Connected and Autonomous Vehicles (CAVs) Challenges with Non-motorized Amenities Environments

With the deployment of Connected and Automated Vehicles in the coming decades,road transportation will experience a significant upheaval.CAVs(Connected and Autonomous Vehicles)have been a main emphasis of Transportation and the automotive sector,and the future of transportation system analysis is widely anticipated.The examination and future devel­opment of CAVs technology has been the subject of numerous researches.However,as three essential kinds of road users,pedestrians,bicyclists,and motorcyclists have experienced little to no handling.We explored the influ­ence of CAVs on non-motorized mobility in this article and seven various issues that CAVs face in the environment.

Cooperative Anti-Jamming and Interference Mitigation for UAV Networks: A Local Altruistic Game Approach

To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.

Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

Investigation and Optimization of Priority for Non-motor Vehicles in the Old Urban Area of Nanchang

Under the background of"people-oriented"thought and"green transportation",the idea of"priority for non-motor vehicles"came into being,which can improve the riding environment of non-motor vehicle riders to a certain extent.According to the current situation of priority for non-motor vehicles in the old urban area of Nanchang,through field investigation,questionnaire investigation and interview,this study summarized the existing problems,and put forward optimization suggestions for these problems,in order to provide reference for areas with similar conditions.

Reentry Attitude Tracking Control for Hypersonic Vehicle with Reaction Control Systems via Improved Model Predictive Control Approach

This paper studies the reentry attitude tracking control problem for hypersonic vehicles(HSV)equipped with reaction control systems(RCS)and aerodynamic surfaces.The attitude dynamical model of the hypersonic vehicles is established,and the simplified longitudinal and lateral dynamic models are obtained,respectively.Then,the compound control allocation strategy is provided and the model predictive controller is designed for the pitch channel.Furthermore,considering the complicated jet interaction effect of HSV during RCS is working,an improved model predictive control approach is presented by introducing the online parameter estimation of the jet interaction coefficient for dealing with the uncertainty and disturbance.Moreover,considering the strong coupling effect between the yaw channel and roll channel,a coupled model predictive controller is designed by introducing the feedback of sideslip angle into the roll control channel to eliminate the coupling effect.Finally,the comparison simulations using the classical control method,MPC and IMPC approach are given to demonstrate the effectiveness and efficiency of the presented IMPC scheme.

基于马尔可夫过程的电动汽车电驱动系统共模干扰抑制方法研究

针对电动汽车电驱动系统的共模干扰问题,提出了一种基于马尔可夫(Markov)过程的三段式伪随机载波频率等效零矢量脉宽调制(PRF-AZSPWM)策略。在等效零矢量作用的基础上,该策略引入双态Markov链生成随机合成信号,使载波频率在一定范围内随机变化,同时选择合适的传递概率,将谐波能量扩展到更宽的频率范围。仿真结果表明,提出的方案有效降低了电驱动系统的共模干扰水平,并通过样机试验进一步证明了提出策略的有效性。

Bivariate macro-level safety analysis of non-motorized vehicle crashes and crash-involved road users

The high risk of injury resulting from non-motorized vehicle(NMV)crashes has created the goal of using the 3E strategy to comprehensively improve NMV safety.Traditional safety improvement methods identify hot zones generally by crash frequency or density,which is effective for roadway engineering improvements but neglects characteristics related to other improvements such as safety education.As safety education would be more effective if targeted at the residences of crash-involved road users,the traditional approach to hot zones may therefore provide biased results for such alternative countermeasures.After confirming that 77.17%of NMV crashes occurred outside the involved riders’areas of residence,this study compared the differences between the locations of crashes and the residences of NMV crash-involved riders in safety influencing factors and hot zone identification.A Poisson lognormal bivariate conditional autoregressive(PLN-BCAR)model was developed to account for potential correlations between crashes and involved riders.The model was compared with the univariate Poisson lognormal conditional autoregressive(UPLN-CAR)model and the bivariate Poisson lognormal conditional autoregressive(BPLNCAR)model;the PLN-BCAR model outperformed the other two models in its better interpretation of the influencing factors and its more efficient parameter estimation.Model results indicated that crashes were mainly associated with roadway and land use characteristics,while involved road users were mainly associated with socioeconomic and land use characteristics.The potential for safety improvement method was adopted to identify hot zones for countermeasure implementation.Results showed over 60%of the identified hot zones were inconsistent:they needed improvement in either engineering or education but not both.These findings can help target the type of improvement to better utilize resources for NMV safety.

