基于虚拟差分的单GPS车道级地图匹配方法

本文提出一种采用最小二乘法拟合单GPS虚拟差分定位参数修正的方法,并在对车道级地图匹配问题的描述基础上,提出采用递阶式地图匹配方式,通过粗匹配和精确匹配两个阶段实现车道级地图匹配,实验测试,表明该方法具有理想的匹配效果。     

一种在电子地图上显示拥堵路段的事故车道的方法

文章介绍了一种在电子地图上显示事故车道的方法,通过分析安装在人工智能移动GPS车辆上的传感器和陀螺仪传感器,通过综合分析,给出了大量智能手机在一定时间范围内的数据资源,可以判断GPS数据和陀螺仪数据是否能呈现一定的规律性,进而影响对车道拥堵的判断,进而利用现代互联网技术发送给正在使用电子地图的智能手机用户堵车信息,告知驾驶员前方哪个车道已关闭,促使他们提前换道。     

卫星收费系统GPS定位信息和路段匹配方法研究

描述了1种GPS定位信息和电子地图收费路段匹配的方法,分为地图精简和地图匹配2部分。根据GPS定位收费系统对地图及地图匹配的要求,对电子地图进行了精简。路段识别采用了GPS位置点和路段收费位置节点的匹配方法,通过设定收费标示值,配合路段间拓扑关系、路段的收费属性值信息,进行地图匹配计算,判断当前车辆是否行驶在收费路段上,从而对行驶在收费路段的车辆进行通行费用计算、对收费地图信息进行精简处理、探讨分析影响地图匹配精度的因素、描述地图匹配的方法。该方法经过实验检测,并在高速公路卫星收费实验系统中实际运行,效果良好。     

基于组件式GIS技术的导航电子地图设计

在车辆导航系统中,通常采用GPS来获得车辆的位置信息,并准确地在电子地图上显示和定位。可以认为通过GPS获得定位数据是GIS的一种数据采集方式。它可以实现车辆位置的实时、动态确定。利用目前较先进的组建式GIS技术开发了一套能够实时动态显示模拟GPS信息的电子地图,具有较高的实用和教学意义。     

基于组件式GIS的模拟导航电子地图设计

在车辆导航系统中,通常采用全球定位系统GPS获得车辆位置信息,并准确在电子地图上显示和定位,可认为通过GPS获得定位数据是地理信息系统GIS的一种数据采集方式。文中利用目前较先进的组件式GIS技术开发了一套能实时动态显示、模拟GPS信息的电子地图。     

基于视觉传感器的ADAS纵向行驶工况识别方法研究

汽车先进驾驶辅助系统在应用时要根据不同的车辆行驶工况对车辆进行相应的控制,而准确的车辆行驶工况识别信号是合理的控制策略的基础.为了得到准确的车辆行驶工况识别信号,利用视觉传感器分别对车辆跟踪定位,以及车道线检测技术进行了研究.利用adaboost分类器检测出前方车辆;应用文中提出的基于坐标映射与定比分线并能够抵抗俯仰角干扰的测距方法进行车辆定位,验证结果显示该测距方法误差小于1m;再应用改进后的基于置信度判断与Kalman滤波技术的车道线跟踪检测方法进行车道线检测,并通过实车道路试验对此进行了验证,验证结果显示该车道线检测方法误差小于1°.提出1种基于PreScan的将所应用的车辆跟踪测距与车道线跟踪检测方法相结合的方法,用以实现汽车ADAS纵向行驶工况的识别,并通过PreScan仿真场景验证了该工况识别方法,结果表明该方法能够为ADAS提供准确的工况识别信号.      

基于GPS信号的导航地图路网生成方法研究

基于对制作电子地图传统方法特点的分析，结合车辆导航用电子地图中道路网络的需要，提出一种利于GPS卫星所提供的平面二维位置住处来生成道路网络的新方法。文中介绍该方法的基本思路，实现方法，优缺点以及改进的方法。实际应用表明，该方法可以应用在制作电子地图道路网络中。     

适用于公交车辆的定位技术研究

智能交通系统包含许多研究内容,其中车辆定位技术是目前的主要研究与开发热点之一.本文介绍了各种定位方法,阐述了公交车辆定位的特点,着重探讨适用于公交车辆的定位技术.在分析全球定位技术和站点信标定位技术的基础之上,文章提出了一种新思路--驾驶员辅助定位技术,由驾驶员在停靠公交站点时操纵车载装置,将定位信息通过通讯链路发送给监控调度中心.文章综合此较了全球定位技术、站点信标定位技术、驾驶员辅助定位技术的性能.     

