WO2024217426A1 - 一种基于多源信息融合的车辆定位方法 - Google Patents

一种基于多源信息融合的车辆定位方法 Download PDF

Info

Publication number
WO2024217426A1
WO2024217426A1 PCT/CN2024/088152 CN2024088152W WO2024217426A1 WO 2024217426 A1 WO2024217426 A1 WO 2024217426A1 CN 2024088152 W CN2024088152 W CN 2024088152W WO 2024217426 A1 WO2024217426 A1 WO 2024217426A1
Authority
WO
WIPO (PCT)
Prior art keywords
vehicle
magnetic
data
error correction
local error
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2024/088152
Other languages
English (en)
French (fr)
Inventor
戴鹏程
杨丽
王文军
孙兆聪
胡基贵
王慷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tsinghua University
CRRC Nanjing Puzhen Co Ltd
Original Assignee
Tsinghua University
CRRC Nanjing Puzhen Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tsinghua University, CRRC Nanjing Puzhen Co Ltd filed Critical Tsinghua University
Priority to MX2024008382A priority Critical patent/MX2024008382A/es
Publication of WO2024217426A1 publication Critical patent/WO2024217426A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device
    • G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers

Definitions

  • the present invention relates to the technical field of vehicle guidance and navigation, and in particular to a vehicle positioning method based on multi-source information fusion.
  • Patent "CN114690231A” proposes a positioning method based on satellite signals.
  • the patent uses a target positioning algorithm to determine the lateral positioning error of the vehicle according to the deviation between the satellite positioning data and the target driving curve.
  • Patent "CN114279453” proposes a vehicle positioning method for autonomous driving vehicles based on vehicle-road collaboration. By obtaining the vehicle reference position information sent by the road test equipment, the vehicle's position in the global map is determined, which can ensure the vehicle positioning accuracy in extreme environments.
  • Patent "CN104460665A” provides a method for establishing a magnetic navigation unmanned vehicle and its map based on a road curvature map.
  • Patent "CN108052107A” uses on-board magnetic sensors and gyroscopes to collect the lateral deviation data and attitude angle data of the vehicle relative to the magnetic nails to achieve tracking control of the autonomous driving vehicle.
  • the present invention provides a vehicle positioning method based on multi-source information fusion.
  • the vehicle positioning method includes lateral positioning and longitudinal positioning of the vehicle, and ensures accurate positioning of the vehicle by adopting a fusion positioning method of multiple data.
  • a vehicle positioning method based on multi-source information fusion characterized in that it includes the following steps:
  • the magnetic markers and RFID tags are arranged on the line in an array distribution manner; the magnetic markers are encoded and spread on the magnetic marker sequence in a binary encoding manner according to the N/S polarity of the magnetic markers; the magnetic marker encoding includes local error correction encoding and padding segments;
  • the magnetic marks on the line are encoded, and the local error correction coding sequences on different sections are the same.
  • the local error correction coding is determined based on the obtained magnetic mark sequence data, and coding padding is set between the local error correction codes of each section.
  • the method further comprises the following steps:
  • the vehicle After the vehicle receives the magnetic tag sequence data, RFID data or RTK data, it records the current vehicle mileage and determines the longitudinal position of the vehicle based on these data;
  • the magnetic mark sequence is maintained by counting, the local error correction code is determined according to the magnetic mark sequence, and the longitudinal position of the vehicle is determined according to the local error correction code and the magnetic mark sequence.
  • the longitude and latitude of the vehicle's location is first determined based on the RTK data, then the nearest magnetic marker sequence is determined based on the longitude and latitude and the local error correction code, and finally the longitudinal position of the vehicle is determined based on the RTK longitude and latitude data and the local error correction code;
  • the EPC number of the RFID tag at the location is first determined according to the RFID data, then the nearest magnetic marker sequence is determined according to the EPC number and the local error correction code, and finally the longitudinal position of the vehicle is determined according to the magnetic marker sequence;
  • the vehicle After the vehicle receives the camera data and the magnetic marker sequence data, it determines the lateral position of the vehicle based on these data;
  • the vehicle directly measures the distance between the vehicle and the center lane line through the camera to obtain the lateral deviation of the vehicle;
  • the vehicle determines the lateral distance of the vehicle relative to the fixed position magnetic marker by collecting the distribution information of the spatial magnetic field when passing the magnetic marker, and finally obtains the size of the vehicle's lateral deviation.
