Formation and Investigation of Cooperative Platooning at the Early Stage of Connected and Automated Vehicles Deployment
Zeyu Mu, Sergei S. Avedisov, Ahmadreza Moradipari, B. Brian Park
TL;DR
The paper tackles the limited benefits of cooperative platooning in the early deployment of connected automated vehicles by introducing an SVIS-enabled control framework that enables mixed cooperative platooning (CACCu) and strategic lane-change decisions. It combines three components—SVIS for leader identification, a MOBIL-based lane-change model, and ACC/CACC/CACCu planners—to form and maintain platoons in sparse-connectivity scenarios. Through high-fidelity microsimulation and extended NGSIM data, it demonstrates that CACCu substantially improves safety, comfort, and traffic efficiency at low CV penetration, and that lane-change strategies further enhance platoon formation and performance, albeit with potential flow disturbances at higher CV MPR. The study highlights the critical role of accurate vehicle identification in realizing CACCu benefits and points to future work in cooperative lane-change modeling and field validation to bridge simulation and real-world deployment.
Abstract
Cooperative platooning, enabled by cooperative adaptive cruise control (CACC), is a cornerstone technology for connected automated vehicles (CAVs), offering significant improvements in safety, comfort, and traffic efficiency over traditional adaptive cruise control (ACC). This paper addresses a key challenge in the initial deployment phase of CAVs: the limited benefits of cooperative platooning due to the sparse distribution of CAVs on the road. To overcome this limitation, we propose an innovative control framework that enhances cooperative platooning in mixed traffic environments. Two techniques are utilized: (1) a mixed cooperative platooning strategy that integrates CACC with unconnected vehicles (CACCu), and (2) a strategic lane-change decision model designed to facilitate safe and efficient lane changes for platoon formation. Additionally, a surrounding vehicle identification system is embedded in the framework to enable CAVs to effectively identify and select potential platooning leaders. Simulation studies across various CV market penetration rates (MPRs) show that incorporating CACCu systems significantly improves safety, comfort, and traffic efficiency compared to existing systems with only CACC and ACC systems, even at CV penetration as low as 10%. The maximized platoon formation increases by up to 24%, accompanied by an 11% reduction in acceleration and a 7% decrease in fuel consumption. Furthermore, the strategic lane-change model enhances CAV performance, achieving notable improvements between 6% and 60% CV penetration, without adversely affecting overall traffic flow.