Different human-simulated characteristics of the driver models in the forward simulation of hybrid electric vehicles

Based on the control theories of PID, fuzzy logic and expert PID, the driver models are built and applied in the forward simulation for hybrid electric vehicles (HEV). The impact to the vehicle speed tracking and the fuel economy is compared among the different driver models. The different human-simulated characteristics of the driver models are emphatically analyzed. The analysis results indicate that the driver models based on PID, simple fuzzy logic and expert PID are corresponding to the handling characteristics of different drives. The driver models of different human-simulated characteristics bring the handling divergence of drivers with different driving level and habit to the HEV forward simulation, and that is significant to the all-around verification and validation of the control strategy for HEV. System simulation results of different driver models validate the impact of driver models to the dynamic and fuel economy performance of HEV.

An extended smart driver model considering electronic throttle angle changes with memory

Based on the fact that the electronic throttle angle effect performs well in the traditional car following model,this paper attempts to introduce the electronic throttle angle into the smart driver model(SDM)as an acceleration feedback control term,and establish an extended smart driver model considering electronic throttle angle changes with memory(ETSDM).In order to show the practicability of the extended model,the next generation simulation(NGSIM)data was used to calibrate and evaluate the extended model and the smart driver model.The calibration results show that,compared with SDM,the simulation value based on the ETSDM is better fitted with the measured data,that is,the extended model can describe the actual traffic situation more accurately.Then,the linear stability analysis of ETSDM was carried out theoretically,and the stability condition was derived.In addition,numerical simulations were explored to show the influence of the electronic throttle angle changes with memory and the driver sensitivity on the stability of traffic flow.The numerical results show that the feedback control term of electronic throttle angle changes with memory can enhance the stability of traffic flow,which shows the feasibility and superiority of the proposed model to a certain extent.

Modelling of a Human Driver’s Interaction with Vehicle Automated Steering Using Cooperative Game Theory

The introduction of automated driving systems raised questions about how the human driver interacts with the automated system. Non-cooperative game theory is increasingly used for modelling and understanding such interaction, while its counterpart, cooperative game theory is rarely discussed for similar applications despite it may be potentially more suitable. This paper describes the modelling of a human driver’s steering interaction with an automated steering system using cooperative game theory. The distributed Model Predictive Control approach is adopted to derive the driver’s and the automated steering system’s strategies in a Pareto equilibrium sense, namely their cooperative Pareto steering strategies. Two separate numerical studies are carried out to study the influence of strategy parameters, and the influence of strategy types on the driver’s and the automated system’s steering performance. It is found that when a driver interacts with an automated steering system using a cooperative Pareto steering strategy, the driver can improve his/her performance in following a target path through increasing his/her effort in pursuing his/her own interest under the driver-automation cooperative control goal. It is also found that a driver’s adoption of cooperative Pareto steering strategy leads to a reinforcement in the driver’s steering angle control, compared to the driver’s adoption of non-cooperative Nash strategy. This in turn enables the vehicle to return from a lane-change maneuver to straight-line driving swifter.

Lattice models of traffic flow considering drivers' delay in response

This paper proposes two lattice traffic models by taking into account the drivers' delay in response. The lattice versions of the hydrodynamic model are described by the differential-difference equation and difference-difference equa- tion, respectively. The stability conditions for the two models are obtained by using the linear stability theory. The modified KdV equation near the critical point is derived to describe the traffic jam by using the reductive perturbation method, and the kink-antikink soliton solutions related to the traffic density waves are obtained. The results show that the drivers' delay in sensing headway plays an important role in jamming transition.

基于驾驶员意图采集的车辆状态控制系统分析

驾驶员操作意图是整车状态变化的基础,对整车运行具有重要影响。以驾驶员操作意图为研究的出发点,对驾驶员执行车辆各种操作时,车辆的状态进行分析,主动包括启动自检工况,档位变化、加速、制动、转向等工况;基于分析结果对各工况的控制流程进行分析和设计;提出了实现车辆基本功能的控制模式,并对控制电路进行设计。在此基础上,应用实车调试,对控制系统进行了测试。结果可知:对车辆进行准确控制的前提是对驾驶员意图进行准确的分析采集,控制流程应简洁明了,尽可能减少控制器的执行周期,缩短控制周期;实车测试表明系统能准确的实现驾驶员的操作意图,实现加速、减速、制动等,表明所设计的控制系统的可靠性与准确性,为此类设计提供参考。

