哈大高铁影响下东北城市群交通网络空间结构特征研究

哈大高铁的运行缩短了东北城市群之间的相对距离,优化了东北城市群城市交通网络空间结构.通过建立向心性分形模型以及相关性分形模型,以交通距离代替空间的实际距离来研究城市群之间分形特征,通过城市间高速铁路时间距离和高速公路时间距离进行对比,计算高铁开通前后东北城市群交通空间聚集维数和空间关联维数,分析东北城市群交通网络空间结...     

基于 GIS-BIM 技术的山地城市长大通道选线方案及空间协同论证研究

山地城市长大通道具有地形条件复杂、里程长、控制因素多、工程投资大的特征。在国土空间规划“三区三线”划定落地的背景下,通道选线阶段应提前做好与“三区三线”的协同对接,集约利用土地等资源。针对山地城市长大通道的特征,分析线路设计方法与原则。以重庆中心城区—綦万快速通道工程为例,运用三维GIS技术建立基于大范围地形数据的基础模型,对路线方案进行三维可视化模拟分析,进行山地城市长大通道选线及空间协同论证实例分析。     

基于空间数据模型的产业集聚发展分析

产业集聚战略已成为我国各级地方政府发展经济的一项重要政策措施.以空间统计为主要研究方法,应用格点数据模型,对地方产业集聚现象进行研究分析,可以有效了解当地经济发展状况,合理规划地区经济发展方向.     

大跨径连续刚构桥主跨底板合龙预应力束的空间效应研究

对大跨径连续刚构桥中跨底板混凝土在底板预应力筋作用下可能纵向开裂的现象进行了分析,阐述了产生这种现象的力学机理。根据一座跨径布置为140 m 268 m 140 m的单箱单室预应力连续刚构桥的结构与设计特点,对该桥在底板预应力作用下的空间效应不利影响进行了分析,提出了避免跨中箱梁底板纵向开裂、底板混凝土向下崩出和腹板竖向拉应力过大的建议,可为大跨度连续刚构桥的设计提供参考。     

三维空间路线连续性衰退对公路安全性影响分析

为深入分析公路三维空间线形连续性衰退对事故频数的影响,采集广东省内3条高等级公路243 km道路设计资料,共1 768条有效事故数据,利用Tobit回归模型分析三维空间路线连续性衰退对公路安全性的影响.应用微分几何空间的基本理论,提出公路线形连续性衰退表征参数,利用Tobit回归模型对数据样本中单元内总曲率差(TCD)...     

国土空间规划体系下地下空间规划编制研究

理解地下空间的内涵,指出地下空间是城市重要的战略资源。提出转变地下空间发展理念,突出规划的引领作用。以北京市为例,结合北京地下空间规划建设经验,探索构建“全市—分区—特定地区”的地下空间规划编制体系,落实“生态优先、底线约束、专项统筹、刚性管控”的国土空间规划要求,提出各级地下空间规划编制的重点内容和技术方法。指出加强地下空间体制机制建设应从建立地下空间综合管理机制、推进地下空间技术标准整合、健全完善地下空间立法体系、建立国土空间三维信息平台4方面着手,健全地下空间规划实施保障。认为： 地下空间规划作为国土空间规划中的专项规划,应建立与国土空间规划体系相衔接的地下空间规划编制体系;在规划层级上,逐步建立和完善“全市—分区—特定地区”的全域、全要素地下空间规划体系,推动各级地下空间规划编制;在规划内容上,地下空间作为重要的国土空间资源,应立足地下空间资源禀赋和环境承载能力,明确地下空间生态安全底线,科学判断地下空间生态适宜性分区和开发利用重点分区,有效协调各类地下功能设施布局关系;在规划实施方面,应健全地下空间的刚性管控传导机制,加强地下空间的体制机制建设,完善地下空间部门管理、技术标准、权属管理、信息管理等方面的相关法律规范,以科学指导地下空间资源的合理有序利用。     

考虑溶洞空间形态的岩溶桩基稳定性分析方法

岩溶桩基的应用随岩溶地区交通工程建设的快速发展而越来越普遍,如何评价桩端岩溶顶板稳定性成为岩溶桩基设计的关键问题之一,针对目前桩端岩溶顶板稳定性分析平面假设的不完善性,考虑溶蚀作用形成的溶洞所具有的空间形态特征进行岩溶桩基稳定性分析。首先,将基桩作用下的岩溶顶板分别简化为固支梁、抛物线拱、圆拱与固支双向板等承载模型,采用结构力学与双向板分析理论建立不同模型的桩端岩溶顶板抗弯最小安全厚度计算方法;其次,通过计算结果对比分析,揭示岩溶顶板最小安全厚度随矢高的变化规律;在分析岩溶顶板冲切破坏与剪切破坏形式的基础上,探讨桩端岩溶顶板破坏模式的控制因素及其影响规律,进而获得桩端荷载、石灰岩抗拉强度、溶洞跨度与矢高等因素对桩端岩溶顶板承载特性的影响规律;然后,基于溶洞钻孔探测所得地质勘查信息构建岩溶桩基稳定性分析流程,提出考虑溶洞空间形态特征的岩溶桩基稳定性分析方法;最后,通过工程案例具体分析桩端岩溶顶板最小安全厚度及其破坏模式随矢高的变化规律。研究结果表明：桩端岩溶顶板破坏模式不仅与溶洞跨度、桩径有关,而且与溶洞形态及其矢高也密切相关,此外,石灰岩抗拉强度对岩溶顶板稳定性的影响同样较大,详细全面的工程勘察资料能使桩端岩溶顶板稳定性分析结果更接近实际情况。     

Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.     

Spatiotemporal traffic forecasting: review and proposed directions

This paper systematically reviews studies that forecast short-term traffic conditions using spatial dependence between links. We extract and synthesise 130 research papers, considering two perspectives: (1) methodological framework and (2) methods for capturing spatial information. Spatial information boosts the accuracy of prediction, particularly in congested traffic regimes and for longer horizons. Machine learning methods, which have attracted more attention in recent years, outperform the naïve statistical methods such as historical average and exponential smoothing. However, there is no guarantee of superiority when machine learning methods are compared with advanced statistical methods such as spatiotemporal autoregressive integrated moving average. As for the spatial dependency detection, a large gulf exists between the realistic spatial dependence of traffic links on a real network and the studied networks as follows: (1) studies capture spatial dependency of either adjacent or distant upstream and downstream links with the study link, (2) the spatially relevant links are selected either by prejudgment or by correlation-coefficient analysis, and (3) studies develop forecasting methods in a corridor test sample, where all links are connected sequentially together, assume a similarity between the behaviour of both parallel and adjacent links, and overlook the competitive nature of traffic links.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.