  • the coded segment data of the magnetic marker is obtained through inverse decoding, thereby updating the local error correction code;
  • the longitudinal position of the vehicle in the local error correction code is obtained through longitudinal integration between the magnetic markers, and the longitudinal integration is to integrate parameters such as speed in the direction of vehicle travel; next, the longitudinal positioning of the vehicle is updated in an incremental manner each time a magnetic marker position is passed.
  • the local error correction code is composed of 16 magnetic marks, and the codes formed by any four consecutive magnetic marks in the local error correction code are different;
  • the initial longitudinal position of the vehicle is determined by combining the received RFID data information or RTK data information with the local error correction code for comparison.
  • the magnetic mark encoding polarities of the filling segments are all the same.
  • the vehicle receives the magnetic mark sequence data and maintains the magnetic mark sequence, it is determined whether the local error correction code can be matched;
  • the magnetic marker sequence matching algorithm is used to perform local error correction coding matching based on the RTK data and RFID data;
  • the approximate longitudinal position of the vehicle is determined, and the historical magnetic marker sequence is matched with the online magnetic marker sequence to finally determine the longitudinal positioning of the vehicle on the global road.
  • the magnetic sensor when the vehicle collects the distribution information of the spatial magnetic field when passing the magnetic marker through the positioning sensor, the magnetic sensor will be affected by the environmental magnetic field except the magnetic field of the magnetic marker; the electromagnetic positioning sensor includes multiple magnetic sensor units, and the magnetic field at the location of the magnetic sensor unit is measured multiple times and the average magnetic field of each magnetic sensor unit is obtained. The magnetic field value of each magnetic sensor unit is subtracted from the average magnetic field of all magnetic sensor units as a deviation, and each magnetic field data subsequently obtained by the electromagnetic positioning sensor is subtracted from the deviation to eliminate the influence of the surrounding environment.
  • the data consistency is calculated by calculating the standard deviation of the magnetic field data of each frame; when the standard deviation of the magnetic field data is less than or equal to a certain value, it is judged to be the magnetic field data of the arranged magnetic marker.
  • the magnetic markers and RFID tags are arranged in one or more rows at a fixed interval in the center of the line.
  • the present invention has the following beneficial effects:
  • multi-source information fusion is used to perform lateral and longitudinal positioning of the vehicle, ensuring that the vehicle's position can be determined at any position on the route based on the data combined with the magnetic tag code;
  • FIG1 is a schematic diagram of a vehicle positioning method based on multi-source information fusion according to the present invention.
  • FIG. 2 is a longitudinal positioning flow chart of a vehicle positioning method based on multi-source information fusion according to the present invention.
  • FIG. 3 is a flow chart of maintaining the magnetic label sequence in FIG. 2 .
  • a vehicle positioning method based on multi-source information fusion includes vehicle longitudinal positioning and vehicle lateral positioning.
  • the vehicle longitudinal positioning adopts multi-source data fusion, mainly based on the detected magnetic marker sequence data, RFID data and RTK data, and is implemented in conjunction with the vehicle longitudinal positioning algorithm.
  • the vehicle lateral positioning adopts multi-source data fusion, mainly based on the detected magnetic marker sequence data and camera data, and is implemented in conjunction with the vehicle lateral positioning algorithm.
  • a vehicle positioning method based on multi-source information fusion includes the following steps:
  • Step (1) installing RTK equipment, including RTK mobile station, base station and antenna;
  • RTK antennas are installed at the front and rear ends of the vehicle, an RTK mobile station is installed in the middle of the vehicle, and an RTK base station is installed on the ground to obtain the latitude and longitude coordinates of the vehicle.
  • the vehicle's positioning information can be obtained by using an RTK mobile station and a paid high-precision 4G module.
  • Step (2) arranging magnetic markers and RFID tags
  • the magnetic markers and RFID tags are arranged on the line in an array distribution manner; the magnetic markers are encoded and spread on the magnetic marker sequence in a binary encoding manner according to the N/S polarity of the magnetic markers; the magnetic marker encoding includes local error correction encoding and padding segments;
  • Magnetic markers (magnetic nails) have positive and negative poles, which are equivalent to 0 and 1 in binary.
  • the so-called coding refers to the numbers composed of different 0s and 1s. For example, 0110 is a 4-bit code, which is 6 when converted to decimal.
  • the filling section is an unimportant section of the road.
  • the polarity of the magnetic marker coding in the filling section is the same, which can greatly reduce the difficulty of construction.
  • the layout of road magnetic markers and RFID directly affects the positioning accuracy of the vehicle.
  • the magnetic markers and RFID tags are arranged in a row in the center of the line, with a magnetic marker interval of 1m, and an RFID tag interval of 8m.
