Optimal Velocity Model Based CACC Controller for Urban Scenarios

Abstract

To address the current high level of congestion, a connected vehicle system in the form of a platoon or Cooperative Adaptive Cruise Control (CACC) presents a promising solution. This system significantly reduces stop-and-go traffic, as well as fuel consumption. A Cooperative Adaptive Cruise Control (CACC) system comprises two or more closely-following vehicles traveling at a desired cruising velocity and distance headway. Compared with human drivers, such a system has the advantage of reducing inter-vehicle distance, making it a promising solution for mitigating traffic congestion as well as reducing aerodynamic drag, and fuel consumption. This work aims to introduce a new Cooperative Adaptive Cruise Control (CACC) based on the optimal velocity model in traffic dynamics. Several controllers for the introduced CACC system will be presented, particularly various versions of the linear quadratic controller. Simulation scenarios for these controllers will also be discussed.