Road Friction Estimation under Complicated Maneuver Conditions for Active Yaw Control

Road friction coefficient is a key factor for the stability control of the vehicle dynamics in the critical conditions. Obviously the vehicle dynamics stability control systems, including the anti-lock brake system（ABS）, the traction control system（TCS）, and the active yaw control（AYC） system, need the accurate tire and road friction information. However, the simplified method based on the linear tire and vehicle model could not obtain the accurate road friction coefficient for the complicated maneuver of the vehicle. Because the active braking control mode of AYC is different from that of ABS, the road friction coefficient cannot be estimated only with the dynamics states of the tire. With the related dynamics states measured by the sensors of AYC, a comprehensive strategy of the road friction estimation for the active yaw control is brought forward with the sensor fusion technique. Firstly, the variations of the dynamics characteristics of vehicle and tire, and the stability control mode in the steering process are considered, and then the proper road friction estimation methods are brought forward according to the vehicle maneuver process. In the steering maneuver without braking, the comprehensive road friction from the four wheels may be estimated based on the multi-sensor signal fusion method. The estimated values of the road friction reflect the road friction characteristic. When the active brake involved, the road friction coefficient of the braked wheel may be estimated based on the brake pressure and tire forces, the estimated values reflect the road friction between the braked wheel and the road. So the optimal control of the wheel slip rate may be obtained according to the road friction coefficient. The methods proposed in the paper are integrated into the real time controller of AYC, which is matched onto the test vehicle. The ground tests validate the accuracy of the proposed method under the complicated maneuver conditions.

Safer Design and Less Cost Operation for Low-Traffic Long-Road Illumination Using Control System Based on Pattern Recognition Technique

The paper covers analysis and investigation of lighting automation system in low-traffic long-roads. The main objective is to provide optimal solution between expensive safe design that utilizes continuous street lighting system at night for the entire road, or inexpensive design that sacrifices the safety, relying on using vehicles lighting, to eliminate the problem of high cost energy consumption during the night operation of the road. By taking into account both of these factors, smart lighting automation system is proposed using Pattern Recognition Technique applied on vehicle number-plates. In this proposal, the road is sectionalized into zones, and based on smart Pattern Recognition Technique, the control system of the road lighting illuminates only the zone that the vehicles pass through. Economic analysis is provided in this paper to support the value of using this design of lighting control system.

Evolution of Road Traffic Congestion Control:A Survey from Perspective of Sensing,Communication,and Computation

Road traffic congestion can inevitably de-grade road infrastructure and decrease travel efficiency in urban traffic networks,which can be relieved by employing appropriate congestion control.Accord-ing to different developmental driving forces,in this paper,the evolution of road traffic congestion control is divided into two stages.The ever-growing num-ber of advanced sensing techniques can be seen as the key driving force of the first stage,called the sens-ing stage,in which congestion control strategies ex-perienced rapid growth owing to the accessibility of traffic data.At the second stage,i.e.,the communica-tion stage,communication and computation capabil-ity can be regarded as the identifying symbols for this stage,where the ability of collecting finer-grained in-sight into transportation and mobility reality improves dramatically with advances in vehicular networks,Big Data,and artificial intelligence.Specifically,as the pre-requisite for congestion control,in this paper,ex-isting congestion detection techniques are first elab-orated and classified.Then,a comprehensive survey of the recent advances for current congestion control strategies with a focus on traffic signal control,vehi-cle route guidance,and their combined techniques is provided.In this regard,the evolution of these strate-gies with continuous development of sensing,com-munication,and computation capability are also intro-duced.Finally,the paper concludes with several re-search challenges and trends to fully promote the in-tegration of advanced techniques for traffic congestion mitigation in transportation systems.

Survey of Controllable Suspension System for Off-road Vehicles

The controllable suspension system can improve the performances of off-road vehicles both on road and cross-country. So far, four controllable suspensions, that is, body height control, active, semi-active and slow-active suspensions, have been developed. For off-road vehicles, the slow-active suspension and the semi-active suspension which have controllable stiffness, damping and body height are more appropriate to use. For many years, some control methodologies for controllable suspension systems have been developed along with the development of modern control theory, and two or more original control methods are integrated as a new control method. Today, for military or civilian off-road vehicles, the R&D of controllable suspension systems is ongoing.