城市交通流诱导系统电子地图的研制及功能实现

GPS、GIS对于现代交通来说是两项极为重要的技术，城市交通流诱导系统利用GPS技术实现车辆的跟踪和定位，电子地图是交通诱导的关键部分之一。实验中把GIS软件的MAPINFO作为开发平台，编辑生态道路、街区矢量图，利用其目标查询、路径分析等功能进行交通的分析和管理。     

基于RFID、视觉和UWB的车辆定位系统

在智能交通系统中获取车辆的精确位置对提升主动安全和实现无人驾驶具有重要意义。针对目前全球定位系统(GPS)和车路通信(V2I)定位方法的不足,结合射频识别(RFID)、视觉和超宽带(UWB)通信提出了一种新的车辆定位系统,目的是在GPS效果不佳的城市环境下实现车道级的定位。提出了基于RFID和视觉的车道判别算法和基于UWB的单锚点V2I定位算法。分析了单锚点V2I定位算法在典型工况下的定位误差。结果表明,在合理布置路侧单元的前提下采用该定位方法可实现直道和弯道定位误差分别在0.3和0.5m以内的定位精度。     

Towards lane-level traffic monitoring in urban environment using precise probe vehicle data derived from three-dimensional map aided differential GNSS

Today's urban road transport systems experience increasing congestion that threatens the environment and transport efficiency. Global Navigation Satellite System (GNSS)-based vehicle probe technology has been proposed as an effective means for monitoring the traffic situation and can be used for future city development. More specifically, lane-level traffic analysis is expected to provide an effective solution for traffic control. However, GNSS positioning technologies suffer from multipath and Non-Line-Of-Sight (NLOS) propagations in urban environments. The multipath and NLOS propagations severely degrade the accuracy of probe vehicle data. Recently, a three-dimensional (3D) city map became available on the market. We propose to use the 3D building map and differential correction information to simulate the reflecting path of satellite signal transmission and improve the results of the commercial GNSS single-frequency receiver, technically named 3D map-aided Differential GNSS (3D-DGNSS). In this paper, the innovative 3D-DGNSS is employed for the acquisition of precise probe vehicle data. In addition, this paper also utilizes accelerometer-based lane change detection to improve the positioning accuracy of probe vehicle data. By benefitting from the proposed method, the lane-level position, vehicle speed, and stop state of vehicles were estimated. Finally, a series of experiments and evaluations were conducted on probe data collected in one of the most challenging urban cities, Tokyo. The experimental results show that the proposed method has a correct lane localization rate of 87% and achieves sub-meter accuracy with respect to the position and speed error means. The accurate positioning data provided by the 3D-DGNSS result in a correct detection rate of the stop state of vehicles of 92%.     

Integration of GPS and monocular vision for land vehicle navigation in urban area

For land vehicle navigation in urban area, Global Positioning System (GPS) receivers often suffer from the lack of positioning accuracy, availability, and continuity due to insufficient number of visible satellites and multipath errors. To mitigate this problem, this paper proposes an efficient hybrid positioning method combining a single frequency GPS receiver and a monocular vision sensor. The proposed method is advantageous in that it requires only low-cost hardware and no external map aiding. Compared with existing vision-based methods, the proposed method directly measures absolute heading angle based on the images of straight road segments. For the reason, the proposed method is resilient to multipath errors. The performance of the proposed method is evaluated by the experiments with field-collected real measurements; one with good satellite visibility and the others with poor satellite visibility. Comparison with existing positioning methods demonstrates the feasibility of the proposed method in urban area.     

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.     

