Figure 2 - uploaded by Benoit Thuilot
Content may be subject to copyright.
Source publication
In this paper, an algorithm dedicated to light ATVs, which estimates and anticipates the rollover, is proposed. It is based on the on-line estimation of the Lateral Load Transfer (LLT), allowing the evaluation of dynamic instabilities. The LLT is computed thanks to a dynamical model split into two 2D projections. Relying on this representation and...
Context in source publication
Similar publications
We consider the credit risk transfer market, where several financial agents interact with each other and generate complex nonlinear relations. All these market participants are defaultable and when one of them defaults, the credit risk contagion can be described by a nonlinear dynamic problem. We propose a particular time delay Susceptible–Infected...
Citations
... In this context, military vehicles should incorporate technological innovations slowly, as has happened with commercial and passenger vehicles. Recent studies have shown a tendency to solutions of this type [4,5,6,7,8], and will be analyzed in more detail on the next sections. ...
... Taking into account that in this work we will consider only situations where no longitudinal acceleration is applied to the vehicle, we can observe that , therefore , from where one could conclude that (7) The forces , and are calculated in a similar way from that presented in [4], with the cornering stiffness , and of the tires, by the expression , (8) where , and are the angles between the longitudinal axis of the tires on the front, intermediary and rear axis and their velocity vectors. Therefore it can be said that , (9) where , (10) and the angles , and are approximated by ...
Semi-autonomous control systems applied to automobiles are Advanced Driver Assistance Systems (ADAS) that have gained importance from similar devices with applications in robotics. The control sharing between humans and automatic controllers is the main characteristic of these systems, and can be accomplished through various different manners. However, the use of Artificial Intelligence (AI) techniques for this purpose remains unexplored. In this paper we propose the design of a semi-autonomous control system applied to military vehicles through the use of Fuzzy Inference Systems for the definition of the controller intervention level. Simulations of a vehicle being operated in highly dangerous situations, represented by the existence of hostile military threats or by unexpected maneuvers that could put the stability of the car at risk were performed. The control system’s level of intervention during the simulations was observed, and we could realize the increase of this variable according to the level of threat that the car was exposed
to. The application of the proposed system results in safer operation of the vehicle, which shall be controlled with greater influence of the automatic controller when in greater danger. We present a critical analysis of these results and new directions for the future of this work.
... While it has been considered that the unmanned military ground vehicles will be the main weapon of the armies in the XXI century (as stated in [2]), it is likely that this evolution may take place gradually, so that the military vehicles shall incorporate technological innovations of driver assistance slowly, as it have been happening with the passenger and commercial cars. Recent studies have shown a tendency to solutions of this type ( [3], [4], [5], [6] and [7]), and will be analyzed in more detail on the next sections. ...
All over the world traffic accidents are a major concern for society. According to studies carried by the World Health Organization, approximately 1.24 million people died in car accidents only in 2010. The decade 2011-2020 was declared the "Decade of Action for Road Safety" by the UN, which evidences this preoccupation. Accidents involving vehicles are mostly caused by drivers who have poorly controlled their vehicles. When it comes to military vehicles, the risks are amplified due to the threats they are exposed to (improvised explosives, anti-tank weapons, etc.), and also the unstructured environment in which they are employed. It is therefore clear that new technologies can be used in order to reduce these risks, with the development of vehicular applications for that. In this paper we propose a semi-autonomous control system capable of providing assistance to the driver by correcting or canceling risky performance in a military vehicle. In this system, the driver's behavior, the presence of external threats and the vehicle’s tendency to evolve to instability are treated as inputs and processed through Artificial Intelligence techniques (Artificial Neural Networks and Fuzzy Logic), resulting in the weighting of control inputs from the driver and from an automatic controller, trying to keep the vehicle under safe operating conditions.