  • a single RFID tag is 0.5m away from the adjacent magnetic marker. According to different working conditions, the magnetic markers and RFID arrangements can be set at different intervals, and the magnetic markers and RFIDs can also be laid in two rows.
  • the arrangement interval between the magnetic marker and the RFID tag may also be set to other fixed distances.
  • Step (3) generating a local error correction code based on the magnetic mark arrangement
  • the magnetic markers on the line are specifically encoded to form local error correction codes, and code padding is set between local error correction codes.
  • the specific arrangement of the codes can be reasonably arranged in combination with the requirements and scope of the construction.
  • the local error correction code is composed of 16 magnetic markers, and the codes formed by any four consecutive magnetic markers in the local error correction code are different; in the local error correction code, the magnetic marker codes of the local error correction code are the same.
  • the local error correction code is used for local longitudinal positioning, that is, to determine the relative position of the vehicle and the magnetic marker in a shorter distance.
  • the longitudinal initial position of the vehicle is determined by combining the received RFID data information or RTK data information with the local error correction code.
  • the codes formed by any four consecutive magnetic markers in the local error correction code are set to be different. In order to reduce the number of codes, the local error correction codes of different sections are kept consistent.
  • Step (4) longitudinal positioning of the vehicle
  • the vehicle receives magnetic tag sequence data, RFID data, or RTK data, it first records the current vehicle mileage based on these data;
  • the magnetic mark sequence is maintained by counting, the local error correction code is determined according to the magnetic mark sequence, and the longitudinal position of the vehicle is determined according to the local error correction code and the magnetic mark sequence.
  • the longitude and latitude of the vehicle's location is first determined based on the RTK data, then the nearest magnetic marker sequence is determined based on the longitude and latitude and the local error correction code, and finally the longitudinal position of the vehicle is determined based on the RTK longitude and latitude data and the local error correction code;
  • the EPC number of the RFID tag at the location is first determined according to the RFID data, then the nearest magnetic marker sequence is determined according to the EPC number and the local error correction code, and finally the longitudinal position of the vehicle is determined according to the magnetic marker sequence;
  • step a after the vehicle receives the magnetic marker sequence data and maintains the magnetic marker sequence, it is determined whether the local longitudinal position has been determined;
  • step d If the local longitudinal position has been determined, proceed to step d;
  • Step d If the distance between the current magnetic marker and the magnetic marker on the previous sequence is less than a certain threshold, the markers are discarded in parallel; if the distance between the current magnetic marker and the magnetic marker on the previous sequence is greater than or equal to a certain threshold, and less than or equal to a certain threshold, proceed to step e;
  • Step e Determine the degree of deviation of the current mark's lateral deviation relative to the lateral deviation of the previous magnetic mark and the lateral deviation of the previous magnetic mark; if so, the mark is in the magnetic mark sequence on the line, and the magnetic mark sequence number is +1; if not, the mark is not in the magnetic mark sequence on the line and is discarded.
  • step f If the local longitudinal position is not determined, proceed to step f;
  • Step f in conjunction with FIG. 2 , determine whether the current number of recent magnetic markers meet the local error correction coding requirement; if so, search for the marker serial number according to the local error correction coding value; if not, proceed to step g;
  • Step g Determine whether the mileage of the most recently received RTK data is greater than the mileage of the most recently received RFID data; if so, proceed to step h; if not, proceed to step i;
  • Step h Determine whether the difference between the mileage when the RTK data was received most recently and the current mileage is less than a certain threshold, and the current magnetic marker sequence size is greater than or equal to a fixed distance; if so, set the vehicle initial position to the magnetic marker sequence number determined according to the RTK data, set the range to half of the fixed distance, and then proceed to step j; if not, it means that insufficient data is obtained to determine the longitudinal position;
  • Step i Determine whether the difference between the mileage when the RFID data was received most recently and the current mileage is less than a certain threshold, and the current magnetic marker sequence size is greater than or equal to a fixed distance; if so, set the initial position of the sliding window to the magnetic marker sequence number determined according to the RFID data, set the sliding range to half of the fixed distance, and then proceed to step j; if not, it means that insufficient data is obtained to determine the longitudinal position;
  • Step j Taking the current magnetic marker as the starting point, take out all magnetic marker sequences with a certain index size; use the magnetic marker sequence matching algorithm to match the vehicle's approximate longitudinal position, historical magnetic marker sequences and on-line magnetic marker sequences, and finally determine the vehicle's position on the magnetic marker sequence;
  • Step k If the magnetic marker sequence that meets the above two conditions is unique, the magnetic marker sequence is determined.
