Improving the Efficiency of Trucks via CV2X Connectivity on Highways

Abstract

Intelligent road infrastructure consisting of sensors and communications is needed to deploy connected and automated vehicles (CAVs) on real highways. Such infrastructure can support the operation of CAVs (e.g., maneuver coordination and onboard energy management), and bridge the connectivity gap resulting from the currently low penetration of connected vehicles and the limited range of vehicle-to-vehicle communication. Moreover, it also allows us to build high-efficiency transportation systems, leading to societal benefits such as emission reduction, energy efficiency improvement, and productivity increase. In this project, we deploy cellular vehicle-to-everything (CV2X) infrastructure along the highway I-275, which consists of roadside units (RSUs), a server managed by the University of Michigan, and communications between them. The RSUs collect traffic information from the downstream vehicles on highway via a custom V2X communication message called traffic history message (THM). The received THMs are transferred via the RSUs’ LTE Internet to the university server for real-time processing. The processed information is then sent to the upstream RSUs and broadcast to vehicles nearby via another custom V2X message called traffic prediction message (TPM). This allows the upstream vehicles to predict the traffic ahead and plan their motions accordingly. This way, traffic prediction and control can be achieved. We conduct experiments on highway I-275 using the installed RSUs and the designed messages with real vehicles. We demonstrate the effectiveness of the infrastructure-supported traffic prediction tailored to the needs of automated vehicles.