基于障碍物斥力场的汽车主动避撞系统

为提高汽车行驶安全性,设计了基于障碍物斥力场模型的汽车主动避撞系统,建立了道路算盘模型和驾驶员预瞄跟随模型,利用算盘模型可求解出避撞路径,使用驾驶员预瞄跟随模型可求解出汽车转向盘最优转角。通过动静态障碍物环境下的仿真试验表明,利用算盘模型规划出的路径平滑、安全、可跟踪;驾驶员预瞄跟随模型的路径跟随精度高,实现了汽车主动避撞。     

自动驾驶车辆侧向路径跟随控制算法仿真

路径跟随是依照规划轨迹信息通过对执行元件的控制实现沿期望轨迹行驶,控制算法对实现路径跟随非常重要。针对自动驾驶车辆的侧向控制技术,文章研究了基于最优预瞄理论的路径跟随控制,建立车辆二自由度模型和预瞄误差模型,设计模型预测控制（MPC）侧向跟随控制器以提高跟随精度。利用CarSim-Simulink联合仿真,仿真结果表明,该算法策略能稳定跟踪规划路径。     

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。     

基于稳态特性的路程预瞄转向模型

为实现车辆稳态转向的理想状态,建立更真实的预瞄-跟踪行为,提出了2种基于稳态转向的路程预瞄转向模型,假设车辆处于稳态转向状态,预测车辆的行驶轨迹,基于预测轨迹的侧向误差最小原则,分别建立了将单点预瞄转化为路程预瞄的理想转向模型和修正转向模型。CarSim/Simulink联合仿真结果表明,2种转向模型均具有较好的路径跟踪精度、适应性和转向平顺性。     

汽车ACC系统纵向控制六模式切换策略仿真研究

为了增强现有六模式汽车自适应巡航(ACC)系统全工况下的适应性,文中综合考虑了2车相对速度、相对距离和本车速度等参数对ACC系统控制策略的影响,提出了1种六模式ACC系统控制模式的划分方法,并定量地确定了控制模式划分的边界条件.为了使ACC系统能够根据车辆行驶工况做出合理的响应,分别设计了各控制模式的加速度算法.将模式划分方法及控制策略建立相应的Simulink模型,考虑到PreScan具有场景建立便利性和可视化等优点,采用PreScan仿真场景并通过CarSim车辆动态模型,对所设计的六模式ACC系统进行了仿真试验.仿真结果表明:提出的六模式ACC系统,在全工况特别是前车切入等复杂工况下,较现有的六模式ACC系统表现出更好的适应性.      

基于弧长预瞄的车辆侧向跟踪控制研究

为提高基于预瞄理论的路径跟踪控制算法的计算效率与适应性,本文中在预瞄最优曲率模型的基础上,提出了一种依据车辆实际行驶路程获取预瞄点侧向位移的弧长预瞄方法。并在该方法下,推导了预瞄点侧向位移与车辆前轮转角之间的关系,之后通过侧向跟踪闭环系统方框图,建立了路径跟踪的侧向控制模型。最后,在CarSim/Simulink联合仿真环境下,通过建立若干典型仿真工况,对该模型的有效性和人-车-路闭环系统转向盘稳定性影响因素进行了仿真分析。结果表明,该方法在侧向路径跟踪控制方面具有跟踪精度高、计算速度快和适应性好的特点。并且,当闭环系统同时满足期望路径点方向连续和预瞄距离大于临界前视距两个条件时转向盘趋于稳定。     

