Vehicle dynamics

About: Vehicle dynamics is a research topic. Over the lifetime, 12909 publications have been published within this topic receiving 204091 citations.

Path planning in time dependent flow fields using level set methods

Abstract: We develop and illustrate an efficient but rigorous methodology that predicts the time-optimal paths of ocean vehicles in continuous dynamic flows. The goal is to best utilize or avoid currents, without limitation on these currents or on the number of vehicles. The methodology employs a new modified level set equation to evolve a front from the starting point of a vehicle until it reaches the desired goal location, combining flow advection with nominal vehicle motion. The optimal path of the vehicle is then obtained by solving a particle tracking equation backward in time. The computational cost of this method increases linearly with the number of vehicles and geometrically with spatial dimensions. The methodology is applicable to any continuous flow and in scenarios with multiple vehicles. Present illustrations consist of the crossing of a canonical uniform jet and its validation using a classic optimization solution, as well as swarm formation in more complex time varying 2D flow fields, including jets, eddies and forbidden regions.

Crash Mitigation in Motion Planning for Autonomous Vehicles

Abstract: A motion planning method for autonomous vehicles confronting emergency situations where collision is inevitable, generating a path to mitigate the crash as much as possible, is proposed in this paper. The Model predictive control (MPC) algorithm is adopted here for motion planning. If avoidance is impossible for the model predictive motion planning system, the potential crash severity, and artificial potential field are filled into the controller objective to achieve general obstacle avoidance and the lowest crash severity. Furthermore, the vehicle dynamic is also considered as an optimal control problem. Based on the analysis mentioned earlier, the model predictive controller can optimize the command following, obstacle avoidance, vehicle dynamics, road regulation, and mitigate the inevitable crash based on the predicted values. The proposed MPC algorithm has been proved by simulation to have the ability to avoid obstacles and mitigate the crash if collision is inevitable.

Vehicle Stability Enhancement of Four-Wheel-Drive Hybrid Electric Vehicle Using Rear Motor Control

Abstract: A vehicle stability enhancement control algorithm for a four-wheel-drive hybrid electric vehicle (HEV) is proposed using rear motor driving, regenerative braking control, and electrohydraulic brake (EHB) control. A fuzzy-rule-based control algorithm is proposed, which generates the direct yaw moment to compensate for the errors of the sideslip angle and yaw rate. Performance of the vehicle stability control algorithm is evaluated using ADAMS and MATLAB Simulink cosimulations. HEV chassis elements such as the tires, suspension system, and steering system are modeled to describe the vehicle's dynamic behavior in more detail using ADAMS, whereas HEV power train elements such as the engine, motor, battery, and transmission are modeled using MATLAB Simulink with the control algorithm. It is found from the simulation results that the driving and regenerative braking at the rear motor is able to provide improved stability. In addition, better performance can be achieved by applying the driving and regenerative braking control, as well as EHB control.

Vehicle Yaw Control via Second-Order Sliding-Mode Technique

Abstract: The problem of vehicle yaw control is addressed in this paper using an active differential and yaw rate feedback. A reference generator, designed to improve vehicle handling, provides the desired yaw rate value to be achieved by the closed loop controller. The latter is designed using the second-order sliding mode (SOSM) methodology to guarantee robust stability in front of disturbances and model uncertainties, which are typical of the automotive context. A feedforward control contribution is also employed to enhance the transient system response. The control derivative is constructed as a discontinuous signal, attaining an SOSM on a suitably selected sliding manifold. Thus, the actual control input results in being continuous, as it is needed in the considered context. Simulations performed using a realistic nonlinear model of the considered vehicle show the effectiveness of the proposed approach.

Combined Path-following and Obstacle Avoidance Control of a Wheeled Robot

Abstract: This paper proposes an algorithm that drives a unicycle type robot to a desired path, including obstacle avoidance capabilities. The path-following control design relies on Lyapunov theory, backstepping techniques and deals explicitly with vehicle dynamics. Furthermore, it overcomes the initial condition constraints present in a number of path-following control strategies described in the literature. This is done by controlling explicitly the rate of progression of a “virtual target” to be tracked along the path; thus bypassing the problems that arise when the position of the path target point is simply defined as the closest point on the path. The obstacle avoidance part uses the Deformable Virtual Zone (DVZ) principle. This principle defines a safety zone around the vehicle in which the presence of an obstacle induces an “intrusion of information” that drives the vehicle reaction. The overall algorithm is combined with a guidance solution that embeds the path-following requirements in a desired intrusion information function, which steers the vehicle to the desired path while the DVZ ensures minimal contact with the obstacle, implicitly bypassing it. Simulation and experimental results illustrate the performance of the control system proposed.