Worst-Case Vehicle Evaluation Methodology - Examples on Truck Rollover/Jackknifing and Active Yaw Control Systems

A worst-case vehicle evaluation methodology is presented in this paper. This evaluation method identifies worst-case excitation signals so that the vehicle performance under extreme conditions can be assessed. Two case study examples are presented to illustrate the design procedure and potential benefits of this method: the rollover and jackknifing of an articulated truck, and the evaluation of an active yaw control system. In both cases, the worst-case method was able to produce unstable results at very modest steering/braking levels.     

Worst-Case Vehicle Evaluation Methodology – Examples on Truck Rollover/Jackknifing and Active Yaw Control Systems

A worst-case vehicle evaluation methodology is presented in this paper. This evaluation method identifies worst-case excitation signals so that the vehicle performance under extreme conditions can be assessed. Two case study examples are presented to illustrate the design procedure and potential benefits of this method: the rollover and jackknifing of an articulated truck, and the evaluation of an active yaw control system. In both cases, the worst-case method was able to produce unstable results at very modest steering/braking levels.     

Investigation of automatic path tracking using an extended Kalman filter

This paper proposes a lane marker recognition method that uses the steering angle in addition to image information. A Kalman filter was reconfigured regarding the yaw motion and lateral motion of lane markers, previously treated as a stochastic process, as the states of a vehicle model driven on the basis of the steering angle. Driving tests conducted with an actual vehicle verified that this method provides good tracking at the time of steering input and avoids misrecognition of lane marker candidate points in inclement weather.     

The critical hitch angle for jackknife avoidance during slow backing up of vehicle–trailer systems

We set out to answer the question: At what hitch angle does it become impossible for a vehicle and trailer to continue to backing up without getting into a jackknife? Jackknifing during backing up of trailers occurs when the hitch angle increases to a point such that the vehicle and trailer fold together about the hitch point like a jackknife. If the backward motion is continued, the jackknife effect progressively worsens, until the vehicle and trailer are in physical contact with each other. Jackknifing can result in traffic disruptions and wasted time, and can potentially cause damage or personal injury. Our goal is to analytically determine the ‘critical hitch angle’ (θ_cr), the hitch angle threshold beyond which a continued reverse motion causes an inescapable jackknifing. In this paper, we provide a formal definition of θ_cr for slow backing up of vehicle–trailer systems on a level solid surface, beyond which the vehicle must stop backing up and revert to forward motion in order to escape from jackknifing. The critical hitch angle is sub-categorised into Absolute (θ_cr, a) and Directional (θ_cr, d) critical hitch angles depending on the operating constraints and vehicle steering objectives. One solution for θ_cr is posed as a numerical solution to the steady-state conditions of the dynamic equations. The effects of such hitch angle limitations are demonstrated through simulation. Also, a warning system making use of the θ_cr is proposed. Such warning systems can assist drivers in avoiding jackknifing while backing up a vehicle–trailer system.     

Robust yaw stability control for electric vehicles based on active front steering control through a steer-by-wire system

A robust yaw stability control design based on active front steering control is proposed for in-wheel-motored electric vehicles with a Steer-by-Wire (SbW) system. The proposed control system consists of an inner-loop controller (referred to in this paper as the steering angle-disturbance observer (SA-DOB), which rejects an input steering disturbance by feeding a compensation steering angle) and an outer-loop tracking controller (i.e., a PI-type tracking controller) to achieve control performance and stability. Because the model uncertainties, which include unmodeled high frequency dynamics and parameter variations, occur in a wide range of driving situations, a robust control design method is applied to the control system to simultaneously guarantee robust stability and robust performance of the control system. The proposed control algorithm was implemented in a CaSim model, which was designed to describe actual in-wheel-motored electric vehicles. The control performances of the proposed yaw stability control system are verified through computer simulations and experimental results using an experimental electric vehicle.     

