六自由度汽车运动模拟器姿态分析

根据非零最小可达章动角球形主工作空间的解析解答，探讨了六自由度汽车运动模拟器姿态能力的评价，并讨论了结构参数对姿态能力的影响规律。     

全动飞行模拟器运动系统浅析

全动飞行模拟器的六自由度运动系统，它给提供模拟器在空间x、y、z三个直角坐标轴方向的直线运动自由度(对应于前后、左右、上下)和绕坐标轴的转动自由度(对应于俯仰、翻滚、偏航)。六自由度运动系统保证机组训练的真实度。运动系统实现方式由最初传统的液压系统，到目前改进的电动系统(EMM)以及电液混合系统(EM2K)来实现，达到节能、环保的目的。本文主要介绍电动系统和EM2K系统实现方式和在使用维护过程中的特点。     

基于频域积分的汽车动力总成运动姿态监测方法研究

动力总成的运动姿态直接影响着汽车振动性能和舒适性能,而常规的加速度信号特征往往无法有效表征出动总的低频运动特征。文章基于频域二次积分原理和多点运动合成方法,提出了一种汽车动力总成质心运动姿态监测算法。对加速度信号进行频域二次积分,同时对超低频成分置零处理,从而较好地消除传感器零漂和温漂的误差,提高了位移信号的获取精度;对多测点信号进行运动合成,获取了动总刚体六自由度运动特征信息。汽车加速窜动工况和静态点熄火工况的工程应用表明:所提算法能够有效并直观地合成出动力总成质心刚体的运动特征信息。     

汽车动态驾驶模拟顺运动系统分析及数学建模

分析了汽车动态驾驶模拟器运动系统的工作机理，并从驾驶动态体感要求出发，对模拟器运动系统的各种动作姿态做了详细阐述，提出了用于运动系统控制的实用数学模型，为研究高性能三自由运动系统提供了理论依据。     

用于开发型驾驶模拟器的17自由度汽车动力学仿真的数学模型及算法

文中对17自由度汽车动力学仿真的数学模型进行了分析,具体描述了该汽车动力学仿真模型微分—代数方程组的结构特征,并针对该结构特征提出了一种适用于在开发型驾驶模拟器上运行的求解算法。仿真实践证明,这种算法快速准确,并可应用到具有类似结构的汽车动力学仿真模型或其它多体系统微分—代数方程组的求解中。     

基于三自由度的智能汽车模糊滑模横向运动控制研究

针对智能汽车运动过程中存在的车身姿态变化问题以及运动控制精度问题，设计了一种基于非线性3自由度动力学模型的模糊滑模横向运动控制器。建立了包括侧倾运动的3自由度动力学模型，进行了模型线性化；对基于线性化处理后的动力学模型进行了滑模控制器设计，通过控制前轮转角实现了路径跟踪横向控制，并引入了模糊控制提高控制效果，本控制系统能够在跟踪过程中对车身姿态变化进行观察。仿真结果表明，搭建的基于3自由度动力学模型的模糊滑模控制器能够在考虑侧倾运动的基础上，实现路径跟踪，且构建的模糊滑模控制系统相较于传统滑模控制其横向偏差与方向偏差分别降低了7.28%和1.50%，同时模糊控制也减弱了滑模控制固有的抖振影响。     

主被动式网络化汽车驾驶模拟器的研究及应用

本文介绍主、被动式网络化的汽车驾驶模拟器。该模拟器除采用了先进的计算机虚拟现实技术和汽车动力学模型外，还具有模拟器间的网络交互、主被动驾驶模式、运动约束、语音提示、驾驶评价等方面的特点，在应用上具有显著的特色。     

侧风对高速汽车行驶稳定性影响的仿真分析

汽车高速运动时的方向稳定性受侧向风的影响非常明显,其影响规律与侧风气动中心的位置密切相关。但是,对侧向风的影响有两种不同的观点,一种观点认为与气动中心和中性转向点的相对位置相关;另一种观点则认为取决于气动中心和质心的相对位置。基于二自由度汽车动力学模型,用Matlab软件对侧风引起的汽车行驶稳定性进行了仿真分析,认为汽车在侧风作用下的运动规律取决于侧风气动中心与中性转向点的相对位置。     

