海平面上升对长江口涨落潮历时差的影响

针对近年来全球变暖,海平面上升影响河口地区水文特性的问题,对海平面上升对长江口涨落潮历时差的影响进行研究。采用二维潮流数学模型的方法,模拟在长江口上游大通的洪枯季及年平均径流量条件下,海平面上升100 cm对涨落潮历时的影响。结果表明:海平面上升减小了长江口北支上半段、南支和南北港等中上游区域的涨落潮历时差,对靠近外海的北支末段和南北槽的涨落潮历时差影响很小。海平面上升加大了河口地区的涨潮动力,使长江口的涨落潮历时差有所减小,由此对长江口地区的盐水入侵和泥沙输运带来的影响必须引起重视。     

基于线段模型的高速公路安全与流量关系研究

高速公路上的车辆行驶速度快,因此保证高速公路上车辆的行驶安全至关重要.通过线段模型分析了高速公路安全与车流量之间的关系,确定了高速公路在轻载与重载中的运行性能标准,把超车过程抽象化,即将车视为质点,把车道视为一条线段,当后一质点每次超越前一质点时,记录并累加求和来替代超车.在上述指导方法下,引入车流量分析车流量与安全的关系,最后引入智能交通概念,对车流量与安全的关系进行深入分析.     

车队认知能力增强的通信区块间隙优化方法

为了在单车超越车队的过程中缩短超车车辆与车队间通信范围，减少车队通信压力，锁定影响车辆入队的关键车队区块，同时通过将待进入关键区块的车队进行间隙优化调整，为驾驶人提供定制化换道入队引导服务，提出了基于驾驶人超车风格特征参数的车队内信息传输关键区块锁定算法，通过分析影响驾驶人换道入队位置范围的关键因素，将驾驶人换道入队过程分为本车道速度调整过程与入队速度调整过程，利用非参数贝叶斯算法获取驾驶人超车换道特征数据并提出基于关键区块所在车队位置序列的车辆间隙优化调整策略。研究结果表明：超车车辆加速度、与前车预计碰撞时间、与车队相对速度是影响驾驶人换道入队范围的关键因素；通过非参数贝叶斯算法将超车车辆运行数据分类获取的驾驶人换道入队驾驶操作基元，可准确提供驾驶人行为特征关键参数；通过将驾驶人换道特征分为48个子类型，可锁定驾驶人换道入队范围且车队关键区块范围随着超车车辆与车队速度差值不同在各个特征类型上呈现不同变化趋势；针对驾驶人入队特征对待进入车队关键区块的车辆间隙进行优化调整，不仅可以为驾驶人提供可接受的驾驶辅助信息，同时减少了车队间隙产生过程中车辆加速度范围，提升了车队运行的舒适性。     

交叉口绿灯倒计时信号对黄灯时长的影响研究

在分析绿灯倒计时信号对驾驶员驾驶行为的影响以及最佳黄灯时间计算方法的基础上,建立车辆在绿灯末期运动过程的数学模型,确定考虑绿灯倒计时信号的最佳黄灯时间计算方法。计算分析结果表明：车辆加速性能对最佳黄灯时间的影响可以忽略;考虑绿灯倒计时信号的情况下,信号灯的可见距离越长,所需的黄灯时间越长;在信号灯可见距离足够远的情况下,最佳黄灯时长比未考虑绿灯倒计时信号多0.6～0.7 s。建议对于信号灯可见距离较远、流量未饱和,且未安装交通违法检测装置的交叉口,黄灯时间延长一个闪烁周期,并去除黄灯倒计时信号。     

基于贝叶斯网络的交通事件持续时间预测

随着数据采集手段的不断提高和相关研究技术的发展,基于数据挖掘的模型逐渐成为交通事件持续时间研究的主要方向。根据荷兰交通部门提供的交通事件采集数据,进行分类和预处理,观察事件持续时间的频数图,并根据相关的研究按照事件典型的类别把采集的数据进行分类。使用主成分分析和逐步回归提取出显著性的影响因子,利用数据挖掘软件WEKA建立贝叶斯网络模型,用数据集中80%的数据进行学习建模,20%的数据作为测试集来检测模型的预测效果,并做出性能评价。实验结果表明,与同类数据集的其他预测方法相比,贝叶斯网络模型对于变数众多,随机性特别大的交通事件,预测精度较高,证明贝叶斯网络模型的算法是具有一定优越性和实用价值。     

Examination of factors affecting freeway incident clearance times: a comparison of the generalized F model and several alternative nested models

Traffic incidents are a principal cause of congestion on urban freeways, reducing capacity and creating risks for both involved motorists and incident response personnel. As incident durations increase, the risk of secondary incidents or crashes also becomes problematic. In response to these issues, many road agencies in metropolitan areas have initiated incident management programs aimed at detecting, responding to, and clearing incidents to restore freeways to full capacity as quickly and safely as possible. This study examined those factors that impact the time required by the Michigan Department of Transportation Freeway Courtesy Patrol to clear incidents that occurred on the southeastern Michigan freeway network. These models were developed using traffic flow data, roadway geometry information, and an extensive incident inventory database. A series of parametric hazard duration models were developed, each assuming a different underlying probability distribution for the hazard function. Although each modeling framework provided results that were similar in terms of the direction of factor effects, there was significant variability in terms of the estimated magnitude of these impacts. The generalized F distribution was shown to provide the best fit to the incident clearance time data, and the use of poorer fitting distributions was shown to result in severe over‐estimation or under‐estimation of factor effects. Those factors that were found to impact incident clearance times included the time of day and month when the incident occurred, the geometric and traffic characteristics of the freeway segment, and the characteristics of each incident. Copyright © 2012 John Wiley & Sons, Ltd.     

长江江苏段船舶追越速度模型

船舶航行中,经常会出现追越局面.长江江苏段航道条件比开阔水域航道条件复杂,海事部门对追越作了严格规定.介绍了在追越受限前提下的长江江苏段航行船舶的追越模型,可为航行船舶提前计算追越时间、距离,避免违章追越,减少追越时产生的安全风险.     

Modeling transit vehicle repair duration and active service time

Abstract

The need for dependable and flexible models of transit vehicle maintenance has been well established in the literature as a means for improving daily operations, capital planning and service quality. Stemming from the practical need to predict the duration of maintenance activities and active service time for buses, this paper uses the principles of duration modeling to address two important questions: what is the duration of vehicle maintenance activities and, given that a bus is in active service, how long will it take? We extend previous work by including exogenous factors directly affecting maintenance duration and active service time in fully parametric duration models and examine such activities for the transit system in Athens (Greece). Results indicate that vehicle age, kilometers travelled and repair type are amongst the most important determinants of maintenance duration.     

Use of duration models for predicting vehicular delay at a US/Canadian border crossing

Delays caused by congestion at the US/Canadian border crossing between Washington state and British Columbia have underscored the need for some sort of intervention. One obvious congestion-mitigation measure would be to estimate delay times and then relay this information to motorists so that they could select among alternative border crossing sites, or delay their trips. This paper applies duration models to estimate vehicular delay and demonstrates the usefulness of such models as a basis for a fully automated motorist information system. The paper also explores the flexibility of duration models, in providing estimates of vehicle delay, by using alternate parametric forms and assessing prediction accuracy.