An adaptive information fusion model to predict the short-term link travel time distribution in dynamic traffic networks

As intelligent transportation systems (ITS) approach the realm of widespread deployment, there is an increasing need to robustly capture the variability of link travel time in real-time to generate reliable predictions of real-time traffic conditions. This study proposes an adaptive information fusion model to predict the short-term link travel time distribution by iteratively combining past information on link travel time on the current day with the real-time link travel time information available at discrete time points. The past link travel time information is represented as a discrete distribution. The real-time link travel time is represented as a range, and is characterized using information quality in terms of information accuracy and time delay. A nonlinear programming formulation is used to specify the adaptive information fusion model to update the short-term link travel time distribution by focusing on information quality. The model adapts good information by weighing it higher while shielding the effects of bad information by reducing its weight. Numerical experiments suggest that the proposed model adequately represents the short-term link travel time distribution in terms of accuracy and robustness, while ensuring consistency with ambient traffic flow conditions. Further, they illustrate that the mean of a representative short-term travel time distribution is not necessarily a good tracking indicator of the actual (ground truth) time-dependent travel time on that link. Parametric sensitivity analysis illustrates that information accuracy significantly influences the model, and dominates the effects of time delay and the consistency constraint parameter. The proposed information fusion model bridges key methodological gaps in the ITS deployment context related to information fusion and the need for short-term travel time distributions.     

On the income elasticity of the value of travel time

Transport infrastructure is long-term and in appraisal it is necessary to value travel time savings for future years. This requires knowing how the value of time (VTT) will develop over time as incomes grow. This paper investigates if the cross-sectional income elasticity of the VTT is equal to inter-temporal income elasticity. The study is based on two identical stated choice experiments conducted with a 13 year interval. Results indicate that the relationship between income and the VTT in the cross-section has remained unchanged over time. As a consequence, the inter-temporal income elasticity of the VTT can be predicted based on cross-sectional income elasticity. However, the income elasticity of the VTT is not a constant but increases with income. For this reason, the average income elasticity of the VTT in the cross-sections has increased between the two survey years and can be expected to increase further over time.     

适于TBM施工的HSP法实时预报技术设计与实现

为实现TBM施工隧道的实时地质预报,以TBM刀盘滚刀破岩震动作为震源的HSP法地质预报技术为基础,通过分析TBM施工工艺与机身结构特点,对HSP系统硬件和软件进行优化设计,使其小型化、自动化和智能化,并搭载于TBM上进行智能控制。在TBM掘进过程中,首先,通过隧道轮廓位置的检波器连续或高频次地采集地震反射波信号; 然后,经系统软件对数据的自动处理,实时获取掌子面前方地层反射特征参数图谱; 其次,通过智能识别技术完成对不良地质反射界面的有效拾取与判识; 最后,实现不良地质的探测。通过对适于TBM施工的HSP法实时预报技术进行优化设计,实时探查前方地层不良地质(体)位置、规模与性质,为TBM的高效施工起到一定的推助作用。     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

智能网联车环境下高速匝道汇入车流轨迹优化模型

为了解决传统匝道控制车流汇入时车辆需要减速至停止,从而造成延误时间过长的问题,提出了一种智能网联车环境下的高速匝道汇入车辆轨迹优化的两阶段优化模型,其中,第1 阶段优化车辆进入匝道口的时序;第2 阶段基于第1 阶段的最优时序,优化车辆轨迹. 根据所构建的模型设计了一种启发式算法优化车辆通过匝道冲突区域的时序,然后结合 GPOPS工具优化车辆的轨迹.为了验证所提出方法的有效性,将所提出的方法应用到20 min 随机到达的车流,进行仿真实验.实验结果表明,与先进先出的方法相比,本文所提出的方法能够使总延误减少59.7%,总油耗减少10.5%,说明该方法能够实现车辆以较高的速度通过匝道冲突区域,有效地减少了车辆汇入延误,同时也节约了油耗.     

