Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.

Introduction to Vehicle Modeling

This course introduces core vehicle dynamics modeling for autonomous driving functions. Topics include vehicle kinematics, Ackermann steering, longitudinal and lateral dynamics, tire models, and engine modeling, with an emphasis on deployment in MATLAB/Simulink and simulation environments like IPG TruckMaker and dSpace ASM.

Introduction to Autonomous Wheeled Robot Control

This course introduces high-level control (HLC) architecture for autonomous wheeled robots, focusing on event-driven decision-making and finite state machines (FSM). Building upon low-level control fundamentals, it covers operational logic modeling for key autonomous behaviors including adaptive cruise control, convoy control, lane following, and intersection management, with practical insights drawn from the DARPA Urban Challenge.

Introduction to AIV Control - Low Level Control

This course introduces low-level control systems for autonomous vehicles, combining vehicle dynamics modeling with practical execution. It explores the distinction between high and low-level control, point-mass models, lateral control maneuvers, obstacle avoidance, and waypoint following techniques.