Road vehicle-induced vibration control of microelectronics facilities

A hybrid control platform is investigated in this paper to mitigate microvibrations to a group of vibration-sensitive equipment installed in a microelectronics facility subject to nearby road vehicle-induced horizontal and vertical ground motions. The hybrid control platform, on which microelectronics equipment is installed, is mounted on a building floor through a series of passive mounts and controlled by hydraulic actuators in both horizontal and vertical directions. The control platform is an elastic body with significant bending modes of vibration, and a sub-optimal control algorithm is used to manipulate the hydraulic actuators with actuator dynamics included. The finite element model and the equations of motion of the coupled platform-building system are then established in the absolute coordinate to facilitate the feedback control and performance evaluation of the platform. The horizontal and vertical ground vibrations at the base of the building induced by nearby moving road vehicles are assumed to be stationary random processes. A typical three-story microelectronics building is selected as a case study. The case study shows that the vertical vibration of the microelectronics building is higher than the horizontal. The use of a hybrid control platform can effectively reduce both horizontal and vertical microvibrations of the microelectronics equipment to the level which satisfies the stringent microscale velocity requirement specified in the Bolt Beranek & Newman (BBN) criteria.

车内单座椅局部区域有源噪声控制研究

目前,汽车局部区域降噪主要通过有源降噪头枕来降低人耳处的噪声,但乘客的移动会影响降噪效果.结合人头跟踪系统可解决这一问题,代价是增加系统的复杂性和成本.以车门扬声器为次级声源,在副驾驶位置乘客头部周围较大的区域进行局部降噪,并优化误差传感策略提升其降噪性能.首先,建立轻度阻尼边界的闭空间声场有限元模型;然后,基于该模型研究了某一局部区域内取得3 dB降噪效果的频率上限、误差点数量和位置对降噪效果的影响以及误差点布放的优化问题;最后,在典型城市道路上进行不同车速下的有源噪声控制实验.结果表明,车速为50,60和80 km·h^(-1)时,副驾驶头部区域内(0.4 m×0.4 m×0.2 m)3 dB降噪的频率上限约为370 Hz,误差点位置对降噪效果有较大影响.采用遗传算法优化误差点选择可提高降噪性能,使用12个优选误差点即可达到使用75个均匀布放误差点的降噪效果.

考虑道路可用宽度的自适应避撞控制

针对紧急避撞中车辆避开障碍物后回归直线行驶时容易出现过多转向性失控问题,提出一种利用道路空间换取车辆稳定性的解决方案——考虑道路可用宽度的自适应避撞控制方法。首先搭建7自由度车辆模型,基于最优控制和MPC理论设计避撞控制器,并通过大量仿真再现过多转向失控工况,进而对失控工况的车辆输入与车辆状态进行剖析,明晰车辆失控机理。接着基于失控机理设计考虑道路可用宽度的自适应避撞控制系统,其中包括基于深度神经网络的参数自适应控制,基于启动车速的介入准则以及基于Lyapunov保守稳定域的切出时机。仿真实验证明,所提出的自适应避撞控制策略可以充分利用当前道路可用宽度,在避撞后回归直线行驶时提高车辆稳定性,从而达到避免事故发生的效果,弥补了传统定参数控制器无法适应复杂多变工况的缺陷。最后,基于dSPACE硬件在环实验,验证了所提出控制策略的实时性能够满足紧急工况避撞要求。

