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首页> 外文期刊>IEEE Vehicular Technology Magazine >Connected Vehicular Transportation: Data Analytics and Traffic-Dependent Networking
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Connected Vehicular Transportation: Data Analytics and Traffic-Dependent Networking

机译：联网汽车运输：数据分析和交通相关网络

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摘要

With onboard operating systems becoming increasingly common in vehicles, the realtime broadband infotainment and intelligent transportation system (ITS) service applications in fast-moving vehicles become ever demanding, and they are expected to significantly improve the efficiency and safety of our daily on-road lives. The emerging ITS and vehicular applications (e.g., trip planning), however, require substantial efforts in real-time pervasive information collection and big data processing to allow quick decision making and feedback to fast-moving vehicles, which imposes significant challenges on the development of an efficient vehicular communication platform. In this article, we present TrasoNET, an integrated network framework that provides real-time intelligent transportation services to connected vehicles by exploring the data analytics and networking techniques. TrasoNET is built upon two key components. The first guides vehicles to the appropriate access networks by exploring the real-time status of local traffic, specific user preferences, service applications, and network conditions. The second mainly involves a distributed automatic access engine, which enables individual vehicles to make distributed access decisions based on recommendations, local observations, and historic information. We highlight the application of TrasoNET in a case study on real-time traffic sensing based on real traces of taxis.
机译：随着车载操作系统在车辆中变得越来越普遍，快速移动车辆中的实时宽带信息娱乐和智能运输系统（ITS）服务应用变得越来越苛刻，它们有望显着提高我们日常道路生活的效率和安全性。然而，新兴的ITS和车辆应用（例如行程计划）需要实时进行广泛的信息收集和大数据处理，以做出快速的决策并反馈给快速行驶的车辆，这对汽车的发展提出了重大挑战。高效的车辆通讯平台。在本文中，我们介绍了TrasoNET，这是一个集成的网络框架，可通过探索数据分析和联网技术为连接的车辆提供实时智能运输服务。 TrasoNET建立在两个关键组件上。第一部分通过探索本地流量的实时状态，特定的用户偏好，服务应用程序和网络状况，将车辆引导至适当的接入网络。第二个主要涉及分布式自动访问引擎，该引擎使各个车辆能够根据建议，本地观察和历史信息做出分布式访问决策。我们重点介绍了TrasoNET在基于出租车真实轨迹的实时交通传感案例研究中的应用。

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