Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

GPS一机多天线技术在公路边坡灾害监测中的应用研究

文章主要介绍了GPS一机多天线监测系统及其在公路边坡变形监测中的实际应用情况,通过实践可以证明:GPS一机多天线监测系统的定位精度可以达到3～5mm,与常规的GPS静态相对定位的精度相当,同时能够大大降低GPS监测系统的成本,使得公路边坡灾害监测能够实现高精度、自动化和全天候等目标。     

现代物流位置服务系统的设计

介绍了一个用于现代物流业的位置服务系统LTLBS，并着重就系统设计中的关键技术和与现代物流业有关的问题进行了分析。针对现代物流的特殊应用，在LTLBS中设计了一些特殊的功能，如货物跟踪，到达时间估计等。系统的性能分析表明定位精度和数据传输时延完全满足要求。     

南京长江第四大桥首级控制网的建立

介绍了南京长江四桥首级施工控制网的建立及特点．对如何采用当前测绘新技术布测特大型桥梁首级控制网并提高其成果精度、可靠性等相关技术指标进行了探讨,可供类似精密工程项目参考。     

基于GPS载波相位信号确定运动体姿态的关键技术

应用GPS载波相位信号确定运动体姿态,针对二维两天线系统情况,设计了姿态测量系统的硬件结构及算法流程框图,文章介绍了GPS姿态测量的关键技术：GPS姿态观测方程、整周模糊度的解算、误差的消除。从系统设计角度证明了技术的可行性。     

泰州长江大桥巨型深水沉井施工技术

泰州长江大桥中塔沉井号称"世界第一巨型深水沉井",高76m,入土深度达55m,详细介绍了该沉井施工的整体工艺流程,其多项创新性施工工艺对类似沉井施工具有借鉴意义。     

GPSRTK技术在道路测量中的应用

道路测量一般具有测线长、工期短、精度要求高等特点。GPSRTK适应这一要求,在各种道路测量中得到广泛应用。GPSRTK技术在简化道路测量的作业程序、提高作业效益的同时,其测量精度成为测绘工作者普遍关心的问题。结合实践工作,在分析GPSRTK技术产生误差原因的基础上,提出削弱误差的方法,验证GPsRTK技术的定位精度,供类似测量作业借鉴。     

基于GPS/GIS/GPRS的长途客车主动监控管理软件

针对目前长途客车主动监控管理软件需要人工抽检,自动化程度低和管理落后的现状,提出基于GPS/GIS/GPRS的长途客车主动监控管理系统软件的设计方法。在分析监管系统原理和组成的基础上,采用delphi＋MapX进行软件开发,实现地图操作、异常车辆显示、车辆通讯等功能,并建立系统数据库,完成对车辆异常情况的检索统计及分析。实车试验表明：该文提出的设计方法能提高对长途客车的监控效率和管理水平。     

公路GPS控制网建立方法的探讨

针对公路工程特点，就GPS测地系统建立公路GPS控制网的方法等问题进行了探讨。     

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电动汽车运行监控与统计分析系统主要由电动汽车信息采集与传输终端、运行监控系统以及运行统计分析系统构成.对信息采集与传输终端系统,主要讨论了系统的硬件组成结构和主要功能;在监控系统设计中,讨论了系统的功能,重点给出地理信息系统管理模块的实现方法;对统计分析系统,主要讨论了系统的组成、功能及设计方法.本系统现已经过长时间的试运行,实验结果表明:系统总体设计合理、功能齐全,工作性能稳定可靠.