An Emergency Obstacle Avoidance Control Strategy for Automated Highway Vehicles

Summary This paper presents an emergency obstacle avoidance control strategy that may be used in automated highway vehicles. In the proposed control strategy, an inverse vehicle dynamics problem is solved on the selected emergency lane-change path to find out the nominal feedforward control inputs such as the steering wheel angle and the braking force. Then the overall vehicle lateral and yaw motion is controlled additionally in the feedback path by an active yaw moment for stability augmentation as well as a corrective steering angle that is added to the nominal steering angle in order to compensate for uncertainties involved in the nominal control input computation. The proposed control strategy has been tested by an ABS Hardware-In-the-Loop Simulation (HILS) system for rapid and safe control prototyping in a lab. Simulation results with a sample emergency avoidance distance (45 m) show that the proposed control strategy may be used as a feasible obstacle avoidance strategy for automated highway vehicles.     

An Emergency Obstacle Avoidance Control Strategy for Automated Highway Vehicles

Summary This paper presents an emergency obstacle avoidance control strategy that may be used in automated highway vehicles. In the proposed control strategy, an inverse vehicle dynamics problem is solved on the selected emergency lane-change path to find out the nominal feedforward control inputs such as the steering wheel angle and the braking force. Then the overall vehicle lateral and yaw motion is controlled additionally in the feedback path by an active yaw moment for stability augmentation as well as a corrective steering angle that is added to the nominal steering angle in order to compensate for uncertainties involved in the nominal control input computation. The proposed control strategy has been tested by an ABS Hardware-In-the-Loop Simulation (HILS) system for rapid and safe control prototyping in a lab. Simulation results with a sample emergency avoidance distance (45 m) show that the proposed control strategy may be used as a feasible obstacle avoidance strategy for automated highway vehicles.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

Vehicle Handling Improvement by Active Steering

Summary This paper first analyses some stability aspects of vehicle lateral motion, then a coprime factors and linear fractional transformations (LFT) based feedforward and feedback H 8 control for vehicle handling improvement is presented. The control synthesis procedure uses a linear vehicle model which includes the yaw motion and disturbance input with speed and road adhesion variations. The synthesis procedure allows the separate processing of the driver reference signal and robust stabilization problem or disturbance rejection. The control action is applied as an additional steering angle, by combination of the driver input and feedback of the yaw rate. The synthesized controller is tested for different speeds and road conditions on a nonlinear model in both disturbance rejection and driver imposed yaw reference tracking maneuvers.     

Vehicle Handling Improvement by Active Steering

Summary This paper first analyses some stability aspects of vehicle lateral motion, then a coprime factors and linear fractional transformations (LFT) based feedforward and feedback H 8 control for vehicle handling improvement is presented. The control synthesis procedure uses a linear vehicle model which includes the yaw motion and disturbance input with speed and road adhesion variations. The synthesis procedure allows the separate processing of the driver reference signal and robust stabilization problem or disturbance rejection. The control action is applied as an additional steering angle, by combination of the driver input and feedback of the yaw rate. The synthesized controller is tested for different speeds and road conditions on a nonlinear model in both disturbance rejection and driver imposed yaw reference tracking maneuvers.     

基于变权重系数的分布式驱动无人车轨迹跟踪

为了提高分布式无人车轨迹跟踪的精度，提出了基于自主与差动协调转向控制的轨迹跟踪方法。首先，在车辆三自由度模型基础上，基于模型预测控制（MPC）实时计算前轮转角以控制车辆进行自主转向轨迹跟踪。在此过程中，为了提高自主转向下车辆的轨迹跟踪精度与行驶的稳定性，考虑多种因素，利用经验公式及神经网络控制对MPC的预瞄步数和预瞄步长进行多参数调整，实现预瞄时间的自适应控制。其次，在恒转矩需求的情况下，以轨迹偏差为PID控制器的输入及左右轮毂电机转矩为输出进行差动转向控制，实现了差动转向下的轨迹跟踪控制。然后，通过设置权重系数的方法将自主与差动转向相结合。考虑到车辆横纵向动力学因素，采用模糊控制及经验公式对权重系数进行了调整，从而在提高车辆转向灵活性与轨迹跟踪效果的同时保证车辆行驶的稳定性。CarSim与Simulink联合仿真以及实车试验结果表明：与自主转向轨迹跟踪相比，采用变权重系数的协调控制可以在不同的工况下提高车辆的转向灵活性与轨迹跟踪的精度，轨迹跟踪偏差的均方根值改善率达到了11%。所提出的协调转向控制方法可为分布式驱动车辆转向灵活性的提高及轨迹跟踪精度的改善提供一种新的思路。     

