Accurate INS position solution during GPS outages or degraded GPS

Temporary degraded GPS (DGPS) position loss, in circumstances such as an overhead bridge, can be alleviated by an inertial navigation system (INS) that uses onboard sensors, such as yaw and speed sensors, to determine vehicle position. This paper introduces a post-processing DGPS/INS integration approach based on using the INS solution during DGPS outages or periods of low accuracy DGPS position solutions. In this approach, the INS solution initialization is performed using the DGPS solution before DGPS position solution loss, and measurements from the Inertial Measurement Unit (IMU). The final post-processed INS solution is a weighted average of the INS forward and backward solutions. This work constitutes two parts: the INS initialization methods for different degrees of freedom vehicle positioning models, and the developed weighting model necessary to combine the forward and the backward solutions. The former part is essential in obtaining acceptable INS initial states for both the stand-alone INS or any post-processing or real time INS/GPS integrated system. The latter part is based on the use of the complementary error behaviours of the backward and the forward solutions, and can be used as a survey method with acceptable position solutions accuracies. Applying the forward/backward INS combined solution method on real data shows that the resultant INS solution accuracy is 35 cm or less over a 1000 m road segment. This method is used to survey freeways interchange road segments where 50% of the surveyed distance has no DGPS solution or has a degraded DGPS solution. The average achieved accuracy over the whole freeways interchange is around 40 cm over a 23 km distance.     

基于当前统计模型的地图匹配车辆跟踪研究

为提高车辆跟踪系统的精度，减小差分全球定位系统（DGPS）的定位误差，通过分析行驶在城市道路上的车辆运动过程及其相应的运动模型，提出采用当前统计模型作为车辆运动模型。通过地图辅助位置择近和速度择角算法来修正卡尔曼滤波，为运行在道路上的车辆确定地图匹配估计。实际运行结果表明；整个车辆跟踪系统的精度有明显的提高。     

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.     

车载导航系统陀螺的自适应校正方法

分析了低成本压电振动陀螺误差及其影响因素,在实验的基础上得出采用温度补偿陀螺误差的可行性。建立了联合卡尔曼滤波方程融合GPS和INS信息,估计定位信息和陀螺误差。提出车载GPS/INS组合导航系统中陀螺零漂误差和标度因子误差的校正过程启动条件,当条件满足时,以估计的陀螺误差为输入,采用温度误差校正表学习算法对陀螺误差模型进行训练。用道路实验数据对提出的陀螺校正算法进行验证,结果表明该算法精度高、收敛快、可操作性好。     

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.     

上海市中环线真北路武宁路立交方案设计

分析了中环线真北路武宁路立交在上海城市道路网格局中的地位,明确了其功能定位,确定了该立交的建设标准和建设规模,提出了几个立交设计方案并分别进行了评价分析,通过比选确立了建议方案,并对城市立交的建设提出了一些建设性意见。     

基于GPS、GIS与GSM开发车辆监控调度系统的研究

论述了基于GPS、GIS与GSM开发车辆监控调度系统的主要内容与关键技术，包括车载GPS定位数据处理、GIS中用于车辆监控调度的电子地图的制作方法、数据通信等。最后结合实际开发工作给出了实现系统主要功能的编程思路。     

A Trajectory-Based Map-Matching System for the Driving Road Identification in Vehicle Navigation Systems

Driving road identification is the key issue of a vehicle navigation system that supports various services of intelligent transportation systems. The method for driving road identification is also known as map matching (MM). In spite of the development of MM algorithms, limitations still exist in obtaining the positioning data and preparing candidate roads (CRs) that may result in mismatches in some special difficult road configurations such as flyovers and parallel roads. To overcome the limitations, an integrated trajectory-based MM (tbMM) system is proposed based on the trajectory similarity evaluation method. The system can fuse the information from global positioning systems (GPS) and inertial sensors to generate the vehicle trajectory that represents the vehicle continuous movement in three dimensions. The elevation data of vehicle and roads are involved to enhance the trajectory-based matching process. Also the method employs an optimized mechanism for generating and maintaining CRs. Using the mechanism, separated road segments in a digital map are reorganized in the form of possible driving roads and the topology among them is guaranteed. Moreover, the CRs are obtained considering all the possibilities in determining the driving road so that the valuable historical information can be effectively reserved to provide more reliable matches in ambiguous situations. The tbMM system was evaluated using a number of real-world vehicle-level test datasets in urban areas in Beijing. Also a comparison test was performed to evaluate the driving road identification accuracy against existing MM algorithms. The results show that the tbMM system can provide reliable matches with about 99% accuracy in all the difficult scenarios and outperforms the existing algorithms.     

