支持向量机在货运量预测中的应用研究

在分析现有货运量预测方法所存在问题的基础上,建立了货运量预测的支持向量机模型,并以我国1981～2001年的货运量和相关经济指标的历史统计数据作为学习样本,分别选用3种不同的核函数,通过拟合训练和外推预测分析,验证了支持向量机用于货运量预测的有效性,并对模型中的有关参数进行了探讨分析。     

广州市票务政策对轨道交通客运量的影响

票务政策是影响城市轨道交通客运量规模最直接有效的工具.为了充分发挥城市轨道交通疏解城市交通拥堵的作用,在借鉴国内外城市相关票务经验的基础上,解析广州市城市轨道交通票务现状,并建立交通规划模型,对客流规模的敏感性进行了定量研究.对票价的调整措施提出了建议,并对票价调整前后的客流效果进行了评价.     

有限体积法在一维平底溃坝问题研究中的应用

以一维平底溃坝问题为例,讨论了有限体积法的应用。从溃坝基本方程入手,采用Roe方法计算界面数值通量,采用空间一阶、时间二阶格式（预测校正二步格式）计算溃坝问题,得到了满意的结果。     

精轧螺纹吊底平台在大体积高桩墩台中的应用与创新

从工程实际出发,对墩台施工水上作业平台工艺进行对比分析,介绍精轧螺纹吊底平台的工艺特点、原理、流程及操作要点。结合全直桩基墩台结构特点,对桩基与上部结构连接方式的设计进行创新,在钢管桩外侧设置4块扇形钢板,并围焊成环形,与精轧螺纹吊底平台共同形成一种新型组合支承结构,提高吊底和底模的周转率,加快工程进度,确保大体积高桩墩台施工的安全和质量,经济和技术效益明显。可为类似墩台施工、钢管桩与上部结构连接方式设计提供参考。     

汽油机燃烧室紧凑性评价参数分析

对燃烧室紧凑性评价参数面容比A/V值进行了分析,讨论了其局限性。提出了新的内燃机燃烧室紧凑性的衡量方法,即面面比S/A,在等容积条件下,进行了各种燃烧室紧凑性及火焰传播距离的比较。     

涵洞基坑降水方案比选与参数分析

结合哈大铁路客运专线DK651+972涵洞施工的实例,论述了根据实际水文地质条件确定降水方案,对以往经验参数进行修改,以达到降水目的及确保工程顺利进行。     

浅谈当前交调工作意义与存在的问题

交调工作是公路规划、建设的重要基础工作,详细地分析了交调工作的意义及河北省开展现状及存在的问题,并提出相应建议。     

CDUBGM-Markov模型在铁路客运量预测中的应用

文章在传统的灰色模型和马尔柯夫模型的基础上,提出了动态无偏灰色马尔柯夫模型,阐述了该模型的建立方法,并采用这三种模型对我国铁路客运量进行了预测,对比结果表明动态无偏灰色马尔柯夫模型的拟合效果较好,预测精度较高,是一种行之有效的预测方法。     

大体积承台混凝土施工

文章以新寨河特大桥主墩承台施工为例,介绍了大体积混凝土施工的质量控制要点、施工工艺及质量保障措施,并重点讲述了大体积混凝土在施工中,如何预防因温度应力而引起混凝土开裂的温度监测措施。     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.