ITC模式下地铁列车单/双线出段能力比较分析

主要以地铁十四号线马泉营车辆段为例,分析比较ITC模式下列车自车辆段停车库内采用单线出段和双线出段两种运行组织方式下的出段能力。     

城市轨道交通列车运行自动调整研究方法综述

基于城市轨道交通列车运行自动调整的概念和必要性,介绍实现列车运行自动调整的基本思路:时刻表调整和行车间隔调整。并结合国内外学者的研究成果,对目前存在的列车运行自动调整研究方法进行分析,为列车运行自动调整问题的建模和算法实现提供参考。     

基于强度折减法的浅埋偏压小净距隧道围岩稳定性分析

针对广东某浅埋偏压小净距高速公路隧道,采用有限元强度折减法基本原理,研究隧道施工过程中各施工工序的安全系数动态变化过程,并对极限状态下关键施工工序的围岩塑性区与隧道围岩位移进行分析,结论为:隧道左洞第一步开挖时,由于中岩柱的出现,其安全系数最小,为最危险施工步,其次为两个洞室临时岩柱上台阶开挖;施工中中岩柱、洞室左拱腰和右拱脚出现大量塑性区,为围岩应力危险区域;中岩柱水平位移在施工过程中呈现出左右往返变化,右侧隧道竖向位移及其上部地表沉降较大,为监控量测重点部位。     

基于元胞自动机理论的沪杭高铁通过能力仿真研究

沪杭高铁除嘉兴南站外,其他沿途车站各方向均仅有1条到发线,不可避免会出现在同一股道接发同向列车的情况,列车发到间隔时间较大,阻碍了沪杭高铁运能的提升。通过元胞自动机理论,建立沪杭高铁通过能力仿真系统,以现行运行图停站方案为基础,对同股道列车发到间隔时间为7 min和6 min两种情况进行仿真分析,对比压缩列车同股道发到间隔时间对沪杭高铁通过能力的影响。仿真结果表明,在现行较优的运行方案下,压缩列车发到间隔时间对目前沪杭高铁通过能力的提升幅度有限。     

现代有轨电车最小发车间隔及相关指标研究

最小发车间隔是确定现代有轨电车开行密度和运输能力的参数。现代有轨电车作为一种新型的中低运量的地面快速轨道交通系统,其最小发车间隔的确定与地铁、BRT(快速公交)等其他交通方式均有所差异。通过对道路交叉口、列车停站、列车折返及区间长度等影响因素分析,研究了现代有轨电车最小合理发车间隔,并对其运输能力与车辆配属进行了探讨,为现代有轨电车规划建设提供决策参考。     

运行参数对汽车燃油经济性影响程度的区间分析方法

为了提高汽车燃油经济性,介绍了区间数学基本概念,运用Matlab建立了发动机万有特性的数学模型,应用区间数学分析了公交汽车在运行过程中行驶车速、载质量、道路阻力系数等运行参数波动对汽车燃油经济性的影响程度。分析结果表明:车速波动对汽车油耗量的影响程度随着车速的增大而明显增大,但汽车油耗量的波动随载质量的不同相差不大;道路阻力系数波动对汽车油耗量的影响最大,其次是载质量和行驶车速。     

SPJ900/32架桥机快速区间转场技术研究

对SPJ900/32架桥机调头作业进行分析和技术改进,介绍了桥梁、路基交互时的区间转场工艺流程和操作要点。     

On finite sample performance of confidence intervals methods for willingness to pay measures

This paper systematically compares finite sample performances of methods to build confidence intervals for willingness to pay measures in a choice modeling context. It contributes to the field by also considering methods developed in other research fields. Various scenarios are evaluated under an extensive Monte Carlo study. Results show that the commonly used Delta method, producing symmetric intervals around the point estimate, often fails to account for skewness in the estimated willingness to pay distribution. Both the Fieller method and the likelihood ratio test inversion method produce more realistic confidence intervals for small samples. Some bootstrap methods also perform reasonably well, in terms of effective coverage. Finally, empirical data are used to illustrate an application of the methods considered.     

Quantifying uncertainty in short-term traffic prediction and its application to optimal staffing plan development

In this paper, we aim to quantify uncertainty in short-term traffic volume prediction by enhancing a hybrid machine learning model based on Particle Swarm Optimization (PSO) and Extreme Learning Machine (ELM) neural network. Different from the previous studies, the PSO-ELM models require no statistical inference nor distribution assumption of the model parameters, but rather focus on generating the prediction intervals (PIs) that can minimize a multi-objective function which considers two criteria, reliability and interval sharpness. The improved PSO-ELM models are developed for an hourly border crossing traffic dataset and compared to: (1) the original PSO-ELMs; (2) two state of the art models proposed by Zhang et al. (2014) and Guo et al. (2014) separately; and (3) the traditional ARMA and Kalman filter models. The results show that the improved PSO-ELM can always keep the mean PI length the lowest, and guarantee that the PI coverage probability is higher than the corresponding PI nominal confidence, regardless of the confidence level assumed. The study also probes the reasons that led to a few points being not covered by the PIs of PSO-ELMs. Finally, the study proposes a comprehensive optimization framework to make staffing plans for border crossing authority based on bounds of PIs and point predictions. The results show that for holidays, the staffing plans based on PI upper bounds generated much lower total system costs, and that those plans derived from PI upper bounds of the improved PSO-ELM models, are capable of producing the lowest average waiting times at the border. For a weekday or a typical Monday, the workforce plans based on point predictions from Zhang et al. (2014) and Guo et al. (2014) models generated the smallest system costs with low border crossing delays. Moreover, for both holiday and normal Monday scenarios, if the border crossing authority lacked the required staff to implement the plans based on PI upper bounds or point predictions, the staffing plans based on PI lower bounds from the improved PSO-ELMs performed the best, with an acceptable level of service and total system costs close to the point prediction plans.     

自由飞行环境中飞机对导弹的规避方法*

在当今空战情况下,导弹对于飞机的威胁愈发增长。为避免发生飞行冲突,需要飞机驾驶员适当改变航行诸元,但是由于导弹的速度在一般情况下远远大于飞机速度,且发现时双方距离较近,留给驾驶员的反应与操作时间较少。文章采用速度矢量三角形分析法,在二维平面上分析了飞机对于导弹的规避方法,提出了综合调整航向和航速冲突的方法。