车辆GPS监控导航系统研究

综合分析了GPS车辆监控导航管理系统的研究背景以及国内外GPS车辆监控导航管理系统的研究现状.在此基础之上,以MapInfo为研究平台,选用VC++作为系统的开发工具,研制了符合我国国情的车辆导航系统.文中重点阐述了GPS车辆监控导航管理系统的设计方法,进而拟定了系统软件开发框架和各组成部分的性质功能.并以武汉市一环线为案例进行了模拟研究,结果表明所研制的GPS车辆监控导航管理系统能够有效的实施车辆的跟踪导航.     

基于GPS的公路视频影像信息系统

为了提高公路路况管理及路产管理的效率，开发了基于全球定位系统（GPS）的公路视频影像信息系统.通过视频影像的实时采集压缩和GPS定位，系统可实现基于里程和道路设施的多种视频影像搜索和定位功能，同时可根据电子地图快速定位到相应的视频图像帧.在论述了系统的体系结构后，推导了利用GPS坐标推算里程的算法，该算法通过录入关键帧对应的里程，内插出每帧的里程数，并对其进行修正.实践证明：该算法可有效地控制图像帧的里程误差，该系统可有效用于公路路况管理和公路路产管理.     

基于出租车GPS数据的城市次干道阻抗函数研究

城市道路阻抗函数的合理性、准确性和实时性是进行动态交通诱导的先要条件,也是交通规划领域的经典问题.目前对城市次干路,特别是违法停车影响下道路通行能力下降时的道路动态变化研究较少.以武汉市出租车GPS海量数据为基础,提出了不同道路情景及不同出租车行驶状态下的海量数据筛选策略,建立了出租车行程分析方法.另选用Smats便携式蓝牙和Wi-Fi扫描仪采集数据,针对该设备的工作原理提出了误差数据处理方法,得到真实交通流量和实验数据之间的对应关系.在BPR阻抗函数中引入非法停车条件下的道路通行能力变化规律,由出租车GPS数据和实验采集的道路交通流数据对阻抗函数表达式中的系数进行标定,并对结果进行了对比验证.结果表明,重新标定后BPR函数与真实道路阻抗的平均误差值与未改进的BPR函数相比,由26.1 s降为6.8 s.      

北京市城市快速道路系统节点分析与研究

快速路网中的节点功能定位是否恰当、立交选型是否合理 ,是能否实现快速路交通特性的重要因素。本文从北京市快速道路系统中的节点现状分析 ,提出节点存在的问题 ,采用“最短路径法”,对快速道路系统中的节点进行功能定位 ,并对今后快速道路系统中节点的建设与改造 ,提供指导原则和思路     

基于北斗-GPS双模导航在汽车行业应用的探讨

采用高灵敏、高定位精度、高可靠性的北斗-GPS双模车载导航系统,可以很大程度上弥补GPS的技术应用弊端,提升整体汽车产业的技术水平,增强中国汽车行业在国际上的影响力和话语权。     

Employment of instrumented vehicles to identify real-time snowy weather conditions on freeways using supervised machine learning techniques – A naturalistic driving study

This study introduces the idea of using vehicles as weather sensors to identify real-time weather on freeways in the same context as Road Weather Information System (RWIS) but in a continuous, trajectory-level, and for road segments allocated in the vehicles paths. The study developed a novel approach to detect snowy and clear weather conditions by utilizing real-time data collected from vehicles' external sensors and CANbus. The proposed approach used time series datasets from the SHRP2 Naturalistic Driving Study (NDS), collected during normal driving conditions on freeways. Trips occurring in snowy weather alongside matched trips in clear weather were segmented into time- and distance-based segments such as a one-minute, one-mile, and half a mile. Three assemblies of the input data are considered in the modeling step: data collected from external sensors, CANbus data, and these two data combined. Data analysis was implemented using the Deep Learning Artificial Neural Network, Decision Tree, Random Forest, and Gradient Boosted Trees models. The results indicate that using different segmentation levels provides decent results in detecting snowy weather. The accuracy in estimating the real-time snowy weather was in ranges of 80% to 85%, 71% to 79%, and 73% to 83% for the one-minute, one-mile, and half mile segmentation types, respectively. The GBT model performed the best among all models based on the area under the Receiver Operating Characteristics (ROC) curve, the highest cumulative percentage in estimating the snowy weather using the lower portion of the population, and the highest overall accuracy. Results indicated that an accuracy of 83% in estimating snowy weather conditions could be accomplished using the data collected from external sensors only without accessing CANbus data.     

