作为新兴自动驾驶研究的关键平台，并为高素质人才（HQP）创造一个独特，充满活力和多学科的学习和培训环境。它将补充现有的约克自主无人驾驶车辆研究设施（YU- AUV），并将为自主驾驶技术的研究活动提供一个关键的研究平台。这是理想的基础设施，可以进行必要的实验，从而开发技术，促进自动驾驶汽车上路。

An autonomous driving vehicle (ADV), also known as a self-driving car or driverless car, is a vehicle capable of sensing its environment and moving safely with little or no human input. Autonomous--driving cars combine a variety of sensors to perceive their surroundings such as radar, lidar, sonar, GPS, odometry and inertial measurement units. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. The hardware capabilities of autonomous driving cars are already approaching the levels needed for well--optimized ADV software to run smoothly. However, the software (perception, planning, coordination, and human interaction) to complement and utilize the full potential of autonomous vehicle hardware is still undeveloped. Solving these software challenges requires not only significant upfront research and development but also lengthy testing and validation periods. Therefore, appropriate infrastructure is in urgent need to support the research on key autonomous--driving technologies, especially decision--making, sensor--fusion, and optimization strategies, which are vital to complement and utilize the full potential of autonomous vehicles. The requested infrastructure, Autonomous Driving Research Facility (ADRF), will build a unique facility in the Canadian university environment capable of serving as a critical platform for emerging research on autonomous--driving, as well as create a unique, vibrant and multidisciplinary learning and training environment for highly qualified personnel (HQP). It will be complementary to the existing York Research Facility for Autonomous Unmanned Vehicles (YU--AUV) and will provide a key research platform for research activities in autonomous-driving techniques. It is the ideal infrastructure to enable the necessary experiments to be performed and therefore develop the technology to facilitate autonomous vehicles getting on the road.