沥青混凝土路面预防性养护效益计算及参数

路面预养护效益分析是路面预养护技术的核心,是比选预养护方案和确定实施时机的前提。根据美国等路面预养护效益分析的经验,结合我国公路养护技术水平,对沥青混凝土路面预养护效益分析中的效益指标、效益计算基线和预养护时间范围展开了讨论;进而,提出我国现阶段沥青混凝土路面预养护分析中效益指标选用建议和它们计算下基线的参考值,以及预养护时间范围的控制指标和控制标准的建议值。     

高地应力千枚岩隧道二次衬砌施作时机研究

二次衬砌施作时机一直是高地应力软岩隧道工程设计与施工过程中面临的关键技术难题之一。为此,依托在建成都-兰州铁路典型千枚岩隧道工程,基于隧道变形长期监测结果,分析高地应力软岩隧道变形时程特点,考虑软岩隧道荷载特点,确定了二次衬砌施作时机原则;考虑隧道测量丢失变形,提出软岩隧道第1稳定阶段变形量确定方法;通过现场实测变形数据统计回归,基于一定保证率确定不同大变形等级和不同断面下的软岩隧道二次衬砌施作时机,并进行现场试验验证。研究结果表明:适当刚度的初期支护可以实现高地应力软岩隧道前期变形稳定,但无法保持围岩长期稳定,二次衬砌应该在初期支护变形达到第1稳定阶段后施作,既可以减少二次衬砌荷载,又可以控制围岩变形;采用指数函数拟合软岩隧道变形具有较好的相关性,但参数差异性较大,同时在确定隧道第1稳定阶段变形量时应考虑测量丢失变形;轻微、中等大变形段拱顶下沉变形速率小于0.1~0.2mm·d^-1,边墙收敛速率小于0.5mm·d^-1,严重、极严重大变形段拱顶下沉变形速率小于0.4mm·d^-1,边墙收敛小于0.6mm·d^-1,即可进行二次衬砌施作;轻微大变形段、中等大变形段和严重大变形段分别在隧道开挖45~55 d,55~60 d和80~90 d后达到二次衬砌施作标准。     

M型风电运维船船型设计与波浪增阻和耐波性能研究

本文基于三体风电运维船船型,结合M型船的特征要素设计改造出M型风电运维船。利用数值仿真技术模拟出M型风电运维船波浪航行时的波浪增阻与纵摇、垂荡情况,将数值仿真计算结果与原三体船的试验数据进行比较,以此探索不同M型船船型对船舶波浪航行时的波浪增阻与纵摇、垂荡情况的影响。最终确定了耐波性能较优的船型方案,从而为M型风电运维船船型设计提供了一定的参考和借鉴。     

考虑健康损失的路阻模型的构建

运用高斯烟羽模型计算机动车尾气排放量,然后利用支付意愿法定量分析健康损失,同时考虑延误和健康损失构建考虑健康损失的路阻模型。根据实例,分别使用Transcad和新的路阻模型计算出2个路阻,并进行交通分配。结果显示2次交通分配的路网流量不同,表明考虑健康损失的路阻模型影响了人们的出行选择,可有效解决主干路拥挤,增加次干路车流量,协调整个路网车流量均衡,提高路网交通效率。     

Assessment of factors associated with travel time reliability and prediction: an empirical analysis using probabilistic reasoning approach

Significant efforts have been made in modeling a travel time distribution and establishing measures of travel time reliability (TTR). However, the literature on evaluating the factors affecting TTR is not well established. Accordingly, this paper presents an empirical analysis to determine potential factors that are associated with TTR. This study mainly applies the Bayesian Networks model to assess the probabilistic association between road geometry, traffic data, and TTR. The results from this model reveal that land use characteristics, intersection factors, and posted speed limits are directly associated with TTR. Evaluating the strength of the association between TTR and the directly related variables, the log odds ratio analysis indicates that the land use factor has the highest impact (0.83) followed by the intersection factor (0.57). The findings from this study can provide valuable resources to planners and traffic operators in their decision-making to improve TTR with quantitative evidence.     

快速公交系统站台停靠时间模型研究

快速公交系统停靠站台停车延误是影响快速公交运行车速的关键因素之一,因此构建快速公交系统站台停靠时间模型是提升快速公交服务水平的基础理论研究。本文选取盐城BRT-1号线的起始站、中途站、客流离散站等三类站点为研究对象,综合运用数理统计法与数据挖掘法,构建快速公交系统站台停靠时间模型,并对该模型的合理性进行了检验。研究表明:盐城市BRT-1号线三类站台的快速公交车辆停靠时间与上下车乘客人数呈线性关系,即快速公交车辆停靠时间与上下车乘客人数的检验参数R2均大于0.8。     

红水河滚装运输方式价值研究

文章针对红水河运输需求大与通航设施能力小的矛盾。提出新型的滚装运输方式,介绍了滚装运输的线路、车型、船型选择方法。并通过与公路、铁路等运输方式在运价、运能及资源综合利用率方面的比较,论述了滚装运输方式的经济价值和社会价值。     

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.

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.     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.