Development of the Lane Keeping Control System Using State-Varying Surface for Vulnerable Road Users

This paper proposes a new Lane Keeping Assist (LKA) system based on the integrated control strategy with AFS and BTV. To be specific, the steering controller calculates the gear ratio of AFS to align with the target lane whereas the braking controller determines differential brake pressure using Sliding Mode Control (SMC) theory according to the state-varying sliding surface with Fuzzy model. In recent years, auto industries have produced the lane keeping applications to prevent lane departure caused by drivers’ distractions or drowsiness. To also prevent wrist injury in drivers while steering, current LKA systems limit the output values of steering-wheel assist torque. This limiting mechanism, however, can cause a problem that cannot follow a road curvature when an older driver overexerts an inappropriate control effort. A new LKA system of the AFS and BTV integrated controller has since been drafted to solve this problem, and validated its performance in regards to the test conditions given with various driver models.     

考虑驾驶人特性的一主多从混合博弈容错控制

为保证线控底盘电动汽车在遭遇执行器失效时的稳定性，并考虑人-车交互行为，提出了以驾驶人为领导者的一主多从（Single-leader-multiple-follower，SLMF）混合博弈容错控制框架。为实现驾驶人-车辆的交互控制，首先建立了两者的耦合模型。其次，将驾驶人及5个底盘子系统即主动前轮转向（Active Front Steering，AFS）系统和4个轮毂电机建模为博弈中的6个参与者，基于Stackelberg主从博弈与多人合作博弈设计了SLMF混合博弈控制框架。考虑驾驶人具有优先控制权限及执行器对驾驶人行为的补偿作用，基于Stackelberg博弈理论建立了驾驶人与底盘子系统的主从博弈模型，其中驾驶人作为领导者通过感知跟随者的行为做出转向决策，而5个底盘子系统被建模为跟随者。由于跟随者追求共同的横向稳定控制目标，因此基于合作博弈理论建立了合作模型，并对领导者的转向策略做出最优响应。最后，为研究跟随者之间追求不同目标导致不合作时的控制效果，设计了非合作Nash博弈与Stackelberg博弈相结合的混合博弈为对比方法，通过实时硬件在环测试验证并对比了2种方法。结果表明：针对不同风格的驾驶人，所设计的方法可以保证遭遇执行器卡死失效车辆的稳定性。与不合作的情况相比，2种不同风格的驾驶人驾驶的车辆在底盘子系统合作时，车辆稳定性分别提升了54.62%和53.78%，驾驶人工作负荷分别降低了31.79%和36.07%。     

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.     

电动转向器中助力控制器的研究

从研究探讨助力特性曲线出发,确定了电动转向器(Electronic Power Steering,简称EPS)的助力特性曲线,设计了助力控制器以达到电动助力转向的控制目标,通过仿真和分析的结果表明,加入助力控制器的电动转向器系统提高了转向的轻便性和平稳性。     

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.     

Optimal preview game theory approach to vehicle stability controller design

Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.     

Active front wheel steering model and controller for integrated dynamics control systems

We report a model and controller for an active front-wheel steering (AFS) system. Two integrated dynamics control (IDC) systems are designed to investigate the performance of the AFS system when integrated with braking and steering systems. An 8-degrees-of-freedom vehicle model was employed to test the controllers. The controllers were inspected and compared under different driving and road conditions, with and without braking input, and with and without steering input. The results show that the AFS system performs kinematic steering assistance function and kinematic stabilisation function very well. Three controllers allowed the yaw rate to accurately follow a reference yaw rate, improving the lateral stability. The two IDC systems improved the lateral stability and vehicle control and were effective in reducing the sideslip angle.     

Additional 4WS and Driver Interaction

This investigation is based on a complex 4-wheel vehicle model of a passenger car that includes steering system and drive train. The tyre properties are described for all possible combined longitudinal and lateral slip values and for arbitrary friction conditions. The active part is an additional steering system of all 4 wheels, additionally to the driver's steering wheel angle input. Three control levels are used for the driver model that thereby can follow a given trajectory or avoid an obstacle.

The feedback control of the additional 4 wheel steering is based on an observer which can also have adaptive characteristics. Moreover a virtual vehicle model in a feedforward scheme can provide desired steering characteristics.

