Vibration characteristics of sandwich plates with an auxetic honeycomb core and laminated three-phase skin layers under blast load

In this article,vibration characteristics of sandwich plates with an auxetic honeycomb core and laminated three-phase skin layers subjected to blast load are studied.Higher-order ES-MITC3 element based on higher-order shear deformation theory(HSDT)to achieve the governing equations.The sandwich plates with the ultra-light feature of the auxetic honeycomb core layer(negative Poisson’s ratio)and reinforced by two laminated three-phase skin layers.The obtained results in our work are compared with other previously published to confirm accuracy and reliability.In addition,the effects of parameters such as geometrical and material parameters on the vibration characteristics of sandwich plates with an auxetic honeycomb core and laminated three-phase skin layers are fully investigated.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Application Progress of Teaching in the Form of Traffic Short Videos in Nursing Education

With the rapid development of the information technology era,the teaching quality requirements continue to surge,and the mode of education in colleges and universities has also carried out certain innovations.The integration of modern information technology into the teaching process and the combination of medical content has become a new hotspot for reform and innovation of medical education at home and abroad.In this paper,we will describe the application of traffic short videos as the main teaching form in nursing education in domestic and foreign studies,and the role of the application of this teaching form in the improvement of theoretical knowledge and clinical skills of nursing students,as well as the impact on the cultivation of nursing students’professional cognition,communication skills,critical thinking,etc.,with the aim of providing new perspectives for the subsequent nursing education.

Network Traffic Based on GARCH-M Model and Extreme Value Theory

GARCH-M ( generalized autoregressive conditional heteroskedasticity in the mean) model is used to analyse the volatility clustering phenomenon in mobile communication network traffic. Normal distribution, t distribution and generalized Pareto distribution assumptions are adopted re- spectively to simulate the random component in the model. The demonstration of the quantile of network traffic series indicates that common GARCH-M model can partially deal with the "fat tail" problem. However, the "fat tail" characteristic of the random component directly affects the accura- cy of the calculation. Even t distribution is based on the assumption for all the data. On the other hand, extreme value theory, which only concentrates on the tail distribution, can provide more ac- curate result for high quantiles. The best result is obtained based on the generalized Pareto distribu- tion assumption for the random component in the GARCH-M model.

Integration Theory and Optimal Application of the Traffic Accident Management System

With the development of the social economy,the traditional transportation mode will be replaced by the new mode which emphasizes the integration and cooperation between the transportation modes.The advent of automobilization in China has further intensified the pressure of the road traffic.The traffic jam alarm caused by the traffic accidents is increasing year by year.The minor accidents that can be dealt with quickly account for more than 70%of the traffic accidents.Traditionally,when dealing with the minor accidents,car owners often choose to stay on the spot and wait for the traffic police to deal with them.It is easy to cause"minor accidents and big traffic jams",which lead to the congestion of a road,a bridge and even a block.

Physics of Traffic and the Crowds Theory： AMultidisciplinary Approach to Mobility Education

Crowding is a reality in which we find ourselves involved daily. The crowd produced in a traffic jam is a dynamic entity inwhich the application of physics, mathematics and biology can provide practical help to understand how and why this problematicsituation occurs and what solutions can be found to resolve it. In the mobility education project ＂SicuraMENTE＂, we carried out anexperiment on the conduct of a crowd by simulating a situation of intense city traffic. Taking a cue from an experimental situationproposed in traffic physics, we have verified that a route with limited access can generate a traffic jam and the crowd of pedestrianscan be mitigated by forcing the crowd to use dedicated streets. Taking the outgoing time of the student crowd from the outlet road,with and without the presence of an obstacle in the middle of the roadway, it was found that the traffic jam is resolved more quicklyin the situation with an obstacle because the flow of people is divided into two separate channels, reducing the probability that twoindividuals are close and that this creates an obstruction （example of counter-intuitive physical principle）. We also verified that thespeed of the elements of the crowd influences the formation of traffic jams, which are on average more likely in the case of higherspeed. These important aspects in the design of road networks and transport infrastructure have made students reason on physics＇topics, but also on the correct conduct in traffic. The multidisciplinary approach in education for safe and sustainable mobility, soinnovative in Italy, turned out to be effective in terms of teaching in the frame of a mix of academic disciplines, in which road safetyeducation has become the context and the goal.