“一带一路”共建国家结核病流行及控制现状分析

目的:分析“一带一路”共建国家2021年结核病(TB)的流行现状、患者发现及治疗转归等控制相关情况。方法:选择与我国签署了共建“一带一路”合作文件的151个国家作为研究对象;数据资料来源于2022年全球结核病年报。分析151个国家2021年发病和死亡负担,以及患者发现及治疗转归。结果:2021年151个国家总人口为36.91亿,约占全球总人口的46.84%。结核病发病患者为645.70万例,占全球总发病患者数的60.92%,发病率为174.94/10万;人类免疫缺陷病毒(HIV)感染阴性死亡患者数为81.62万例,占全球结核病总死亡患者的59.14%;耐多药/利福平耐药结核病(MDR/RR-TB)发病患者为26.37万例,占全球患者总例数的58.59%。TB/HIV患者为61.17万例,占全球87.01%;死亡患者为16.51万例,占全球88.32%。结核病发病和死亡主要分布在亚洲和非洲国家,且有8个国家为结核病、MDR/RR-TB、TB/HIV三项高负担国家。151个“一带一路”共建国家结核病患者发现率仅为56.00%,明显低于我国75.04%的发现率水平,也低于全球60.70%的平均水平。报告的肺结核患者经实验室诊断的比例为63.00%,与全球平均水平(63.47%)接近。151个国家中,仅有68个国家新发和复发患者治疗成功率≥85%;仅有19个国家复治结核病治疗成功率≥85%。结论:依托“一带一路”合作框架,建立不同疫情国家结核病防控经验的交流与合作机制,强化国家间传染病信息交流与共享,建立现代化国境检验检疫机制,不断降低各国结核病的流行。

考虑道路识别的四驱电动汽车再生制动策略

为了充分利用路面附着条件分配再生制动力,提高制动能量回收率,根据双电动机四驱结构电动汽车复合制动系统的特点,对其制动能量回收控制策略进行了研究.分析了驱动轮与地面附着特性,设计了道路识别器来计算每个轮胎与当前路面之间的峰值附着系数,并使用模糊控制策略确定每个车轮与8种道路的滑移率和附着利用率的相似输入.根据双电动机外部特性的制动力分配关系,提出了使更多制动能量回馈给电池的策略.结果表明:制动强度为0.3时,能量回收率为65.55%,具有较高的回收效率.

基于路面激励预瞄范围切换的主动悬架滑模控制

针对不同行驶工况下悬架控制力与实际路面激励反馈的不匹配问题,提出一种切换路面激励预瞄范围的主动悬架滑模控制方法。搭建由激光雷达、惯性测量单元和GPS(Global Positioning System)组成的路面预瞄系统,采集原始路面信息并完成数据坐标转换;建立车轮运动轨迹数学模型,根据该数学模型设计了预瞄范围切换的路面激励识别方法;以理想天棚模型为参考模型,设计主动悬架滑模控制器;仿真分析了直线工况和转向工况下的悬架动态性能。仿真结果表明,直线工况下,预瞄范围切换的主动悬架与预瞄范围固定的主动悬架系统动态性能一致;转向工况下,相比于预瞄范围固定的悬架,预瞄范围切换的悬架系统在簧载质量加速度均方根值和轮胎动载荷均方根值分别降低了8.42%和8.76%,验证了所提出控制方法对悬架动态性能提升的有效性。

履带车辆主动悬挂多点布置优化

为实现履带车辆主动悬挂减振性能和能耗达到综合最优,基于正交试验方法开展履带车辆主动悬挂多点布置优化设计。首先,建立了履带车辆悬挂系统动力学模型,并通过道路模拟试验验证了该模型的合理性;其次,开展了履带车辆悬挂系统正交试验,分析了4种典型路面下各子悬挂对悬挂系统减振性能影响的敏感性;最后,设计了主动悬挂作动器的6个布置方案,通过建立基于线性二次最优(linear quadratic regulator,简称LQR)控制的履带车辆主动悬挂动力学模型,分析了典型路面下各布置方案对悬挂系统减振性能的影响规律及能耗变化规律。结果表明,通过对履带车辆主动悬挂作动器的布置优化,可以实现悬挂减振性能和能耗之间的平衡。