To get information for critical situations a cornering manoeuvre with sudden u-split conditions is simulated. Further a similar manoeuvre is used to evaluate the reentry in a high friction area from low friction conditions. And finally the performance of the controller is shown in a severe lane change manoeuvre.     

Using µ Feedforward for Vehicle Stability Enhancement

A differential braking control strategy using yaw rate feedback, coupled with µ feedforward is introduced for a vehicle cornering on different µ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input. It is shown that knowledge of µ offers significant improvement of the vehicle desired trajectory over that of a yaw rate controller alone. Uncertainties and time delay in estimating µ are shown to still yield a system that is superior to using no µ information at all.     

Model-based design of a variable nozzle turbocharger controller

Variable Nozzle Turbocharger (VNT) was invented to solve the problem of matching an ordinary turbocharger with an engine. VNT can harness exhaust energy more efficiently, enhance intake airflow response and reduce engine emissions, especially during transient operating conditions. The difficulty of VNT control lies in how to regulate the position of the nozzle at different engine working conditions. The control strategy designed in this study is a combination of a closed-loop feedback controller and an open-loop feed-forward controller. The gain-scheduled proportional-integral-derivative (PID) controller was implemented as the feedback controller to overcome the nonlinear characteristic. As it is difficult to tune the parameters of the gain-scheduled PID controller on an engine test bench, system identification was used to identify the plant model properties at different working points for a WP10 diesel engine on the test bench. The PID controller parameters were calculated based on the identified first-order-plus-dead-time (FOPDT) plant model. The joint simulation of the controller and the plant model was performed in Matlab/Simulink. The time-domain and frequency-domain performances of the entire system were evaluated. The designed VNT control system was verified with engine tests. The results indicated that the real boosting pressure traced the target boosting pressure well at different working conditions.     

Using µ Feedforward for Vehicle Stability Enhancement

A differential braking control strategy using yaw rate feedback, coupled with µ feedforward is introduced for a vehicle cornering on different µ roads. A nonlinear 4-wheel car model is developed. A desired yaw rate is calculated from the reference model based on the driver steering input. It is shown that knowledge of µ offers significant improvement of the vehicle desired trajectory over that of a yaw rate controller alone. Uncertainties and time delay in estimating µ are shown to still yield a system that is superior to using no µ information at all.     

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.     

线控双电机转向系统滑模同步控制及其硬件在环仿真

为了满足高等级自动驾驶转向执行机构的高安全性需求，研究一种采用冗余双电机转向执行机构的线控转向系统，针对双电机在转角伺服控制过程中存在的不同步问题，提出一种基于滑模控制的同步控制策略。首先，对采用冗余双电机转向执行机构的线控转向系统进行结构原理的分析，建立线控系统转向执行机构模型和车辆二自由度模型；然后，为实现转向执行机构的转角伺服控制，在位置、速度、电流的三闭环控制策略的基础上设计速度同步控制器。为解决2个转向执行电机运行过程中存在的速度不同步问题，采用滑模控制方法，将2个电机的转速差值作为控制器的输入量，得到双电机电流的补偿量，并将其叠加至双电机的目标电流中。同时，将上述控制策略与传统PID控制进行对比仿真试验，验证了基于滑模同步控制的线控双电机执行器能够更好地协调双电机的转速，实现双电机同步运行。最后，搭建线控转向硬件在环试验台，对所设计的控制策略的有效性进行验证。结果表明：所设计的双电机线控转向系统滑模同步控制策略能够在实现转角伺服控制的同时，减少双电机的速度不同步现象，保证线控转向系统转角伺服的同步性能。     

Integrated fuzzy/optimal vehicle dynamic control

There are basically two methods to control yaw moment which is the most efficient way to improve vehicle stability and handling. The first method is indirect yaw moment control, which works based on control of the lateral tire force through steering angle control. It is mainly known as active steering control (ASC). Nowadays, the most practical approach to steering control is active front steering (AFS). The other method is direct yaw moment control (DYC), in which an unequal distribution of longitudinal tire forces (mainly braking forces) produces a compensating external yaw moment. It is well known that the AFS performance is limited in the non-linear vehicle handling region. On the other hand, in spite of a good performance of DYC in both the linear and non-linear vehicle handling regions, continued DYC activation could lead to uncomfortable driving conditions and an increase in the stopping distance in the case of emergency braking. It is recommended that DYC be used only in high-g critical maneuvers. In this paper, an integrated fuzzy/optimal AFS/DYC controller has been designed. The control system includes five individual optimal LQR control strategies; each one, has been designed for a specific driving condition. The strategies can cover low, medium, and high lateral acceleration maneuvers on high-μ or low-μ roads. A fuzzy blending logic also has been utilized to mange each LQR control strategy contribution level in the final control action. The simulation results show the advantages of the proposed control system over the individual AFS or DYC controllers.     