Novel Distance Measures on Hesitant Fuzzy Sets Based on Equal-Probability Transformation and Their Application in Decision Making on Intersection Traffic Control

The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets(HFSs).The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements(HFEs)in a special way.Firstly,a probability density function is assigned for any given HFE.Thereafter,equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function.The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs,the higher the credibility of the mentioned membership degrees is,then,the bigger the probability density values for them are.According to this transformation technique,a set of novel distance measures on HFSs is provided.Finally,an illustrative example of intersection traffic control is introduced to show the usefulness of the given distance measures.The example also shows that this study is a good complement to operation theories on HFSs.

集成学习框架下的车辆跟驰行为建模

为了提高复杂行驶环境下车辆跟驰行为预测精度,提出了一种集成学习框架下融合理论驱动模型和数据驱动模型的车辆跟驰行为建模方法。基于stacking集成学习框架,选择理论驱动的智能驾驶模型(IDM)、考虑车辆队列和周围行驶条件因素的数据驱动的长短时记忆(LSTM)网络和门控循环单元(GRU)网络作为跟驰行为特征的一级学习算法,选择3种线性和8种非线性回归方法作为备选二级学习算法来融合一级学习器的输出特征。通过对比使用实际车辆轨迹数据计算的模型预测精度,确定了最优模型。研究结果表明:包含车辆队列和周围行驶条件变量的数据驱动跟驰模型比IDM模型的预测精度更高;多数情况下采用非线性二级学习算法的融合跟驰模型的预测精度高于IDM模型、数据驱动跟驰模型以及采用线性二级学习算法的融合跟驰模型;分别采用GBRT回归和随机森林回归作为二级学习算法的IDM-LSTM-stacking模型和IDM-GRU-stacking模型具有最高的预测精度;外界干扰下的融合跟驰模型稳定性优于单一的理论和数据驱动跟驰模型。集成学习为驾驶行为建模提供了新方法。

平行式快速路出口交通组织方法研究

针对平行式快速路出口排队溢出的交通问题,本文提出平行式快速路出口在无信号控制和信号控制情况下的5种交通组织方法,根据主辅车流的车头时距分布,建立主辅车流产生延误的计算模型。从方案选择的角度,以车均延误为评价指标,研究平行式快速路不同交通流量状态下出口最适合采用的交通组织方法。结果表明:当平行式快速路主路驶出车流和辅路车流的总流量低于1500 pcu·h^(-1)时,采取无信号让行的控制方法。主路驶出交通量较高时,采用主路驶出优先控制;辅路交通量较高时,采用辅路优先控制。当总流量在[1500,2300]pcu·h^(-1)时,采用辅路信号与让行相结合的控制方法。当主路驶出交通量较大时,采用辅路信号主路优先控制;当辅路交通量较大时,采用辅路信号辅路优先控制。当总流量高于2300 pcu·h^(-1)时,采用主辅全信号的控制方法。

高速公路混合交通环境下的智能网联汽车换道策略研究

为推动智能网联汽车应用落地,提出高速公路混合交通环境下智能网联汽车换道策略。首先,改进NaSch元胞自动机模型,并采用马尔科夫链算法计算道路通行能力;其次,针对目标车道为专用车道和普通车道分别建立基于车速引导的决策模型和基于博弈论的双矩阵决策模型;最后,采用多目标轨迹优化算法优化换道轨迹。结果表明:目标车道为专用车道和普通车道时,所提出的策略可分别提高换道效率6%、3.38%。

