Intelligent architectures and tools for Internet of Vehicles

车联网(IoV)被定义为三个网络的集成：车载网络、车内网络和车载移动互联网。基于三网合一的概念，我们可以将车联网定义为根据商定的通信协议和数据交互标准，在车辆、路旁单位、互联网和人之间进行无线通信和信息交换的大规模分布式系统。*车载网络依赖于从空间上分布的异构源收集信息，用于交通监控、信息娱乐等应用。尽管这些资源可以提供丰富的信息，但通常会产生海量和压倒性的数据。*在万物互联中，快速增长的连接组件数量正在以指数速度产生数据。例如，一辆联网的汽车每秒可以产生10兆字节的数据。将所有数据发送到云将需要高得令人望而却步的网络带宽，并在满足许多新的服务质量(QoS)要求方面遇到越来越多的挑战。*本研究计划的主要目标是设计和评估智能模型、协议和架构，以实现上下文感知环境中协作车辆的实时和高精度态势感知。更具体地说，本项目研究的目标是：*1.定义一套支持不同智能应用和智能交通系统领域中使用的异构设备的无缝集成的智能IoV体系结构；*2.设计一个不仅能够支持动态拓扑变化、可扩展性、实时和可用性，而且能够在IoV系统的设备和服务之间实现高效可靠的数据共享的体系结构；*3.通过模拟和与预先定义的需求集的比较，对所提出的体系结构的性能进行原型化和评估；*4.设计和评估模型的性能，将计算、通信、控制和存储的资源和服务更接近用户，以提高整体系统的效率、可靠性和性能；*5.提出并评估上下文感知环境下城市交通管理的新认知信息收集机制；*6.设计和验证一个专用于互联和自动化车辆的智能微观交通流动模型，能够考虑驾驶员的行为和车辆轨迹。*我们将进行模拟以评估性能和准确性。为评价目标5，将使用概率朴素贝叶斯模型、隐马尔可夫模型以及时空数据挖掘。*最后，该研究项目将直接支持三名硕士和两名博士生。

The Internet of Vehicles (IoV) is defined as an integration of three networks: an inter-vehicle network, an intra-vehicle network and a vehicular mobile Internet. Based on this concept of three networks integrated into a single one, we can define an Internet of Vehicles as a large-scale distributed system for wireless communication and information exchange between vehicles, roadside units and Internet, and humans, according to agreed communication protocols and data interaction standards. ******Vehicular networks rely on gathering information from spatially distributed heterogeneous sources for applications such as traffic monitoring, infotainment, etc. Although these resources can provide rich information, a vast and overwhelming amount of data are usually generated. ******In IoV, the rapidly growing number of connected components is creating data at an exponential rate. A connected car, for example, can create ten megabytes of data per second. Sending all the data to the cloud will require prohibitively high network bandwidth and encounters growing challenges in meeting many new quality of service (QoS) requirements. ******The main objective of this research program is to design and evaluate intelligent models, protocols and architectures for achieving real-time and high accuracy situational awareness for cooperating vehicles in context-aware environments. More specifically, this program research aims at:***1. Defining a set of requirements for an intelligent IoV architecture supporting seamless integration of heterogeneous devices used in different smart applications and in intelligent transportation system domains;***2. Designing an architecture that is not only capable of supporting dynamic topology changes, scalability, real time and availability but which also enables efficient and reliable data sharing between devices and services of the IoV system;***3. Prototyping and evaluating the performance of the proposed architecture using simulations and comparisons with the predefined set of requirements;***4. Designing and evaluating the performance of a model that distributes the resources and services of computation, communication, control and storage closer to the users in order to enhance overall system efficiency, reliability and performance;***5. Proposing and evaluating a new cognitive information gathering mechanism in a context-aware environment for urban traffic management; ***6. Designing and validating an intelligent microscopic traffic mobility model dedicated to connected and automated vehicles, capable of taking into account drivers' behaviors and vehicles trajectories.******We will conduct simulations to assess performance and accuracy. To evaluate objective 5, Probabilistic Naïve Bayesian, hidden Markov models, as well as spatio-temporal data mining will be used. ******Finally, this research program will directly support three masters and two doctoral students.