Additional 4WS and Driver Interaction

SUMMARY

This investigation is based on a complex 4-wheel vehicle model of a passenger car that includes steering system and drive train. The tyre properties are described for all possible combined longitudinal and lateral slip values and for arbitrary friction conditions. The active part is an additional steering system of all 4 wheels, additionally to the driver's steering wheel angle input. Three control levels are used for the driver model that thereby can follow a given trajectory or avoid an obstacle.

The feedback control of the additional 4 wheel steering is based on an observer which can also have adaptive characteristics. Moreover a virtual vehicle model in a feedforward scheme can provide desired steering characteristics.

To get information for critical situations a cornering manoeuvre with sudden u-split conditions is simulated. Further a similar manoeuvre is used to evaluate the reentry in a high friction area from low friction conditions. And finally the performance of the controller is shown in a severe lane change manoeuvre.     

Application of time-variant predictive control to modelling driver steering skill

The paper addresses the need for improved mathematical models of human steering control. A multiple-model structure for a driver's internal model of a nonlinear vehicle is proposed. The multiple-model structure potentially offers a straightforward way to represent a range of driver expertise. The internal model is combined with a model predictive steering controller. The controller generates a steering command through the minimisation of a cost function involving vehicle path error. A study of the controller performance during an aggressive, nonlinear steering manoeuvre is provided. Analysis of the controller performance reveals a reduction in the closed-loop controller bandwidth with increasing tyre saturation and fixed controller gains. A parameter study demonstrates that increasing the multiple-model density, increasing the weights on the path error, and increasing the controller knowledge range all improved the path following accuracy of the controller.     

Steering disturbance rejection using a physics-based neuromusculoskeletal driver model

The aim of this work is to develop a comprehensive yet practical driver model to be used in studying driver–vehicle interactions. Drivers interact with their vehicle and the road through the steering wheel. This interaction forms a closed-loop coupled human–machine system, which influences the driver's steering feel and control performance. A hierarchical approach is proposed here to capture the complexity of the driver's neuromuscular dynamics and the central nervous system in the coordination of the driver's upper extremity activities, especially in the presence of external disturbance. The proposed motor control framework has three layers: the first (or the path planning) plans a desired vehicle trajectory and the required steering angles to perform the desired trajectory; the second (or the musculoskeletal controller) actuates the musculoskeletal arm to rotate the steering wheel accordingly; and the final layer ensures the precision control and disturbance rejection of the motor control units. The physics-based driver model presented here can also provide insights into vehicle control in relaxed and tensed driving conditions, which are simulated by adjusting the driver model parameters such as cognition delay and muscle co-contraction dynamics.     

电动助力转向系统控制的台架试验研究

提出了将基于模糊神经网络的PID控制策略用于电动助力转向系统中助力电机的控制。设计了电动助力转向试验台，并进行了电动助力转向系统的台架试验。试验结果证明，采用模糊神经网络控制器确定目标电流，并使用PID反馈控制器跟踪目标电流的控制策略是十分有效的，能显著提高汽车的转向轻便性和灵敏性。     

Study on the performance of active front steering system

The performance of a steering system equipped with active front steering (AFS) device is investigated with the consideration of AFS intervention and a proposed dynamic model. Firstly, the kinematics and dynamics of AFS are illustrated based on the mechanism of AFS with planetary gear set and a detailed dynamic model. Furthermore, a basic control on the voltage of DC motor at AFS actuator is proposed. It is realized by a proportional controller that the input is the difference of desired steering ratio and a conventional gear ratio. Finally, two numerical simulations are carried out. One is on-center handling test to demonstrate the basic characteristics of AFS. The other simulation is to demonstrate the effects of vehicle speed, frequency of steering input and AFS intervention on steering system performance. It is shown that the proposed AFS dynamic model is capable to simulate dynamic performance of AFS. The effect of AFS intervention on turning efforts at hand steering wheel is inevitable and the turning comfort is deteriorated to some extent.