Lamri Nehaoua

Bio: Lamri Nehaoua is an academic researcher from University of Évry Val d'Essonne. The author has contributed to research in topics: Observer (quantum physics) & Vehicle dynamics. The author has an hindex of 14, co-authored 46 publications receiving 498 citations. Previous affiliations of Lamri Nehaoua include Centre national de la recherche scientifique.

Design and Control of a Small-Clearance Driving Simulator

Abstract: This paper presents a driving simulation whose aim is twofold: (1) to investigate the possibility of reducing motion clearance to achieve compact and low-cost driving simulators and (2) to 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 (DOF) These consist of the longitudinal displacement and seat rotations The simulator is also equipped with a force feedback steering wheel for virtual drive assistance These components are gathered on a serial kinematics-type platform to facilitate a control scheme and avoid the architecture complexity A comparative study was made to devise a motion cueing strategy, taking into account both the psychophysical and technological constraints Experimentations were carried out for several case combinations of the longitudinal displacement and seat rotations

Motion cueing algorithms for small driving simulator

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) are discussed. Only the longitudinal restitution is 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

Mechatronics, Design, and Modeling of a Motorcycle Riding Simulator

Abstract: This paper describes a new motorcycle riding simulator whose purpose is twofold: 1) it can be used as a training tool for new riders in different scenarios, such as a normal traffic environments or in dangerous riding situations (avoidance, emergency braking, nearly failing or slipping situations, and bad weather conditions) and 2) it can be used to study motor cyclist behavior in such situations and rider-motorcycle interaction. Our studies have led to the development of an original five DOF mechanical platform including double haptic feedback on the handlebar. The remaining components are the basic movements consisting of pitch, roll, and yaw. These components are gathered in a parallel kinematics-type platform to enhance the movement bandwidth of the two-wheeled riding simulator. Despite its simplicity, the particular appeal of this simulator lies in the possibility of reproducing important motorcycle movements and inertial effects, which allow for the perception of sensations close to reality. The motivation behind the choice of platform movements and system actuation are described. Also, theoretical issues (modeling, identification, and control aspects) and performance results are provided.

Classic and Adaptive Washout Comparison for a Low Cost Driving Simulator

Abstract: The paper deals with control of small driving simulator SIM comparing the useless of adaptive and classic approaches. Driving simulators are considering as an interactive virtual reality tools, which take a considerable place in the human factors studies. The difficulty to reproduce in reality some drive situations mainly for risk and reproducibility reasons increases the interest of this tool. Nevertheless, the validation of the experiments carried out on driving simulator is closely related to embedding realism of the driver in the simulated world. In this article, we present the design of a low cost and small motion platform, which allow the restitution of 2 DOF movements. This overall system is considered as two independent systems linked mechanically. The first system consists in motorized rail for the longitudinal movement while the second system consists in motorized seat allowing either pitch movement of this one or just back seat inclination (this case would not be discussed in the rest of paper)

From Design to Experiments of a 2-DOF Vehicle Driving Simulator

Abstract: Driving simulators are increasingly being used for driver evaluation and/or education. In this paper, we describe the design and the modeling aspects of a 2-degree-of-freedom (2-DOF) low-cost motion platform allowing the rendering of the longitudinal and yaw movements. This prototype will be used to study various configurations of motion rendering and the impact of these variants on controllability and simulator sickness. The whole motion platform is considered as two coupled systems that are linked mechanically. The first system consists of a motorized rail for the longitudinal movement, which is mounted on top of the second system, which is a motorized turret allowing rotation of the platform. We present the platform mechanics and a number of experimental studies that have been carried out to obtain a characterization of the platform capabilities and frequency responses, as well as to assess platform performance in a classical drive operation. First conclusions and directions of future work are presented.

