Short-term travel flow prediction method based on FCM-clustering and ELM

Short-term travel flow prediction has been the core of the intelligent transport systems(ITS). An advanced method based on fuzzy C-means(FCM) and extreme learning machine(ELM) has been discussed by analyzing prediction model. First, this model takes advantages of ability to adapt to nonlinear systems and the fast speed of ELM algorithm. Second, with FCM-clustering function, this novel model can get the clusters and the membership in the same cluster, which means that the associated observation points have been chosen. Therefore, the spatial relations can be used by giving the weight to every observation points when the model trains and tests the ELM. Third, by analyzing the actual data in Haining City in 2016, the feasibility and advantages of FCM-ELM prediction model have been shown when compared with other prediction algorithms.

THE NONLINEAR STABILITY OF TRAVELLING WAVE SOLUTIONS FOR A REACTING FLOW MODEL WITH SOURCE TERM

In this paper, author considers a 3 x 3 system for a reacting flow model propesed by [9]. Since this model has source term, it can be considered as a relaxation approximation to 2 x 2 systems of conservation laws, which include the well-known p-system. From this viewpoint, the author establishes the global existence and the nonlinear stability of travelling wave solutions by L-2 energy method.

Exploring the Evolution of Passenger Flow and Travel Time Reliability with the Expanding Process of Metro System Using Smartcard Data

Metro system has experienced the global rapid rise over the past decades. However,few studies have paid attention to the evolution in system usage with the network expanding. The paper's main objectives are to analyze passenger flow characteristics and evaluate travel time reliability for the Nanjing Metro network by visualizing the smart card data of April 2014,April 2015 and April 2016. We performed visualization techniques and comparative analyses to examine the changes in system usage between before and after the system expansion. Specifically,workdays,holidays and weekends were specially segmented for analysis.Results showed that workdays had obvious morning and evening peak hours due to daily commuting,while no obvious peak hours existed in weekends and holidays and the daily traffic was evenly distributed. Besides,some metro stations had a serious directional imbalance,especially during the morning and evening peak hours of workdays. Serious unreliability occurred in morning peaks on workdays and the reliability of new lines was relatively low,meanwhile,new stations had negative effects on exiting stations in terms of reliability. Monitoring the evolution of system usage over years enables the identification of system performance and can serve as an input for improving the metro system quality.

Numerical Investigation of Traveling Wave Electroosmotic Flows in A Microchannel

In this paper, a coordinate transformation method (CTM) is employed to numerically solve the Poisson–Nernst–Planck (PNP) equation and Navier–Stokes (NS) equations for studying the traveling-wave electroosmotic flow (TWEF) in a two-dimensional microchannel. Numerical solutions indicate that the numerical solutions of TWEF with and without the coordinate transformation are in good agreement, while CTM effectively improves stability and convergence rate of the numerical solution, and saves computational cost. It is found that the averaged flow velocity of TWEF in a micro-channel strongly depends on frequency of the electric field. Flow rate achieves a maximum around the charge frequency of the electric double layer. The approximate solutions of TWEF with slip boundary conditions are also presented for comparison. It is shown that the NS solution with slip boundary conditions agree well with those of complete PNP-NS equations in the cases of small ratios of Electric double layer(EDL) thickness to channel depth(λD/H). The NS solution with slip boundary conditions over-estimates the electroosmotic flow velocity as this ratio(λD/H) is large.

A Study on Optimizing the Double-Spine Type Flow Path Design for the Overhead Transportation System Using Tabu Search Algorithm

Optimizing Flow Path Design(FPD)is a popular research area in transportation system design,but its application to Overhead Transportation Systems(OTSs)has been limited.This study focuses on optimizing a double-spine flow path design for OTSs with 10 stations by minimizing the total travel distance for both loaded and empty flows.We employ transportation methods,specifically the North-West Corner and Stepping-Stone methods,to determine empty vehicle travel flows.Additionally,the Tabu Search(TS)algorithm is applied to branch the 10 stations into two main layout branches.The results obtained from our proposed method demonstrate a reduction in the objective function value compared to the initial feasible solution.Furthermore,we explore howchanges in the parameters of the TS algorithm affect the optimal result.We validate the feasibility of our approach by comparing it with relevant literature and conducting additional tests on layouts with 20 and 30 stations.

