We live in the era of the advent of automated vehicles. These will bring dramatic changes in both the automotive industry and everyday life, revolutionizing the concept of passenger mobility. The issue of perception is crucial for an autonomous vehicle and presents important challenges, many of which still need to be addressed. In this context, the choice of sensors is pivotal, yet there is still no general consensus on what the potential “best” sensory equipment should consist of. Furthermore, perception-related information is then used to make timely decisions on path planning and vehicle dynamics control to ensure efficient and safe vehicle behavior. Here, machine learning algorithms are playing an increasingly important role, for example, in the generation of trajectories perceivable as “natural” by the car’s occupants or in object recognition.

中文翻译：

---

自动驾驶技术的最新进展 [来自客座编辑]


我们生活在自动驾驶汽车出现的时代。这些将为汽车行业和日常生活带来巨大变化，彻底改变乘客出行的概念。感知问题对于自动驾驶汽车至关重要，并带来了重要的挑战，其中许多挑战仍需要解决。在这种情况下，传感器的选择至关重要，但对于潜在的“最佳”传感设备应该由什么组成，目前还没有达成普遍共识。此外，感知相关信息可用于及时做出路径规划和车辆动力学控制决策，以确保高效、安全的车辆行为。在这里，机器学习算法发挥着越来越重要的作用，例如，在生成可被汽车乘员感知为“自然”的轨迹或在物体识别中。