考虑占用率的大型停车库泊位动态分配模型

为提高驾驶员泊车效率,本文考虑不同停车库占用率下的停车库运营者及驾驶员泊位分配需求,构建大型停车库泊位分配模型。本文引入停车库占用率将停车库空满等级划分为空闲泊位充裕时段、空闲泊位适中时段、空闲泊位紧缺时段,综合考虑停车库运营者运营管理需求与驾驶员快速寻泊需求,以寻位行驶时间、离开停车库行驶时间为参数构建运营管理时间效用函数,以寻位行驶时间、停车入位耗时、步行时间为参数构建驾驶员泊车耗时效用函数;将运营管理时间效用与驾驶员泊车耗时效用加权统一为总时间效用,以总时间效用最大化为目标,建立兼顾停车库运营者及驾驶员泊位分配需求的泊位分配模型;引入泊位利用率、停车总耗时量化模型性能。以西安市某大型商业停车库为例,选取9:00、11:30、13:00表征空闲泊位充裕、空闲泊位适中、空闲泊位紧缺时段进行泊位分配。不同停车库空满等级下,停车库内空闲泊位的总时间效用与停车总耗时均呈负显著相关,其中,空闲泊位充裕时段,停车库内空闲泊位的总时间效用与停车总耗时的相关性最弱,相关系数为-0.461;空闲泊位紧缺时段,停车库内空闲泊位的总时间效用与泊位利用率呈正显著相关,相关系数为0.710。研究表明本模型可在优选停车总耗时较小泊位的基础上,为停车高峰时段预留利用率较高的泊位,提高空闲泊位紧缺时段的泊车效率及驾驶员的泊车满意度。

基于TAM-CPV模型的共享电单车持续使用意愿分析

深入剖析共享电单车的使用因素,增强共享电单车用户持续使用意愿对促进共享电单车健康有序发展、提升投放管理精细化水平至关重要。以技术接受模型(technology acceptance model,TAM)为基础,引入感知价值理论(customer perceived value,CPV)中的感知愉悦性、感知风险,并引入感知成本因素;构建基于TAM-CPV模型的共享电单车持续使用意愿模型;以重庆市共享电单车运营的监管数据、现场调查数据和网络调查数据为基础,综合运用SPSS、AMOS软件对结构方程模型开展检验及分析。研究结果表明:感知易用性是影响持续使用意愿的最显著正向因素,感知愉悦性次之,感知成本是唯一负向影响因素;这预示着政府管理部门应当注重共享电单车投放点的合理性,企业应当注重共享电单车APP的使用体验、计费规则。

考虑异质交通流的随机参数优化速度跟驰模型

为分析交通流异质性对车辆跟驰行为的影响,基于随机参数线性回归方法改进优化速度函数.根据分位数回归对交通流速度-密度数据进行分类,对每个类别数据进行随机参数线性回归,并得到不同类别的改进优化速度函数与假设检验结果,结合改进的优化速度函数和全速度差跟驰模型建立随机优化速度跟驰模型,利用傅里叶变化理论对跟驰模型进行稳定性分析,并搭建环形车道仿真平台对跟驰模型进行数值实验.结果表明,分类处理后的随机参数模型误差较未分类降低28%;随机参数跟驰车队的速度值随着0.5分位点车辆的增多而增大;随机参数跟驰模型车队较固定参数跟驰模型车队更能反映交通流异质性对车队的影响.建立的模型能够提高仿真维度,真实反映交通流的复杂运行状况.

分形视角下城市非规则道路网近百年演化过程研究

城市道路网在不同时期具有独特的网络结构,然而在近百年历程中如何演变,其过程并不清晰。研究以城市非规则道路网为例,通过历史资料整理提取了南京市鼓楼片区1900年来4个时期道路网,运用分形理论量化表达道路网覆盖均匀度和发育复杂度。结果表明:鼓楼片区非规则路网是由贯通性主干路牵引形成的;其路网相对稀疏,依然有更新和改进的空间;路网覆盖度和连通度近年来趋于平缓,城市应重视干道的功能拓展和“大院制”支路的打通。通过文献史料分析,解释了不同阶段规划思想、社会变革等因素对道路网演变起到的作用,认为历史古城道路网的更新保护应重视起牵引作用的骨架干道,同时重视非机动车和行人的需求,提升其可达性。

基于安全势场理论的高速公路交通事故下协同换道引导策略

为缓解交通事故对道路通行效率的影响,提高事故路段的通过能力,利用车路协同系统中车与车、车与路的实时信息交互,提出一种高速公路突发交通事故下基于安全势场理论的车辆协同换道引导策略。首先,针对单向双车道和多车道等不同车道下发生交通事故的多种场景,将协同换道的引导区域划分为事故保护区、引导过渡区、协同换道引导区和自由换道区4个区域,并确定换道引导阈值,以便更新车辆状态;然后,构建交通事故的安全势场,针对不同场景提出相应的车辆协同换道引导策略,并给出引导过程中车辆换道安全距离和最晚换道位置的计算方法;最后,基于城市交通仿真(SUMO)软件进行多种场景下的仿真验证。结果表明:在单向双车道场景下,当车辆协同引导率在75%时优化效果最明显;在多车道场景下,引导率在50%时的优化效果最明显;此外,通过对比分析发现,采用换道引导策略后,车辆通过事故路段的平均速度最高提升了6.3%,车辆延误最高减少了14.6%。