异常点云干扰下的车身构件鲁棒性配准方法

点云配准是大型车身构件位姿参数测量的关键方法,但现有算法在大量异常点云干扰下难以配准至有效位姿,从而导致匹配失真,进而无法保证后续机器人作业质量。针对此问题,提出一种能够有效抑制异常点云干扰的车身构件鲁棒性配准算法——鲁棒函数加权方差最小化(RFWVM)算法。建立鲁棒函数加权目标函数,通过施加随迭代次数可变的动态权重来抑制配准过程中异常点云的影响,并由高斯-牛顿法迭代完成刚性转换矩阵的求解。以高铁白车身侧墙、汽车车门框为研究对象的试验结果表明,较经典的最近点迭代(ICP)算法、方差最小化(VMM)算法、加权正负余量方差最小化(WPMAVM)算法和去伪加权方差最小化(DPWVM)算法,所提出的RFWVM算法配准精度更高,能够有效抑制各种异常点云对配准结果的影响,并具有更好的稳定性和鲁棒性,能够有效实现各类车身构件点云的精确配准。

外界干扰下车对车2×2 MIMO-VLC系统研究

为了研究干扰车辆和穿越道路行人对车对车可见光通信系统的影响,本文提出了带有外界干扰的车对车2×2 MIMO可见光通信模型.该模型以基于市场加权灯束模型的汽车前照灯作为2个发射器,以光电探测器作为2个接收器,考虑了间隔车道车辆和过道行人对系统性能的影响.研究结果表明:当误码率小于为10^(−4)时,同道、邻道和间隔车道车辆的纵向通信距离分别为:28 m、5~18 m、0 m;间隔车道的两车不能直接通信,但其前照灯发射光线会进入信号接收车辆从而对正常通信两车产生影响;行人穿越道路会使正常通信两车的误码率产生较大波动且存在积极影响,正常通信两车横向距离越大积极影响占比越高;本文提出的模型考虑了行人和车辆的干扰,为改善可见光通信在复杂交通网的应用效果提供了理论依据.

基于RadTransformer神经网络的辐射场强预测

研究板级辐射干扰时,由于PCB内部信号频率极高、走线结构复杂,难以精准分析干扰传播路径和提取路径上的寄生参数,导致建模时考虑因素不全,仿真的辐射场强值不够准确。因此,利用多头自注意力神经网络自研RadTransformer模型,结合CST软件,对车载指示灯系统的辐射场强进行快速准确的预测。首先依据国家标准GB/T 18655-2018进行辐射发射试验,同时搭建对标实际测试环境的仿真模型,获取预测数据集。选取与辐射场强相关的三个重要参数:共模电流、传递函数、天线系数,利用RadTransformer模型提取它们对辐射场强的注意力特征值,预测指定频率下的辐射场强值。研究结果表明,该模型预测的方法兼具准确性与快速性,预测时间仅用时0.1 ms,平均误差值仅为2.0,相比于基准模型平均误差值减少了30%。

四轮转向干预下电动助力转向控制策略研究

四轮转向(4WS)车辆相较于前轮转向(FWS)车辆具有更高的灵活性,其后轮转向在提高车辆操稳性的同时转向阻力矩也发生变化,使得原电动助力转向系统助力策略与四轮转向车辆不匹配,对行车安全产生影响.本文以线性二自由度车辆模型为基础,对比分析了前轮转向车辆与四轮转向车辆的转向特性,提出电动助力转向修正控制策略.仿真结果表明,角阶跃工况下,有助力修正的四轮转向车辆,驾驶员操纵方向盘力矩与驾驶前轮转向车辆基本一致,既保证了四轮转向车辆低速时的操纵轻便性,也兼顾了高速时的操纵稳定性.

