线路客流预测分析与运营组织设计

从运营需要出发,提出客流预测的年限和内容;通过对客流量级的阐述,分析客流预测三级数据,确定运营的规模;根据OD(起讫点)客流分析来研究行车交路,做出满载率和拥挤度的评价;最终确定车辆编组与行车密度的合理组合,形成系统全面的技术方案,使客流预测更好地为运营组织服务.     

基于ARIMA的交通流量短时预测

采用AKIMA方法进行交通流量趋势预测．建模是利用现场调查得到的非平稳时间序列进行数据处理、建模．并根据AIC准则进行模型定阶,最后通过实测数据进行验证,结果表明。该ARIMA模型能够获得较好的中短期预测精度,因而可用于动态交通信号控制。     

高速公路动态交通流Elman神经网络模型

为了提高高速公路交通流建模的精度,分析了离散的高速公路动态交通流数学模型,基于Elman网络原理,建立了回归神经网络交通流模型。回归神经网络的输入层、上下文层、隐含层和输出层的节点数目分别选为8、30、30和2,采用Levenberg-Marquardt算法对回归神经网络进行训练,并对一条5路段的高速公路进行仿真。结果表明:回归神经网络平均相对误差为8.683 7×10-5,最大相对误差为4.237 1×10-4,与BP神经网络和RBF神经网络相比较,Elman回归神经网络能更好地逼近交通流数学模型,真实地描述交通流基本特性,能准确地建立动态交通流模型,适应交通状况的变化。     

叙泸段河道非恒定流作用下水力参数的变化

金沙江与岷江干支流上水电站调峰发电下泄非恒定流引起下游叙泸段河道水流条件显著变化。结合一维非恒定流数学模型和实测资料分析研究叙泸段河道内代表性非恒定流传播过程及其造成水力参数相对于概化恒定流条件时的变化情况。结果表明:叙泸段河道内典型非恒定流波长为218 km,传播速度3 m/s;随着传播距离增加波衰减幅度减小,波形变得光滑;当宜宾水位处于波峰时,下游沿程流量呈现递减趋势,波谷则正好相反;相对于恒定流条件,其流量变化范围为0~730 m3/s,水位抬升0.5~2 m;断面平均流速变化在-0.5~0.2 m/s,比降变化范围为-0.2‰~0.2‰,比降最大值为1.38‰。     

金沙江宜宾段非恒定流过程及传播特性

金沙江、岷江的非恒定流调节过程较为复杂,在宜宾汇合后形成新的非恒定流向下游传播。通过近年实测资料,分析金沙江、岷江非恒定流特征及汇合效果。结果表明:宜宾段非恒定流特征与向家坝电站下泄非恒定流的符合度更高,岷江的非恒定流无典型过程;宜宾段水位变幅和金沙江、岷江水位变幅存在线性关系;涨幅在1.7 m左右,起调水位在1 m左右的泄水波可作为宜宾段非恒定流过程的典型代表,其在下游的传播速度沿程基本保持一致,衰减幅度随着距离的增加而减小。     

水力式升船机竖井内水体的振动分析

地震荷载下升船机系统内水体与浮筒间的耦合作用是影响升船机安全运行的一个难题。通过流体动力学模拟(CFD)方法,讨论在不同频率的正弦激励下升船机竖井内水体的振荡。结果表明:竖井的水体存在一个自振频率,此频率比相同径度、相同水深的矩形池的值大约10%,自振周期约为0.42s;竖井水体的自振频率基本不随高度变化。     

Modeling the interactions between car and bicycle in heterogeneous traffic

In this paper, a new cellular automata model is proposed to simulate the car and bicycle heterogeneous traffic on urban road. To capture the complex interactions between these two types of vehicles, a novel occupancy rule is adopted in the proposed model to consider the variable lateral distances of mixed vehicular traffic. Based on massive simulations, microscopic fundamental diagrams under different bicycle densities are devised. With these, the bicycle's spilling behavior is then investigated and discussed. In order to reflect the interference of a bicycle on a car, the interference transformation from friction state to block state is modeled explicitly. Finally, different simulation results under different occupancy rules indicate that the constant and fixed occupancy rule adopted in the previous studies might lead to overestimation of car flux in the heterogeneous traffic flows with different bicycle densities. Copyright © 2013 John Wiley & Sons, Ltd.     

Instantaneous communication throughputs of vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) formed by connected vehicles in a traffic stream could be applied to improve safety, mobility, and environmental impacts of a transportation system. In this paper, we present analytical models for the instantaneous communication throughputs of VANETs to measure the efficiency of information propagation under various traffic conditions at a time instant. In particular, we define broadcast and unicast communication throughputs by the wireless channel bandwith multiplied by the average probabilities that one vehicle is a successful receiver and sender in a VAENT, respectively. With a protocol communication model, we derive formulas to determine the probabilities for an equipped vehicle to be a successful broadcast receiver and a successful unicast receiver/sender, and obtain broadcast and unicast throughputs along discrete and continuous traffic streams. We further examine the impacts on communication throughputs of the transmission range and the interference range of dedicated short range communication devices as well as the market penetration rate of equipped vehicles and the percentage of senders. Finally, we investigate the influence of shock waves on communication throughputs.     

公路隧道运营通风横通道周围流场特性研究

为研究公路隧道巷道式运营通风横通道周围的流场特性,以贵州凉风坳隧道为研究背景,利用流体力学研究软件Fluent建立隧道三维模型并进行了数值仿真计算。通过在隧道两边等风速条件下,对隧道内人行横通道以及车行横通道附近的流场特点研究,分析了运营通风横通道周围流场分布的具体特点。模拟结果表明:车行横通道与人行横通道两边流场分布基本相同;横通道内风速相对较小,约为隧道内风速的10%;不同风速下,横通道附近的速度分布和总压分布整体走势一致;两边流场相对稳定,不会进行风流和污染物的串流。     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.