驾驶员最优预瞄纵向加速度模型

利用预瞄跟踪理论、模糊决策理论和非线性系统描述函数法建立了一个驾驶员速度控制模型，即加强员最优预瞄纵向加速度模型，仿真结果表明，该模型通过对驾驶安全性、合法性、轻便性、驾驶员自身滞后特性及汽车动力学系统强非线性特性的考虑，可以有效地模拟驾驶员控制汽车速度的行为特性，为人-车-路闭环系统中速度控制研究提供了一条可行途径。     

预瞄驾驶员模型中车辆操控稳定性的分析

通过将驾驶员模型、汽车运动学模型与闭环控制系统相结合,给出了一种基于最大预瞄距离驾驶员模型的空间方程.采用Lyapunov-Krasovskii泛函方法,分析基于该模型的“人—车—路”闭环控制系统的指数稳定性条件.利用所建立的4轮车辆驾驶员模型,分别采用不同的最大预瞄距离值和驾驶员反应时滞值,对车辆路径跟随进行了仿真试...     

基于轴间预瞄的主动悬架研究

以某型汽车的1／2车辆模型为研究对象，提出了一种轴间预瞄控制的方法，并结合最优控制理论设计了车辆悬架的控制策略。通过模拟和仿真分析，验证了所提出的轴间预瞄比传统的轴距预瞄具有更好的控制效果。     

基于横向预瞄偏差的驾驶员前视轨迹控制模型

文章给出了横向预瞄偏差的概念，提出了一种基于横向预瞄偏差的驾驶员前视轨迹控制模型。通过计算机仿真，验证了该控制模型的正确性。该模型与现行的预瞄驾驶员模型相比，具有理解容易，分析计算简单，实用性强的优点。     

预瞄跟随理论与人-车闭环系统大角度操纵运动仿真

本文是人-车闭环操纵系统“预瞄最优曲率模型”和“预瞄跟随理论”的进一步验证与推广应用。特别是通过更真实地模拟了驾驶员获取各种信息的参考系统随汽车运动而变化的过程,从而使原来只能模拟小角度转向运动的方法推广到各种大角度转向路径(包括各种封闭形路径)下闭环操纵运动。     

智能车路径跟踪控制算法的简述

智能车主要分为路径规划、路径跟踪、自动泊车三大部分。路径规划主要研究车辆的避障问题,路径跟踪主要研究车辆跟随期望路径的有效性,自动泊车主要分析车辆在有限的几何空间内将车辆泊到指定的空间位置。其中路径跟踪是其核心部分,根据研究方法的不同,主要分为"预瞄跟随模型"和"智能控制模型"。文章根据预瞄点的不同,主要分析单点预瞄模型、两点预瞄模型、路程预瞄模型。根据智能控制方法的不同,主要分析模糊逻辑控制驾驶员模型、神经网络控制驾驶员模型、模型预测控制驾驶员模型。     

基于表征驾驶风格的驾驶员纵向加速度模型

驾驶员驾驶风格的差异会引起纵向加速度决策与最优值存在一定程度的偏差.改进了基于最优预瞄的驾驶员纵向加速度模型,以跟随速度为参考量,提出了多点多目标的二阶预瞄决策模型,并以预瞄视野、决策意愿和决策偏差表征驾驶员的驾驶风格进行建模.通过Simulink-Carsim联合仿真,验证模型可以反映出不同驾驶风格下的驾驶行为,为研究分析真实驾驶行为提供借鉴.     

主动悬架最优控制整车模型的研究

以一个车辆的整车模型为研究对象，通过利用轴距预瞄信息，应用最优控制理论设计了一个车辆的悬架控制策略，通过模拟和仿真的结果，验证了该模型和算法的可行性，并分析了轴距预瞄控制对于改进车辆性能的能力，检验了所建立的整车模型。     

结合卡尔曼滤波器的车辆主动悬架轴距预瞄控制研究

利用轴距预瞄信息，即前后轮路面输入之关系，同时结合卡尔曼滤波器作为状态估计器，本文提出了一种算法用于车辆悬架控制律的设计，根据模拟结果，研究了算法的可行性，分析了卡尔曼滤波器对状态变量的估计精度，以及轴距预瞄控制对进一步改进车辆性能的潜力。     

三点预瞄的智能控制补偿驾驶员模型

为适应不同驾驶员的预瞄风格和推理决策能力,提出了一种基于三点预瞄的智能控制补偿驾驶员模型,根据预瞄前方远、中、近3个点的坐标值对目标路径的位置关系进行判断,结合当前车速建立了预瞄距离自适应的经验指数模型,提出了以车速、航向角、中点侧向误差为输入,转向盘转角为输出的模糊智能控制驾驶员模型,并对转向角进行补偿校正。仿真结果表明:该模型能够合理地判断目标路径的位置关系,适应预瞄距离的动态调节机理;在不增加失稳风险的条件下,有补偿模型较未补偿校正模型的路径跟踪精度更高。     