基于3D点云语义地图表征的智能车定位

为提高智能车节点定位准确率, 研究了基于3D点云语义地图表征的智能车定位方法。该方法分为3个部分: ①基于三维激光点云的语义分割, 包括地面分割, 交通标志牌分割和杆状语义目标分割; ②面向智能车的点云语义地图表征, 利用分割的语义目标投影, 生成带权有向图, 语义路, 语义编码, 再以语义编码和高精度GPS的全局位置组成语义地图表征模型; ③基于语义表征模型的智能车定位, 包括基于GPS匹配的粗定位和基于语义编码渐进匹配的节点定位。实验在3种长度不同、复杂度不同的道路场景下进行, 节点定位准确率分别为98.5%, 97.6%和97.8%, 结果表明所提出的定位方法节点定位准确率高、鲁棒性强且适用于不同的道路场景。      

基于多级网络划分的匹配道路初筛方法研究

针对GPS车辆定位系统地图匹配过程中传统匹配道路初筛方法在筛选速度和准确性方面的不足,提出了一种基于多级网络划分的匹配道路筛选方法。算法采用多级网络简单划分、层层筛选的策略,保证了初筛区域的快速、准确定位与初筛路段的准确获取,与多种传统的筛选方法,进行了基于实际数据的运行效果的对比。实证分析可知,文中提出的方法效果较好。     

高精度车载导航定位系统的研究

通过对车载导航系统结构、功能的分析，对车辆的高精度导航定位进行了研究。在常见的卫星导航（GPS）、航位推算（DR）等导航定位的基础上，进一步研究并实现了地图匹配算法，克服了GPS信号受阻时定位间断或失效的缺点，避免了航位推算定位误差随时间的积累。通过大量的跑车试验表明，基于GPS／DR／MM的车辆导航系统，可以高精度地实现车辆定位，进而可以实现地理信息的查询、交通诱导等功能。具有重要的实际应用价值。     

A hybrid dead reckoning error correction scheme based on extended Kalman filter and map matching for vehicle self-localization

In this research, a hybrid dead reckoning error correction scheme is developed based on extended Kalman filter (EKF) and map matching (MM) to improve the positioning accuracy for vehicle self-localization. The developed method aims at obtaining accurate positions when the GPS signals are occasionally unavailable or weakened. First, the heading data collected from an odometer and an optical fiber gyroscope are integrated by an EKF to reduce the random errors in dead reckoning. Then a modified topological MM algorithm is developed to reduce the systematic errors in dead reckoning. In this work, both cross-track errors and along-track errors are considered to improve positioning accuracy of MM. The errors are finally corrected using the results achieved from both the dead reckoning and the MM when the driving distance of a vehicle exceeds a predefined length or the vehicle turns in an intersection. Experiments have been conducted to evaluate the developed method and the results show that the maximum error and average error of dead reckoning can be respectively reduced to 15.4?m and 5.2?m during the experiment with total distance of 43?km. This positioning accuracy is even better than the accuracy of the low-cost GPSs which are usually at the order of 15–20?m (95%). The developed method is effective to achieve the positions of the vehicle when the GPS signals are occasionally unavailable or weakened.     

基于电子地图信息的车辆主动转向仿真

以驾驶员预瞄点处的横向偏移最小为目标，以道路曲率输入的车辆运动模型为基础，分析了车辆进行主动转向所需要的道路环境信息，并研究了利用电子地图及车辆定位传感器得到这些信息的方法。利用设计的转向控制器进行了恒定道路曲率及基于电子地图数据的实际道路信息输入下的主动转向仿真。仿真结果表明，利用电子地图提供的信息能够在投入较低成本的条件下进行主动转向，使车辆在道路曲率变化的情况下沿预定道路行驶并有着较小的侧向加速度；从而提高车辆在弯曲道路行驶的安全性、舒适性。     

基于地图匹配的城市道路实时交通状态模糊综合判别方法

依托于浮动车数据,基于地图匹配对城市道路交通状态模糊综合判别方法进行深入研究.首先根据浮动车数据特点和道路交通信息,基于Mapbasic编程对数据进行地图匹配,并进行MapInfo二次开发,通过相关模型计算指定时段内的道路交通参数.建立模糊综合评价判别模型,对判别结果量化处理,以最大隶属度原则确定道路交通状态.最后,选...     

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。