基于Driver Studio的PCI设备WDM驱动程序的设计

为了实现PCI数据采集卡的数据传输,必须开发PCI设备的驱动程序。介绍了以DriverStudio中的Driver Works为工具,开发PCI设备WDM驱动程序的方法。探讨了PCI设备的I/O端口访问、中断处理、驱动程序与应用程序之间的通信等主要问题,重点对编写驱动程序的过程和主要例程的代码进行了说明,并实现了驱动程序的安装与调试。最后对实际中遇到的问题及解决方法做了总结,实践证明该驱动程序调试通过,运行稳定。

基于自然驾驶数据的驾驶换道风格分析与辨识

为了研究在换道工况下个体驾驶行为及其辨识,基于NGSIM轨迹数据提取532组换道有效数据。分析处理驾驶员换道特征参数,运用K-means算法对驾驶员进行聚类分析,可分为谨慎型、一般型、激进型三类。并对聚类的参数进行统计分析和时频分析验证各类驾驶人的差异性,并提取出有效参数作为辨识模型的输入,基于惯性权重非线性变化和粒子最大速度非线性递减的策略来改进粒子群,建立起基于改进粒子群优化SVM的驾驶人风格辨识模型,对SVM模型的两个关键参数C和g进行优化更新,驾驶人识别准确率可达到96.25%,且与BP神经网络、PSO-SVM、随机森林、KNN算法相比具有更高的识别准确率。

新疆农业源非二氧化碳温室气体排放变化趋势预测

基于2000-2020年新疆农作物产量、化肥投入、稻田播种面积等统计数据,根据IPCC排放因子法,核算新疆农业源非CO_(2)温室气体(GHG)排放总量,通过对数平均迪氏指数(LMDI)模型对农业源非CO_(2)GHG排放驱动因素进行分解,使用蒙特卡洛模拟结合情景分析法预测其排放趋势。结果表明,研究期内新疆农业源非CO_(2)GHG排放呈现波动上升趋势,增幅达到34.43%,畜牧养殖是主要排放源。驱动因素研究结果表明,2000-2020年,农业经济发展水平和城镇化水平的提高促进了农业源非CO_(2)GHG的排放,贡献排放量分别达4211.74×10^(4)tCO_(2)eq和1016.08×10^(4)tCO_(2)eq。农业非CO_(2)GHG排放强度、乡村人口以及农业结构的降低抑制了农业源非CO_(2) GHG的排放,2000-2020年减排量分别为4163.36×10^(4)tCO_(2)eq、224.84×10^(4)tCO_(2)eq和130.64×10^(4)tCO_(2)eq。农业源非CO_(2)GHG排放在基准和规划情景下均呈上升趋势,但规划情景下的增速快于基准情景,在低碳情景下通过提高农业非CO_(2)GHG排放强度、改善生产结构有效减缓增速,可能在2035年实现负增长。实现农业源非CO_(2)GHG排放达峰需要强化对减排政策的落实,强制约束农业源非CO_(2)GHG排放;降低农业非CO_(2)GHG排放强度,控制因农业生产技术落后所导致的农业源非CO_(2)GHG排放;通过完善减排惩戒激励机制,鼓励技术突破引导新疆农业的低碳转型。

基于自适应PI模型的压电陶瓷驱动器精密定位方法

由于具备较高的定位精确度,压电陶瓷驱动器在超精密加工、微纳米测试等领域应用广泛,然而压电陶瓷固有的迟滞性严重影响其定位精确度。研究了驱动范围对压电陶瓷驱动器迟滞性的影响,实验得出迟滞性随驱动范围增大而显著。而在压电陶瓷驱动器的实际应用中,驱动范围是其主要的设置参数之一。为此,提出基于自适应Prandtle-Ishlinskii(PI)模型的拟合方法,根据不同驱动范围下获得的迟滞曲线的斜率变化趋势设置分段区间,采用二次规划算法辨识PI模型的权重参数,基于分段区间对迟滞曲线进行拟合,大大提高了拟合精确度。设计基于自适应PI模型的逆模型作为前馈控制器对压电陶瓷驱动器进行迟滞补偿,并搭建基于Labview的实验平台验证了该算法的可行性。实验结果表明,基于自适应PI逆模型的前馈控制器将压电陶瓷驱动器的定位精确度提高至1.8 nm。

驾驶员对高速公路收费政策调整满意度的影响因素研究

为了研究高速公路收费费率调整和驾驶员满意度之间的关系,选取了8个相关因素,以重庆市为例,通过调查问卷、实地勘察、数据分析等方式获取调查数据,并选择基于有序Logit研究模型,从个人方面、车辆因素、出行因素、政策方面等四个维度考虑,最后进行实证结果分析。研究得出:驾驶员的年龄、收入、出行距离、出行时间、出行目的、是否办理ETC、是否了解调价政策和驾驶员满意度之间存在显著相关关系;其中,驾驶员的年龄和驾驶员满意度之间存在负相关关系;驾驶员的收入、出行距离、是否了解调价政策和驾驶员满意度之间存在正相关关系。

