高速车辆车道偏离辅助控制研究

针对高速公路上因驾驶员注意力不集中或疲劳容易发生车辆偏离车道事故的问题,提出基于动态车辆横越车道线时间(Time to lane crossing,TLC)触发阈值的辅助控制决策策略和基于差动制动的车道偏离辅助控制方法。根据车-路航向角偏差、路面附着、车速、驾驶员反应时间及执行机构响应时间实时计算动态TLC触发阈值,进行预警和辅助控制决策。在辅助控制决策的基础上,基于预瞄点处的车-路偏差、车辆状态和道路附着限制计算期望的横摆响应,设计滑模控制器控制辅助横摆力矩,通过差动制动产生横摆力矩,使车辆横摆响应跟踪目标值,达到车道偏离辅助控制的目的。在Carsim/Simulink联合仿真平台上对基于差动制动的车道偏离辅助控制方法进行仿真试验,研究结果表明所提出方法将车辆限制在车道范围内,有效避免车道偏离事故发生。建立由CarsimRT/LabviewRT实时平台及转向、制动执行机构组成的车道偏离辅助控制系统快速原型试验台架,对基于差动制动的辅助控制方法进行台架试验,其结果与Carsim/simulink联合仿真结果基本一致。     

基于人机共享和分层控制的车道偏离辅助系统

针对车道偏离辅助系统转向控制中的人机协同问题,提出一种人机共享的决策与控制方法。考虑驾驶员转矩、道路曲率及纵向车速,设计模糊控制器确定虚拟车道边界宽度,再根据车轮是否超出虚拟边界进行辅助控制决策。在此基础上根据车-路位置关系建立车辆预瞄处偏差的动态模型,设计LPV/H∞控制器跟踪车道中心线决定期望前轮转角。应用滑模观测器估计转向阻力矩,设计考虑驾驶员转矩和转向阻力矩的二阶滑模控制器决定辅助转矩,再由主权分配模块进一步对人机控制主权进行分配,实现辅助系统与驾驶员之间的共享控制。在veDYNA/Simulink联合仿真平台上对提出的控制方法进行仿真试验,仿真结果表明所提出方法在各种车速下均能有效避免车辆偏离车道,减少控制器对驾驶员的干预,人机冲突较小。建立基于veDYNA/LabVIEW的车道偏离辅助控制系统试验台架,对该方法进行硬件在环仿真试验,其结果表明该方法能有效辅助驾驶员通过复杂道路,获得较好地人机协调性能。     

基于差动制动的车道偏离辅助控制

针对高速公路上因驾驶员注意力不集中容易发生车辆偏离车道事故的问题,提出采用四轮差动制动对车辆施加辅助横摆力矩以避免车辆偏离车道的方法。基于预瞄点处的车-路偏差、车辆状态和道路附着限制计算期望的横摆响应,设计滑模控制器控制辅助横 摆力矩。通过在同侧车轮定比例分配制动力产生横摆力矩,使车辆横摆响应跟踪目标值,达到车道偏离辅助控制的目的。在Carsim/Simulink联合仿真平台上对基于差动制动的车道偏离辅助控制方法进行仿真实验,研究结果表明所提出方法将车辆限制在车道范围内,有效避免了车道偏离事故的发生。     

Development of a lane departure monitoring and control system

The lane departure avoidance systems have been considered promising to assist human drivers in AVCS (Advanced Vehicle Control System). In this paper, a lane departure monitoring and control system is developed and evaluated in the hardware-in-the-loop simulations. This system consists of lane sensing, lane departure monitoring and active steering control subsystems. The road image is obtained based on a vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active steering controller for avoiding the lane departure is designed based on the lane departure metric. The proposed lane departure avoidance system is realized in a steering HILS (hardware-in-the-loop simulation) tool and its performance is evaluated with a driver in the loop.     

