Shockwave-based queue estimation approach for undersaturated and oversaturated signalized intersections using multi-source detection data

With the progress of information and sensing technologies, estimating vehicular queue length at signalized intersections becomes feasible and has attracted considerable attention. The existing studies provided a solid theoretical foundation for the estimation; however, the studies have some restrictions or limitations more or less. This paper presents a new methodology for estimating vehicular queue length at signalized intersections using multi-source detection data under both undersaturated and oversaturated conditions. The methodology applies the shockwave theory to model queue dynamics. Using data from probe vehicles and point detectors, analytical formulations for calculating the maximum and minimum (residual) queue lengths of each cycle are developed. Ground truth data were collected from numerical experiments conducted at two intersections in Shanghai, China, to verify the proposed methodology. It is found that the methodology has mean absolute percentage errors of 17.09% and 12.28%, respectively, for maximum queue length estimation in two tests, which are reasonably effective. However, the methodology is unsatisfactory in estimating the residual queue length. Other limitations of the proposed models and algorithms are also discussed in the paper.     

Classification of Livebus arrivals user behavior

With the increasing use of Intelligent Transport Systems, large amounts of data are created. Innovative information services are introduced and new forms of data are available, which could be used to understand the behavior of travelers and the dynamics of people flows. This work analyzes the requests for real-time arrivals of bus routes at stops in London made by travelers using Transport for London's LiveBus Arrivals system. The available dataset consists of about one million requests for real-time arrivals for each of the 28 days under observation. These data are analyzed for different purposes. LiveBus Arrivals users are classified based on a set of features and using K-Means, Expectation Maximization, Logistic regression, One-level decision tree, Decision Tree, Random Forest, and Support Vector Machine (SVM) by Sequential Minimal Optimization (SMO). The results of the study indicate that the LiveBus Arrivals requests can be classified into six main behaviors. It was found that the classification-based approaches produce better results than the clustering-based ones. The most accurate results were obtained with the SVM-SMO methodology (Precision of 97%). Furthermore, the behavior within the six classes of users is analyzed to better understand how users take advantage of the LiveBus Arrivals service. It was found that the 37% of users can be classified as interchange users. This classification could form the basis of a more personalized LiveBus Arrivals application in future, which could support management and planning by revealing how public transport and related services are actually used or update information on commuters.     

公交联动发车模型的研究

乘客的候车时间可分为2部分(在出发站点的等待时间及在换乘站的换乘时间),仅考虑换乘时间最短的区域公交协调调度模型无法降低乘客在出发站点的等待时间。针对此问题,提出了公交联动发车的概念及需满足的条件。在对乘客类型分类的基础上,分析了弹性乘客候车时间的计算方法,统计了各类型乘客的各部分候车时间,以所有乘客总的候车时间最短为目标建立公交联动发车模型。针对模型变量多的特点,选用遗传算法进行了求解。采用实例对模型的有效性进行了验证。结果表明,在维持发车间隔不变的基础上,联动发车模型较区域协调调度模型在降低乘客候车时间方面具有明显的优势,乘客候车时间降低了15.2%。      

某过江通道工程始发井地表施工监测分析

以南京市纬三路过江通道工程江北始发井为工程背景,介绍了盾构机推进路线上方的施工监测项目、测点布设原则及情况,结合盾构机掘进位置分析地表及周边建构筑物的施工监测数据,研究地表结构的沉降变化规律。     

破碎岩体注浆加固后的力学特性研究（双语出版）

基于理论分析建立破碎岩体注浆加固体力学模型,通过室内试验制作加固体试样并开展单轴抗压试验,分析破碎岩体含量、破碎程度、界面粗糙程度以及注浆材料黏结性能等因素对加固体强度的影响。试验表明：注浆加固体试样在单轴压缩破坏过程中,其内部石块基本保持完整性,破坏主要产生在交界面以及注浆材料内部;当V_BP较大时,在碎石体的阻隔作用下,破裂面无法一次性产生,且多为剪切型破坏;当V_BP较小时,压缩破坏过程中直接形成了上下贯通的破裂面,且多为拉断型破坏;对于未加固的破碎岩体,其强度随V_BP增加而减小,且强度离散程度较大;加固后其强度随V_BP的增大而增大,整体强度大幅提高,同时呈现出明显的线性相关性;加固体强度随碎石数量的增加而减小,二者的线性相关性不显著;加固体强度随着注浆材料黏结强度的增加而增加,随交界面体密度的增加而减小;交界面体密度与黏结强度相互影响,总体强度是二者耦合作用的结果。基于加固体力学模型以及单轴抗压试验数据提出了加固体强度计算公式,该公式考虑了破碎岩体含量、破碎程度、界面粗糙程度以及注浆材料黏结性能等因素对加固体强度的影响。通过与实际试验数据比较,证明了该公式可以较好地对破碎岩体加固强度进行预测。     

