An MPC approach to the design of motion cueing algorithms for driving simulators

Abstract

Driving simulators play an important role in the development of new vehicles and advanced driver assistance devices. In fact, on the one hand, having a human driver on a driving simulator allows automotive OEMs to bridge the gap between virtual prototyping and on-road testing during the vehicle development phase. On the other hand, novel driver assistance systems (such as advanced accident avoidance systems) can be safely tested by having the driver operating the vehicle in a virtual, highly realistic environment, while being exposed to hazardous situations. In both applications, it is crucial to faithfully reproduce in the simulator the drivers perception of forces acting on the vehicle and its acceleration. The strategy used to operate the simulator platform within its limited working space to provide the driver with the most realistic perception goes under the name of motion cueing. In this paper we describe a novel approach to motion cueing design that is based on Model Predictive Control techniques. Two features characterize the algorithm, namely, the use of a detailed model of the human vestibular system and a predictive strategy based on the availability of a virtual driver. Differently from classical schemes based on washout filters, such features allows a better implementation of tilt coordination and to handle more efficiently the platform limits

A non-linear MPC based Motion Cueing implementation for a 9 DOFs dynamic simulator platform

“…Model 1) Linear vestibular model: One of the distinctive elements of the adopted approach is the modelling of the human vestibular system, i.e. the dynamics of the set of organs that are responsible for the perception of linear acceleration and angular velocities [3], [4], [5]. Each perceptive degree of freedom is represented by a linear, continuous-time, second order system.…”

“…In [3], [4], [5] a MCA based on a linear MPC technique has been proposed. In that particular setup the system can be split into four sub-systems (due to partial decoupling of DOFs) to "parallelize" the computation of the optimal solution, thus improving real-time performance.…”

Explicit MPC motion cueing algorithm for real-time driving simulator

“…Dagdelen [8], Augusto [9] and Baseggio's [10] studies on implicit MPC algorithm for MCA application are based on online optimization technique. Due to the real-time requirement (step time in milliseconds), this technique could be limited by the predictive horizon time and the iterative number.…”

“…One of the common weaknesses of filter algorithms for LP and HP independent filters' structure is the filter's delay which could influence the numerical model evaluation for some fast maneuvers' tests. Some studies try to use MPC algorithm for MCA applications [8][9][10], considered as a novel motion cueing algorithm. It reveals its advantage of integrating directly with the constraints during its optimization process.…”

MPC-Based Motion Cueing Algorithm for a 6 DOF Driving Simulator with Actuator Constraints

“…The scheme of a typical MPC-based MCA is shown in figure 3. To keep the problem linear, the algorithms designed in the past ( [7,8]) apply the constraints on the position and velocity of the driver's eye-point. In order to find the available workspace for the eye-point displacement, the forward kinematic relations have to be used which is concerned with determining the displacement of the platform given the position of all the actuators.…”