预测层面的人车合作：利用人类预见增强自动驾驶
Human-Vehicle Cooperation on Prediction-Level: Enhancing Automated Driving with Human Foresight
摘要：
为了最大限度地提高安全性和驾驶舒适性，自动驾驶系统可以从实施考虑不同潜在场景发展的前瞻性行动选择中受益。虽然人工场景预测方法正在取得快速进展，但细心的人类驾驶员仍然能够识别系统没有充分考虑的相关背景特征，或者人类驾驶员可能对系统适当对待它们的能力缺乏信任。我们实现了一种方法，可以让人类驾驶员通过凝视快速直观地为自动驾驶系统补充场景预测。我们说明了这种方法的可行性，在现有的自动驾驶系统中运行的模拟器中的各种方案。此外，设计并集成了一个图形化的用户界面（GUI），以增强系统的可信性和可解释性。利用这种协作增强的场景预测有可能提高系统的预见驾驶能力，并使自动驾驶更加可信，舒适和个性化。
英文摘要：
To maximize safety and driving comfort, autonomous driving systems can benefit from implementing foresighted action choices that take different potential scenario developments into account. While artificial scene prediction methods are making fast progress, an attentive human driver may still be able to identify relevant contextual features which are not adequately considered by the system or for which the human driver may have a lack of trust into the system's capabilities to treat them appropriately. We implement an approach that lets a human driver quickly and intuitively supplement scene predictions to an autonomous driving system by gaze. We illustrate the feasibility of this approach in an existing autonomous driving system running a variety of scenarios in a simulator. Furthermore, a Graphical User Interface (GUI) was designed and integrated to enhance the trust and explainability of the system. The utilization of such cooperatively augmented scenario predictions has the potential to improve a system's foresighted driving abilities and make autonomous driving more trustable, comfortable and personalized.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
