Decentralized Platoon Control of Heterogeneous Automated Vehicles in Urban Scenario

Abstract

To address the current high level of congestion, particularly in urban areas, a connected vehicle system in the form of a platoon or Connected Cruise Control (CCC) could be a solution. Such a system significantly reduces stop-and-go traffic, as well as fuel consumption. A vehicular platoon system comprises two or more closely-following vehicles traveling at a desired cruising velocity and distance. Compared with human drivers, an automatic platoon control system has the advantage of reducing intervehicle distance, or tight formation, making it a promising solution for reducing traffic congestion, aerodynamic drag, and fuel consumption. This thesis aims to review existing platoon technology , as well as its similarities with Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC). It will also study the platoon mathematically, including its characteristics such as stability and string stability, components, and dynamic behavior. The thesis will review several platoon models, including the Intelligent Vehicle Model (IVM), the first-order model for each vehicle in a platoon, and the Optimal Velocity Model (OVM). To create a linear plant stable and string stable platoon, the Optimal Velocity Model will be modified and linearized, followed by an open-loop simulation of the model. Several controllers will be introduced for the linearized model, such as the Linear Quadratic Regulator, Feedback-feedforward Linear Quadratic Regulator, and Model predictive Controller, and benchmarked against some driving scenarios