基于多尺度骨架图和局部视觉上下文融合的驾驶员行为识别方法

识别非驾驶行为是提高驾驶安全性的重要手段之一。目前基于骨架序列和图像的融合识别方法具有计算量大和特征融合困难的问题。针对上述问题,本文提出一种基于多尺度骨架图和局部视觉上下文融合的驾驶员行为识别模型(skeleton-image based behavior recognition network,SIBBR-Net)。SIBBR-Net通过基于多尺度图的图卷积网络和基于局部视觉及注意力机制的卷积神经网络,充分提取运动和外观特征,较好地平衡了模型表征能力和计算量间的关系。基于手部运动的特征双向引导学习策略、自适应特征融合模块和静态特征空间上的辅助损失,使运动和外观特征间互相引导更新并实现自适应融合。最终在Drive&Act数据集进行算法测试,SIBBR-Net在动态标签和静态标签条件下的平均正确率分别为61.78%和80.42%,每秒浮点运算次数为25.92G,较最优方法降低了76.96%。

基于LQR的智能驾驶汽车横纵向控制研究

为了提高智能驾驶汽车跟踪控制器的稳定性和跟踪精度,提出了一种基于线性二次型调节器(LQR)控制算法和驾驶员预瞄模型的横向跟踪控制策略,结合纵向比例-积分-微分(PID)控制算法实现横纵向控制。首先建立带有前馈的LQR控制器,采用梯度下降优化算法优化LQR控制器权重参数,并在此基础上引入驾驶员预瞄模型,设计了基于经验的预瞄距离自适应控制器;其次建立双PID纵向控制器进行速度控制。最后通过Carsim和Matlab/Simulink联合仿真以及实车测试验证,结果表明:仿真工况下最大横向偏差小于0.035 m,最大航向偏差小于0.09 rad,实车测试工况下也能够良好遵循规划轨迹的整体趋势,速度跟踪效果良好且前轮转角与横摆角速度变化平稳。因此,该控制器能够保证较高精度且平稳的轨迹跟踪,在高速状态下更为明显。

直线变压器驱动源磁芯磁化过程的仿真研究

磁芯行为对于异常工况下直线变压器驱动源(linear transformer driver,LTD)的输出特性具有很大的影响,为了预测磁芯剩磁状况,为LTD装置调试和运行提供指导,基于磁芯的测试结果构建了准确的数值模型,并应用于LTD的电路仿真。基于4级串联共用腔体LTD数值仿真研究了开关理想时序放电、开关异常自放电、开关非理想时序触发放电及去磁状况下各级磁芯的磁场强度和磁感应强度变化过程。在±70 kV充电电压下的理想时序放电后,各级磁芯最大剩磁变化量为1.27 T,稳态剩磁约为-0.38 T;在±70 kV充电电压下的单支路开关自放电引起的磁芯最大剩磁变化量为1.88 T,稳态剩磁约0.39 T,多支路开关同时自放电将使磁芯快速饱和;当触发时序系数的绝对值>1时,除最先放电的模块,其余模块磁芯先受到反向励磁,然后再正常磁化;去磁过程中越靠近负载的磁芯越早被去磁,磁场强度随着各级磁芯依次去磁而呈现阶梯式上升。该研究结果能够有效地模拟各种工况下LTD磁芯的磁化过程与剩磁状态,判断当前磁芯剩磁对下一次放电脉冲的影响。

Parallel Distributed Compensation/H∞Control of Lane‑keeping System Based on the Takagi‑Sugeno Fuzzy Model

Current research on lane-keeping systems ignores the effect of the driver and external resistance on the accuracy of tracking the lane centerline.To reduce the lateral deviation of the vehicle,a lane-keeping control method based on the fuzzy Takagi-Sugeno(T-S)model is proposed.The method adopts a driver model based on near and far visual angles,and a driver-road-vehicle closed-loop model based on longitudinal nonlinear velocity variation,obtaining the expected assist torque with a robust H∞controller which is designed based on parallel distributed compensation and linear matrix inequality.Considering the external influences of tire adhesion and aligning torque when the vehicle is steering,a feedforward compensation control is designed.The electric power steering system is adopted as the actuator for lane-keeping,and active steering redressing is realized by a control motor.Simulation results based on Carsim/Simulink and real vehicle test results demonstrate that the method helps to maintain the vehicle in the lane centerline and ensures driving safety.