  • the step of maintaining the magnetic label sequence is:
  • This embodiment detects the magnetic field of the magnetic marker in the direction of vehicle travel and uses the magnetic field polarity to obtain a local magnetic marker sequence, thereby accurately determining the specific position of a single magnetic marker and determining the longitudinal relative position of the magnetic marker and the vehicle, thereby achieving local longitudinal positioning of the vehicle. Since the position of the magnetic marker on the road is fixed, the position of the vehicle on the complete road can be determined by obtaining the longitudinal distribution of the magnetic marker magnetic field.
  • Step (4) lateral positioning of the vehicle
  • the vehicle directly measures the distance between the vehicle and the center lane line through the camera.
  • the positioning information can provide deviation information for the automatic lateral control of the vehicle during driving;
  • the vehicle determines the lateral distance of the vehicle relative to the fixed-position magnetic marker by collecting the distribution information of the spatial magnetic field when passing through the magnetic marker, and finally obtains the magnitude of the vehicle's lateral deviation.
  • the positioning sensor When the vehicle collects the spatial magnetic field distribution information when passing the magnetic marker through the positioning sensor, it will be affected by the environmental magnetic field other than the magnetic field of the magnetic marker.
  • the positioning sensor includes 16 array-distributed magnetic sensing units, each of which detects the magnitude and direction of the magnetic field at its location. The positioning sensor is measured multiple times and the average value of each magnetic sensing unit is obtained. The value of each magnetic sensing unit is subtracted from the average value of all magnetic sensing units as a deviation. Each subsequent data obtained by the positioning sensor is subtracted from the deviation to eliminate the influence of the surrounding environment.
  • the positioning sensor In the calculation process of the positioning sensor, it is very necessary to determine whether there is a magnetic mark. Only when it is determined that there is a magnetic mark, it is necessary to further process the data. First, determine whether there is a magnetic mark under the positioning sensor and compare the consistency of each positioning sensor. The closer the magnetic mark is to the positioning sensor, the worse the consistency. In practical applications, by determining whether the standard deviation of the consistency data is greater than a certain value, it is possible to determine whether there is a magnetic mark. By determining the trend of the standard deviation, the changing relationship between the distance between the magnetic mark and the positioning sensor can be determined. Finally, the lateral distance between the magnetic nail and the positioning sensor is detected. After obtaining the distance between the magnetic mark and the positioning sensor, the relative distance between the vehicle and the magnetic mark can be determined to achieve the lateral positioning of the vehicle.
  • the present invention is designed to solve the problems of low accuracy, high cost and great difficulty in engineering application of current vehicle positioning methods. It can be seen from this embodiment that the advantages of the present invention are:
  • the longitudinal positioning method based on RFID data can ensure that the vehicle can enter the road with magnetic markers before entering the road with magnetic markers; and after entering the road with magnetic markers, the magnetic markers on the magnetic marker sequence can be quickly extracted;
  • the vehicle needs to pass through a coded magnetic tag before the specific position of the coding group can be determined, which means that the vehicle cannot determine its specific position in the map before obtaining the longitudinal positioning information, that is, the environmental conditions of the position cannot be obtained, which will have a certain impact on the lateral and longitudinal control of the vehicle.
  • the present invention uses RFID and RTK to solve this problem.
  • the principle of this technology is to use the reader to read the location information stored in the tag installed on the ground through non-contact data communication between the reader and the tag.
  • RTK technology mainly uses GPS combined with data transmission technology to determine the latitude and longitude of the vehicle in a short time through real-time solution, so as to facilitate high-precision positioning.
  • the combination of these two methods enables the vehicle to obtain longitudinal position information through the tag before passing the magnetic marker;
  • the present invention avoids positioning blind spots when the vehicle is driving and improves the stability and accuracy of positioning.

