Steering Angle Of Front Wheels Research Articles

Parallel auto-parking of a model vehicle using a self-organizing fuzzy controller

The vehicle backward auto-parking process can be divided into three steps. First, the relative position between the Ego car and an available parking space should be detected using additional sensors, and the two-dimensional (2D) environmental map can be constructed. Then, the optimal parking trajectory is planned online based on this 2D environmental map. Finally, the auto-parking controller executes the real-time vehicle motion path estimation and the planned parking trajectory-tracking control. Here, multiple ultrasonic sensors were installed on a model vehicle to construct the 2D map of the area surrounding the vehicle. A sinusoidal function parking trajectory is planned and the corresponding state variable trajectories of the X and Y components and front-wheel steering angle are derived. A model-free intelligent self-organizing fuzzy controller is proposed to track the parking path by regulating the deviation of a selected state variable. The output command is the real-time front-wheel steering angle. This intelligent controller has a system-learning mechanism without expertise knowledge or a trial-and-error process. It is implemented on a one-sixth model vehicle for experimental study. The experimental results are compared with those of a non-linear feedback linearization controller.

An expert fuzzy strategy for vehicle lateral control under urban environments

Under urban environments, vehicle lateral control faces new challenges, such as autonomous driving not only with a small steering angle of front wheel but also with a large one, which has rarely been reported in previous papers. In this paper, an Expert Fuzzy Controller (EFC) with the strategy of two look-ahead points is proposed to gain good control performance in all driving tasks. At the end of the paper, simulation and experiment results are presented to show that the proposed expert fuzzy strategy is accurate and effective for the normal lateral control problem under urban environments.

Vehicle Planar Motion Stability Study for Tyres Working in Extremely Nonlinear Region

Many researches on vehicle planar motion stability focus on two degrees of freedom(2DOF) vehicle model, and only the lateral velocity (or side slip angle) and yaw rate are considered as the state variables. The stability analysis methods, such as phase plane analysis, equilibriums analysis and bifurcation analysis, are all used to draw many classical conclusions. It is concluded from these researches that unbounded growth of the vehicle motion during unstable operation is untrue in reality thus one limitation of the 2DOF model. The fundamental assumption of the 2DOF model is that the longitudinal velocity is treated as a constant, but this is intrinsically incorrect. When tyres work in extremely nonlinear region, the coupling between the vehicle longitudinal and lateral motion becomes significant. For the purpose of solving the above problem, the effect of vehicle longitudinal velocity on the stability of the vehicle planar motion when tyres work in extremely nonlinear region is investigated. To this end, a 3DOF model which introducing the vehicular longitudinal dynamics is proposed and the 3D phase space portrait method is employed for visualization of vehicle dynamics. Through the comparisons of the 2DOF and 3DOF models, it is discovered that the vehicle longitudinal velocity greatly affects the vehicle planar motion, and the vehicle dynamics represented in phase space portrait are fundamentally different from that of the 2DOF model. The vehicle planar motion with different front wheel steering angles is further represented by the corresponding vehicle route, yaw rate and yaw angle. These research results enhance the understanding of the stability of the vehicle system particularly during nonlinear region, and provide the insight into analyzing the attractive region and designing the vehicle stability controller, which will be the topics of future works.

Steering control of six-wheeled vehicles using linear quadratic regulator techniques

The middle- and rear-wheel steering angles of a six-wheeled vehicle need to be coordinated with the front-wheel steering angle to obtain the maximum manoeuvrability. A steering control strategy using the linear quadratic regulator technique with integral control is proposed in this paper such that both zero side-slip angle and target yaw rate following can be achieved simultaneously. An estimator to be used with the control law is also designed to provide the estimate of side-slip angle. AutoSim is used to establish a complex vehicle model with tyre dynamics in MATLAB/Simulink. Both open-loop and closed-loop manoeuvres are performed to evaluate the control performance of the proposed strategy.

STUDY OF DRIVER FACTORS AFFECTING THE DIRECTIONAL RESPONSE OF AN ARTICULATED VEHICLE USING NEURAL NETWORKS

A two-layer neural network with 12 neurons in the first layer is applied to model the directional control behaviour of a driver-articulated vehicle system. Six different training schemes are employed using combinations of input variables related to visual perception of tracking error in terms of position and orientation, and motion perception of the driver. The network is trained using the results derived from a comprehensive closed-loop analytical model under an obstacle avoidance manoeuvre. The input data to the neural network included: the coordinates of the previewed path, lateral position, velocity, and acceleration of the tractor and lateral acceleration of the trailer. The front wheel steer angle was considered as the desired output of the trained network. The effectiveness of the trained network describing the driver behaviour is investigated under different directional maneuvers of varying severity. It is concluded that the neural network can be trained to model the directional control behavior of the driver, while the effectiveness of the trained network depends upon the input variables supplied to train the network. The results show that the visual perception of the driver based on the position error contributes most significantly to the training of the network. The motion perception variables in terms of lateral accelerations of the articulated vehicle yield a more effective neural network model of the driver.

On Inverse Equations for Vehicle Dynamics

Abstract Instead of writing equations which when solved yield the response of a vehicle to an input such as the front wheel steer angle, one can often invert the equations so that a response quantity is specified as an input and a new set of equations is solved yielding the steer angle required as an output. Using these equations one can discover the input steer angle a driver would need to impose in order to accomplish a specific maneuver for various vehicles. It is shown that there are many possible inverse equation sets and that the eigenvalues of the inverse equations are hard to interpret since they may have little to do with the vehicle parameters. The linear single-input single-output case is studied first to fix ideas using a simple example. For the bicycle model vehicle, it is shown that any vehicle may have unstable inverse equations depending upon the response quantity used. Extensions to nonlinear and multiple-input multiple output systems are discussed.

Measurement of Vehicle Handling by Tethered Testing

The technique of tethered testing is introduced as a method of measurement of vehicle steady state handling, where the vehicle under test is attached to a large parent vehicle by means of an arm attached at its centre of gravity, and the tyre forces, which in the normal free vehicle situation produce a centrifugal acceleration, are simply reacted by this arm. The tethered testing rig built at M.I.R.A. is described. It is shown that the concept of tethered testing leads naturally to the idea of describing vehicle steady state handling by means of a quantity which depends only on lateral acceleration, and suitable quantities are shown to be static margin and the slope of a curve of mean front wheel steer angle against vehicle slip angle. These quantities are defined and their derivation in terms of vehicle stability derivatives is outlined in an appendix. Some examples of tethered test measurements are given in the form of plots of static margin against lateral acceleration, and a tentative set of criteria for good steady state handling is given in terms of the behaviour of static margin with lateral acceleration.