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

到本世纪末，美国交通部(DOT)可能会要求所有新车辆都是互联车辆(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，以减少撞车次数和拯救生命。车辆到车辆(V2V)和车辆到基础设施(V2I)连接支持的碰撞避免应用程序交换安全关键信息，如速度、位置和移动方向，以基于车辆的接近程度来评估碰撞风险。虽然专用短程通信(DSRC)等标准将发挥关键作用，但其他技术，如WiFi、LTE(蜂窝)或其他新兴技术，可以降低系统总体成本，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。南卡罗来纳州互联车辆试验台(SC-CVT)位于85号州际公路10英里路段，靠近克莱姆森位于南卡罗来纳州格林维尔的国际汽车研究中心(ICAR)园区。将开发的两个具体示例CV应用程序是交通事件检测和队列警告。这两个应用程序提供了一个方便的起点，用于说明CV应用程序如何受益于在CV系统中集成多种无线技术的先进网络技术。异质网络(HetNet)是集成和利用多种并发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程序。该项目使用软件定义的网络、GENI机架提供的本地计算和基于统计学习理论的控制相结合来演示SC-CVT上优化的HetNet操作。

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.