汽车动态仿真器运动系统控制算法研究

汽车动态仿真器的研制必须建立在驾驶员视觉，触觉，听觉及体感的高逼真度模拟的基础上，研究了体感模拟技术的算法及建模，并进行了计算机仿真，仿真结果表明，所研究的运动控制算法，可为驾驶员提供逼真的运动感觉，可用于汽车动态仿真器的开发研究中心。     

驾驶员运动感觉及其评价

本文提出三类感觉模拟的评价方法：主观评价，生理心理效应评价及计算机仿真评价，利用前庭系统模型，拟定了驾驶员运动感觉模拟逼真度的仿真评价方程式，并对汽车动态仿真器运动驱动算法进行了仿真评价。仿真结果表明，本文采用的前庭系统模型在所用频率范围内具有可信的精度，用它评价运动感觉模拟逼真度是行之有效的。     

汽车动态仿真器运动系统的软件限制方法

汽车动态仿真器中，驾驶员的运动感觉是由运动系统提供，运动感觉的真实性是影响仿真器逼真度的因素之一，提出了一种从软件上限制仿真器运动系统运动速度，位移的方法，建立了其模型，编制了程序，并用于实际的仿真器系统。     

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。     

利用力矩电机全工况仿真汽车转向盘反力矩

在汽车动态模拟系统中，转向盘反力矩的仿真逼真度影响实验驾驶员的操纵行为，从而影响驾驶模拟实验的准确性。本文系统地阐述了利用力矩电机进行全工况仿真汽车转向盘反力矩的原理、力矩电机的工况分析及稳态误差分析等，为全工况仿真汽车转向盘反力矩提供了一种新方法。     

汽车响应分析方法的探讨

本文将精细积分算法推广应用到考虑轮胎非线性的驾驶员－汽车－道路闭环系统的运动微分方程组的求解，推广后的算法原则上可用来求在计算机精度范围内的精确解，以转向盘角阶跃为例进行了非线性的仿真计算，对汽车的动态运动特性进行了分析。     

基于驾驶员路径选择的动态交通仿真模型

描述一个基于路径的动态交通仿真模型(RDTS)，它使用一个微观交通流仿真器结合一个驾驶员路径策划器来实现路网中每辆车从出发地到目的地行程的模拟。应用开发的时间相关最短路模型，驾驶员在向目的地前进途中可以根据交通条件的动态变化而动态地选择和变更路径。RDTS模型采用一个路径选择模型来模拟详细的动态交通分配过程，并且致力于反映路网中个别车辆的行为表现及其相互作用，其中包含车辆生成、路径选择和车辆移动模型，可以很好地应用于驾驶员动态路径诱导领域。     

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。     

汽车自适应巡航的间距算法和控制策略

基于汽车行驶模型和制动模型,建立汽车自适应巡航系统的间距算法常微分方程组,且给出通用数值解计算方法。基于此间距算法,设计汽车自适应巡航控制的控制策略,将前后两车间距进行区域划分,并设计各区域内驱动与制动控制策略。汽车自适应巡航系统能够基于间距算法的数值解,输出相应驱动或制动数值指令。     

基于人体工程学约束的汽车驾驶员动态H点人体机构的研究

建立了汽车驾驶员动态H点人体机构模型．利用人体工程学约束的方法，分析了驾驶员H点调整及靠背角调整时的人体机构的运动规律。     

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).     

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).     

考虑道路因素的智能车辆纵向运动决策与控制研究

针对智能车辆纵向运动时的交通道路适应性问题,考虑路面附着系数和前车运动速度等因素,研究了智能车辆纵向运动决策与控制方法。论文研究了基于车头时距的纵向运动决策方法并建立不同驾驶行为的目标车速模型,运用变论域模糊推理算法设计了目标加速度模型。基于纵向动力学模型,运用自适应反演滑模控制算法建立了驱动控制器和制动控制器。对高附着系数路面和低附着系数路面的行驶工况进行仿真试验验证,结果表明,在不同的附着系数路面和前车变速行驶条件下,智能车辆能实时、合理地决策目标车速、目标加速度,实现安全、高效、稳定的跟驰。     

线控转向稳态增益与动态反馈校正控制算法

以29自由度汽车动力学模型为基础,提出了保证线控汽车转向增益不变的稳态控制策略,使线控汽车转向特性不随车速和转向盘转角变化;提出了基于状态反馈的动态校正稳定性控制算法。仿真和驾驶模拟器实验表明,基于转向增益不变的稳态控制策略保证了汽车转向特性不变,减轻了驾驶员的负担,适合于更多的驾驶人群;基于状态反馈的动态校正稳定性控制算法有效提高了汽车的稳定性。     

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.     

The perspectives of research for enhancing active safety based on advanced control technology

This paper considers the scope and the methodologies for enhancing active safety of road vehicles by sensing and control technologies. The first part of this paper introduces statistical data of traffic accidents in Japan, and describes the development of the drive recorder for accident/incident survey and analysis. Based on vehicle dynamics data, the algorithm of the drive recorder for capturing near-miss incident data is introduced. The second part of this paper reviews control problems of vehicle dynamics on micro-scale electric vehicles for enhancing vehicle dynamics and driving assistance function. In particular, the direct yaw moment control using in-wheel-motors and the active front steering control algorithm are described. The third part of the paper introduces the advanced driver assistance system adapted to driver characteristics and traffic situations. This part mainly describes an adaptive system, which adjusts the assisting manoeuvre depending on individual driver behaviour and situation, and some experimental investigations using the active interface vehicle and driving simulator. Finally, some perspectives and new challenges for future research on vehicle control technology are mentioned.     

A polynomial chaos approach to the analysis of vehicle dynamics under uncertainty

The ability of ground vehicles to quickly and accurately analyse their dynamic response to a given input is critical to their safety and efficient autonomous operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this uncertainty must be considered in the analysis of vehicle motion dynamics. Here, polynomial chaos approaches that explicitly consider parametric uncertainty during modelling of vehicle dynamics are presented. They are shown to be computationally more efficient than the standard Monte Carlo scheme, and experimental results compared with the simulation results performed on ANVEL (a vehicle simulator) indicate that the method can be utilised for efficient and accurate prediction of vehicle motion in realistic scenarios.