Mechatronics기술개발 현황과 과제

Abstract: Mechatronics Technology is a growing career field that deals with the integration of mechanical and electronic components managed by control systems. Mechatronics technicians troubleshoot, maintain and repair mechanical equipment controlled by electrical, electronic and computer systems. These types of systems are increasingly used in a wide variety of manufacturing and industrial settings. Clark College's Mechatronics Technology (MTX) classes emphasize current concepts and technology by providing practical, hands-on experiences with the latest, industry standard equipment. In addition to the technical knowhow needed to maintain and repair equipment, the certificate and degree programs will help prepare students to think critically, function as a successful team member and communicate clearly too internal and external customers.

Combined longitudinal and lateral control for automated vehicle guidance

Abstract: This paper deals with the longitudinal and lateral control of an automotive vehicle within the framework of fully automated guidance. The automotive vehicle is a complex system characterised by highly nonlinear longitudinal and lateral coupled dynamics. Consequently, automated guidance must be simultaneously performed with longitudinal and lateral control. This work presents an automated steering strategy based on nonlinear model predictive control. A nonlinear longitudinal control strategy considering powertrain dynamics is also proposed to cope with the longitudinal speed tracking problem. Finally, a simultaneous longitudinal and lateral control strategy helps to improve the combined control performance. This whole control strategy is tested through simulations showing the effectiveness of the present approach.

Enhancing Localization Accuracy of MEMS-INS/GPS/In-Vehicle Sensors Integration During GPS Outages

Abstract: In this paper, we propose a novel localization methodology to enhance the accuracy from two aspects, i.e., adapting to the uncertain noise of microelectromechanical system-based inertial navigation system (MEMS-INS) and accurately predicting INS errors. First, an interacting multiple model (IMM)-based sequential two-stage Kalman filter is proposed to fuse the information of MEMS-INS, global positioning system (GPS), and in-vehicle sensors. Three bias filters are built with different covariance matrices to cover a wide range of noise characteristics. Then, IMM algorithm provides a soft switching among the three bias filters to adapt to the uncertain noise of MEMS-INS. Further, an elaborate predictor is developed to accurately predict INS errors during GPS outages. The elaborate predictor comprises an online trained autoregressive integrated moving average (ARIMA) model and an offline trained extreme learning machine (ELM) model. The ARIMA model is designed to predict the basic accumulation process of INS errors, while the ELM model is designed to correct the errors caused by the changes of noise characteristics. Thus, the INS errors can be properly compensated when GPS observations are not available. In all, the proposed localization methodology can achieve accurate performance when facing uncertain noises of MEMS-INS and GPS outages simultaneously. To verify the effectiveness of the proposed methodology, road test experiments with various driving scenarios were performed. The experimental results illustrate the feasibility and effectiveness of the proposed methodology.

Robust Optimal Motion Cueing Algorithm Based on the Linear Quadratic Regulator Method and a Genetic Algorithm

Abstract: The aim of this paper is to design and develop an optimal motion cueing algorithm (MCA) based on the genetic algorithm (GA) that can generate high-fidelity motions within the motion simulator’s physical limitations. Both, angular velocity and linear acceleration are adopted as the inputs to the MCA for producing the higher order optimal washout filter. The linear quadratic regulator (LQR) method is used to constrain the human perception error between the real and simulated driving tasks. To develop the optimal MCA, the latest mathematical models of the vestibular system and simulator motion are taken into account. A reference frame with the center of rotation at the driver’s head to eliminate false motion cues caused by rotation of the simulator to the translational motion of the driver’s head as well as to reduce the workspace displacement is employed. To improve the developed LQR-based optimal MCA, a new strategy based on optimal control theory and the GA is devised. The objective is to reproduce a signal that can follow closely the reference signal and avoid false motion cues by adjusting the parameters from the obtained LQR-based optimal washout filter. This is achieved by taking a series of factors into account, which include the vestibular sensation error between the real and simulated cases, the main dynamic limitations, the human threshold limiter in tilt coordination, the cross correlation coefficient, and the human sensation error fluctuation. It is worth pointing out that other related investigations in the literature normally do not consider the effects of these factors. The proposed optimized MCA based on the GA is implemented using the MATLAB/Simulink software. The results show the effectiveness of the proposed GA-based method in enhancing human sensation, maximizing the reference shape tracking, and reducing the workspace usage.