汽车预期轨迹驾驶员模糊决策模型及典型路况仿真

本文分析了预瞄最优曲率模型的特点。在此基础上应用系统模糊决策理论，通过合理的预期轨迹决策策略，建立了驾驶员动态决策汽车预期行驶轨迹的模糊决策模型。最终仿真计算了驾驶员在多种典型路况下对汽车预期轨迹的决策行为。     

融合预瞄与势场栅格法的紧急避撞驾驶人模型

紧急避障工况下的驾驶人操作具有响应快且动作幅值较大的特点，传统预瞄驾驶人模型已不能适应紧急避障工况的需求，故考虑实际避撞场景开发相应的驾驶人模型就显得尤为必要。针对此种状况，基于驾驶模拟器，结合紧急避撞工况实际驾驶人操纵数据，提出了一种融合预瞄与势场栅格法的紧急避撞驾驶人模型。首先针对紧急避撞工况下车辆运动特点，建立车辆横、纵向耦合非线性动力学模型，并给出其状态空间方程描述；其次，离线仿真分析紧急避撞系统特征，并结合线性二次型最优控制，建立最优曲率预瞄+跟踪误差反馈驾驶人模型；再者，基于紧急避撞工况下真实驾驶人经验转向行为数据，开发基于势场栅格法的驾驶人模型，为进一步提高驾驶人模型对避障行驶工况的适应性，将基于势场栅格法的驾驶人模型与最优曲率预瞄+跟踪误差反馈驾驶人模型进行融合，并基于Sigmoid函数实现两者输出的权重分配；最后，针对所提出的融合预瞄与势场栅格法的驾驶人模型，开展基于避撞台架的驾驶人在环仿真试验以及实车试验。研究结果表明：在紧急避撞工况下，对比最优曲率预瞄+跟踪误差反馈驾驶人模型，融合预瞄与势场栅格法的驾驶人模型输出的转向动作与实际驾驶人行为较为接近，可在保证避障安全性的前提下，兼顾避障路径跟踪精度与车辆行驶的稳定性。     

基于驾驶员行为模拟的ACC控制算法

基于驾驶员最优预瞄加速度模型建立了一种适用于多种典型行驶工况的ACC控制算法。该算法采用基于多目标模糊决策方法的驾驶安全性、工效性、轻便性与合法性评价指标以及基于预瞄跟随理论的微分校正函数，描述了ACC控制系统对自由工况、跟随工况和切入工况等不同行驶条件及汽车动力学系统强非线性特性的考虑。     

驾驶员统计特性对人—车闭环系统响应的影响与汽车主动安全性评价

基于预瞄跟随理论，本文应用一般随机摄动法，对考虑驾驶员不确定性的人－车闭环系统进行响应分析，结合实例，说明该方法在汽车主动安全性评价中的应用。     

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.     

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.     

Preview Control Algorithms for the Active Suspension of an Off-Road Vehicle

The potential performance improvement using preview control for active vehicle suspension was first recognized in the late nineteen sixties. All work done since that time has been based on optimal control theory using simple vehicle models.

In this article, the performance of quarter vehicle preview controllers when applied to a real off-road vehicle is simulated using both two degree of freedom quarter and ten degree of freedom full vehicle models. The results, which are compared with non-preview active and conventional passive suspensions, confirm that preview control reduces vertical acceleration of the body centre of gravity, which results in improved ride quality. Further, reductions in pitch and roll motion result from smaller vertical displacements of the vehicle quarters. Coupling between quarters, through the vehicle body, appears to have a smoothing effect on the control.

As an alternative to optimal control theory based controllers, a simple ad hoc preview controller based on isolating the vehicle body from dynamic loads transmitted through the suspension is proposed. Simulation results show that such a controller outperforms the optimal control theory based controllers over small discrete disturbances but responds poorly to disturbances encountered from other than steady state.     

基于预期偏移距离的人机权值分配策略研究

针对智能车辆横向运动控制中驾驶员和辅助系统的控制权限冲突问题,本文中提出一种人机权值分配策略。采用车辆在预瞄点处的预期偏移距离(PDLC)衡量车道偏离危险度,预期偏移距离通过对预瞄偏差修正获取。权值分配函数设计时以PDLC为自变量,以保证驾驶员的权值为优先控制目标,以一定的横向运动控制精度为先决条件。在CarSim/Simulink联合仿真平台和CarSim/Labview RT硬件在环实验台上对提出的控制策略进行了实验验证和数据分析。结果表明,采用权值分配策略协调驾驶员和辅助系统的控制,可在有效跟踪理想道路中心线的前提下保证驾驶员的控制权值,降低其工作负荷以及纠正驾驶员的误操作行为。     

Stability Analysis of the Human Controlled Vehicle Moving Along a Curved Path

A method to study handling characteristics of a vehicle moving along a curved path is presented. A simple bicycle model and a feedback controller with proportional gain are used to simulate the vehicle and the driver. The lateral stability of the vehicle/driver system is analyzed by using the root locus method and numerical integration in the time domain. The effect of the curvature on the system stability is discussed in detail. A new suggestion is made for the look ahead distance to calculate the preview lateral error of the vehicle with respect to the center of the road. Interesting results are shown for some important parameters such as the gain factor, the vehicle speed and the curvature of the path. Possible extensions of the method to more general cases and other applications are discussed.