基于人机工程学的汽车驾驶模拟器后视镜布置研究

为进一步提升汽车驾驶模拟器的感受真实度和视野舒适度,对驾驶模拟器上的后视镜在驾驶视景中的位置布置进行了研究。依据人机工程学原理和驾驶员的视觉特性,结合解析几何学的相关知识,分别对驾驶模拟器的驾驶视景中的左、右后视镜和内后视镜的水平方向和垂直方向的位置与驾驶员视角之间的关系式进行了推导,得到了后视镜位置布置公式。通过对该公式的应用,以期进一步提升汽车驾驶模拟器的视景逼真度,同时改善驾驶员的视觉效率、减少视觉疲劳。     

汽车驾驶模拟器研究现状与未来展望

汽车驾驶模拟器是一种能正确模拟汽车驾驶动作，并能在主要性能上获得与实车驾驶相同感觉的仿真设备。按用途不同，可分为训练型汽车驾驶模拟器和开发型汽车驾驶模拟器。训练型模拟器可以初步完成对新驾驶员的训练；开发型模拟器能对人一车一环境系统进行研究，从而验证事故的发生原因，预防车辆事故的发生，为汽车工程设计提供帮助。     

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.     

汽车动态仿真器运动系统的两种驱动算法模拟逼真度分析与比较

本文利用驾驶员前庭系统模拟型分析比较汽车动态仿真器运动系统的两种驱动自满的模拟逼真度。仿真结果表明，自适应Ｗａｓｈｏｕｔ驱动算法比传统Ｗａｓｈｏｕｔ驱动算法具有更高的模拟逼真度，因此，汽车动态仿真器用自适应算法可为驾驶员提供更为逼真的运动感觉 。     

开发型驾驶模拟器体感模拟算法及其评价

运用开发型汽车驾驶模拟器，可在模拟的汽车驾驶环境中，研究人－车－环境闭环系统特性，从而研制出高主动安全性汽车，驾驶员的视觉，听觉，触觉及体感是模拟器的四大模拟要素，直接影响模拟器逼真度，本文提出一种驾驶员体感模拟滤波算法，并建立驾驶员体感评价模型，仿真计算的结果表明，该算法既可充分发挥体感模拟系统硬件的模拟能力，并获得满意的体感模拟逼真度，又可为研制汽车驾驶模拟器需体感模拟软件的逼真度评价提供一种行之有效的方法。     

神经元实时辨识车辆导航系统中的GPS多径误差

在城市车辆导航过程中,多径误差是近距离差分GPS等高精度定位的主要误差源。文章首次提出神经元实时辨识GPS多径误差方法,它能实时辨识当前时刻GPS接收机输出的GPS信号是否含有多径误差,从而解决GPS多径误差对城市车辆导航定位精度的影响。把该方法用到实际工程中,其结果显示能够有效的消除GPS多径误差对城市车辆导航系统定位精度的影响。     

Modeling of Double Lane Change Maneuver of Vehicles

Lane change maneuver is one of most riskiest driving tasks. In order to increase the safety level of the vehicles during this maneuver, design of lane change assist systems which are based on dynamics behavior of driver-vehicle unit is necessary. Therefore, modeling of the maneuver is the first step to design the driver assistance system. In this paper, a novel method for modeling of lateral motion of vehicles in the standard double-lane-change (DLC) maneuver is proposed. A neuro-fuzzy model is suggested consisting of both the vehicle orientation and its lateral position. The inputs of the model are the current orientation, lateral position and steering wheel angle, while the predicted lateral position and orientation of the vehicle are the outputs. The efficiency of the proposed method is verified using both simulation results and experimental tests. The simulation and experimental maneuvers are performed in different velocities. It is shown that the proposed method can effectively reduce the undesirable effects of environmental disturbances and is significantly more accurate in comparisons with the results in the recent available papers. This method can be used to personalize the advanced driver assistance systems.     

车-车协同下无人驾驶车辆的换道汇入控制方法

多车协同驾驶是智能车路系统领域的研究热点之一,可有效降低道路交通控制管理的复杂程度,减少环境污染的同时保障道路交通安全。基于多车协同驾驶控制结构,提出了一种无人驾驶车辆换道汇入的驾驶模型及策略,系统分析了多车协同运行状态的稳定条件。在综合分析无人驾驶车辆换道汇入的协作准则、安全性评估后,基于高阶多项式方法,结合车辆运行特性,通过引入乘坐舒适性的指标函数,设计得到无人驾驶车辆换道汇入的有效运动轨迹。通过研究汇入车辆与车队中汇入点前、后各车辆的运动关系,详细分析车辆发生碰撞的类型和影响因素,给出避免碰撞的条件准则,从而确保无人驾驶车辆汇入过程中多车行驶的安全性和稳定性。基于车辆运动学建立车辆位置误差模型,结合系统大范围渐进稳定的条件,选取线速度和角速度作为输入,应用李雅普诺夫稳定性理论和Backstepping非线性控制算法,设计了无人驾驶车辆换道汇入后的路径跟踪控制器。仿真试验和实车试验结果表明：所设计的换道汇入路径是可行、安全的,控制器具有良好的跟踪效果,纵向和横向的距离误差在15 cm以内,方向偏差的相对误差在10%以内。研究结果为智能车路系统中的多车状态变迁与协同驾驶研究提供了参考,可服务于未来道路交通安全设计和评价。     

