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.     

固结黏土地层盾构直接破除排水板关键技术研究

宁波地铁5号线1期下穿高速公路路基时存在68°斜交长40 m的含塑料排水板的固结黏土地层,为研究盾构直接通过可行性、刀具选型、施工参数优化等问题,利用TBM掘进模态综合试验平台,进行了不同类型刀具、不同掘进参数的固结黏土地层排水板破除试验。研究表明： 对于含排水板的固结黏土地层,在合理选择刀具、盾构参数并优化掘进参数情况下,盾构法施工直接破除基本可行,试验为宁波地铁工程建设提供了依据,也可为类似工程设计及施工提供参考。     

基于三点模型的柴油机热工参数预测

准确预测热工参数劣化趋势是对柴油机实施预测维修的前提。已有预测技术均视不同时段信息所具有的建模价值相等,忽略了近期信息比远期信息更能反映设备当前运行态势这一客观事实,导致预测模型难以准确描述柴油机热工参数的真实变化规律。针对该问题,提出一种基于三点模型的柴油机热工参数预测方法,并采用新陈代谢法同步更新建模数据,以提高建模数据的利用效率及预测精度。与灰色系统GM(1,1)模型预测精度的对比结果表明,三点模型能够有效处理不同时段信息在反映设备运行态势能力上的差异,得到更为准确的预测结果。     

Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data

We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object may have passed between, given known origin and destination points. This paper utilizes a new form of TGDE to investigate taxicab GPS traces over a specified time horizon with position ‘gaps’. To this end, we propose a new extension to the TGDE framework, TGDE-C, which is used to determine the cumulative TGDE values for a group of GPS traces, at a given location. These metrics are applied to multiple taxis and allow for time of day analysis. Additionally, we combine these new extensions with existing TGDE metrics that allow us to determine how accessible individual or groups of vehicles are to urban opportunities.     

基于GPS和GSM的清管器智能跟踪系统

为了在清管施工中实时跟踪清管器,设计一种基于GPS系统和GSM通信系统的智能清管器跟踪系统,系统包括发射机、中继器和监控系统。发射机搭载在清管器上持续发射电磁信号和静磁信号,中继器预先埋设在设定的跟踪点接收和转发通过信息;清管器通过跟踪点时,中继器接收发射机发出的信号,精确识别出清管器并将通过时间和跟踪点GPS位置信息通过GSM网络发送至监控系统;监控系统接收到信息后,在监控界面地图上实时显示通过位置和通过时间。清管器卡堵时,系统可及时在地图上指示卡堵区间和到达卡堵现场路径。现场应用表明:该系统实现了清管器智能跟踪,通过时间和通过位置记录精确,降低清管施工中安全风险,节约成本。     

导管螺旋桨水动力学性能的影响因素

为了获取导管螺旋桨水动力性能的主要影响因素,指导导管螺旋桨的优化设计,采用计算流体力学CFD对Ka4-7010+19A导管螺旋桨进行水动力性能研究,分析不同导管长度、导管攻角、螺旋桨纵倾角及多导管组对其水动力特性的影响。结果表明：减少导管长度将使推力系数及扭矩系数同时增大,而敞水效率下降;适当增加导管长度可以略微提高其敞水性能;减小导管攻角在一定进速范围内使推力系数和扭矩系数同时大幅度增加,增加导管攻角将导致推力系数和扭矩系数同时下降;当螺旋桨纵倾角保持在10°以内时,不会对敞水性能产生太大影响。对于多导管螺旋桨而言,前置、后置及不同附属导管直径大小都对敞水性能有很大影响,其中后置大导管组螺旋桨能明显降低螺旋桨扭矩系数,并且能在低进速范围内提升敞水效率。研究成果可支撑导管螺旋桨的优化设计。     

GPS天线线型对AUV阻力和尾流场的影响

靠近艉部的GPS天线线型对AUV的阻力以及桨盘面处的伴流品质有直接影响。高品质的伴流场能有效地降低噪声并提高水动力性能。为了获得最优的GPS天线线型,以某自主式水下机器人(AUV)为母型,采用ICEM-CFD、Fluent等CFD软件,结合RANS方法和SSTκ-ω模型对搭载不同线型GPS天线的AUV进行数值计算。研究结果表明GPS天线设计前倾角可以有效降低天线的阻力,从而降低AUV受到的整体阻力。具有一定前倾角和尾端曲线的GPS天线有利于改善AUV尾部伴流特性,减小桨盘面伴流速度的不均匀度。     

振冲法加固砂土地基工艺选择及施工参数控制

根据砂土的黏粒含量,振冲法可采用不加填料的振冲密实法或有填料的振冲置换法,选择合适的振冲施工工艺和确定合理的工艺参数,与地基加固效果和地基处理的工程投资密切相关。在振冲器的振动荷载作用下,由于饱和砂土的液化产生振密作用,根据孔隙水压力的增长模型,推导了饱和砂土的临界液化时间,并分析留振时间的影响因素。结合两个工程实例,探讨了振冲密实法和振冲置换法两种工艺的适应性及加固效果。根据砂土的类型和黏粒含量,将砂土地基分为3类,不同的砂土地基采用合适的振冲工艺,并得出施工参数的合理区间。     

基于粗糙-模糊软计算的船板线加热成形加工参数预报方法

提出一种基于粗糙-模糊软计算的建模方法,构造一种基于贴近方向修正的高精度模糊推理算法,通过有限元分析(FEA)建立板材线加热成形工艺信息系统,根据粗糙集软计算获取线加热成形的工艺规律,运用模糊推理实现加工参数的快速准确预报。粗糙-模糊建模适用于线加热成形过程的静态或动态模型的构建,为实现该工艺的智能建模与控制提供一种新的技术手段。     

基于扩展卡尔曼滤波的GPS信号跟踪技术

提出一种基于扩展卡尔曼滤波的GPS信号跟踪方法,通过扩展卡尔曼滤波器,得到基于相干积分支路的滤波模型,有效地削弱常规GPS跟踪环路中的跟踪误差,增强接收机的抗干扰性能,提升其在信号较弱位置下环路的跟踪性能,对加入惯性信息条件下惯性信息对系统所产生的影响做了相应的分析研究。通过仿真对比结果可以知道:当处于弱信号条件时,与通常用到的GPS信号跟踪方式相比,基于扩展卡尔曼滤波的信号跟踪算法可以有效提升跟踪的精度。