Artificial Intelligence for Autonomic Urban Traffic Control

目前，世界上一半以上的人口居住在城市，全球城市化进程继续稳步推进。随着这一趋势的持续，流动性正成为一个日益严重的问题。仅在英国，2018年拥堵造成的时间损失和燃料消耗就达到近80亿英镑，并已成为一个主要的健康威胁。与此同时，联网自动驾驶汽车等新型交通方式和新的商业模式（如移动即服务）正在颠覆交通运输行业。交通控制行业必须重塑自身，以适应一个分散控制（车辆决策）、无处不在的传感器信息、日益增长的城市化压力和大规模互联的世界。人工智能提供了一系列方法，可以利用不断增长的可用数据量和过去几十年交通部门获得的知识来支持城市交通。特别是，拟议的研究路线旨在设计和创建一个自主的城市交通管理和控制框架。自主框架将具有自我管理和自我配置的能力，并将对受控区域的状况有一个整体的看法，以主动采取行动，防止环境和流动性问题，或对观察到的问题做出反应。

Over half of the world's population now lives in cities, and global urbanisation continues at a steady pace. As this trend continues, mobility is becoming an increasingly critical problem. In the UK alone, the cost of congestion reached nearly £8 billion in 2018 in lost time and fuel consumption, and has become a major health threat.At the same time, new modes of transport, such as Connected Autonomous Vehicles, and new business models (e.g., Mobility as a Service) are disrupting the transportation sector. The traffic control industry has to reinvent itself to operate in a world of decentralised control (vehicles making decisions), ubiquitous sensor information, increasing urbanisation pressure, and large-scale interconnectivity.Artificial Intelligence provides a range of approaches that can leverage the growing volume of available data, and the knowledge gained by traffic authorities in the past decades, to support urban mobility. In particular, the proposed line of research aims at designing and creating an autonomic urban traffic management and control framework. The autonomic framework will have the capability to self-manage and self-configure, and will have an holistic view of the condition of the controlled region to proactively act to prevent environmental and mobility issues, or react to mitigate observed problems.