时程分析法在大蒲春河特大桥主桥抗震验算中的应用

采用时程分析法对大蒲春河特大桥进行抗震分析,对主桥控制部位E1概率和E2概率地震作用下的响应进行验算,并利用验算结果指导该桥的抗震设计.     

利用改进交叉算子的混合遗传算法求解VRPTW

设计了一种改进的混合遗传算法求解带有时间窗、有车辆重量限制的车辆优化调度问题（VRPTW），根据问题的实际情况，建立了数学模型，提出了改进的交叉算子，丰富了种群的多样性；并结合模拟退火算法的思想，对染色体的适应度适当变化，改善了传统的遗传算法容易“早熟”的缺点，加强了染色体的局部搜索能力。     

大跨度钢管混凝土拱桥地震反应分析

利用有限元法分析大跨度钢管混凝土拱桥的地震反应，考虑了剪切变形的影响，用子空间迭代法分析了其振动规律和动力特性，应用反应谱法和时程分析法分析了该拱桥的地震反应，得出了一些有价值的结论。     

城市道路拥挤收费福利影响研究

城市道路拥挤收费虽然使总的社会福利增加,但对不同时间价值出行者的福利影响却不尽相同.以福利经济学为理论基础,以出行的货币成本和时间成本为影响因素,量化分析收费后不同出行者的福利得失.研究发现,在确定拥挤方案后如果能得到交通量的变化量,就可以得到不同选择方案出行者的福利得失.时间价值较低的出行者只有选择公共交通时才能从拥挤收费中受益,而时间价值较高的出行者,选择付费出行使他们获益最大.     

沥青洒布车智能递阶控制系统

为了探讨沥青洒布车的新智能控制方式,在传统的沥青洒布车智能控制的基础上,提出利用智能递阶控制的自适应性、自学习、实时性等优点,使沥青洒布车能根据工作环境的变化进行调节,保证其喷洒恒定和实时性,使其具有良好的作业质量。建立了递阶控制四层系统,介绍了该系统的总体结构和沥青洒布车递阶控制系统的软件结构与硬件结构以及算法,并给出了沥青洒布车的四层递阶控制的试验结果,能实时达到工程施工较高的作业要求。     

高速公路软基固结度分析及应用

在原有固结度计算理论基础上，对广珠西线高速公路试验段实测资料进行分析，提出一种可计算超载或欠载路段在设计荷载下的固结度，为加载设计和卸载时机判断提供依据，理论计算与实测结果符合程度较好。     

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。     

软弱地层中瑞雷波传播的数值模拟研究

瑞雷波技术已经广泛用于工程物探和质量检测中,但对软弱地层的探测尚缺乏系统深入的研究.本文采用有限差分软件FLAC3D对横向存在软硬分区、表层软弱及软弱夹层3种地层模型作数值模拟,分析了相应地层模型中瑞雷波时域信号传播特征,得出了传播规律.为工程技术人员现场快速时域信号分析提供了帮助.     

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.     

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.