长白山地区土壤水蚀时空演变特征及驱动因素分析

探讨长白山地区受极端降水、地形复杂、植被破坏等因素影响造成的土壤侵蚀状况,可以研判该地区水土流失情况,为当地水土生态保护提供科学参考。利用修正的通用土壤流失方程(RUSLE)、趋势及相关分析法,定量分析长白山地区土壤水蚀的空间格局及时空分布特征,并探究土壤水蚀与气候、植被覆盖度及地形驱动因子的关系。结果表明:2000-2020年长白山地区土壤水蚀模数均值总体呈“西南高,东北低”的空间格局。相较于其他地类,草地、未利用地、林地更易发生土壤水蚀。近21 a来,土壤水蚀模数平均以0.0255 t/(hm^(2)·a)的速度上升,土壤水蚀模数表现为上升趋势的地区占研究区总面积的68.3%,侵蚀等级总体以微度和轻度为主,且轻度侵蚀比例也呈增加趋势,表明该地区土壤侵蚀状况趋于好转,未来吉林市中北部和延边州部分地区的水土流失风险较高。土壤水蚀与降水、海拔高度及坡度具有较为显著的正相关关系,而与气温、植被覆盖度的相关性以负相关为主。海拔大于1000 m或坡度大于20°的草地、林地区域是水土防治的重点地形区。

基于模型预测的智能汽车辅助驾驶控制研究

辅助驾驶控制是智能汽车的重要功能,可有效协助驾驶员完成驾驶操作,减少驾驶疲劳并提升驾驶安全。智能车辆的辅助驾驶控制需要在不干扰驾驶员的情况下,提供合适的车辆运动控制量并防止可能发生的碰撞。文章提出了一种基于模型预测控制的智能汽车辅助驾驶控制方法。该控制方法在驾驶员正常操作时符合驾驶员的操作特性,在可能发生碰撞时纠正驾驶员的转向操作,能够保证安全性且不干扰驾驶员。为了避免与周围车辆的碰撞,基于周围车辆位置建立约束条件,并引入模型预测辅助驾驶控制设计。通过仿真研究验证了所提出的辅助驾驶控制方法,结果表明,所提出的预测控制方法可以帮助驾驶员避免与附近车辆可能发生的碰撞,从而保证智能汽车的行驶安全。

基于Minidriver的MPEG-4视频流实时播放

介绍了DirectShow对WDM设备的支持及Minidriver驱动程序的工作原理,实现了基于StreamingMinidriver的MPEG-4视频流的实时接收、解码和播放。实验证明,该系统能实时接收播放多种格式视频流,图像清晰、流畅,控制灵活。

考虑驾驶员记忆的多前车速度差跟驰模型研究

为了探究驾驶员记忆和多前车速度差对交通流的影响,本文基于全速度差模型(full velocity difference model,FVDM),结合驾驶员记忆因素和多前车对跟驰车的作用,构建了一种考虑了驾驶员记忆和多前车速度差的跟驰模型。通过改进模型的线性稳定性特征,得出改进模型的稳定性条件。再对改进模型下的车流启动和制动过程进行仿真,并与FVDM的仿真结果作对比。然后采用微小扰动法对改进模型进行数值仿真,研究驾驶员记忆因素和多前车速度差对交通流稳定性的影响。最后,利用下一代仿真(next generation simulation,NGSIM)数据标定了改进模型的参数,并预测了其加速度。研究结果表明:驾驶员记忆在一定程度上不利于交通流的稳定,而多前车速度差对稳定交通流具有积极作用;与FVDM相比,改进模型的启动延迟和制动延迟分别降低了10.0%和19.0%,预测精度更高,均方根误差降低了24.3%。

Simulation of automobile fuel consumption and emissions for various driver's manual shifting habits

The effects of different habits of the drivers on gear shifting strategies for manual powertrain were investigated. For the realization of simulation, the shifting habits of the drivers were conducted in the Advisor software to investigate and compare the emission rates. Simulation was developed based on the optimal gear shifting strategy and criteria and was validated both in fuel economy and emissions by analyzing the results in the various driving cycle and driving styles. To explore an optimal gear shifting strategy with best fuel economy and lowest emission for a manual transmission, a strategy was designed with a highest possible gear criterion as long as the torque requirement can be satisfied. Based on two different criteria, namely the engine working conditions and the driver's intention, the governing parameters in decision making for gear shifting of manual transmission in conventional engine were discussed. It is also shown that the optimum gear shifting strategy is based on that both the engine state and the driver's intention eliminates unnecessary shiftings that are present when the intention is overlooked. The optimum shifting habit and the best driving cycle in terms of minimum emissions and fuel consumption were proposed.