Abstract
Autonomous/unmanned driving is the major state-of-the-art step that has a potential to fundamentally transform the mobility of individuals and goods. At present, most of the developments target standalone autonomous vehicles, which can sense the surroundings and control the vehicle based on this perception, with limited or no driver intervention. This paper focuses on the next step in autonomous vehicle research, which is the collaboration between autonomous vehicles, mainly vehicle formation control or vehicle platooning. To gain a deeper understanding in this area, a large number of the existing published papers have been reviewed systemically. In other words, many distributed and decentralized approaches of vehicle formation control are studied and their implementations are discussed. Finally, both technical and implementation challenges for formation control are summarized.
Highlights
A driverless vehicle is a big innovation in the transport industry
The aim of the platoon formation control is to confirm that all vehicles in a platoon move at the same speed while maintaining a desired formation shape or geometry, which is stated by a desired inter-vehicle spacing strategy [4]
A leader–follower formation tracking control of the autonomous vehicles was achieved on a straight path proving that recursive implementation of a cascaded system inspired controller leads to a spanning-tree communication topology [21]
Summary
A driverless vehicle is a big innovation in the transport industry. Many automotive companies are working on five levels of autonomy [1]. The behaviour coordinator multiplies the output of each behaviour by its relative weight, summing and normalizing the results One advantage of this approach is that it can operate in the unknown and dynamic environment because it is a parallel, real-time and distributed method, requiring less information sharing [5]. To track the agents, a tracking controller for each individual agent is derived in which the formation is maintained by minimising the error between the virtual structure and the current agent position In this approach, the desired trajectory is not assigned to the single agent, but it is shared by the whole formation team.
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