论文标题
车辆云与自动驾驶的整合：调查和未来观点
Integration of Vehicular Clouds and Autonomous Driving: Survey and Future Perspectives
论文作者
论文摘要
数十年来，车辆临时网络（VANETS）和自动驾驶汽车的研究人员分别提出了各种解决方案，以实现车辆安全和自主权。然而，这两个领域的发达工作主要是在自己的独立世界中进行的，尽管有明显的关系，但却几乎没有影响一所。在接下来的几年中，有望桥接许多技术，以启用许多技术，以提供增值信息，以便自动驾驶汽车导航，从而减少板上计算的车辆，并提供所需功能。弥合这两个世界之间差距并创建这两种技术的协同作用的潜力最近开始引起许多公司和政府机构的重大关注。 In this article, we first present a comprehensive survey and an overview of the emerging key challenges related to the two worlds of Vehicular Clouds (VCs) including communications, networking, traffic modelling, medium access, VC Computing (VCC), VC collation strategies, security issues, and autonomous driving (AD) including 3D environment learning approaches and AD enabling deep-learning, computer vision and Artificial Intelligence (AI) techniques.然后，我们讨论了最近相关的工作和合并这两个世界的潜在趋势，以丰富车辆对周围环境的认识，并使更安全，更明智，更协调的广告系统。与其他调查论文相比，这项工作提供了文献中最相关的VC和ADS系统的更详细摘要，以及有关不同技术如何融合提供安全，自治和信息娱乐服务的一些关键挑战和见解。
For decades, researchers on Vehicular Ad-hoc Networks (VANETs) and autonomous vehicles presented various solutions for vehicular safety and autonomy, respectively. Yet, the developed work in these two areas has been mostly conducted in their own separate worlds, and barely affect one-another despite the obvious relationships. In the coming years, the Internet of Vehicles (IoV), encompassing sensing, communications, connectivity, processing, networking, and computation is expected to bridge many technologies to offer value-added information for the navigation of self-driving vehicles, to reduce vehicle on board computation, and to deliver desired functionalities. Potentials for bridging the gap between these two worlds and creating synergies of these two technologies have recently started to attract significant attention of many companies and government agencies. In this article, we first present a comprehensive survey and an overview of the emerging key challenges related to the two worlds of Vehicular Clouds (VCs) including communications, networking, traffic modelling, medium access, VC Computing (VCC), VC collation strategies, security issues, and autonomous driving (AD) including 3D environment learning approaches and AD enabling deep-learning, computer vision and Artificial Intelligence (AI) techniques. We then discuss the recent related work and potential trends on merging these two worlds in order to enrich vehicle cognition of its surroundings, and enable safer and more informed and coordinated AD systems. Compared to other survey papers, this work offers more detailed summaries of the most relevant VCs and ADs systems in the literature, along with some key challenges and insights on how different technologies fit together to deliver safety, autonomy and infotainment services.
