CSR: III: Small: Collaborative Research: Hybrid Vehicle-Cloud Solutions for Robust, Cost-Efficient Road Monitoring

今天的许多车辆都配备了GPS、联网功能、计算资源以及各种环境和车辆性能传感器。这些技术的结合以及这类车辆的日益增多为大规模道路传感应用提供了一个强大的平台，以帮助司机进行路线规划和安全驾驶。随着参与的车辆数量的增加，庞大的数据量及其在蜂窝网络中传输的成本使当前的集中式解决方案变得不可持续。该项目提出了一种综合的方法，以克服协作道路感知的成本和可扩展性挑战的算法和系统障碍。该项目进行了四项主要研究任务：(1)获得车辆传感器读数和网络连通性的相关测量；(2)通过车到车(V2V)消息委托降低车到云(V2C)通信的成本；(3)开发新的通信高效的算法方法，用于协作道路传感；(4)在仿真框架中评估通信和算法解决方案，该框架汇集了车辆传感器数据、蜂窝和V2V连通性测量以及来自I-90/94走廊信息系统的交通流量数据。该项目的成果将包括城市和农村环境下可靠的互联车辆通信体系结构，以及理论上健全的分布式传感和估计算法，这将引起更广泛的分布式计算系统社区的兴趣。通信体系结构和传感算法将作为大规模协作、实时道路传感的原型。这种方法的广泛采用将使司机更好地了解危险驾驶条件，支持更安全和更高效的交通。该项目开发的技术和系统还将应用于需要分析分布在大量设备或系统上的大量传感数据的环境中，例如在飞机上的协作空域监测和物联网中的环境监测中。

Many of today's vehicles are equipped with GPS, networking capabilities, computational resources, and a variety of environment and vehicle performance sensors. The combination of these technologies and the growing presence of such vehicles offer a powerful platform for large-scale road sensing applications to assist drivers in route planning and safe driving. As the number of participating vehicle grows, the sheer amount of data and the cost of its transmission in cellular networks make current, centralized solutions unsustainable. This project proposes an integrated approach to overcoming algorithmic and systems barriers to the cost and scalability challenges of collaborative road sensing. The project conducts four main research tasks: (1) obtain correlated measurements of vehicle sensor readings and network connectivity, (2) reduce the cost of vehicle-to-cloud (V2C) communication through vehicle-to-vehicle (V2V) message delegation, (3) develop new communication-efficient algorithmic approaches for collaborative road sensing, (4) evaluate the communication and algorithmic solutions in an emulation framework that pulls together vehicle sensor data, measurements of cellular and V2V connectivity, and traffic flow data from a I-90/94 corridor information system. Results of this project will include reliable connected vehicle communication architecture for both urban and rural settings and theoretically sound decentralized algorithms for sensing and estimation that will be of interest to the broader distributed computing systems community.The communication architecture and sensing algorithms will serve as a prototype for large-scale collaborative, real-time road sensing. The widespread adoption of such an approach will provide drivers with better awareness of hazardous driving conditions, supporting safer and more efficient transportation. Techniques and systems developed in this project will also have applications in settings that require analysis of vast amount of sensed data that is distributed over a large number of devices or systems, for example, in collaborative airspace monitoring in airplanes and environment monitoring in the Internet of Things.