The vehicle of the future is expected to be automated. High levels of vehicle automation are seen as enabling technologies to improve road safety and road utilization and to reduce air pollutant emissions. However, to make this happen, research communities still need to address several challenges. Vehicle automation requires information about the surrounding environment, road conditions, and vehicle states, which are difficult to accurately sense. This uncertain information creates challenges for safe and reliable decision making and control of vehicles, as well as for testing and validation. Additionally, with the increase in vehicle automation, the rate of utilization is expected to grow significantly—think of self-driving taxis or trucks operating 24/7. This will raise vehicles’ reliability demands, requiring effective mitigation strategies for resilient operation. This special issue (SI) brings together researchers working in this field to share their latest developments on control, estimation, and diagnosis.

中文翻译：

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自动驾驶车辆运动控制、估计和诊断的最新进展 [来自客座编辑]


未来的车辆预计将实现自动化。高水平的车辆自动化被视为改善道路安全和道路利用率以及减少空气污染物排放的使能技术。然而，为了实现这一目标，研究界仍然需要解决一些挑战。车辆自动化需要周围环境、路况、车辆状态等信息，而这些信息很难准确感知。这种不确定的信息给车辆的安全可靠的决策和控制以及测试和验证带来了挑战。此外，随着车辆自动化程度的提高，利用率预计将显着增长——想想 24/7 运行的自动驾驶出租车或卡车。这将提高车辆的可靠性要求，需要有效的缓解策略来实现弹性运行。本期特刊 (SI) 汇集了该领域的研究人员，分享他们在控制、估计和诊断方面的最新进展。