基于视觉特性的驾驶人预瞄时间建模

针对固定时长的预瞄时间无法真实反映驾驶人预瞄行为的问题,首先对自由流条件下的驾驶人视觉特性进行研究,得到直行路段驾驶人注视点多分布在车道中央、弯道路段驾驶人注视点多分布在内侧边缘线附近且视线近似与内侧边缘线相切的结论;在此基础上,探究直行和弯道路段驾驶人预瞄时间的求解方法,并借助驾驶模拟器进行试验,获得了17位驾驶人的预瞄时间。由于预瞄时间的原始数据分布离散程度高,难以直观地体现其随道路线形的变化规律,因而对预瞄时间随道路线形的分布特征进行研究,利用分组求中位数的方法进行数据处理,最终构建预瞄时间关于道路线形的分段线性函数和非线性指数函数。最后,通过数值仿真研究不同类型的预瞄时间（固定时长的预瞄时间、分段线性函数预瞄时间及指数函数预瞄时间）对人-车-路闭环系统动力学特性的影响。研究结果表明：驾驶人预瞄特性会对车辆的轨迹跟随和车道保持绩效产生重要影响;在闭环系统中使用随道路线形变化的预瞄时间可以显著提高车辆的轨迹跟随绩效,确保车辆在指定车道内行驶;驾驶人对道路环境的感知具有自适应性,通过其视觉特性可准确感知环境变化,并据此调整决策目标及其操纵特性。     

基于状态反馈和预瞄前馈的智能车半主动悬架控制

为提高智能车辆的半主动悬架综合控制性能，提出一种基于状态反馈和预瞄前馈的半主动悬架控制方法。首先，以8轮车为研究对象建立11自由度半主动悬架模型，设计LQR状态反馈控制器。然后，为解决状态反馈控制抗路面干扰能力弱和基于固定时序延迟的预瞄反馈控制适用性差的问题，提出一种基于状态反馈和预瞄前馈的控制器：建立车轮运动规划模型和路面预瞄模型，计算出悬架控制系统所需的车轮规划轨迹点序号和控制延迟响应时间；以路面激励和垂向加速度为输入、以前馈阻尼力为输出，设计基于类模糊的预瞄前馈控制器，并与LQR反馈控制器一并构成所提控制器。最后，基于MATLAB/Simulink和Trucksim联合仿真平台，进行匀速转向工况、变速直线工况、变速转向工况和匀速直线工况下的试验验证。结果表明，在垂向加速度、俯仰角加速度、侧倾角加速度均方根值方面，与被动悬架相比，所提控制方法在4种工况下至少降低了23.52%、13.59%、19.35%；与基于固定时序延迟的预瞄反馈控制相比，所提控制方法在前3种工况下至少降低了14.04%、8.09%、13.79%；与基于状态反馈的控制方法相比，所提控制方法在第4种工况下降低了13...     

基于多点序列预瞄的自动驾驶汽车路径跟踪算法研究

针对自动驾驶汽车自主行驶问题,提出了一种基于预瞄信息的路径跟踪算法。以GPS轨迹点序列作为目标路径,建立车辆—路径相对运动关系模型,使用实时差分GPS数据确定车辆位置。通过预瞄点序列,计算路径的预瞄偏差角和路径弯曲度。根据路径弯曲度确定行驶速度,实现纵向控制;通过Pure Pursuit算法将预瞄偏差角转换成前轮转角的控制量,实现横向控制。试验结果表明,提出的路径跟踪方法在纵向、横向控制和跟踪平稳性方面都具有良好的效果。     

基于驾驶员特征的汽车自适应巡航控制研究

汽车自适应巡航控制系统(ACC)是当前汽车驾驶员辅助系统研究中的热点课题之一。在介绍ACC原理和对驾驶员行为特征进行分析的基础上，建立了2自由度ACC控制模型，并对模型跟随前车和前车切入情况进行了模拟分析。     

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。     

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.     

An adaptive integrated algorithm for active front steering and direct yaw moment control based on direct Lyapunov method

In this article, an adaptive integrated control algorithm based on active front steering and direct yaw moment control using direct Lyapunov method is proposed. Variation of cornering stiffness is considered through adaptation laws in the algorithm to ensure robustness of the integrated controller. A simple two degrees of freedom (DOF) vehicle model is used to develop the control algorithm. To evaluate the control algorithm developed here, a nonlinear eight-DOF vehicle model along with a combined-slip tyre model and a single-point preview driver model are used. Control commands are executed through correction steering angle on front wheels and braking torque applied on one of the four wheels. Simulation of a double lane change manoeuvre using Matlab^®/Simulink is used for evaluation of the control algorithm. Simulation results show that the integrated control algorithm can significantly enhance vehicle stability during emergency evasive manoeuvres on various road conditions ranging from dry asphalt to very slippery packed snow road surfaces.     