Vehicle actuation based short-term traffic flow prediction model for signalized intersections

Traffic flow prediction is an important component for real-time traffic-adaptive signal control in urban arterial networks.By exploring available detector and signal controller information from neighboring intersections,a dynamic data-driven flow prediction model was developed.The model consists of two prediction components based on the signal states(red or green) for each movement at an upstream intersection.The characteristics of each signal state were carefully examined and the corresponding travel time from the upstream intersection to the approach in question at the downstream intersection was predicted.With an online turning proportion estimation method,along with the predicted travel times,the anticipated vehicle arrivals can be forecasted at the downstream intersection.The model performance was tested at a set of two signalized intersections located in the city of Gainesville,Florida,USA,using the CORSIM microscopic simulation package.Analysis results show that the model agrees well with empirical arrival data measured at 10 s intervals within an acceptable range of 10%-20%,and show a normal distribution.It is reasonably believed that the model has potential applicability for use in truly proactive real-time traffic adaptive signal control systems.

Solitary wave solution to Aw-Rascle viscous model of traffic flow

A traveling wave solution to the Aw-Rascle traffic flow model that includes the relaxation and diffusion terms is investigated. The model can be approximated by the well-known Kortweg-de Vries （KdV） equation. A numerical simulation is conducted by the first-order accurate Lax-Friedrichs scheme, which is known for its ability to capture the entropy solution to hyperbolic conservation laws. Periodic boundary conditions are applied to simulate a lengthy propagation, where the profile of the derived KdV solution is taken as the initial condition to observe the change of the profile. The simulation shows good agreement between the approximated KdV solution and the numerical solution.

Identification method of crowded passenger flow based on automatic fare collection data of Nanjing Metro

To relieve traffic congestion in urban rail transit stations,a new identification method of crowded passenger flow based on automatic fare collection data is proposed.First,passenger travel characteristics are analyzed by observing the temporal distribution of inflow passengers each hour and the spatial distribution concerning cross-section passenger flow.Secondly,the identification method of crowded passenger flow is proposed to calculate the threshold via the probability density function fitted by Matlab and classify the early-warning situation based on the threshold obtained.Finally,a case study of Xinjiekou station is conducted to prove the validity and practicability of the proposed method.Compared to the traditional methods,the proposed comprehensive method can remove defects such as efficiency and delay.Furthermore,the proposed method is suitable for other rail transit companies equipped with automatic fare collection systems.

基于Flowmaster平台的雷达行波管多支路液冷系统流动换热分析

为研究雷达行波管的多支路散热问题,运用一维流体仿真软件Flowmaster建立雷达行波管多支路液冷系统的仿真模型,对该液冷系统的稳态流动换热过程及多泵并联"启动/停止"切换的瞬态流动过程进行仿真分析。仿真结果表明,稳态流动下调节各支路流阻特性可使各支路达到流量相同的平衡状态,从而使各支路的换热特性保持一致;多泵并联"启动/停止"切换的瞬态过程对系统的压力分布产生较大影响。从数值仿真方面解决行波管散热的多支路流动换热特性分析的问题,对雷达行波管液冷系统的设计工作有着一定的参考价值。

Influence of the Domain Boundary on the Speeds of Traveling Waves

Let H > 0 be a constant, g ≥ 0 be a periodic function and Ω ={(x, y) ||x| H + g (y), y ∈R}. We consider a curvature flow equation V = κ + A in Ω, where for a simple curve γt Ω, V denotes its normal velocity, κ denotes its curvature and A > 0 is a constant. [1] proved that this equation has a periodic traveling wave U, and that the average speed c of U is increasing in A and H, decreasing in max g' when the scale of g is sufficiently small. In this paper we study the dependence of c on A, H, max g' and on the period of g when the scale of g is large. We show that similar results as [1] hold in certain weak sense.

Vision-Based Obstacle Avoidance in Sidewalk Environment Using Top-View Transform and Optical-Flow

This paper presents a vision-based obstacle avoidance method for blind pedestrians in an outdoor sidewalk environ- ment. Unlike many existing travel-aid systems using stereo-vi- sion based methods, the proposed method is able to get obstacle position as well as user motion information by just one monocu- lar camera fixed at the belly of the user. To achieve this goal, a top-view transformation of the road image is used for obstacle detection and user motion estimation, based on which a grid map is generated for navigation. For detection part, the bottom points of erect obstacles are detected by extracting local-maxima and minima on the top-view image while user motion is estimat- ed by analysing the optical flow vector field in the user sur- rounding area. For the obstacle avoidance part, a step score is calculated on the grid map for evaluating the safety of next moving step. Experiments with several sidewalk video-clips show that the proposed obstacle avoidance method is able to provide useful guidance instructions under certain sidewalk environments.

