Intelligent architectures and tools for Internet of Vehicles

车联网（IoV）被定义为三种网络的融合：车际网络、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车辆、路边单元、互联网和人之间根据商定的通信协议和数据交互标准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分布的异构源收集信息，用于交通监控、信息娱乐等应用。虽然这些资源可以提供丰富的信息，但通常会产生大量的数据。在车联网中，连接组件数量的快速增长正在以指数级速度创建数据。例如，一辆联网汽车每秒可以产生10兆字节的数据。将所有数据发送到云将需要极高的网络带宽，并且在满足许多新的服务质量（QoS）要求方面面临越来越大的挑战。该研究计划的主要目标是设计和评估智能模型、协议和架构，以便在上下文感知环境中为协作车辆实现实时和高精度的态势感知。更具体地说，本项目研究的目标是：1。1 .定义一套智能车联网架构需求，支持不同智能应用和智能交通系统领域异构设备的无缝集成；2 .设计一种既能支持动态拓扑变化、可扩展性、实时性和可用性的架构，又能实现车联网系统中设备和服务之间高效、可靠的数据共享；3 .通过模拟和与预定义的需求集进行比较，对所提出的体系结构进行原型设计和性能评估；4 .设计并评估一个模型的性能，该模型将计算、通信、控制和存储的资源和服务更接近用户，以提高整个系统的效率、可靠性和性能；基于上下文感知环境的城市交通管理新认知信息收集机制的提出与评价6. 设计并验证一个智能微观交通移动模型，该模型专门用于联网和自动驾驶车辆，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。为了评估目标5，将使用概率中贝叶斯、隐马尔可夫模型以及时空数据挖掘。最后，本研究项目将直接资助3名硕士生和2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 Nave 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.