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Automation & Control Theory (AREA)
  • General Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Navigation (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

一种基于多源信息融合的车辆定位方法，包括：布置磁标记和RFID标签；基于磁标记布置生成局部纠错编码；车辆纵向定位，车辆接收到RTK数据时，根据经纬度以及局部纠错编码确定最近的磁标记序列；车辆接收到RFID数据时，根据EPC号以及局部纠错编码确定最近的磁标记序列；车辆接收到磁标记序列数据时，通过计数的方式维护磁标记序列并根据磁标记序列确定车辆的纵向位置；车辆横向定位，车辆通过阵列式传感单元接收到磁场强度时，计算车辆相对于道路的横向偏差。该方法采用多源信息融合来对车辆进行横向定位与纵向定位，保证车辆在线路的任意位置都能够根据局部纠错编码，结合RTK或RFID确定车辆的位置，提高了定位精度、实用性与工程可能性。

Description

一种基于多源信息融合的车辆定位方法 技术领域
本发明涉及车辆导向导航技术领域，具体地，涉及一种基于多源信息融合的车辆定位方法。
背景技术
近些年来，自动驾驶技术发展迅速。各种传感器如视觉系统、毫米波雷达、激光雷达和RTK，为自动驾驶车辆提供了诸多感知和定位的方式。各种驾驶辅助系统如全景环视系统、视觉辅助系统等已经在自动驾驶汽车上得到了广泛的应用。
现有研究中用于车辆定位的方法较多，专利“CN114690231A”提出了一种基于卫星信号的定位方法，该专利采用目标定位算法根据卫星定位数据和目标行驶曲线之间的偏差确定车辆的横向定位误差。专利“CN114279453”提出了一种基于车路协同的自动驾驶汽车车辆定位方法，通过获取路测设备发送的车辆参考位置信息确定车辆在全局地图中的位置，可以保证在极端环境下的车辆定位精度。专利“CN104460665A”提供了一种基于道路曲率地图的磁导航无人车与其地图的建立方法，车辆在自动驾驶时能通过控制计算机并且结合车辆自身的参数和曲率地图的信息实现有效的循迹控制。该方法可以有效弥补导航坐标地图法的地域限制问题，在地面铺设磁钉的磁导航道路布置方式已被大多数技术人员认可。专利“CN108052107A”利用车载磁传感器与陀螺仪采集车辆相对于磁钉的横向偏差数据与姿态角数据，实现自动驾驶车辆的循迹控制。
现有技术存在的不足是：上述专利主要基于单一的传感器实现车辆的横向定位或纵向定位，无法兼顾车辆定位的高精度与高鲁棒性。
发明内容
针对目前车辆定位方法精度低、鲁棒性不足等问题，本发明提供一种基于多源信息融合的车辆定位方法。本车辆定位方法包括车辆的横向定位与纵向定位，通过采用多种数据进行融合定位的方式保证车辆的定位精准。
本发明通过以下技术手段实现：一种基于多源信息融合的车辆定位方法，其特征在于，包括如下步骤：
1)安装RTK设备，包括RTK移动站、基站以及天线；
在车辆前端与后端分别安装RTK天线，在车辆中间安装RTK移动站，在地面安装RTK基站，用以获取车辆经纬度坐标；
2)布置电磁标记，电磁标记包括磁标记和RFID标签；
采用阵列式分布的方式分别将磁标记与RFID标签排列在线路上；对磁标记进行编码，根据磁标记N/S极性，按照二进制编码的方式在磁标记序列上展开；磁标记编码包括局部纠错编码以及填充段；
3)基于电磁标记布置生成局部纠错编码；
对线路上的磁标记进行编码，不同路段上的局部纠错编码序列相同，根据所获得的粢标记序列数据数据确定局部纠错编码，各路段局部纠错编码之间设置编码填充。
优选的，还包括如下步骤：
1)车辆纵向定位；
车辆接收磁标记序列数据、RFID数据或RTK数据后，根据这些数据记录当前车辆的行驶里程，并确定车辆的纵向位置；
a、当车辆接收到磁标记序列数据时，通过计数的方式维护磁标记序列,根据磁标记序列确定局部纠错编码，根据局部纠错编码和磁标记序列确定车辆的纵向位置。
b、当车辆接收到RTK数据时，首先根据RTK数据确定车辆所处位置的经纬度，然后根据经纬度以及所述局部纠错编码确定最近的磁标记序列，最后根据RTK经纬度数据和局部纠错编码确定车辆的纵向位置；
