边缘计算在智慧交通系统中的应用

随着汽车的普及，交通拥堵问题日益严重，依靠传统云计算的智慧交通系统虽能在一定程度上缓解交通压力，但已无法满足辅助驾驶、自动驾驶等新型车载应用对传输带宽与时延的需求。为了实现海量数据的实时处理，保障公众信息及交通安全，提升交通系统运行效率，将边缘计算应用于智慧交通。首先对智慧交通的发展概况进行整体描述，提出基于边缘计算的智慧交通总体架构，充分利用边缘计算物理邻近、高带宽、低时延、位置认知的特点解决目前交通系统信息传递延迟、数据处理不及时、传输负载大等问题。然后，基于无线传输、信息感知、计算卸载及协同处理等方面阐述边缘计算应用于智慧交通亟需解决的关键技术。最后，指出边缘计算应用于智慧交通面临的未来机遇与挑战。

Application of Edge Computing in Intelligent Transportation Systems

With the popularization of automobiles, traffic congestion is becoming increasingly serious. Although the cloud-based intelligent transportation systems (ITS) can relieve traffic pressure, it can no longer meet the demand of transmission bandwidth and delay requirements of new on-board applications such as assisted driving and autonomous driving. In order to realize the data real-time processing, ensure public information and traffic safety, and improve the transportation system efficiency, edge computing (EC) is applied to ITS. The development of ITS is described and the overall architecture of edge-based ITS is proposed, which makes full use of the characteristics of edge computing such as physical proximity, high bandwidth, low latency and location recognition to solve the problems of information transmission delay, data processing delay and large transmission load. Next, the key technologies of edge computing in ITS are discussed from the aspects of wireless transmission, information perception, computing offloading and collaborative processing. Finally, the future opportunities and challenges for the application of EC in ITS are pointed out.