Short-term inbound rail transit passenger flow prediction based on BILSTM model and influence factor analysis

Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.

基于出行链的铁路车站开通初期客流预测研究

【目的】为解决铁路车站开通初期客流预测缺乏数据支撑,以及估计不同交通方式成本来计算客流转移量结果与实际偏差较大的问题。【方法】以新开通南沿江城际铁路江阴站为例,考虑该线与既有高速及城际铁路的线位关系,基于城际出行链,依托旅客出行行为调查对区域内可选择的不同交通方式的城际出行效用进行定量计算,采用Multinominal Logit(MNL)模型,区分工作日与非工作日,结合客流分配现状对效用变量系数进行标定,据此预测南沿江城际铁路江阴站开通后发往南京、上海枢纽的客流量,同时结合城市经济和社会发展推演计算发往沿线其他站点的客流。【结果】结果表明,南沿江城际铁路江阴站的开通可以有效吸引江阴地区原本选择既有铁路、公路去往南京、上海的客流以及选择公路去往南沿江城际铁路沿线其他城市的客流。【结论】因此,南沿江城际铁路的开通能有效缓解辐射范围内既有铁路、公路的运输压力,客流预测结果还将支撑站点运力资源配置优化研究。

基于乘客OD间路径旅行时间的城市轨道交通客流分布计算模型的适用性研究

[目的]针对目前城市轨道交通(以下简称“城轨”)线网客流分布计算模型的客流计算结果与实际客流存在偏差的现象,需基于OD间路径的实际旅行时间,对基于多路径概率分配的客流分布计算模型的适用性展开研究。[方法]基于乘客OD间路径的实际旅行时间,分析揭示了现有城轨客流分布计算模型存在的主要问题;融合AFC(自动售检票)系统和ATS(列车自动监控)系统两类数据,构建并标定了基于乘客OD间路径旅行时间的城轨客流分布计算模型;对目前国内城轨系统广泛采用的基于多路径概率分配的城轨客流分布计算模型的适用性进行了分析与评价。[结果及结论]现有城轨客流分布计算模型在路径选择集和路径选择比例上存在主要问题。通过基于多路径概率分配的城轨客流分布计算模型获取的路径分配比例,得到的旅行时间分布模拟结果均为单峰,无法重现从AFC票卡提取的实际旅行时间分布的多峰情况。当城轨线网较为简单时,基于多路径概率分配的城轨客流分布计算模型基本适用;当线网规模不断增加,线网结构进一步复杂,列车运行方式的多样性、乘客出行行为的差异性等不断加大的条件下,该模型对于路径阻抗差异小的OD可能适用,而对于路径阻抗差异大的OD不适用。

喀斯特旅游地虚拟旅游体验对实地旅游意愿的影响-以武隆喀斯特旅游区为例

文章以重庆市武隆喀斯特旅游区为例,采用游客问卷调查数据和结构方程模型,分析游客在喀斯特旅游区虚拟旅游体验后产生的心流体验以及对实地旅游意愿的影响。结果表明:喀斯特旅游地虚拟旅游体验对游客的注意力集中度、远程呈现、时间感的变化和实地旅游意愿均产生显著正向影响,注意力集中度发挥部分中介作用。建议武隆喀斯特旅游区加强以下建设:优化虚拟应用技术,营造更真实的虚拟旅游体验情境;提供全面优质的旅游信息,减少游客信息收集成本;扩大虚拟旅游宣传,赢得更多潜在游客。