Drive control algorithm for an independent 8 in-wheel motor drive vehicle

This paper describes a drive control algorithm based on optimal coordination of drive torque for an independent 8 in-wheel motor drive vehicle. The drive controller improves lateral stability and maneuverability. The drive controller consists of upper level controller and lower level controller. The upper level controller determines front, middle steering angle, additional net yaw moment and longitudinal net force according to the reference velocity and steering commands. The lower level controller coordinates additional tractive and braking forces to guarantee desired longitudinal net force and yaw moment. This controller is based on optimal control theory and takes into consideration the friction circle related to the vertical tire force and friction coefficient acting on the road and tire. Distributed tractive and braking forces are determined as proportional to the size of the friction circle according to the changes at driving conditions. The response of the 8 in-wheel drive vehicle implemented with this drive controller has been evaluated via computer simulations conducted using Matlab/Simulink dynamic model. Computer simulations of an open-loop J-turn maneuver and a closed-loop driver model subjected to double lane change have been conducted to demonstrate improved performance and stability of the proposed drive controller.     

汽车自适应巡航系统的多模式切换控制

在复杂交通环境下,由于前车运动状态和驾驶意图的不可预知性,使得传统的自适应巡航控制(Adaptive cruise system,ACC)的应用受到限制,因此提出一种多模式自适应巡航控制策略。在现有上、下位控制器的基础上增加模式切换层,通过将车辆纵向运动状态划分为八种工况,使得系统根据实际工况条件选择最优的控制模式,并采用加速度加权平均算法提高模式切换的准确性和输出连续性。分别设计定速巡航、稳态跟随、接近前车、强加速、强减速和避撞六种控制模式。基于每种模式侧重的控制目标,设计相应的上位控制器并对其控制参数进行整定,从而改善了系统整体的控制品质。最后通过实车试验验证了多模式切换算法的有效性和实用性。     

基于隐马尔可夫模型的驾驶行为预测方法研究

根据驾驶行为受驾驶意图驱使,在时空上应先产生驾驶意图后有驾驶动作执行,再有具体的驾驶行为的时空顺序,利用意图到行为实现过程中的时间差,研究建立了基于多驾驶操作动作特征观测信息和隐马尔可夫模型的驾驶行为预测方法,实现了跑偏驾驶、一般转向和紧急转向3种驾驶行为的预测。从机动车安全预警的角度进行分析,预测出驾驶员的驾驶行为等同于获得驾驶员对车辆未来运行状态的需求,有助于及时纠正或干预驾驶员正在或即将实施的危险行为。     

低附着系数路面车道保持模型预测控制及汽车稳定性控制

提出了车道保持模型预测控制算法。在低附着系数路面上分析了双移线工况下转向角和侧向加速度二次低通滤波之差的峰值与汽车失稳程度之间的关系,基于可测信号(转向角、侧向加速度、横摆角速度和车速)提出了模糊控制算法,设计了汽车稳定性控制器。为了阻止低速和不严重失稳工况下汽车稳定性控制器的误启动,提出了不稳定指标模糊控制算法;为了避免汽车稳定性系数急速减小,设计了稳定性系数保持器。CarSim/Simulink仿真结果表明,在低附着系数路面上所设计的转向控制器和汽车稳定性控制器具有更好的车道保持能力和稳定性。     

基于遗传优化的车辆稳定性模糊控制器设计

为了保证车辆在极限危险工况下的行驶稳定性,提出了利用后轮主动转向与差动制动联合产生校正横摆力矩的稳定性控制策略,并进行了相应的车辆稳定性模糊控制器设计;为了改进所设计模糊控制器的控制品质,克服在控制器设计中隶属函数划分与控制参数确定的主观性,利用遗传算法对所设计模糊控制器的隶属函数分布及比例、量化因子进行了优化研究.     

