Abstract-This paper presents a driving simulation which aim is twofold: (i) investigate the possibility to reduce motion clearance in order to achieve compact and low cost driving simulators, and (ii) evaluate multimodal and immersive virtual reality motion restitution in platooning driving. The choice has been made for a driving simulator having at least two degrees of freedom. These consist of the longitudinal displacement and seat rotations. The simulator is also equipped with force feedback steering wheel for virtual drive assistance. These components are gathered on a serial kinematics type platform in order to facilitate control scheme, and avoid the architecture complexity. A comparative study was made to devise a motion cueing strategy, taking into account both psychophysical and technological constraints. Experimentations were carried out for several cases combinations of longitudinal displacement and seat rotations.
Abstract-This paper presents the various stages for the construction of a two wheeled riding simulator. Despite its simplicity, the particularity of this simulator comes from the possibility to reproduce most of the movements and the inertial effects allowing to perceive sensations close to reality cases. This simulator has been developed for two purposes:• as a training tool for new riders with different scenarios: normal traffic environment, dangerous riding situations (avoidance, emergency braking, nearly failling or slipping situations, bad weather conditions, etc.) • to study riders behaviours in such situations Our studies have lead to an original 5 degrees of freedom (DOF) mechanical platform including a double haptic feedback on the handlebar. The three basic movements are classical and consist of pitch, roll and yaw one. The choices of the platform movements and the system actuation are motivated and described. Also, some performances results are shown validating the initial requirements.
Abstract-This paper deals with motion control problem for a 2 DOF small driving simulator. The main idea is to test and compare performances of different Washout Algorithms applied to such platform category. The experimentations allow us to have the best compromise between quality of the perception (sensation), implementation complexity and platform architecture.Implementation of different Washout Algorithms (optimal, adaptive and classical one) will be discussed. Only the longitudinal restitution will be studied. The results show that there is not significant differences between these approaches using with platform type. The lack of pitch DOF in our simulator does not allow a restitution of the sustained acceleration and no coordination between longitudinal and pitch channels may be done.
In this paper, a nonlinear observer is designed in order to estimate the lateral dynamics of motorcycles. A nonlinear model of motorcycle's lateral dynamics is considered and is transformed in a Takagi-Sugeno (TS) exact form. An unknown input (UI) nonlinear observer is then designed in order to reconstruct the state variables whatever the forward velocity variations. The observer convergence study is based on the Lyapunov theory. The boundedness of the state estimation error is guaranteed thanks to the Input to State Stability (ISS) property. The observer has been tested on a nonlinear multibody model.
This paper presents an image-based approach to simultaneously estimate the lateral position of a powered-two wheeled vehicle on the road, its steering behavior and predict the road curvature ahead of the motorcycle. This work is based on the inverse perspective mapping technique combined with a road lanes detection algorithm capable of detecting straight and curved lanes. Then, a clothoid model is used to extract pertinent information from the detected road markers. Finally, the performance of the proposed approach is illustrated through simulations carried out with the well-known motorcycle simulator "BikeSim". The results are very promising since the algorithm is capable of estimating, in real time, the road geometry and the vehicle location with a better accuracy than the one given by the commercial GPS.
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