大直径钢管桩承载力恢复过程试验研究

针对目前预制桩承载力恢复特性研究与工程应用中的不足,依托西非某海工工程,提出高应变法。采用对同一钢管桩进行初打与不同休止时间复打相结合的试验方法,研究了大直径钢管桩沉桩后的承载力恢复过程。结合地质情况、沉桩与试验结果,得到了钢管桩承载力、侧阻力及端阻力随时间变化的一般规律及影响因素,并通过静载试验对研究结果进行了验证。该研究在提高项目施工效率、降低成本的同时,还得到了有意义的规律与结论,可为后续类似项目提供参考。     

表面损伤斜拉索雷诺数临界区气动力与流场分析

斜拉索由于具有自身质量轻、结构刚度差、结构阻尼小和自身长细比大的特点,极容易发生风（雨）致振动,对桥梁结构的安全性能产生很大的影响,而斜拉索作为斜拉桥的重要受力构件,准确掌握其风荷载对于桥梁抗风设计具有重要意义,特别是斜拉索在生产、运输和安装过程中表面可能受到损伤,该斜拉索在临界雷诺数区的气动力特性和流场特性更是值得研究的问题。针对此种状况,通过同步测力风洞试验,对表面无损伤斜拉索模型和表面损伤斜拉索模型在不同风攻角下的升力系数进行时程分析,得到边界层转捩的3个区域;将升力系数时程进行快速傅里叶变换计算得到升力时程频谱图,并通过频谱图分析随机信号的频域特征;对比从雷诺数亚临界、临界到超临界区表面无损伤和表面损伤斜拉索的流场变化,并从周围流场变化的角度分析雷诺数临界区斜拉索气动稳定性及可能的机理。研究结果表明：表面无损伤和表面损伤模型的升力系数随雷诺数的变化规律基本一致,二者的升力时程在TrBL0向TrBL1阶段和TrBL1向TrBL2阶段过渡过程中会出现双稳态现象,损伤会影响斜拉索尾流区旋涡脱落的情况,进而对不同雷诺数下的Strouhal数值变化产生一定的影响。     

基于全数检验与定时截尾试验的地铁列车整车可靠性验收方法

提出地铁列车可靠性验收的基本条件,分别介绍了基于定时截尾试验、序贯截尾试验和全数检验的3种经典的可靠性验收方法;提出基于全数检验和定时截尾试验的地铁列车整车可靠性验收方法,设计了可靠性验收的流程;以某一具体项目为例,对该可靠性验收方法进行了验证。结果证明:基于全数检验与定时截尾试验的地铁列车整车可靠性验收方法是有效的,可以节省试验时间。     

基于客流需求的城市轨道交通动态时刻表优化模型

为使城市轨道交通列车运行时刻表更贴合客流需求,依据不断变化的客流需求确定每列车的发车时刻和停站时间,采用多目标优化方法构建以乘客出行时间费用和列车运行时间费用最小为目标、列车发车时刻和停站时间为决策变量的城市轨道交通动态时刻表优化模型,并采用粒子群算法求解。以广州地铁13号线为例进行验证,结果表明优化后的时刻表更满足客流需求,能有效地提高乘客出行效率,具有更好的动态适应性。     

基于MQ插值的变形网格在船舶阻力预报中的应用

在非结构切分网格的框架下,发展了一种基于Multi-Quadric插值的变形网格技术,结合CFD软件STAR-CCM+,采用SST湍流模型,并以VOF法进行自由液面的追踪,将该变形网格技术应用于带附体穿浪双体船的阻力预报中。分别以网格的拉伸变形和斜率变形实现了阻流板和尾楔的边界运动,计算了阻流板高度为4 mm、6 mm和8 mm以及尾楔角度为5°、10°和15°时的工况。计算结果表明,变形网格方法与固定网格方法取得了相同的精度;同试验值相比,在不同工况下变形网格最大平均误差约为6.67%,验证了其可行性。但是,相比于固定网格方法,变形网格方法的计算时耗最大可减少40%,因此采用该变形网格方法可极大地提高带可变形附体的船舶的阻力预报效率。