c、当车辆接收到RFID数据时，首先根据RFID数据确定所处位置的RFID标签的EPC号，然后根据EPC号以及所述局部纠错编码确定最近的磁标记序列，最后根据磁标记序列确定车辆的纵向位置；
2)车辆横向定位；
车辆接受摄像头数据与磁标记序列数据后，根据这些数据确定车辆的横向位置；
a、车辆通过摄像头直接测量车辆相对中心车道线之间的距离，得到车辆的横向偏差；
b、车辆通过采集经过磁标记时的空间磁场的分布信息，来判断车辆相对于固定位置磁标记的横向距离，最终得到车辆横向偏差的大小。
当车辆经过一个完整的磁标记后，通过反解码获得磁标记的编码段数据，从而更新局部纠错编码；在磁标记之间通过纵向积分即获得车辆在局部纠错编码中的纵向位置，纵向积分即在车辆行驶方向上，对速度等参数进行积分；接下来，每经过一个磁标记位置就以递增的方式更新车辆的纵向定位。
优选的：所述局部纠错编码由16个磁标记组成，局部纠错编码中任意连续4个磁标记形成的的编码都不相同；
当车辆经过一个局部纠错编码时，通过结合接收到的RFID数据信息或RTK数据信息与局部纠错编码比对，确定车辆纵向初始位置。
优选的：所述填充段的磁标记编码极性都相同。
优选的：当车辆接收到磁标记序列数据，并维护磁标记序列之后，判断是否能够匹配局部纠错编码；
若否，则在经过里程阈值与前置条件的判断后，采用磁标记序列匹配算法，根据RTK数据与RFID数据，进行局部纠错编码匹配；
若是，则判断判定车辆的大致纵向位置，结合历史磁标记序列与在线路磁标记序列匹配，最终确定车辆在全局道路上的纵向定位。
优选的：车辆通过定位传感器采集经过磁标记时的空间磁场的分布信息时，磁传感器会受到除磁标记磁场外的环境磁场影响；电磁定位传感器包括多个磁传感单元，通过多次测量磁传感单元所在位置的磁场并获得每个磁传感单元的磁场平均值，将每个磁传感单元的磁场值减去所有磁传感单元的磁场平均值作为偏差，后续电磁定位传感器获得的每个磁场数据都减去该偏差以消除周围环境的影响。
优选的：当车辆通过定位传感器接收到磁标记的磁场数据时，通过计算每帧的磁场数据的标准差来计算数据一致性；当磁场数据的标准差是小于等于某定值时，判断是所布置磁标记的磁场数据。
优选的：所述布置磁标记和RFID标签在线路中心以固定间距布置成一排或多排。
与现有技术相比，本发明的有益效果是：
充分结合磁标记序列数据、RFID数据、摄像头数据以及RTK数据各自的特点，采用多源信息融合来对车辆进行横向定位与纵向定位，保证车辆在线路的任意位置都能够根据数据结合磁标记编码确定车辆的位置；
相比于传统的车辆定位方法精度更高并且降低了定位的成本，实用性与工程可能性都有大幅度的提高，能够解决现有技术定位方法存在鲁棒性不足并且精度低的问题，为自动驾驶车辆定位技术提出了新的思路与可行方案。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明一种基于多源信息融合的车辆定位方法的原理图。
图2是本发明一种基于多源信息融合的车辆定位方法的纵向定位流程图。
图3是图2中维护磁标记序列的流程图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
结合图1所示，一种基于多源信息融合的车辆定位方法，包括车辆纵向定位和车辆横向定位。车辆纵向定位采用多源数据融合，主要基于检测到的磁标记序列数据、RFID数据以及RTK数据，配合车辆纵向定位算法实现。车辆横向定位采用多源数据融合，主要基于检测到的磁标记序列数据和摄像头数据，配合车辆横向定位算法实现。
一种基于多源信息融合的车辆定位方法，包括如下步骤：
步骤(1)，安装RTK设备，包括RTK移动站、基站以及天线；
在车辆前端与后端分别安装RTK天线，在车辆中间安装RTK移动站，在地面安装RTK基站，用以获取车辆经纬度坐标。
同样地，也可以通过RTK移动站加付费高精度4G模块的方式，获取车辆的定位信息。
步骤(2)，布置磁标记和RFID标签；
采用阵列式分布的方式分别将磁标记与RFID标签排列在线路上；对磁标记进行编码，根据磁标记N/S极性，按照二进制编码的方式在磁标记序列上展开；磁标记编码包括局部纠错编码以及填充段；
磁标记(磁钉)有正负极，相当于二进制中的0和1，所谓编码就是指不同的0和1组成的数字，比如0110就是4位编码，换算成10进制就是6。填充段为不重要路段，填充段的磁标记编码极性都相同，能够极大的减少施工难度。道路磁标记与RFID布置方式直接影响到车辆的定位精度，本实施例中磁标记与RFID标签在线路中心排成一列，磁标记间隔1m安排一个，RFID标签间隔8m安排一个，单个RFID标签与相邻磁标记间隔0.5m。根据不同的工况需求，磁标记与RFID排列可设置不同的间距，磁标记与RFID也可铺设成两排。