Robust control of nonlinear integrated ride and handling model using magnetorheological damper and differential braking system

The interaction of the ride and handling systems is one of the challenging topics in vehicle dynamics and control. In this study the dynamic behavior of a passenger car considering coupling among all the fourteen degrees of freedom is modeled using Boltzmann Hamel equations. In order to improve the ride quality and stability of the vehicle, a Magnetorheological damper and a differential braking system are used as control devices. Based on the nonlinear integrated ride and handling vehicle model, a nonlinear H-infinity controller is designed for an intermediate passenger car. The dynamic behavior of the controlled vehicle is simulated for single lane change and bump input, considering three different road conditions: Dry, rainy and snowy. The robustness of the designed controller is investigated when the vehicle is under these road conditions. The simulation results confirm the interactive nature of the ride and handling systems and the robustness of the designed control strategy.     

基于ANFIS及MPC的车辆转向换道控制系统设计

为提高智能车辆在高速工况下进行转向换道避撞时的行驶稳定性,设计了一种基于ANFIS及MPC的车辆转向换道控制系统。车辆转向换道控制系统是以模型预测控制(Model Predictive Control, MPC)算法为基础,结合五阶多项式换道路径和最小车距安全模型搭建的;以理想横摆角速度与实际横摆角速度的偏差及其变化率为双输入,利用自适应神经模糊系统(Adaptive Network-based Fuzzy Inference System, ANFIS)规则输出所需的附加横摆力矩,对车轮进行差动制动,以修正车身姿态,实现行车稳定。仿真结果对比表明,此车辆转向换道控制系统可显著提高车辆在高速工况下进行转向换道避撞时的行驶稳定性。     

基于滑模变结构理论的车辆主动横向稳定杆控制

为实现对车辆的侧倾控制,自主设计了主动横向稳定杆（AARB）装置。针对车辆在侧倾中存在的非线性、时变性特点,采用滑模变结构控制理论建立了滑模控制器从而实现对理想侧倾角的跟踪,并采用鱼钩与双移线转向工况进行了仿真试验。仿真结果表明,该主动横向稳定杆装置与传统被动横向稳定杆装置相比,能有效减小车辆的侧倾,同时具有良好反馈特性以,有利于驾驶员对车身姿态的判断,从而大大提高了车辆行驶的安全性与乘坐舒适性。     

考虑车间反应时距的汽车自适应巡航控制策略

通过引入车间反应时距的概念,使用单一控制算法实现汽车自适应巡航控制（Adaptive cruise control,ACC）。结合熟练驾驶员经验,使用车间反应时距定量描述自车何时对目标车辆做出反应,将ACC系统分为上位控制器和下位控制器,给出考虑车间反应时距的上位控制器架构,分别设计线性二次型调节器（Linear quadratic regulator,LQR）和模型预测控制器（Model predictive control,MPC）,通过MATLAB/Simulink与CarSim联合仿真初步验证系统可行性,并以乘用车辆为试验平台在平直铺装路进行实车试验。仿真及实车试验结果表明：目标车辆信息跳变、目标车辆行驶速度超过自车驾驶员设定限速时,考虑车间反应时距的LQR或MPC控制器均能有效处理复杂交通环境信息,实现自车安全、舒适行驶,有效避免模式切换过程中车辆加速度突变,提升车内乘员乘车体验。     

Integrated control of lateral and vertical vehicle dynamics based on multi-agent system

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention（BDI）-agent model framework, the TYRE agent, electric power steering（EPS） agent and active suspension system（ASS） agent are proposed. In the system（SYS） agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system（MAS） controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.     

An investigation on the integrated human driver model for closed-loop simulation of intelligent safety systems

This paper presents an integrated human driver model for a closed-loop simulation of the intelligent safety system. A lateral human driver model was developed to represent the steering behavior of a human driver using the finite preview optimal control method. A longitudinal human driver model represents a human driver’s throttle and brake control behavior relative to the preceding vehicle motion. It computes the desired acceleration and generates throttle/brake inputs to maintain vehicle-to-vehicle clearance at a desired level or to control vehicle speed. An integrated driver model was been developed using the longitudinal and lateral driver models to represent the behavior of a human driver in alternative driving situations, that is, vehicle following, lane following, emergency braking, and so on. Simulation studies were conducted using “Carsim” model which is validated using vehicle test data. Results showed that a human driver’s behaviors could be well represented by the integrated human driver model presented in this paper. Closed-loop simulations of a unified chassis control system with the integrated human driver model were conducted.     

