Formation and Investigation of Cooperative Platooning at the Early Stage of Connected and Automated Vehicles Deployment

TL;DR

This paper proposes a novel control framework for cooperative platooning in mixed traffic, improving safety, comfort, and efficiency even at low CAV market penetration rates through innovative strategies and lane-change models.

Contribution

It introduces a mixed cooperative platooning strategy and a lane-change decision model to enhance platoon formation and performance in early CAV deployment stages.

Findings

Platoon formation increases by up to 24%.

Fuel consumption decreases by 7%.

Safety and traffic efficiency improve significantly.

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.