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在目前的出租车调度系统中,调度的出租车可能需要经过城市堵车区域,不能及时为乘客提供服务,本文对城市道路堵车对出租车调度的影响进行研究.根据出租车自动上传的城市道路堵车信息,建立出租车通过堵车区域的损耗方程,结合城市各道路交叉路口之间的距离,采用Dijkstra算法对最佳调度路径进行求解.实验仿真结果给出了发生堵车时,不同单位额外损耗(β)情况下对应的调度路程、路径和规避堵车区域发生的时间.最后与未考虑城市道路堵车的调度系统进行比较.比较结果表明,通过设置合理的β值,系统可根据堵车严重程度,合理规划出租车路径,规避堵车较严重区域.     

Developing travel time estimation methods using sparse GPS data

Existing methods of estimating travel time from GPS data are not able to simultaneously take account of the issues related to uncertainties associated with GPS and spatial road network data. Moreover, they typically depend upon high-frequency data sources from specialist data providers, which can be expensive and are not always readily available. The study reported here therefore sought to better estimate travel time using “readily available” vehicle trajectory data from moving sensors such as buses, taxis, and logistical vehicles equipped with GPS in “near” real time. To do this, accurate locations of vehicles on a link were first map-matched to reduce the positioning errors associated with GPS and digital road maps. Two mathematical methods were then developed to estimate link travel times from map-matched GPS fixes, vehicle speeds, and network connectivity information with a special focus on sampling frequencies, vehicle penetration rates, and time window lengths. Global positioning system (GPS) data from Interstate I-880 (California) for a total of 73 vehicles over 6 h were obtained from the University of California Berkeley's Mobile Century Project, and these were used to evaluate several travel time estimation methods, the results of which were then validated against reference travel time data collected from high resolution video cameras. The results indicate that vehicle penetration rates, data sampling frequencies, vehicle coverage on the links, and time window lengths all influence the accuracy of link travel time estimation. The performance was found to be best in the 5-min time window length and for a GPS sampling frequency of 60 s.     

A weight-based map-matching algorithm for vehicle navigation in complex urban networks

A map-matching algorithm is an integral part of every navigation system and reconciles raw and inaccurate positional data (usually from a global positioning system [GPS]) with digital road network data. Since both performance (speed) and accuracy are equally important in real-time map-matching, an accurate and efficient map-matching algorithm is presented in this article. The proposed algorithm has three steps: initialization, same-segment, and next-segment. Distance between the GPS point and road segments, difference between the heading of the GPS point and direction of road segments, and difference between the direction of consecutive GPS points and direction of road segments are used to identify the best segment among candidates near intersections. In contrast to constant weights applied in existing algorithms, the weight of each criterion in this algorithm is dynamic. The weights of criteria are calculated for each GPS point based on its: (a) positional accuracy, (b) speed, and (c) traveled distance from previous GPS point. The algorithm considers a confidence level on the assigned segment to each GPS point, which is calculated based on the density and complexity of roads around the GPS point. The evaluation results indicate 95.34% correct segment identification and 92.19% correct segment assignment. The most important feature of our algorithm is that the high correct segment identification percentage achieved in urban areas is through a simple and efficient weight-based method that does not depend on any additional data or positioning sensors other than digital road network and GPS.     

基于AIS人员落水应急示位系统的研究与实现

历年来,船上人员落水事故频繁发生,如果不能确定落水人员的确切位置,搜救工作很难进行。针对这一现象,研究并实现了基于 AIS 的人员落水应急示位系统,系统应用AIS（自动识别系统）和GPS（全球定位系统）两种技术,能够及时向岸上AIS基站以及配备有AIS装备的船舶发送求救信号,该信号可较为准确地给出落水人员现处位置并实时监测其位置变化。这两项技术的应用使得该系统比传统的救生装置速度更快、效率更高,为搜救人员提供更可靠的信息,从而大大减少搜救人员的工作量,降低因人员落水造成的伤亡事件的发生率。     

基于流量和出租车GPS数据的城市道路网络宏观基本图

为把握城市宏观交通状况,发掘城市道路网络交通流内在特性,从而达到缓解日益严峻的交通问题的目的,对交叉口流量和出租车GPS两类数据进行数据融合,运用宏观基本图(MFD)和广义宏观基本图(GMFD)在城市道路网络中的存在性以及二者之间存在的差异,以路网平均车辆数、路网通行能力和密度分布为指标来描述MFD和GMFD,并提出一种利用路段流量和出租车GPS数据拟合得到MFD和GMFD的方法,发现路网中密度的不均匀分布是导致路网通行能力不高的原因.针对由长沙市13个道路交叉口组成的区域路网,分别计算出分小区和分路段的MFD特征值,提出了根据存储空间能力(即临界路网平均车辆数的大小)对拥堵路网进行合理分流的方法,实现高峰时期拥堵路段的路径诱导以及路网通行能力的最大化.     

基于GPS定位信息的出租车OD矩阵推算

针对现有出租车OD调查方法在实际操作过程中存在的不足问题,提出了一种基于全球定位系统和地理信息系统,通过使用FME Universal Translator矢量图形转换软件和Excel-VBA宏,实现出租车OD矩阵推算的方法。     

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云计算借助高速网络将各种计算能力联接起来,为交通信息提供了几乎无上限的可伸缩的计算能力. 本文分析了交通信息云计算的优势、特征、方法和部署,认为交通信息云计算也是一种信息高效采集和服务的概念,是实现交通行为控制的基础. 以车辆GPS定位信息的获取、传送、计算和应用为例,对比了浮动车信息现有处理模式与云计算信息处理模式,提出了以云计算模式产生高效用度、闭环可验证的个性化路径导航信息作用于海量驾驶员个体,实现控制性路径诱导的方法.     

基于GPS的成品烟运输跟踪器的开发

应用AVR微程序控制器芯片、GPS接收板、GPRSMODEM模块研制了成品烟运输跟踪器,采用GPRS无线移动通讯技术与指挥中心建立了TCP/IP连接,传递了车辆的位置信息及运行状态.指挥中心可对车辆做出调度指挥与全程监管,以降低物流成本、提高服务质量,保证运输安全.     

GPS控制网的建立及精度分析研究

以GPS测量控制网作为首级控制网,对网内各点进行GPS测量,并对各点坐标(平面)进行有关转换,解算出各点平面坐标(城市坐标系),对测量数据精度进行分析;进行GPS测量替代水准测量试验,分析GPS高程拟合精度,从而验正基于GPS技术建立城市首级测量控制网的可行性。     

GPS高精度测速研究

文章介绍了GPS系统测速的基本原理和算法,并在此基础上讨论了对卫星轨道误差、对流层误差、电离层误差、载波相位噪声和星钟误差等误差源的修正算法及其对测速精度的影响。最后,通过实验测试进一步验证了高精度测速算法的可行性。