四轮轮毂电机驱动智能电动汽车转向失效容错控制研究

四轮轮毂电机驱动电动汽车各轮驱动力矩独立可控,可通过控制前轴左右两轮的力矩差实现前轮转向。以四轮轮毂电机驱动智能电动汽车为研究对象,针对线控转向系统执行机构失效时的轨迹跟踪和横摆稳定性协同控制问题,提出一种基于差动转向与直接横摆力矩协同的容错控制方法。该方法采用分层控制架构,上层控制器首先基于时变线性模型预测控制方法求解期望前轮转角和附加横摆力矩,然后考虑转向执行机构建模不确定性以及路面干扰,设计基于滑模变结构控制的前轮转角跟踪控制策略。下层控制器以轮胎负荷率最小化为目标,利用有效集法实现四轮转矩优化分配。最后,分别在高速换道和双移线工况下仿真验证了该控制方法的有效性和实时性。     

ACTIVE FRONT STEERING DURING BRAKING PROCESS

An active front steering （AFS） intervention control during braking for vehicle stability is presented. Based on the investigation of AFS mechanism, a simplified model of steering system is established and integrated with vehicle model. Then the AFS control on vehicle handling dynamics during braking is designed. Due to the difficulties associated with the sideslip angle measurement of vehicle, a state observer is designed to provide real time estimation. Thereafter, the controller with the feedback of both sideslip and yaw angle is implemented. To evaluate the system control, the proposed AFS controlled vehicle has been tested in the Hardware-in-the-loop-simulation （HILS） system and compared with that of conventional vehicle. Results show that AFS can improve vehicle lateral stability effectively without reducing the braking performance.     

基于线控电动汽车的驱动转向 一体化控制器研究

Aiming at the problem that recently both the driving strategy for the motor in wheel and steering strategy for the electric vehicle were researched independently,the structure,the control system,the motor in wheel driving control system,the independent steering system, the CAN communication network and the power tube isolation drive were studied,and the integrated controller for the electric vehicle was proposed. Experiments on 5 kinds of vehicle working mode were carried out based on the integrated steering controller driver. The steering and electronic diferential control of tlie normal working mode was focused by experiment. The results indicate that tlie integrated controller can meet tlie real time,accuracy and reliability requirements of tlie electric vehicle. [ABSTRACT FROM AUTHOR]     

电动助力转向系统模糊控制算法研究

针对电动助力转向系统(EPS)对控制系统的实时性、稳定性的要求,提出了一种应用于EPS的模糊控制算法,并将其应用在EPS控制器上组成模糊控制器。兼顾转向的轻便性和平稳性,在EPS实验平台上测试所设计的模糊控制器,并在线调整模糊控制参数,使EPS转向手感达到最佳。实验结果表明,所提出的模糊控制算法具有良好的跟踪性能,能满足EPS快速、频繁启停以及转向轻便、稳定的要求。     

A novel technique for optimal integration of active steering and differential braking with estimation to improve vehicle directional stability

This study deals with the enhancement of directional stability of vehicle which turns with high speeds on various road conditions using integrated active steering and differential braking systems. In this respect, the minimum usage of intentional asymmetric braking force to compensate the drawbacks of active steering control with small reduction of vehicle longitudinal speed is desired. To this aim, a new optimal multivariable controller is analytically developed for integrated steering and braking systems based on the prediction of vehicle nonlinear responses. A fuzzy programming extracted from the nonlinear phase plane analysis is also used for managing the two control inputs in various driving conditions. With the proposed fuzzy programming, the weight factors of the control inputs are automatically tuned and softly changed. In order to simulate a real-world control system, some required information about the system states and parameters which cannot be directly measured, are estimated using the Unscented Kalman Filter (UKF). Finally, simulations studies are carried out using a validated vehicle model to show the effectiveness of the proposed integrated control system in the presence of model uncertainties and estimation errors.