气举阀流量预测新模型

为解决Thornhill-Craver方法预测气举阀流量不准确的问题,以空气为介质,在气举阀实验平台上开展气举阀流量研究。对2.8、3.2、4.8、6.4 mm阀孔尺寸的气举阀进行实验,得到不同阀孔尺寸下阀杆行程与流量系数、临界压力比的函数关系;通过考虑阀球表面压力随工况条件的动态变化过程,引入阀的打开程度,优化了阀杆行程求解方法;对气举阀过流面积进行建模,利用已知参数分析推导了过流面积计算新方法;在实验及理论分析基础上,建立了气举阀流量预测新模型。研究结果表明:新模型对不同阀孔尺寸及工况条件下气举阀流量预测准确,平均相对误差为3.34%,较Thornhill-Craver方法有了较大提高,对判断气举阀在井下的工作状态及提高气举设计的精度具有重要意义。

城市轨道交通网络系统效率评价指标改进

为提高城市轨道交通网络系统效率评价指标的可比性和完备性,引入有效行程速度和有效客流密度的概念,改进了网络系统效率评价指标,并以重庆市中心城区2017年和2019年运营的城市轨道交通线网为例验证了改进后评价指标的科学性和可操作性。研究表明:既有评价指标由于显著受到线网服务范围的影响,且未体现网络的投入产出效率,无法直接作为网络结构优化的目标函数;改进后的系统效率评价指标能够综合反映剔除线网服务范围影响后的网络结构性能和投入产出效率,且存在理论上的最优值;平衡网络中节点换乘时间和路段行程时间,并适度加密城市核心区域的轨道交通线路和站点,是持续提升网络系统效率的2个重要手段。

质子交换膜燃料电池随行波流场设计与传质特性

为了提高质子交换膜燃料电池(PEMFC)的膜电极的传质性能与电池的功率密度,设计了一种以圆弧凹面作为强化传质结构的随行波流场板。结合铣削工艺,实现了随行波流场结构的制造。采用计算流体动力学软件,建立包括随行波流场与膜电极在内的燃料电池三维模型。实验验证了该模型的准确性。探索了强化传质结构对电池内部速度场、浓度场及电场的分布规律,分析了电池性能的提升效果。结果表明:与流道深宽0.6 mm×0.8 mm的常规流场相比,该文的随行波流场的平均流速提升了27.7%,压损降低了19.2%,双极板—气体扩散层界面的氧气含量提升了1.44%,出口的排水速率增大16.7%,功率密度提升了8.6%。

基于网络数据挖掘的长江经济带户外体育旅游流时空特征研究

随着旅游数字化变革和在线旅游网站的日益普及,基于Python技术挖掘的网络游记为户外体育旅游研究提供可靠的数据源和开辟新的研究方法,对于进一步理解户外体育旅游业的发展具有重要意义。综合运用GIS空间分析法和统计分析法,研究长江经济带户外体育旅游流时空特征。研究认为:1)时间上,户外体育旅游流年内变化呈“山岭”型峰林结构分布和“三峰四谷”的峰林结构变化规律;户外体育旅游流季节性变化特征明显,呈现出不稳定的发展态势;户外体育旅游流在清明小长假、“五一”假期、“十一”假期客流量大,形成3个明显波峰;户外体育旅游流从周五开始拉升,周六达到峰值,客流量周内幅度变化呈现淡季-旺季客流量>旺季-淡季客流量>淡季客流量>旺季客流量>整体客流量的变化特征。2)空间上,户外体育旅游流客源地主要分布在长江下游地区的长三角城市群,呈明显集聚态势;户外体育旅游流目的地主要分布在户外体育旅游资源丰富的城市,呈“大分散、小集聚”的空间分布特征;户外体育旅游流的辐射中心为客流流动量大、流动频次高的成都市和上海市等城市节点,具体表现出地理邻近效应显著、经济发达城市与户外体育旅游资源丰富的城市之间流动频繁等特征。

基于网络游记的桂林旅游流网络结构研究

旅游流网络结构可以反映游客在旅游目的地的移动特征,关系到区域旅游协同发展。为了识别旅游流的网络结构特征,运用空间分析、社会网络分析等方法,基于网络游记对桂林旅游流进行探讨。研究表明:游客在桂林主要旅行景点呈“大分散,小聚集”的空间分布格局,桂林整体旅游流网络密度较低,存在典型的核心-边缘特征,核心区景点对边缘区景点影响有限,凝聚子群在桂林中心城区和阳朔县呈现集聚态势。漓江景区、龙脊梯田、象鼻山景区、两江四湖、兴坪古镇、西街、相公山7个景点在节点中心性和结构洞分析中优势明显,综合实力强,在旅游流网络中处于重要地位。