To be autonomous, systems must be able to capture, perceive, analyse, plan, make decisions and act without human intervention. These characteristics are very important and should be carried out in real time. This is what creates the challenge for autonomous systems to come out and become established players in real world. Different autonomous vehicles that are used in different environments, constrained or not, like roads, rails, overwater, underwater, air, need to have different capabilities and characteristics and in addition pose different kind of challenges that need to be overcome. Therefore, there exists many taxonomies that have been proposed by researchers with different backgrounds in order to address the needs of their specific systems in the most effective way. However, there is some common base between the different taxonomies that are proposed for various vehicles and it would be beneficial to try and learn from the experience of the approaches proposed. In this paper, we try to compare the most frequently proposed taxonomies in autonomous vehicles operating in different modes and help the readers find the similarities and differences amongst them.