基于本体和知识图谱的城市空间数字底座架构及应用

为支撑城市数字化转型,解决目前智慧城市数据不能满足多领域兼容覆盖的需要、数据孤岛等问题,本文提出融合城市动静态多源数据、城市数据运算方案和数据组织管理方案的城市空间数字底座的概念,进而提出一种依托本体框架的城市空间数字底座架构,以多源多模知识图谱为核心来管理城市治理的数据模块、数据运算模块、数据可视化模块和城市服务模块,使得所有数据和事件、行为都在同一框架与协议下运作。本架构有三个特点:①依托本体框架,构建语义解释器覆盖领域全要素,保证数据结构完整和质量可靠;②数据与业务脱钩,原始数据从具体事物中抽象出来,重构为知识单元,适度脱敏推动数据融合;③空间运算升级为知识运算,利用知识图谱通过知识推理、知识发现等来优化传统计算,拓展服务边界及节省运算资源。通过知识图谱的管理架构,可以保证城市空间数字底座的数据质量可靠性、完整性、可解释性和共享性,确保了空间数字底座对城市空间信息服务的支撑能力。

雨雾环境下城市道路动态控速技术与实现

针对雨雾环境下的行车安全问题,构建动态控速模型,旨在合理确定行车速度,减小不安全因素对行车安全的影响。利用小波降噪法对行车数据进行处理,通过长短期记忆神经网络(LSTM)方法对动态速度数据训练,并根据对应路段的历史车速预测新的车速,以预测车速的85%位车速作为参考,设置对应路段的限速值。为了检验所确定限速值的实际效果,以加减速力度、踩踏油门踏板及制动踏板的频率作为检测因子。实验结果表明,LSTM模型在处理对时间具有依赖性的交通速度预测问题上具有很好的优越性,在设定的新限速值下,驾驶员在行车过程中加、减速力度明显减弱,急加速和急减速频率减少,实验路段高速行驶车辆数量减少,交通流趋于平稳。

有轨电车通过平交路口车路协同速度控制系统

[目的]为解决有轨电车在平交路口必须降速的问题,提出一种有轨电车通过平交路口车路协同速度控制系统。[方法]分析了有轨电车平交路口运行特征;介绍了有轨电车通过平交路口车路协同速度控制系统的设计思路,以及控制算法模块的实现流程;对所提控制系统的实施效应进行分析。[结果及结论]所提控制系统通过车辆定位技术和清空区冲突检测技术,结合与路口交通信号机的通信,判定有轨电车通过路口的方式。当有轨电车获得通过路权且清空区无冲突时,采用可控实体隔离设施临时性地创建有轨电车通行的独享封闭区间,保障有轨电车安全高效地通过平交路口。所提控制系统可以实现有轨电车在信号绿灯条件下不减速通过路口。所提控制系统对于前后站台相距250 m以上的无站台平交路口适用性较好,其能提高约15%的运行速度,减少40%的区间运行能耗,同时还能减少因平交路口干扰造成站间运行时间的随机偏差。

矿用无人运输车辆轨迹跟踪控制算法研究

矿用无人运输车辆作业环境恶劣,存在大曲率弯道、坡道等非结构化道路明显特征,对无人化运输控制要求高。为改善PID等传统控制算法适应性问题,提高无人驾驶轨迹跟踪的车辆横纵向控制精度,提出一种纯跟踪与PID结合的多点预瞄横向控制、考虑模糊控制表参数拟合的纵向控制方法,减少控制参数的同时提高算法效果。根据传统控制算法设计基础控制器,结合基础算法优势进行横向与纵向控制算法设计,通过硬件在环仿真和实车测试验证算法的性能。试验结果表明,横向控制算法与斯坦利算法相比,车辆路径跟踪精度有明显改善,纵向控制方面,速度跟随误差<1 km/h,保证了车辆驾驶时的平稳性与舒适性。

基于浮动车轨迹数据的干线信号协调配时优化

为了提高城市干线的通行效率,缩短车辆在干线行驶时的平均延误,基于浮动车轨迹数据提出一种城市干线交通信号协调控制优化方法。该方法根据浮动车采集的时空轨迹数据,使用最大期望算法对混合车流(浮动车和其他车辆)到达率进行预测。结合信号状态,通过计算干线道路上、下行双向饱和度,以总延误最短为优化目标建立了干线协调配时优化算法,并采用遗传算法进行求解。以合肥市黄山路路段为例,比较无协调控制、传统定时协调控制和基于轨迹数据的信号协调控制。结果表明,所提供的方案可有效缩短干线交叉口车辆总延误,减少燃油消耗。