A lateral driver model for vehicle–driver closed-loop simulation at the limits of handling

This paper presents a lateral driver model for vehicle–driver closed-loop simulation at the limits of handling. An appropriate driver model can be used to evaluate the performance of vehicle chassis control systems via computer simulations before vehicle tests which incurs expenses especially at the limits of handling. The driver model consists of two parts. The first part is an upper-level controller employing force-based approach to reduce the number of unknown vehicle parameters. The feedforward part of the upper controller has been designed by using the centre of percussion. The feedback part aims to minimise ‘tangential error’, defined as the sum of body slip angle and yaw error, to match vehicle direction and road heading angle. The part is designed to regenerate an appropriate skid motion similar to that of a professional driver at the limits. The second part is a lower-level controller which converts the desired front lateral force to steering wheel angle. The lower-level controller also consists of feedforward and feedback parts. A two-degree-of-freedom bicycle model-based feedforward part provides nominal steering wheel angle, and the feedback part aims to eliminate unmodelled error. The performance of the lateral driver model has been investigated via computer simulations. It has been shown that the steering behaviours of the proposed driver model are quite close to those of a professional driver at the limits. Compared with the previously developed lateral driver models, the proposed lateral driver model shows good tracking performance at the limits of handling.     

基于MPC的分布式驱动越野车辆原地转向控制研究

针对轮毂电机分布式驱动越野车辆在狭小空间快速机动的需求,设计了一种分层结构的原地转向控制策略。基于动力学原理分析了各轮载荷、附着条件对原地转向横摆速度的影响机理,并搭建原地转向运动学模型,上层采用模型预测控制算法设计原地转向理想轨迹以及期望的横摆角速度,开发基于PI滑模控制的横摆运动跟踪算法,通过补偿转向横摆力矩以提高方向角控制的鲁棒性和稳定性,下层以最优轮胎利用率为目标,设计二次规划算法优化分配各轮附加横摆力矩。dSPACE硬件在环测试结果表明,所提出的控制算法可在保证稳定性的前提下实现原地转向,大幅提高了车辆的转向机动性,在方向盘动态输入仿真中,车辆最大转弯半径为0.157 m,转向中心的最大偏移量为3.610 m;同时,驾驶员能对转向过程进行闭环控制,实现了原地转向过程中横摆速度的实时调节。     

Nonlinear optimal integrated vehicle control using individual braking torque and steering angle with on-line control allocation by using state-dependent Riccati equation technique

This paper proposes the solution of state-dependent Riccati equation as a nonlinear optimal regulator to stabilise the motion dynamics of the vehicle model subjected to sudden disturbance inputs in the lateral direction. The proposed nonlinear regulator coordinates individually actuated wheel braking torque and steering wheel angle simultaneously in an optimal manner. Performance criteria are satisfied by solving the Riccati equation based on the given cost function subjected to the nonlinear vehicle dynamics. On-line control allocation in terms of optimal brake torque distribution enhanced by optimal wheel steering angle input is achieved. Furthermore, the proposed optimal nonlinear regulator is an active fault-tolerant control system against partial by-wire actuator failures while guaranteeing stability with good performance due to its capability to allocate the individual control inputs in an optimal way. The main aim is to stabilise the motion dynamics of the vehicle model during short-term emergency situations along the desired straight trajectory manageable by average drivers and to provide vehicle stability and handling predictability through the interaction of individual wheel braking and steering actuators. Simulation results are used to illustrate the effectiveness of the proposed methodology.     