同样地，磁标记与RFID标签的布置间隔也可设为其他固定距离。
步骤(3)，基于磁标记布置生成局部纠错编码；
对线路上的磁标记进行特异性编码形成局部纠错编码，局部纠错编码之间设置编码填充，编码具体排列可结合施工的要求与范围合理布置。当车辆经过一个完整的局部纠错编码后，通过反解码获得编码段数值，即可获得一定范围内车辆在纵向上相对于局部纠错编码的位置；接下来，每经过一个磁标记位置就以递增的方式更新车辆的纵向位置。
本实施例中局部纠错编码由16个磁标记组成，局部纠错编码中任意连续四个磁标记形成的的编码都不相同；在局部纠错编码中，局部纠错编码的磁标记编码都是相同的。局部纠错编码用于局部纵向定位，即在较短的距离里确定车辆与磁标记的相对位置，当车辆经过一个局部纠错编码时，通过结合接收到的RFID数据信息或RTK数据信息与局部纠错编码比对，确定车辆纵向初始位置。为了更好地进行局部定位，局部纠错编码中任意连续四个磁标记形成的编码都设置为不相同，为了减少编码数，不同路段的局部纠错编码保持一致。
步骤(4)，车辆纵向定位；
如图2所示，无论车辆接收磁标记序列数据、RFID数据还是RTK数据，均先根据这些数据记录当前车辆的行驶里程；
这里分三种工况；
a、当车辆接收到磁标记序列数据时，通过计数的方式维护磁标记序列,根据磁标记序列确定局部纠错编码，根据局部纠错编码和磁标记序列确定车辆的纵向位置。
b、当车辆接收到RTK数据时，首先根据RTK数据确定车辆所处位置的经纬度，然后根据经纬度以及所述局部纠错编码确定最近的磁标记序列，最后根据RTK经纬度数据和局部纠错编码确定车辆的纵向位置；
c、当车辆接收到RFID数据时，首先根据RFID数据确定所处位置的RFID标签的EPC号，然后根据EPC号以及所述局部纠错编码确定最近的磁标记序列，最后根据磁标记序列确定车辆的纵向位置；
优选的：上述步骤a中，当车辆接收到磁标记序列数据，并维护磁标记序列之后，判断是否已确定了局部纵向位置；
若已确定了局部纵向位置，进入步骤d；
步骤d：若当前磁标记距离上一颗序列上的磁标记距离小于一定阈值，则并列舍弃标记；若当前磁标记距离上一颗序列上的磁标记距离大于等于一定阈值，小于等于一定阈值，进入步骤e；
步骤e：判断当前标记横向偏差相对于上颗磁标记横向偏差以及上上颗磁标记横向偏差的偏离程度；若是，则该标记是线路上磁标记序列中的，磁标记序列号+1；若否，该标记不是线路上磁标记序列中的，舍弃。
若未确定局部纵向位置，进入步骤f；
步骤f：结合图2，判断当前最近的若干颗磁标记是否满足局部纠错编码；若是，则根据局部纠错编码数值查找标记序列号；若否，则进入步骤g；
步骤g：判断最近一次接收到的RTK数据时的里程是否大于最近一次接收到RFID数据时的里程；若是，则进入步骤h；若否，则进入步骤i；
步骤h：判断最近一次接收到RTK数据时的里程与当前里程是否相差小于一定阈值，当前磁标记序列大小大于等于某固定距离；若是，将车辆初始位置设置为根据RTK数据确定的磁标记序列号，范围设置为某固定距离的一半，然后进入步骤j；若否，则表示未获得足够数据确定纵向位置；
步骤i：判断最近一次接收到RFID数据时的里程与当前里程是否相差小于一定阈值，当前磁标记序列大小大于等于某固定距离；若是，将滑动窗口初始位置设置为根据RFID数据确定的磁标记序列号，滑动范围设置为某固定距离的一半，然后进入步骤j；若否，则表示未获得足够数据确定纵向位置；
步骤j：以当前磁标记为起点，取出所有索引大小一定的磁标记序列；采用磁标记序列匹配算法，根据车辆的大致纵向位置、历史磁标记序列与在线路磁标记序列匹配，最终确定车辆在磁标记序列上的位置；
步骤k：满足以上两个条件的磁标记序列唯一，则确定磁标记序列。
优选的：上述步骤a中，维护磁标记序列的步骤是：
结合图3所示，接收新磁标记后，判断距离上帧距离是否丟标签；若是，则清空序列，创建首序列；若否，当前磁标记建立连接，然后进入下一步：
判断上个序列是否为两个；若是，则规整上一序列连接；若否，则删除久远序列，递归输出序列。
本实施例通过在车辆行驶方向上对磁标记磁场的检测，利用磁场极性，获取到局部磁标记序列，从而准确判断单个磁标记的具体位置，并确定该磁标记与车辆的纵向相对位置，实现车辆的局部纵向定位。由于磁标记在道路上的位置是固定的，因此通过获取磁标记磁场在纵向上的分布即可确定车辆在完整道路中的位置。
