![]() Scientific evidence indicates that realistic and dynamic training using simulators improves the user’s decision-making, cognitive functions and, consequently, performance and skill in the on-road driving task. To achieve this, they must introduce stimuli for as many senses as possible: sight, sound, balance, smell, touch, etc. The common link in both cases is that the simulator designer always tries to achieve the maximum level of abstraction of reality for the user. As costs decreased, simulators of all types of vehicles began to emerge: flight, ship, car, truck, and submarine, among many others.Ĭurrently, the use of driving simulators is focused on entertainment and training. It was in the 1960s and 1970s when, with the advent of digital computers, the simulators known as full-motion appeared, which besides recreating a virtual scenario, simulated the accelerations that occurred. ![]() Since then, all the technologies involved with simulators (graphics, audio, projection, motion, steering wheels, sensing) have evolved in an extraordinary way. The first simulators that were created were airplane simulators, developed by the U.S. In recent decades, technological devices and graphics-based simulators with various functionalities have been developed to meet the needs of users. In this sense, adequate training and education of drivers are essential to achieve a real awareness of the dangers of the road and to provide all the tools necessary to prevent traffic accidents. Data indicate that more than 90% of crashes are due to the human factor, as road users commit infractions or engage in risky behaviors with fatal consequences. Governmental entities worldwide develop prevention measures and strategies to reduce road accidents and mitigate the devastating effects of this problem. Road traffic accidents are a global problem with social, economic and public health repercussions. These events are considered by experts to be of vital importance for the outcome of a learning process in the simulator to be adequate. Still, there are three events where the accelerations are lost. The input to the system has been qualitatively compared with the output, observing that most of the simulation adequately reflects the input to the system. ![]() ![]() ![]() This paper shows a case study where a BMW 325Xi AUT fitted with a sensor, recorded the accelerations produced in all degrees of freedom (DOF) during several runs, and data have been introduced in mathematical simulation software (washout + kinematics + actuator simulation) of a 6DOF motion platform. In the use of these MCAs, there is always information that is lost and, if that information is important for the purpose of the simulator (the training simulators), the result obtained by the users of that simulator will not be satisfactory. Despite the time that has passed since their development, most of these algorithms still use the classical washout algorithm. Since it is impossible to reproduce the accelerations of a vehicle without limitations through a physically limited system (platform), it is common to use washout filters and motion cueing algorithms (MCA) to select which accelerations are reproduced and which are not. Motion platforms have been used in simulators of all types for several decades. ![]()
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