MPC-BASED steering control for backward-driving vehicle using stereo vision

We propose a steering control algorithm for autonomous backward driving in a narrow corridor. Passable spaces are detected using a stereo camera, and the steering angle is controlled by a model predictive controller (MPC). For passable space detection, an UV-disparity map is calculated from the original disparity map. Information regarding passable spaces collected by the stereo camera is used in steering control. Backward driving requires the driver’s preemptive actions, which can be learned by experience because of the non-intuitive responses (the initial motion of the vehicle is opposite to the driver’s steering angle input). This occurs because a backward-driving vehicle is a non-minimum phase system. One of the most popular steering control algorithms is Stanley method, which is based on the feedback of lateral displacement error and heading angle error. The method is very intuitive and works well for forward driving, but it exhibits significant undershoot for backward driving cases. Furthermore, the method does not explicitly consider any constraints on control inputs and states. We designed a steering controller based on the MPC technique that requires future information but can handle constraints explicitly. Because we have near-future information from the stereo camera under limited passable spaces, MPC can be effectively implemented. We performed several simulations and experiments to show the performance and superiority of the suggested method over a simple feedback-based control algorithm.     

Yaw rate and side-slip control considering vehicle longitudinal dynamics

Most conventional vehicle stability controllers operate on the basis of many simplifying assumptions, such as a small steering wheel angle, constant longitudinal velocity and a small side-slip angle. This paper presents a new approach for controlling the yaw rate and side-slip of a vehicle without neglecting its longitudinal dynamics and without making simplifying assumptions about its motion. A sliding-mode controller is used to develop a differential braking controller for tracking a desired vehicle yaw rate for a given steering wheel angle, while keeping the vehicle’s side-slip angle as small as possible. The trade-off that exists between yaw rate and side-slip control is described. Conventional and proposed algorithms are presented, and the effectiveness of the proposed controller is investigated using a seven-degree-of-freedom vehicle dynamics model. The simulation results demonstrate that the proposed controller is more effective than the conventional one.     

Mazda6轿车转向传感器信号的simulink识别

转向传感器信号是车辆控制系统的重要输入信号,但转向传感器的输出不是直接给出转向角大小而是方波信号。为了探究转向传感器原理以及Mazda6轿车实际转向过程中转向传感器信号,本文将介绍如何用simulink来识别该方波信号,输出转向角,最后用该方法识别出实际转向过程的转向角大小。     

Comprehensive lateral driver model for critical maneuvering conditions

A new comprehensive driver model is presented for critical maneuvering conditions with more accurate dynamic control performance. In order to achieve a safe maneuvering mode, a new path planning scheme to maintain stability of the vehicle was designed. A new steering strategy, considering the errors of vehicle position and yaw angle between the real track and the planned path, was established to obtain the steering angle. Therefore, the vehicle can be adjusted to accurately follow the desired path with the driver model, and the stability of the vehicle and the smoothness of the steering angle input were comprehensively considered. Simulation results were used to validate the control performance in comparison with the optimal preview driver model proposed by Macadam.     

Effects of model response on model following type of combined lateral force and yaw moment control performance for active vehicle handling safety

This paper presents a comparison study of the effect of model response on the performance of the model following type combined lateral force and yaw moment control. The combined controls aim to maximize stability limit as well as vehicle responsiveness. In order to realize this aim, two types of model responses are proposed to introduce the required lateral force and yaw moment control. The model responses (a) is the side-slip angle and yaw rate vehicle response of the two degree of freedom vehicle motion (bicycle model). The model responses (b) is an intentional modification from the model responses (a) to the side slip angle converging to zero and first order yaw rate. Three different cases of combining lateral force and yaw moment control have been investigated using the two types of model responses. The effect of model responses is proved by computer simulations of the vehicle response to a single sine wave steering input with braking for the combined control methods proposed. It is found that the influence of the model response has a significant effect on the combined control performance.