大型综合客运枢纽送站坪的车辆延误（双语出版）

为了准确评估大型综合客运枢纽送站坪的服务水平,改善其交通秩序,提高管理水平,针对送站坪车辆的常规落客行为和违规行为造成的延误,进行了量化分析研究。在大量调研数据的基础上,提取车辆轨迹,通过虚拟线圈的方法获取车辆的运动参数和交通流信息,基于车辆运行特征和车流波动理论,提出了落客车辆汇入行车道时等待可穿插间隙的延误模型、行车道车辆受穿插车辆影响的延误模型以及违规行为造成的行车道车辆延误模型等,验证结果表明,延误模型计算结果与实测结果近似。针对客运枢纽常见的两车道送站坪的交通特性,将车辆在落客车道的行驶距离、落客时长、速度、加减速度等参数作为自变量,基于高峰期间车辆到达分布推导出了送站坪车辆的平均延误,在此基础上给出了送站坪车辆行程时间的理论推导模型和多元线性回归模型。实例验证结果显示：2个行程时间模型计算结果与实测数据基本吻合,平均误差均为13%,回归模型的拟合优度为0.868;减少模型变量,以车辆在落客车道的行驶距离和落客时长为自变量,拟合优度也达到了0.853,表明这2个变量对车辆在送站坪系统的总延误影响最大,它们的值可以基本反映出车辆在送站坪系统的总延误,研究结果可为仿真模型的构建及通行能力的研究提供理论基础。     

基于Redis盾构远程监控系统设计

为解决B/S模式的盾构远程监控系统随着处理数据量加大出现数据库负载过大、网页显示延迟等问题,基于B/S模式和Redis缓存技术设计盾构远程监控系统,系统包括数据层、应用层和展示层3部分。在数据层中使用Redis缓存数据,使系统具有高效的数据处理能力,并搭建Redis集群以实现高容灾和高可用性; 应用层和展示层采用分模块方式设计,可降低系统耦合度,简化开发流程。     

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经过规范化的发展,已经涌现出不少成熟的企业信息集成(EII)模型,而城市交通信息集成（UTII）方面还缺乏规范、成熟的模型。基于此,本文从流程再造、数据交互以及数据挖掘三个方面,提出了一种城市交通信息集成三维模型（3D-UTII)。这三个维度的集成即为：基于流程再造的交通信息系统内部的深度集成（DDII）,基于异构数据库技术的交通信息系统间的广度集成（EDII）,以及基于数据挖掘技术的分析式集成（ADII）。本文对这三个维度的实施框架和具体实现技术分别做出了进一步阐述,最后使用北京市奥运交通应急系统的信息集成方案为实例对模型的实施做出了说明和验证。     

A data model applied to the knowledge-based ICAS

Image-guided computer aided surgery system (ICAS) contributes to safeness and success of surgery operations by means of displaying anatomical structures and showing correlative information to surgeons in the process of operation. Based on analysis of requirements for ICAS, a new concept of clinical knowledge-based ICAS was proposed. Designing a reasonable data structure model is essential for realizing this new concept. The traditional data structure is limited in expressing and reusing the clinical knowledge such as locating an anatomical object, topological relations of anatomical objects and correlative clinical attributes. A data structure model called mixed adjacency lists by octree-path-chain (MALOC) was outlined, which can combine patient's images with clinical knowledge, as well as efficiently locate the instrument and search the objects' information. The efficiency of data structures was analyzed and experimental results were given in comparison to other traditional data structures. The result of the nasal surgery experiment proves that MALOC is a proper model for clinical knowledge-based ICAS that has advantages in not only locating the operative instrument precisely but also proving surgeons with real-time operation-correlative information. It is shown that the clinical knowledge-based ICAS with MALOC model has advantages in terms of safety and success of surgical operations, and help in accurately locating the operative instrument and providing operation-correlative knowledge and information to surgeons in the process of operations.     

基于逆向重力模型的枢纽机场旅客吞吐量估计方法

为了利用航空OD客流数据精确估计机场旅客吞吐量, 描述了全连通线性航线网络和枢纽辐射航线网络, 根据枢纽机场之间的OD客流矩阵, 建立了逆向重力模型标准代数算法和基于哈密顿图原理的简化代数算法, 分析了在不同距离修正指数下, 算法的拟合与估计精度。分析结果表明: 简化代数算法与模型标准代数算法最优吞吐量回归直线的可决系数都为0.84, 斜率分别为0.91和0.87, 比较接近。可见算法的拟合效果优良, 估计精度高, 且简化代数算法需要的数据少, 尤其适合大规模OD矩阵分析。