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

CSR：III：小型：协作研究：用于稳健、经济高效的道路监控的混合车辆云解决方案

• 批准号: 1527097
• 负责人: Mike Wittie
• 金额: $ 12.47万
• 依托单位: Montana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1527097&HistoricalAwards=false
• 关键词: CSR; III; Small; Collaborative; Research

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.

当今的许多车辆都配备了GPS，网络功能，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此类车辆的日益增长为大规模的道路传感应用提供了一个强大的平台，以帮助驾驶员进行路线规划和安全驾驶。随着参与车辆的数量的增长，蜂窝网络中庞大的数据量及其传输的成本使得当前的集中解决方案不可持续。该项目提出了一种综合方法，以克服算法和系统障碍，以应对协作道路传感的成本和可伸缩性挑战。该项目执行四个主要研究任务：（1）获得车辆传感器读数和网络连接性的相关测量，（2）通过车辆到露通（V2C）通过车辆到车辆（V2V）消息授权降低车辆对云的成本（V2C），（3）开发新的沟通算法的方法，以开发新的通信算法，以评估协作式的沟通，并评估ALG的沟通（4）ALG ORGOR INGER INGERITIT（4）ALG ONGOR INGRITH（4）传感器数据，蜂窝和V2V连接性的测量以及来自I-90/94走廊信息系统的交通流数据。该项目的结果将包括用于城市和农村环境的可靠连接的车辆通信体系结构以及用于感应和估计的理论上的分散算法，这将引起广泛的分布式计算系统社区的关注。通信体系结构和传感算法将用作大型协作，实时的，实时的，实时的，实时，实时路线的原型。这种方法的广泛采用将使驾驶员对危险驾驶条件有更好的认识，从而支持更安全，更有效的运输。该项目中开发的技术和系统还将在设置中提供应用程序，这些应用需要分析大量感知的数据，这些数据分布在大量设备或系统上，例如在物联网中的飞机和环境监控的协作空域监控中。