Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles by Factoring Communication-Related Constraints

This study proposes a novel CACC strategy, CACC-OIFT, to explicitly factor IFT dynamics and to leverage it to enhance the platoon performance in an unreliable V2V communication context for a pure CAV platoon

Cooperative Control Mechanism for Platoon Formation of Connected and Autonomous Vehicles

69A3551747105Connected and autonomous vehicles (CAVs) can potentially improve traffic safety and mobility significantly through platoon formation wherein vehicles follow each other closely. Such platoons also may reduce energy consumption of individual CAVs by reducing air drag. While control mechanisms have been previously proposed to control vehicles in a platoon, for example, through adaptive cruise control, they mainly focus on seeking a better situation for an individual vehicle by controlling its driving behavior. This study focused on CAV-based control mechanisms to holistically determine the acceleration/deceleration rate of each CAV in a platoon to maximize platoon performance. It designs several robust control mechanisms to coordinate the behaviors of CAVs in a platoon to ensure safe and efficient maneuver of CAV platoon by addressing several realistic challenges such as the unreliable vehicle-to-vehicle communication (i.e., packet loss) and uncertainty of the leading vehicle\u2019s future behavior. The impact of information delay and topology of information that is exchanged among vehicles on platoon dynamics are analyzed. The optimal time headway and platoon size to maximize fuel efficiency of the CAVs in the platoon are determined. Furthermore, this study developed control mechanisms for a platoon of connected and autonomous vehicles to coordinate the behavior of all the following vehicles in the platoon to improve safety, mobility, and energy consumption