流量和信号控制对运行时间预测的影响

通过对实际交通状况的分析，说明路线运行时间不仅是路线交通流量的函数，而且是由于交叉口信号控制引起延误的函数。     

宫胁法在高速公路边坡生态恢复中的应用

本研究根据宫胁法原理,提出高速公路边坡原生态恢复的理念和生态恢复的方法和步骤,包括:基本条件调查,即立地类型和植被环境调查;土壤改良;水土保持措施;乡土植物培育及应用;施工与应用。并把此项研究结果应用于新街至河口高速公路边坡生态恢复工程,将其作为推广示范基地,为其他地区高速公路边坡植被恢复达到近自然状态、缩短演替时间提出了新的理论指导和技术方法。     

汽车空气悬架高度控制阀动力学模型的研究

介绍了汽车空气悬架高度控制阀的基本组成及工作原理,并根据延时型高度控制阀的工作原理建立了动力学模型。分析了高度控制阀动作延迟时间与阻尼、不感带、缓冲弹簧预紧力及杠杆比的关系。针对高度控制阀的单向阻尼非线性特性,根据高度控制阀的试验方法,建立了高度控制阀的Simulink模型,仿真分析了延时和不感带特性,验证了该型高度控制阀的特性是满足设计要求的。     

基于支持向量回归的图像复原方法研究

针对退化图像复原问题,提出了一种基于支持向量回归的退化图像复原方法.该方法利用支持向量机回归算法非线性映射能力,通过训练样本对的学习训练,在退化图像与原始清晰图像之间建立映射关系,然后对测试样本进行复原.实际图像复原实验表明,得到的复原图像在视觉上和定量分析上都获得了比较好的效果.与神经网络方法相比,支持向量机回归算法克服了神经网络的模型选择与过学习问题、局部极小问题等.     

RTA48-T型主机气动操纵系统仿真及应用

主机气动操纵系统的主要功能是完成主机的起动、换向和调速。因其包含的气动元器件多,逻辑关系复杂,一旦发生故障,难于判断,因此加强船员对气动操纵系统方面的训练和培训是轮机管理中的一项重点和难点内容。在现有轮机仿真训练系统中,主机气动操纵系统仿真模型为MAN公司的 MC型气动操纵系统,为了扩展现有轮机仿真系统的训练功能,满足不同机型气动操纵系统的训练要求,本文采用逻辑建模方法,同时又考虑到部件的延时特性,建立了瓦锡兰公司的RTA48-T型主机气动操纵系统仿真模型;利用VC++编程软件完成了模型计算;开发了主机气动操纵系统的二维可视化仿真界面;仿真结果表明,模型可以对常见故障进行仿真并与实际现象相吻合。二维界面既能展现实际系统的逻辑关系,又能对延时过程实现可视化动态展示,更好地满足了教学与培训的使用要求。     

锯齿形过饱和公交优先信号交叉口进口道延误研究

公交优先是缓解城市交通问题的一种有效方法,故提出在过饱和信号交叉口进口道处设置成锯齿形,并设置车道预信号灯。本文基于定数理论的背景和信号交叉口延误理论,在已有延误研究的基础上,对过饱和信号交叉口进口道延误进行分析,推导出相应的进口道延误公式,通过对公交优先方隶实施前后的交通效益评价对比,证明该方案是有效且可行的。     

A delay root cause discovery and timetable adjustment model for enhancing the punctuality of railway services

Knock-on delay, which is the key factor in punctuality of railway service, is mainly related to two factors including the quality of timetable in the planning phase and disturbances which may result in unscheduled trains’ waiting or meeting in operation phase. If the delay root cause and the interactions among the factors responsible for these can be clearly clarified, then the punctuality of railway operations can be enhanced by taking reactions such as timetable adjustment, rescheduling or rerouting of railway traffic in case of disturbances. These delay reasons can be used to predict the lengths of railway disruptions and effective reactions can be applied in disruption management. In this work, a delay root cause discovery model is proposed, which integrates heterogeneous railway operation data sources to reconstruct the details of the railway operations. A supervised decision tree method following the machine learning and data mining techniques is designed to estimate the key factors in knock-on delays. It discovers the root cause delay factor by logically analyzing the scheduled or un-scheduled trains meetings and overtaking behaviors, and the subsequent delay propagations. Experiment results show that the proposed decision tree can predict the delay reason with the accuracy of 83%, and it can be further enhance to 90% if the delay cause is only considered “prolonged passengers boarding” and “meeting or overtaking” factors. The delay root cause can be discovered by the proposed model, verified by frequency filtering in operation records, and resolved by the adjustment of timetable which is an important reference for the next timetable rescheduling. The results of this study can be applied to railway operation decision support and disruption management, especially with regard to timetable rescheduling, trains resequencing or rerouting, system reliability analysis, and service quality improvements.     

某快速路附属雨水地道泵站工程设计案例分析

地道雨水的积水问题是城市积水问题的主要成因之一。对其汇聚的雨水进行收集和排放的最理想方式是在合理的可征用土地范围内建造单独使用功能的地道雨水泵站,并同时在周边寻找到可以有效收纳其排放雨水的相关河道。本工程的实施为当地新建快速路下穿涵洞的雨水及其周边地下水提供了为其服务的雨水地道泵站的建设思路。同时其泵站庭院内部各类给排水管线的实施及其上下游出路的选择也是本工程值得借鉴的因素。     

Development of a maximum likelihood regression tree-based model for predicting subway incident delay

This study aims to develop a maximum likelihood regression tree-based model to predict subway incident delays, which are major negative impacts caused by subway incidents from the commuter’s perspective. Using the Hong Kong subway incident data from 2005 and 2009, a tree comprising 10 terminal nodes is selected to predict subway incident delays in a case study. An accelerated failure time (AFT) analysis is conducted separately for each terminal node. The goodness-of-fit results show that our developed model outperforms the traditional AFT models with fixed and random effects because it can overcome the heterogeneity problem and over-fitting effects. The developed model is beneficial for subway engineers looking to propose effective strategies for reducing subway incident delays, especially in super-large-sized cities with huge public travel demand.     

Traveler delay costs and value of time with trip chains, flexible activity scheduling and information

The delay costs of traffic disruptions and congestion and the value of travel time reliability are typically evaluated using single trip scheduling models, which treat the trip in isolation of previous and subsequent trips and activities. In practice, however, when activity scheduling to some extent is flexible, the impact of delay on one trip will depend on the actual and predicted travel time on itself as well as other trips, which is important to consider for long-lasting disturbances and when assessing the value of travel information. In this paper we extend the single trip approach into a two trips chain and activity scheduling model. Preferences are represented as marginal activity utility functions that take scheduling flexibility into account. We analytically derive trip timing optimality conditions, the value of travel time and schedule adjustments in response to travel time increases. We show how the single trip models are special cases of the present model and can be generalized to a setting with trip chains and flexible scheduling. We investigate numerically how the delay cost depends on the delay duration and its distribution on different trips during the day, the accuracy of delay prediction and travel information, and the scheduling flexibility of work hours. The extension of the model framework to more complex schedules is discussed.