A human-centric eXplainable Automated Vehicle

其目的是创建一种计算模型，以解决人工智能驱动的自动车辆(AV)无法自我解释其行为的问题。该项目将新的多学科方法应用于现实世界的自动驾驶环境中，以正式确定驾驶解释的本质。它探索了司机何时、为什么和如何寻求解释，以及哪种类型的自动解释真正是人类可以解释的。预期的结果包括发现一个可接受的、透明的和符合道德的解释系统，帮助人类理解AVS的决策。这一领域将继续受到重视，并开展亟需的工作，以促进AVs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.