The coordination of multiple autonomous vehicles into convoys or platoons is expected on our highways in the near future. However, before such platoons can be deployed, the new autonomous behaviours of the vehicles in these platoons must be certified. An appropriate representation for vehicle platooning is as a multiagent system in which each agent captures the "autonomous decisions" carried out by each vehicle. In order to ensure that these autonomous decision-making agents in vehicle platoons never violate safety requirements, we use formal verification. However, as the formal verification technique used to verify the agent code does not scale to the full system and as the global verification technique does not capture the essential verification of autonomous behaviour, we use a combination of the two approaches. This mixed strategy allows us to verify safety requirements not only of a model of the system, but of the actual agent code used to program the autonomous vehicles.(V2V) communication is used at a lower (continuous control system) level to adjust each vehicle's position in the lanes and the spacing between the vehicles. V2V is also used at higher levels, for example to communicate joining requests, leaving requests, or commands dissolving the platoon. So a traditional approach is to implement the software for each vehicle in terms of hybrid (and hierarchical) control systems and to analyse this using hybrid systems techniques.However, as the behaviours and requirements of these automotive platoons become more complex there is a move towards much greater autonomy within each vehicle. Although the human in the vehicle is still responsible, the autonomous control deals with much of the complex negotiation to allow other vehicles to leave and join, etc. Traditional approaches involve hybrid automata [12] in which the continuous aspects are encapsulated within discrete states, while discrete behaviours are expressed as transitions between these states. A drawback of combining discrete decision-making and continuous control within a hybrid automaton is that it is difficult to separate the two (high-level decision-making and continuous control) concerns. In addition, the representation of the high-level decision-making can become unnecessarily complex.As is increasingly common within autonomous systems, we use a hybrid autonomous systems architecture where not only is the discrete decision-making component separated from the continuous control system, but the behaviour of the discrete part is described in much more detail. In particular, the agent paradigm is used [26]. This style of architecture, using the agent paradigm, not only improves the system design from an engineering perspective but also facilitates the system analysis and verification. Indeed, we use this architecture for actually implementing automotive platoons, and we here aim to analyse the system by verification.Safety certification is an inevitable concern in the development of more autonomous road vehicles, and verifying the safety and reli...

A systematic review is provided on artificial agent methodologies applicable to control engineering of autonomous vehicles and robots. The paper focuses on some fundamentals that make a machine autonomous: decision making that involves modelling the environment and forming data abstractions for symbolic processing and logic-based reasoning. Most relevant capabilities such as navigation, autonomous path planning, path following control, and communications, that directly affect decision making, are treated as basic skills of agents. Although many autonomous vehicles have been engineered in the past without using the agentoriented approach, most decision making onboard of vehicles is similar to or can be classified as some kind of agent architecture, even if in a naïve form. First the ANSI standard of intelligent systems is recalled then a summary of the fundamental types of possible agent architectures for autonomous vehicles are presented, starting from reactive, through layered, to advanced architectures in terms of beliefs, goals, and intentions. The review identifies some missing links between computer science results on discrete agents and engineering results of continuous world sensing, actuation, and path planning. In this context design tools for 'abstractions programming' are identified as needed to fill in the gap between logic-based reasoning and sensing. Finally, research is reviewed on autonomous vehicles in water, on the ground, in the air, and in space with comments on their methods of decision making. One of the main conclusions of this review is that standardization of decision making through agent architectures is desirable for the future of intelligent vehicle developments and their legal certification.

We present a verification methodology for analysing the decision-making component in agent-based hybrid systems. Traditionally hybrid automata have been used to both implement and verify such systems, but hybrid automata based modelling, programming and verification techniques scale poorly as the complexity of discrete decision-making increases making them unattractive in situations where complex logical reasoning is required. In the programming of complex systems it has, therefore, become common to separate out logical decision-making into a separate, discrete, component. However, verification techniques have failed to keep pace with this development. We are exploring agent-based logical components and have developed a model checking technique for such components which can then be composed with a separate analysis of the continuous part of the hybrid system. Among other things this allows program model checkers to be used to verify the actual implementation of the decision-making in hybrid autonomous systems.

In this paper, a new universal adaptive control scheme for satellite formation flying is developed. The underlying idea of our design is to combine the domination design and the monotone adaptive gain. This scheme is guaranteed to have the properties of position tracking and full adaptivity against all parameters. Simulation studies are given which establish that implementation of this scheme would not require unachievable actuator signals.

Unmanned aerial vehicles (UAVs) are safety-critical systems that often need to fly near buildings and over people under adverse wind conditions and hence require high manoeuvrability, accuracy, fast response abilities to ensure safety. Under extreme conditions, the dynamics of these systems are strongly nonlinear and are exposed to disturbances, which need a robust controller to keep the UAV and its environment safe. In this paper a novel robust nonlinear multi-rotor controller is introduced based on essential modifications of standard dynamic inversion control, which makes it insensitive to payload changes and also to large wind gusts. First a robust attitude controller is

This paper proposes a new method for guaranteed integration of state equations. Within this framework, the variables of interest are trajectories submitted to both arithmetic and differential equations. The approach consists in formalizing a problem thanks to a constraint network and then apply these constraints to sets of trajectories. The contribution of the paper is to provide a reliable framework to enclose the solutions of these differential equations. Its use is shown to be simple, more general and more competitive than existing approaches dealing with guaranteed integration, especially when applied to mobile robotics. The flexibility of the developed framework allows to deal with non-linear differential equations or even differential inclusions built from datasets, while considering observations of the states of interest. An illustration of this method is given over several examples with mobile robots.

Abstract. Modern control systems are limited in their ability to react flexibly and autonomously to changing situations by the complexity inherent in analysing environments where many variables are present. We aim to use an agent approach to help alleviate this problem and are particularly interested in the control of satellite systems using BDI agent programming as pioneered by the PRS. Such systems need to generate discrete abstractions from continuous data and then use these abstractions in rational decision making. This paper provides an architecture and interaction semantics for an abstraction engine to interact with a hybrid BDI-based control system.

No abstract