基于复杂网络的空中交通流量短期预测

为合理预测空中交通流量,结合复杂网络链路预测进行研究。首先,将时间序列转化为可视图得到拓扑特征量,然后结合基于局部信息、路径和随机游走的算法,比较在三亚不同扇区内的预测精度,发现RWR0.85算法预测精度最高。由于链路预测只能预测可能存在的连边,不能预测节点,因此引入D⁃S证据理论预测流量值,预测精度最高可达99.85%。结果表明,复杂网络链路预测结合D⁃S证据理论进行空中交通流量的预测是可行有效的,为进一步深入研究奠定了基础。

考虑电力-交通耦合网动态协调的EV集群灵活性挖掘与优化调度

电动汽车(EV)作为兼具交通与能量双重属性的跨域主体,发挥其时空灵活性将助力电力-交通耦合网的协调运行。为此,文中考虑电力-交通耦合网综合效益,提出了EV集群调控策略。首先,基于弧阻抗函数构建了动态交通网络加载模型。其次,考虑EV用户的各特征参数存在的差异性与耦合性,构建了单体EV灵活运行域模型,并采用基于zonotope线性近似的闵可夫斯基和算法对其聚合,得到EV集群的时变灵活运行域。在此基础上,提出了动态交通流最优分配下EV集群灵活性调控的双层模型,迭代求解得到上下两层耦合变量构成的瞬时单位流量出行成本,从而引导EV的出行与充放电行为。最后,通过与最短路径引导策略进行比较,验证了所提EV集群调控策略的有效性。

清末民国时期中国民族文化西来说对《穆天子传》解读的影响

清末民国时期,经由日本传入中国的拉克伯里的中国民族文化西来说,在中国学术界广为流传,并对中国学术界的《穆天子传》交通地理和西王母传说的研究产生了极为深刻的影响。拉克伯里对《穆天子传》周穆王西征和西王母传说的各种新奇解说,直接影响到晚清民国中国学术界的《穆天子传》交通地理和西王母传说的研究走向。国粹派对周穆王西征和西王母传说“真实性”的各种发挥,不断遭到学术界的质疑和批判。中国民族文化西来说,对《穆天子传》交通地理研究起到了积极的推动作用的同时,也给中国的《穆天子传》交通地理研究增添了诸多错讹和混乱。

城市道路平交口左转专用车道类型及设计长度研究

为了解决城市道路平面交叉口左转车流引起的交通拥堵,提高交叉口的通行能力和安全水平,以十字形交叉口左转专用车道为研究对象,总结了城市道路平面交叉口左转专用车道的设计类型。针对当前国内平面交叉口左转车道设计长度不足的问题,选取典型交叉口对其高峰时段左转车流的转弯情况进行调查,根据运动学方程和车流波动理论推算向上游延伸的最长排队距离,从而提出左转专用车道长度的新算法。该算法考虑了车辆之间的传递性、延迟性、连续性特征,由其计算得到的设计长度可以减少左转车辆在交叉口引起的停车延误,提高交叉口的通行效率。

基于前景理论的疫后旅游景区交通方式选择行为

基于有限理性的前景理论构建了旅客出行方式选择模型,通过对某景区旅游者的个人信息、出行基本情况以及出行意向进行了调查分析,揭示出其出行行为的特点。并且进一步运用前景理论研究旅游者的出行方式选择行为,在完全理性和有限理性的条件下分别计算了各异质类旅客对不同客运方式的模糊选择概率。在此基础上,建立了基于有限理性作用下旅客个体出行决策的模型,得出了各异质类旅客对不同客运方式的出行偏好。通过比较不同类型旅客的出行偏好,可分析出高收入和务工旅客更倾向于驾车出行,而学生游客更倾向于乘坐大巴。相关研究的结论对于旅游景区周边交通设施的规划和建设有一定的指导意义,可更好地服务和满足游客的出行需求。