多方式多类型交通分配模型(MMA)在收费型公路网中的应用研究

在对收费型公路运营模式进行研究的基础上,利用交通规划软件建立了基于广义费用的交通流量分配模型即多方式多类型交通分配模型,通过对模型参数的科学标定和网络的合理设置,得到各类车型在特定网络上的流量分配、路段饱和率以及通行费用,并对此模型的应用效果进行分析,最终为区域高速公路网规划、路段交通量预测提供依据。     

岷江上游大型水电站运行对龙溪口下游航道枯水期水位和流量的影响

根据规划,岷江龙溪口—宜宾段将通过航道整治达到内河Ⅲ级航道标准.该河段多年历时保证率95％的流量仅能达到662 m3/s,但是岷江上游紫坪铺、瀑布沟等大型水电站的建成对下游河段通航流量产生了较大影响.根据紫坪铺水电站蓄水前、后高场水文站的径流、泥沙资料,分析紫坪铺等大型水电站建成后对下游河段水沙特性的影响,得知岷江上游...     

取样剪切对管输原油流变性的影响

通过实验及理论分析,系统研究了取样剪切对管输原油流变性的影响,根据鲁宁线运行工况,计算了阀门节流剪切及过泵剪切时剪切率的大小.对于鲁宁线,在同一泵站,出站处阀门节流平均剪切率是过泵平均剪切率的3倍左右.     

隧道数字化火灾预警系统的在线量化评估

为检查和评价隧道及地下空间火灾预警系统的实际功能,需要一套可行的在线评估手段。根据近年来国内外全尺寸隧道火灾发展曲线的试验结果,提出隧道火情的定义依据;引用运营隧道内准分布式光纤光栅感温火灾探测器的实测数据,证明运营中隧道报警系统的个性化现象;提出合格的数字化报警系统应存在一个在统计学意义上使漏报率和误报率同时达到期望值的合理阈值取值区间;建议以该区间的尺度作为该系统功能完好性的评估指标;对日常隧道运行温度数据的统计分析可估计合理阈值取值区间的下限,对规定条件下的现场点火试验温度数据分析可估计合理阈值取值区间的上限。在隧道运营期该区间尺度可实时在线自动更新。     

多芯管套料工艺改进

为解决船用多芯管套料存在的材料利用率低、现场剩余材料浪费突出的问题,对多芯管的建模流程、采购流程和套料流程进行管控,形成新的更加合理有效的多芯管套料工艺,采用新工艺可达到最大限度提升多芯管套料合理性,提高材料利用率,减轻设计人员工作负荷,降低采购成本的目的.     

球扁钢肋骨三角形加热仿真研究

针对球扁钢肋骨三角形加热矫正纵向弯曲变形,利用ANSYS软件和APDL语言编写仿真程序,实现了热-结构耦合场的数值模拟,得到了加热过程中温度场和结构场的求解结果。对于不同的加热速度与气流输入量,计算了肋骨表面最高温度和高度方向的变形量,利用MATLAB曲面拟合,得到了最高温度和变形量关于加热速度和气流流量的函数。并对这两个参数进行了优化,得到了满足温度约束下变形量最大的参数组合。研究内容和结果对球扁钢肋骨三角形加热的更深入研究和现场施工提供了一定的参考和指导。     

超声相控阵缺陷检测技术研究

为了将相控阵超声检测技术进一步推广应用,对带有人工缺陷的试件分别采用CR、超声相控阵检测技术进行检测,将检测结果进行比对,试验结果表明CR检测技术与相控阵检测技术在体积型缺陷与面积型缺陷检出率方面各具优势,应结合实际工件使用工况,确定可能出现的缺陷类型,采用合适的检测方法与检测工艺,最大限度地提高缺陷检出率.     

Effects of countdown timers on queue discharge characteristics of through movement at a signalized intersection

This study investigates how countdown timers installed at a signalized intersection affect the queue discharge characteristics of through movement during the green phase. Since the countdown timers display the time remaining (in seconds) until the onset of the green phase, drivers waiting in the queue at the intersection are aware of the upcoming phase change, and are likely to respond quicker. Thus, the countdown timers could reduce the start-up lost time, decrease the saturation headway, and increase the saturation flow rate. This study observed vehicle flow at an intersection in Bangkok for 24 h when the countdown timers were operating, and for another 24 h when the countdown timers were switched off. The signal plans and timings remained unchanged in both cases. Standard statistical t-tests were used to compare the difference in traffic characteristics between the “with timer” and “without timer” cases. It was found that the countdown timers had a significant impact on the start-up lost time, reducing it by 1.00–1.92 s per cycle, or a 17–32% time saving. However, the effects on saturation headway were found to be trivial, which implies that the countdown timers do not have much impact on the saturation flow rate of signalized intersections, especially during the off-peak day period and the late night period. The savings in the start-up lost time from the countdown timers was estimated to be equivalent to an 8–24 vehicles/h increase for each through movement lane at the intersection being studied.     

Driver fatigue: a vision-based approach to automatic diagnosis

In this paper, we describe a system that locates and tracks the eyes of a driver. The purpose of such a system is to perform detection of driver fatigue. By mounting a small camera inside the car, we can monitor the face of the driver and look for eye movements which indicate that the driver is no longer in condition to drive. In such a case, a warning signal should be issued. This paper describes how to find and track the eyes. We also describe a method that can determine if the eyes are open or closed. The primary criterion for this system is that it must be highly non-intrusive. The system must also operate regardless of the texture and the color of the face. It must also be able to handle changing conditions such as changes in light, shadows, reflections, etc. Initial experimental results are very promising even when the driver moves his/her head in a way such that the camera does not have a frontal view of the driver’s face.     

Hybrid model for prediction of bus arrival times at next station

Effective prediction of bus arrival times is important to advanced traveler information systems (ATIS). Here a hybrid model, based on support vector machine (SVM) and Kalman filtering technique, is presented to predict bus arrival times. In the model, the SVM model predicts the baseline travel times on the basic of historical trips occurring data at given time‐of‐day, weather conditions, route segment, the travel times on the current segment, and the latest travel times on the predicted segment; the Kalman filtering‐based dynamic algorithm uses the latest bus arrival information, together with estimated baseline travel times, to predict arrival times at the next point. The predicted bus arrival times are examined by data of bus no. 7 in a satellite town of Dalian in China. Results show that the hybrid model proposed in this paper is feasible and applicable in bus arrival time forecasting area, and generally provides better performance than artificial neural network (ANN)–based methods. Copyright © 2010 John Wiley & Sons, Ltd.