无线紫外光中继协作无人机集结编队方法

为了解决无人机集结编队时机间通信易受强电磁干扰问题,采用紫外信标模型完成集群无人机的信息交互,从而实现集结定位,将一致性理论与无线紫外光虚拟势场避障法相结合,在空中集结时使无人机编队的飞行姿态、航向角以及速度保持一致,以跟随无人机作为中继节点,提升相邻无人机发现概率,提高编队队形准确性;同时提出无线紫外光通信协作无人机中继集结编队方法,实现了无人机编队快速准确形成期望编队队形。结果表明,所提方法使得无人机四边形编队、五边形编队、六边形编队的通信可靠性分别提升了7.69%、9.41%和10.0%。该研究为无人机编队集结方法和无人机编队中的机间通信提供了一定的理论参考。

无人机数据链射频前端高强辐射场干扰效应研究

针对四旋翼无人机(UAV,unmanned aerial vehicle)数据链在低空飞行时易受高强辐射场(HIRF,high intensity radiated field)干扰的问题,本文采用场-路联合仿真的方法对其进行干扰效应的研究。首先,利用电磁仿真软件探究UAV整机模型在HIRF下的天线耦合效应,并对不同辐照方向、信号类型和脉宽系数下的耦合电压进行分析;其次,通过电路设计分析软件对数据链射频(RF,radio frequency)前端电路进行注入仿真并分析干扰效应。结果表明,脉宽系数越小,高斯脉冲造成的干扰越强,相同脉宽系数下的调制高斯脉冲造成的干扰强于高斯脉冲;干扰信号的加入会导致射频前端中频(IF,intermediate frequency)输出信号的峰值显著增大,峰值频率发生偏移以及信噪比降低。

基于L-SHADE算法的AUV载体磁干扰参数辨识的数值模拟

采用自主水下航行器(Autonomous Underwater Vehicle,AUV)磁测平台可开展海洋地磁场测量、水下磁性目标探测和识别等工作,AUV磁测平台具有广阔的应用前景,但目前AUV载体磁干扰补偿技术研究尚不成熟,制约着水下航行器测磁精度。基于磁测平台抗磁干扰基本原理,提出一种基于线性种群规模缩减和成功历史的参数自适应差分进化(Success History-based Adaptive Differential Evolution with Linear Population Size Reduction,L-SHADE)算法的AUV载体磁干扰参数辨识的数值模拟方法。用磁偶极子和旋转椭球壳混合模型来等效模拟AUV载体磁干扰,通过模拟航行获得多组磁测数据,据此建立磁干扰参数辨识模型,并采用L-SHADE算法求解。通过数值模拟实验定量分析研究磁测平台测磁精度随磁传感器、平台姿态及航向等误差的传播规律。研究结果表明:当磁传感器测量精度为10 nT、姿态测量精度为0.01°、航向测量精度为0.1°时,测磁误差可小于100 nT。设计的AUV磁测平台抗干扰试验表明,地磁场总量最大相对误差为1.07%。

红山台地磁观测车辆干扰特征研究

近年来,红山台地磁观测数据中多次出现因车辆干扰而引起的异常变化,对台站观测资料的完整率产生相当程度的影响。在红山台实地开展车辆干扰影响实验的基础上,本文重点分析了轻型卡车及其他不同类型车辆在公路行驶过程中对地磁观测数据的影响特征。结果表明,车辆对观测数据产生的干扰影响与其使用的材质密切相关,车辆铁磁性材质的磁化率值越大,影响的距离越远。干扰的强度随着距离增大逐渐衰减,轻型卡车在距离测点300 m处、重型卡车在距离测点120 m处,两者的干扰影响基本消失。轻型卡车干扰幅度的理论值和实验值一致性较好,重型卡车干扰幅度的理论值和实验值却相差很大。这种差异可能还与不同类型车辆的构造、大小、体积和设计的差异有关。结合观测数据各分量受车辆干扰所表现的形态,初步判断车辆产生的干扰磁场总体呈现出磁轴与地面平行的偶极子磁场特征。此外,频谱分析表明,D和H分量均在车辆行驶时间段出现明显的谱峰,车辆行驶速度越快频率越高。此项工作可为今后识别地磁观测数据中的车辆干扰影响提供依据。

