浅谈运行速度与道路线形的连续性

《公路工程技术标准》(JTG B01-2003)中引入了运行速度的概念,故设计人员在设计速度变化路段、爬坡车道、超高等受限制路段时应进行运行速度的验算.公路几何构成参数,例如平、纵曲线半径、纵坡、超高、加宽、停车视距以及指示道路标志等等都是影响汽车运行速度的主要因素.因此,要解决好线形的连续性问题,就要解决运行速度的连续性问题,也就是要解决好公路几何要素之间的组合问题.     

不良天气对交通信号配时的影响分析

天气条件是道路交通运营的重要影响因素之一.从理论上分析不良天气对信号配时的影响,然后运用SYNCHR0和SIMTRAFFIC仿真软件,对正常和不良天气两种条件下的交叉口信号配时进行配时优化和微观交通仿真,研究表明:不良天气对交叉口信号配时的绩效将产生明显的负面影响,针对不良天气专门制定的配时优化方案将改善交通状况、减少延误和提高车速,但是改善程度还与许多因素有关.     

风冷热泵冷热水机组的稳态模拟和试验研究

建立了风冷热泵冷热水机组的稳态模型,并在试验台上进行了试验验证,系统在制冷和制热两种模式下运行,模拟值和试验值吻合良好,试验结果表明合理设计的过冷段换热器可以使冷凝器出口制冷剂产生一定的过冷度,并且在制热模式下融化一部分风侧换热器底部的结冰.     

国有收费公路企业全要素生产率测度及提升路径研究

近年来,收费公路行业绩效问题愈发凸显,但针对政府还贷公路运营载体的国有收费公路企业的研究却相对匮乏.为此,以2000～2019年21家国有收费公路企业的面板数据为研究样本,基于半参数估计法及Sequential-Malmquist指数法对国有收费公路企业全要素生产率(TFP)及其变动的内在结构性因素进行实证测度,得到如...     

江西省高速公路路侧交通事故统计分析和路侧障碍物处理对策

通过调查江西省昌樟高速梅林段、梨温高速和泰井高速2006年至2007年单车路侧交通事故,详细记录并分析事故资料,总结出江西省高速公路单车路侧事故的特点以及相应路侧障碍物在路侧事故中的反应特点,提出13种常见路侧障碍物的处理对策。     

新疆兵团道路运输业发展趋势分析

在对新疆生产建设兵团道路运输业现状分析的基础上,通过利用一元线性回归模型、平均增长率法以及灰色预测法三种方法分别对兵团2011～2015年的道路旅客运输量、道路货物运输量、道路旅客运输周转量、道路货物运输周转量等进行预测。结果显示,在未来5年当中道路旅客运输以年均7.7%增长,道路货物运输以年均9.2%增长,道路旅客周转量以年均10.6%增长,道路运输货物周转量以年均12.6%增长。     

一种改进的Jakes’信道模型及仿真

由于无线通信环境中存在的诸多不确定因素以及其在现代无线通信系统中的重要作用，合理的无线信道成为通信系统仿真研究的重要目的。确立信道仿真模型的目的就是为了尽可能的得到实际信道的统计特性，该文针对Jakes提出的信道模型，通过仿真来分析其局限性，并参考其中的谐波叠加（sum of sinusoids，SOS）法，来建立一种采用了随机分支增益、随机初始相位和有条件的随机多普勒频率改进的信道模型。     

复合地层盾构机推进速度SVM预测模型研究

在复合地层盾构法隧道施工中,如何提高盾构机推进速度一直是盾构机设计、施工人员研究的重点。以长沙轨道交通1号线五一广场到营盘路隧道工程为研究背景,现场采集盾构机掘进参数,应用SVM,建立了"五营"区间复合地层盾构机推进速度的预测数学模型,并对模型进行检测,检测结果表明该预测模型对推进速度预测的平均相对误差≤7%,验证了该模型对推进速度预测的有效性。     

Are HOV/eco-lanes a sustainable option to reducing emissions in a medium-sized European city?

Innovative traffic management measures are needed to reduce transportation-related emissions. While in Europe, road lane management has focused mainly on introduction of bus lanes, the conversion to High Occupancy Vehicles (HOV) and eco-lanes (lanes dedicated to vehicles running on alternative fuels) has not been studied comprehensively. The objectives of this research are to: (1) Develop an integrated microscopic modeling platform calibrated with real world data to assess both traffic and emissions impacts of future Traffic Management Strategies (TMS) in an urban area; (2) Evaluate the introduction of HOV/eco-lanes in three different types of roads, freeway, arterial and urban routes, in an European medium-sized city and its effects in terms of emissions and traffic performance. The methodology consists of three distinct phases: (a) Traffic and road inventory data collection; (b) Traffic and emissions simulation using an integrated platform of microscopic simulation; and (c) Evaluation of scenarios. For the baseline scenario, the statistical analysis shows valid results. The results show that HOV and eco-lanes in a medium European city are feasible, and when the Average Occupancy of Vehicles (AOV) increases, on freeways, the majority of vehicles can reduce their travel time (2%) with a positive impact in terms of total emissions (−38% NO_x, −39% HC, −43% CO and −37% CO₂). On urban and arterial corridors, the reduction in emissions could be achieved only if the AOV increases from 1.50 to 1.70 passengers/vehicle. Total emissions of the corridor with an AOV of 1.70 passengers/vehicle can be reduced up to 35–36% for the urban route while the values can be reduced by 36–39% for the arterial road. With the introduction of Hybrid Electric Vehicles (HEV) and Electric Vehicles (EV) it is possible to reduce emissions, although the introduction of eco-lanes did not show significant reductions in emissions. When both policies are simulated together, an emissions improvement is observed for the arterial route and for two of the scenarios.     

Sensitivity-based uncertainty analysis of a combined travel demand model

Travel demand forecasting is subject to great uncertainties. A systematic uncertainty analysis can provide insights into the level of confidence on the model outputs, and also identify critical sources of uncertainty for enhancing the robustness of the travel demand model. In this paper, we develop a systematic framework for quantitative uncertainty analysis of a combined travel demand model (CTDM) using the analytical sensitivity-based method. The CTDM overcomes limitations of the sequential four-step procedure since it is based on a single unifying rationale. The analytical sensitivity-based method requires less computational effort than the sampling-based method. Meanwhile, the uncertainties stemming from inputs and parameters can be treated separately so that the individual and collective effects of uncertainty on the outputs can be clearly assessed and quantified. Numerical examples are finally used to demonstrate the proposed sensitivity-based uncertainty analysis method for the CTDM.