Optimal Preview Control of a Two-dof Vehicle Model Using Stochastic Optimal Control Theory

An optimal preview control algorithm is applied to a two degree of freedom(dof) vehicle model travelling with constant velocity on a randomly profiled road. The road roughness is modelled as a homogeneous random process being the output of a linear first order filter to white noise. The input from the road irregularity is assumed to be measured at some distance in front of the vehicle and this measured infonnation is utilized by the active controller to prepare the system for the ensuing input. The preview control algorithm is obtained by minimizing a quadratic performance index and by describing the average behaviour of the system by the covariance matrix of the vehicle response state vector. Results are presented for full state feedback and significant improvements in sprung mass acceleration, suspension working space and road holding are observed.     

Using the lead vehicle as preview sensor in convoy vehicle active suspension control

Both ride quality and roadholding of actively suspended vehicles can be improved by sensing the road ahead of the vehicle and using this information in a preview controller. Previous applications have used look-ahead sensors mounted on the front bumper to measure terrain beneath. Such sensors are vulnerable, potentially confused by water, snow, or other soft obstacles and offer a fixed preview time. For convoy vehicle applications, this paper proposes using the overall response of the preceding vehicle(s) to generate preview controller information for follower vehicles. A robust observer is used to estimate the states of a quarter-car vehicle model, from which road profile is estimated and passed on to the follower vehicle(s) to generate a preview function. The preview-active suspension, implemented in discrete time using a shift register approach to improve simulation time, reduces sprung mass acceleration and dynamic tyre deflection peaks by more than 50% and 40%, respectively. Terrain can change from one vehicle to the next if a loose obstacle is dislodged, or if the vehicle paths are sufficiently different so that one vehicle misses a discrete road event. The resulting spurious preview information can give suspension performance worse than that of a passive or conventional active system. In this paper, each vehicle can effectively estimate the road profile based on its own state trajectory. By comparing its own road estimate with the preview information, preview errors can be detected and suspension control quickly switched from preview to conventional active control to preserve performance improvements compared to passive suspensions.     

A Reusability Study of Vehicle Lateral Control System

The architecture of the PATH vehicle lateral control system is presented in this paper. The two main modules are an intelligent reference/sensing system, and an Frequency-Shaped-Linear-Quadratic/preview control algorithm. The whole lateral control system was formerly evaluated on a two-door test vehicle. It was transplanted to a four-door vehicle which is considerably different from the older two-door test vehicle in dynamic characteristics. The objective of this study is to investigate the reusability of our control system.     

驾驶员稳态预瞄动态校正假说

针对汽车运动学和动力学自身的特点及驾驶员对其的理解和认识，基于预瞄跟随理论和预测控制理论，在驾驶员行为建模中作出了汽车运动学和动力学特性的分隔处理，提出了驾驶员稳态预瞄动态校正假说，并结合仿真计算和驾驶模拟器实验论证了假说的合理性和有效性。     

Optimal Linear Preview Control of Active Vehicle Suspension

The problem of linear preview control of vehicle suspension is considered as a continuous time stochastic optimal control problem. In the proposed approach minimal a priori information about the road irregularities is assumed and measurement errors are taken into account. It is shown that estimation and control issues can be decoupled. The problem formulation and the analytical solution are given in a general form and hence they apply to other problems in which the system disturbances are unknown a priori, even in a stochastic sense, but some preview information is possible.

The solution is applied to a two-degree-of-freedom (2-DOF) vehicle model. The effects of preview information on ride comfort, road holding, working space of the suspension and power requirements are examined in time and frequency domains. The results show that the greatest potential is for improving road holding properties. This effect could not have been observed in previous studies based on a 1-DOF vehicle model. It is also demonstrated that the presence of preview drastically reduces power requirements, thus relieving the performance versus actuator power dilemma.     

A Reusability Study of Vehicle Lateral Control System

SUMMARY

The architecture of the PATH vehicle lateral control system is presented in this paper. The two main modules are an intelligent reference/sensing system, and an Frequency-Shaped-Linear-Quadratic/preview control algorithm. The whole lateral control system was formerly evaluated on a two-door test vehicle. It was transplanted to a four-door vehicle which is considerably different from the older two-door test vehicle in dynamic characteristics. The objective of this study is to investigate the reusability of our control system.