具有软启动功能的EMI直流滤波器设计

宽禁带半导体器件的应用使电动汽车的电机驱动系统更加小型化和轻量化,但也引发了更为严重的电磁干扰,使得驱动系统的可靠性面临严峻挑战。为此,以24 V/2 A的EMI直流滤波器为例,通过噪声源、滤波器原理及阻抗影响的分析,依据插入损耗指标进行滤波器参数设计。同时,考虑到整车启动时刻的启动冲击,加入软启动电路,进一步提高电动汽车驱动系统可靠性。实验测试验证了滤波器的电磁干扰抑制效果和软启动性能,证明了滤波器设计的可行性和有效性。

考虑右转车干扰的信号交叉口直行车辆轨迹预测

相交道路右转车辆干扰下的直行车辆轨迹扰动现象成为城市道路信号交叉口交通运行的安全隐患,为提高直行车驾驶人对驶入右转车辆的应对能力并做出正确决策,对于直行车辆扰动轨迹的可靠预测至关重要。研究通过将不同状态下的直行车辆轨迹分布特征与相交道路右转车运行信息相关联,在车辆受扰轨迹识别的基础上将碰撞时间(TTC)指标作为输入层加入模型,构建了3层高斯混合-输入输出隐马尔可夫模型(GMM-IOHMM),提出了一种考虑信号交叉口被交道路右转车对本面直行车作用程度的直行车辆受扰轨迹预测方法。实验结果表明:改进模型相比于传统的隐马尔可夫模型(HMM)在模型训练时能够更好地拟合实际的轨迹数据,且相比于传统的时间序列模型,GMM-IOHMM模型的拟合效果取得较大提升;可将TTC≤4.5 s且偏航角大于2.35°作为直行车辆轨迹扰动的判别标准。轨迹预测结果能够更加准确地判断直行车辆与周围车辆发生冲突的可能性,可作为受扰直行车及同行其他车辆辅助驾驶系统设计的重要依据。

Nakagami-m信道下无人机辅助的速率分拆多址接入协作通信系统性能研究

针对多用户通信资源短缺、分配不均衡的问题,该文研究了基于速率分拆多址接入技术(RSMA)的无人机(UAV)辅助多用户下行通信网络。在复杂的实际通信环境中,频率复用所引起的无用信号的干扰不可避免,考虑无人机与各用户节点信息传输受共道干扰影响,在Nakagami-m衰落信道下推导了该无人机协作通信系统的中断概率和信道容量的精确闭式表达式,证明共道干扰的存在使得高信噪比(SNR)区域系统的分集阶数为0。结果表明,在相同的空间模型下,采用RSMA通信方案的系统性能优于非正交多址(NOMA)方案;无人机飞行速度增大时,地-空通信建立视距链路的概率降低,系统中断性能下降。因此,在满足用户实际通信的需求时需要综合考虑无人机飞行速度、多址接入方式、系统性能以及通信连通性,以实现对无人机通信系统整体的有效权衡。

城轨车辆牵引系统电磁发射机理分析与滤波研究

城轨车辆牵引系统采用脉宽调制控制,具有高电压、大电流、脉冲干扰特性,作为主要的电磁干扰源之一,对列车系统的电磁兼容性产生重要影响;文章根据车辆系统设计,结合电磁干扰电流流通路径,分析牵引逆变系统主要电磁发射回路;通过建立高频干扰电流简化计算模型,研究减小牵引系统电磁发射的滤波参数设计方法,仿真对比各种滤波方案的抑制效果;最后,通过列车对外辐射发射测试验证优化方法的有效性。

基于FMCW毫米波雷达的舱内活体检测及干扰抑制方法

针对儿童被遗留在车内导致的事故频发问题,毫米波雷达由于隐私性好、成本低的优势成为舱内活体检测的主流选择。目前活体检测雷达把呼吸信号作为检测依据,但舱内密闭金属空间的强杂波干扰问题是主要的技术挑战。为解决此问题,提出一种时频域与幅度相位相结合的干扰抑制方法。首先,对时域信号提取的幅度和相位分别作傅里叶变换到频域;然后,将幅度频谱、相位频谱及去除帧间干扰后的时域幅度信号取模相乘生成干扰抑制图;最后,对干扰抑制图进行后处理得到活体检测结果。实测数据表明,该算法可以有效地抑制强杂波干扰,降低漏报和虚警的概率,完成舱内活体检测。