US Ignite: Track 1: Enabling Connected Vehicle Applications through Advanced Network Technology

US Ignite：第一轨：通过先进网络技术实现互联汽车应用

• 批准号: 1531127
• 负责人: James Martin
• 金额: $ 59.86万
• 依托单位: Clemson 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: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1531127&HistoricalAwards=false
• 关键词: US; Ignite; Track; Enabling; Connected

By the end of the decade, the US Department of Transportation (DOT) will likely require all new vehicles to be Connected Vehicles (CV), capable of communicating with other vehicles and roadside infrastructure through wireless communications in order to reduce the number of crashes and save lives. The crash avoidance applications supported by vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity exchange safety critical information such as speed, location and direction of movement to assess the crash risk based on the proximity of vehicles. While standards such as Dedicated Short Range Communications (DSRC) will play a key role, other technologies such as WiFi, LTE (cellular), or other emerging technologies, can lower overall systems cost as well as supplement the availability, coverage, and peak data rate requirements of DSRC-based systems. The South Carolina Connected Vehicle Testbed (SC-CVT) is located along a 10-mile segment of Interstate I-85 near Clemson's International Center for Automotive Research (ICAR) campus in Greenville South Carolina. Two specific example CV applications that will be developed are traffic incident detection and queue warning. These two applications provide a convenient starting point for illustrating how CV applications can benefit from advanced network technology that integrates multiple wireless technologies in a CV system.Heterogeneous networks (HetNets) are networks that integrate and exploit multiple concurrently available networking technologies. For critical applications requiring resource allocation optimization in order to meet safety-driven performance requirements. This project is using a combination of Software Defined Networking, local computing provided by GENI racks, and control based on statistical learning theory to demonstrate optimized HetNet operation on the SC-CVT.

到本世纪末，美国交通部 (DOT) 可能会要求所有新车均为联网车辆 (CV)，能够通过无线通信与其他车辆和路边基础设施进行通信，以减少事故数量并挽救生命。由车辆对车辆 (V2V) 和车辆对基础设施 (V2I) 连接支持的防撞应用程序交换速度、位置和运动方向等安全关键信息，以根据车辆的接近程度评估碰撞风险。 虽然专用短程通信 (DSRC) 等标准将发挥关键作用，但 WiFi、LTE（蜂窝）等其他技术或其他新兴技术可以降低总体系统成本，并补充基于 DSRC 的系统的可用性、覆盖范围和峰值数据速率要求。 南卡罗来纳州联网车辆测试台 (SC-CVT) 位于 I-85 州际公路 10 英里路段，靠近南卡罗来纳州格林维尔的克莱姆森国际汽车研究中心 (ICAR) 园区。 将开发的两个具体的 CV 应用程序示例是交通事件检测和队列警告。这两个应用提供了一个方便的起点，用于说明 CV 应用如何从在 CV 系统中集成了多种无线技术的先进网络技术中受益。异构网络 (HetNet) 是集成和利用多种同时可用的网络技术的网络。适用于需要优化资源分配以满足安全驱动的性能要求的关键应用。该项目结合使用软件定义网络、GENI 机架提供的本地计算以及基于统计学习理论的控制来演示 SC-CVT 上优化的 HetNet 操作。