基于群体智能算法的巷道快速掘进自动化控制研究

以提高掘进效率、优化矿山资源的开采过程为目的,该文提出基于群体智能算法的巷道快速掘进自动化控制方法。采集掘进机截割电机的负载油缸压力、截割臂振动加速度和截割电机电流数据,将其输入到Q-RBF神经网络模型内,通过该模型迭代输出掘进机截割臂载荷信号,对该载荷信号转换成摆速后得到掘进机截割臂期望摆速,将期望摆速与实时摆速同时输入到模糊PID控制器内,并对模糊PID控制器参数进行整定处理,输出掘进机截割臂摆速控制参数,实现巷道快速掘进自动化控制。实验表明,该方法可实现掘进机截割臂摆速控制,超调数值较小,应用效果较为显著。

大跨度斜拉桥超长拉索多模态振动阻尼协同控制技术研究

沪苏通长江大桥是目前世界上最大跨度的公铁两用斜拉桥,其超长超重斜拉索振动模态复杂,振动控制难度大。通过理论分析结合现场实测,得出了适用于大跨度斜拉桥超长斜拉索多模态振动控制方法及技术。研究表明:实测分析超长斜拉索施工期的振动具有多模态特征,既有中低阶振动(5~15阶),也有高阶振动(46~50阶);提出的外置式杠杆质量阻尼器ELMD和摆锤式MTMD阻尼器协同控制分析方法,理论分析结果满足斜拉索多模态控制要求,有效振动控制范围提升至60阶;研发的新型ELMD阻尼器通过杠杆放大和齿轮放大作用,为斜拉索提供附加阻尼和附加惯质作用,中低阶实测阻尼对数衰减率δ≥3%;研发的摆锤式MTMD阻尼器,采用摆锤式结构,利用质量调谐作用实现斜拉索高阶减振,现场无肉眼可见振动;通过长期健康监测系统显示,台风“烟花”过境期间监测到的最大振动加速度为0.012g,大桥正常运营期间,斜拉索的振动加速度基本被控制在0.01g以下。

AMT车辆低附着路面起步控制研究

针对机械式自动变速器(AMT)车辆低附着路面起步行驶驱动轮打滑问题,以装备了6挡AMT的轻卡车型为研究对象,根据AMT系统与防抱死制动系统(ABS)轮速判断车辆低附着路面起步驱动轮打滑情况,对低附着路面车辆起步进行动力学分析,提出AMT车辆低附着路面起步控制策略,设计相应控制软件,在低附着路面进行实车测试验证。试验结果表明,该研究方法能够很好地满足AMT车辆低附着路面起步的要求,有效避免驱动轮打滑,提高车辆操纵稳定性,具有很强的实用性。

基于模型偏差学习的交通信号自适应优化方法

城市交通信号配时优化是保证交通系统整体运行效率的前提条件。传统基于模型的信号控制方法往往基于历史统计数据,并且底层交通流模型不可避免地存在模型偏差,影响控制方案的科学性及其实际应用效果。考虑模型与数据融合驱动,提出一种基于模型偏差学习的交通信号控制自适应优化方法,以最小化路网行程时间为目标,建立信号控制最优化模型。首先,针对交通流预测模型的模型偏差,引入偏差函数表示预测模型与实际交通流状态间的误差;其次,建立基于径向基函数(RBF)神经网络的偏差函数,结合实际交通流数据对模型偏差进行学习,提高偏差函数的拟合效果;在此基础上,提出考虑模型偏差信息的自适应优化方法,以提高信号控制方法的控制性能。以小型测试路网与实际路网为例进行算例分析,基于SUMO仿真对本文提出的模型偏差学习方法进行验证,考虑不同交通流量条件,与固定配时、模型预测控制进行比较,分析其控制性能指标。结果表明,模型与数据融合驱动的信号控制自适应优化方法能有效提高预测模型的准确性,降低路网行程时间,与基于模型的控制和模型预测控制方法相比路网累积行程时间平均减少了38.3%和25.6%,提升了路网的实际运行效果。最后在宣城实际路网的仿真验证了方法的有效性。