改进联合滤波在GPS/DR组合定位中的应用

根据低成本车辆GPS/DR组合定位系统传感器精度低和计算能力弱的特点,提出一种改进联合卡尔曼滤波(FKF)算法,并简化主滤波器信息融合算法,稍微降低融合精度,提高计算效率。试验结果表明,提出的改进联合滤波算法具有融合精度高、容错性好、计算量小、便于工程实现等优点。     

Parameters optimisation of a vehicle suspension system using a particle swarm optimisation algorithm

The purpose of this paper is to determine the lumped suspension parameters that minimise a multi-objective function in a vehicle model under different standard PSD road profiles. This optimisation tries to meet the rms vertical acceleration weighted limits for human sensitivity curves from ISO 2631 [ISO-2631: guide for evaluation of human exposure to whole-body vibration. Europe; 1997] at the driver's seat, the road holding capability and the suspension working space. The vehicle is modelled in the frequency domain using eight degrees of freedom under a random road profile. The particle swarm optimisation and sequential quadratic programming algorithms are used to obtain the suspension optimal parameters in different road profile and vehicle velocity conditions. A sensitivity analysis is performed using the obtained results and, in Class G road profile, the seat damping has the major influence on the minimisation of the multi-objective function. The influence of vehicle parameters in vibration attenuation is analysed and it is concluded that the front suspension stiffness should be less stiff than the rear ones when the driver's seat relative position is located forward the centre of gravity of the car body. Graphs and tables for the behaviour of suspension parameters related to road classes, used algorithms and velocities are presented to illustrate the results. In Class A road profile it was possible to find optimal parameters within the boundaries of the design variables that resulted in acceptable values for the comfort, road holding and suspension working space.     

立交匝道中线及边桩的坐标放样

本文推导了立交匝道等道路交通中线和边桩在城市坐标系中的坐标计算公式 ,并介绍了实现整个线路实现连续统一计算的程序设计思路。采用本文所提供的计算方法 ,采用全站仪、GPS等仪器进行立交匝道放样极为方便     

淄博市湖田立交方案研究

湖田立交是淄博市近中期“二环五射”快速路网中一环南环昌国路和二环东环鲁山大道相交叉的节点立交。受场地内金泰铁路专用线和现状建筑的限制,立交匝道展线受限。根据路网分析并结合立交的建设条件,阐述立交的功能定位、提出建设技术标准、构思巧妙的立交形态并进行方案比选论证,推荐功能完善、合理可行的总体布置方案。     

交通拥堵的治本之道——城市不间断通行道路交通系统介绍

介绍了一种"城市不间断通行道路交通系统"。它是一个能够确保不会堵车的、高效快捷的智能化道路交通系统。这种交通系统没有红绿灯,车辆通行全过程不用停顿等候,排除了各种车辆通行的干扰因素,去除了各种交通瓶颈,避免了不同流向车流之间的交叉干扰,道路通行能力提高6倍以上,能自动保障公交、大中客车全天候畅行,能自动控制道路车流量。在这个系统中,还包括一个快捷高效的公交系统,确保乘坐公交上下班,主城区20 km路程包括换乘时间只需30 min。     

车辆运动方程定位原理的研究及其应用

利用车辆运动方程获取车辆行驶距离,车辆当前位置点处的道路方向作为方向角,根据航位推算原理实时推算车辆位置。通过实地跑车试验分别分析了该定位技术在车载导航系统和监控中心的应用。试验结果显示,在车辆导航系统中该技术能实现GPS盲区内的车辆连续定位功能;在监控中心中,该技术从理论上可以大大减少单个车辆和监控中心之间的信息流量,其实际应用还有待智能交通系统的进一步完善。