A human-centric eXplainable Automated Vehicle

其目的是创建一个计算模型，以解决由人工智能驱动的自动驾驶汽车（AV）无法自我解释其行为的问题。该项目在现实世界的自动驾驶环境中应用新颖的多学科方法，以正式确定驾驶解释的本质。它探讨了驾驶员何时、为什么以及如何寻求解释，以及什么类型的自动解释是真正的人类可解释的。预期成果包括发现一个可接受的，透明的和道德的解释系统，帮助人类理解自动驾驶汽车的决策。这一领域将继续突出，并产生急需的工作，以提高自动驾驶汽车的广泛采用。

The aim is to create a computational model to address the inability of Automated Vehicles (AV), powered by Artificial intelligence, to self explain their behaviours. This project applies novel multidisciplinary methodologies in a real-world self-driving setting to formalise the essence of driving explanations. It explores the when, why and how a driver is seeking an explanation and what type of automated explanation is truly human-interpretable. Expected outcomes include the discovery of an acceptable, transparent and ethical explanation system that helps humans to understand the AVs decision making. This field will continue to rise in prominence and produce much-needed work to improve the widespread adoption of AVs.