Analysing classes of motion drive algorithms based on paired comparison techniques

A paired comparison experiment using 23 subjects was run on the VIRTTEX driving simulator to compare a lane position based motion drive algorithm (MDA) with a classical MDA for a highway speed, lane change manoeuvre. Two different tuning states of the lane position algorithm and four different tuning states for the classical algorithm were tested. The subjective fidelity of the six different motion cases was compared with each other and a Bradley–Terry model was fit to find the fidelity merit of each case. In addition, the driving performance of the subjects for six motion cases was recorded and compared. The motion-tuning cases were selected such that the trade-off in motion quality between overall motion scaling and motion shape distortion (shape-error), as well as the trade-off between lateral specific force and roll-rate motion errors, could be studied. It was found that when the overall scaling is the same, drivers perform better with the lane position algorithm than with the the classical algorithm. A well-tuned, manoeuvre-specific, classical MDA, however, did achieve a subjective fidelity level on a par with the lane position MDA. A generically tuned classical MDA, however, has a significantly reduced fidelity and driving performance when compared with a lane position algorithm with the same scale factor. A strong trade-off between motion shape-errors and overall motion scaling was found. A small increase in motion cue shape-error, combined with an increase in the scale factor from 0.3 to 0.5, led to improved performance and increased subjective fidelity. The results of the experiment also suggest that simulator motion can be improved by reducing the angular-rate shape-error at the expense of the specific force shape-error (while keeping the total normalised shape-error constant).     

Force control for path following of a 4WS4WD vehicle by the integration of PSO and SMC

The aim of this paper is to present a novel control method for a four-wheel steer and four-wheel drive (4WS4WD) vehicle. The novelty is in the integration of sliding mode control (SMC) and particle swarm optimization (PSO) that is proposed to solve the control problem caused by the nonlinear, highly coupled and over-actuated characteristics of the four-wheel steer and four-wheel drive (4WS4WD) vehicle. The validity of the control method is evaluated by two criterions, namely path following performance assessed by the vehicle's position errors with respect to the reference path, and motion quality reflected by the smoothness of vehicle's velocities and accelerations. In vehicle modelling, a kinematic model and a dynamic model considering all slip forces are proposed for the controller design. Simulation results are provided to demonstrate the applicability of the proposed methodology and its robustness.     

Partial range scaling method based washout algorithm for a vehicle driving simulator and its evaluation

Unlike an actual vehicle, a vehicle driving simulator (VDS) has limited kinematics, workspace, and bounded dynamic characteristics making it very difficult to simulate dynamic motions of an actual vehicle. To solve these problems, a washout algorithm was developed. The developed algorithm restricts the workspace of the VDS to within the kinematic limit and makes the person driving the VDS perceive movement of an actual vehicle. However, the classic washout algorithm contains several problems, such as time delay and the generation of a wrong motion signal caused by characteristics of the filters. So the driver feels “simulator sickness,” such as fatigue, nausea, headache and so on because of differences between the sense of movement of the VDS and that of a real vehicle. In this paper, a partial range scaling method based washout algorithm, including a tilt coordination system, is developed to enhance the perception of motion and reduce simulator sickness. It is verified by a simulation, a survey, and a bio signal analysis using an electrocardiogram (ECG).     

Measurements of Path and Other Parameters in Motor Vehicle Dynamics Tests and Their Errors

This paper discusses two equipment layouts for measuring path data, vehicle sideslip angles and tire slip angles by using a gyrosystem, a vehicle speed-measuring unit with contact or non-contact speed sensor(s), and a computer. Measurement errors are analyzed in detail. A method for eliminating the effect of vehicle roll on measurement is given. Some relations between measurement errors and instrument errors are derived using vector analysis. A practical and effective error correction method for vehicle path measurements is developed.