步骤(4)，车辆横向定位；
a、车辆通过摄像头直接测量车辆相对中心车道线之间的距离，通过该定位信息可以给车辆行驶时的自动横向控制提供偏差信息；
b、由于磁标记附近空间各点的磁场方向与大小信息都具有互异性，因此车辆通过采集经过磁标记时的空间磁场的分布信息，来判断车辆相对于固定位置磁标记的横向距离，最终得到车辆横向偏差的大小。
车辆通过定位传感器采集经过磁标记时的空间磁场的分布信息时，会受到除磁标记磁场外的环境磁场影响。本实施例中，定位传感器包括16个阵列分布的磁传感单元，每个磁传感单元都会检测所在位置的磁场强度大小和磁场方向，通过多次测量定位传感器并获得每个磁传感单元的平均值，将每个磁传感单元的值减去所有磁传感单元的平均值作为偏差，后续定位传感器获得的每个数据都减去该偏差以消除周围环境的影响。
在定位传感器的计算过程中，判断是否有磁标记是非常必要的。只有在判断有磁标记时，才有必要进一步处理数据。首先，判断定位传感器下是否有磁标记，比较每个定位传感器的一致性。磁标记越靠近定位传感器则一致性越差。在实际应用中，通过判断一致性数据的标准差是否大于一定值，就可以判断是否有磁标记。通过判断标准差的变化趋势，可以判断磁标记与定位传感器之间距离的变化关系。最后检测磁钉与定位传感器之间的横向距离，在得到了磁标记与定位传感器之间的距离后，即可判断车辆与磁标记的相对距离，实现车辆的横向定位。
本发明针对目前车辆的定位方法精度低、成本高与工程应用难度大等问题而设计，从本实施例可以看出，本发明的优点是：
(1)对于利用电磁标记进行纵向定位的车辆，该纵向定位方法基于RFID数据可以保证车辆在未进入到铺设磁标记的道路前，能够在铺设磁标记的道路进入；并且在进入到铺设磁标记的道路后，能够快速提取在磁标记序列上的磁标记；
(2)如果仅通过磁标记编码来实现车辆的纵向定位存在一些缺点：车辆需要经过一个带编码的磁标记后才能确定编码组的具体位置，这意味着车辆在获得纵向定位信息之前无法确定其在地图中的具体位置，即无法获得该位置的环境情况，这将对车辆的横纵向控制产生一定的影响。本发明利用RFID与RTK解决这一问题。该技术的原理是通过阅读器和标签之间的非接触式数据通信，利用阅读器放读取安装在地面上的标签里存储的位置信息。RTK技术主要利用GPS与数据传输技术相结合，通过实时解算在短时间内确定车辆的经纬度，以便于进行高精度定位。这两种方法相结合使车辆能够在经过磁标记之前通过标签获取纵向位置信息；
(3)本发明基于RFID、RTK和磁标记编码各自的特点，在车辆行驶时避免定位盲区并且提高定位的稳定性与精确性。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。

Claims (10)

  1. 一种基于多源信息融合的车辆定位方法，其特征在于，包括如下步骤：
    1)安装RTK设备，包括RTK移动站、RTK基站以及RTK天线；
    在车辆前端与后端分别安装RTK天线，在车辆中间安装RTK移动站，在地面安装RTK基站，用以获取车辆经纬度坐标；
    2)布置电磁标记，电磁标记包括磁标记和RFID标签；
    采用阵列式分布的方式分别将磁标记与RFID标签排列在线路上；对磁标记进行编码，根据磁标记N/S极性，按照二进制编码的方式在磁标记序列上展开；磁标记编码包括局部纠错编码以及填充段；
    3)基于电磁标记布置生成局部纠错编码；
    对线路上的磁标记进行编码，不同路段上的局部纠错编码序列相同，多个连续的磁标记序列数据形成一个局部纠错编码，根据所获得的磁标记序列数据确定局部纠错编码，各路段局部纠错编码之间设置编码填充。
  2. 根据权利要求1所述的一种基于多源信息融合的车辆定位方法，其特征在于，还包括如下步骤：
    1)车辆纵向定位；
    车辆接收磁标记序列数据、RFID数据或RTK数据后，根据这些数据记录当前车辆的行驶里程，并确定车辆的纵向位置；
    a、当车辆接收到磁标记序列数据时，通过计数的方式维护磁标记序列,根据磁标记序列确定局部纠错编码，根据局部纠错编码和磁标记序列确定车辆的纵向位置。
    b、当车辆接收到RTK数据时，首先根据RTK数据确定车辆所处位置的经纬度，然后根据经纬度以及所述局部纠错编码确定最近的磁标记序列，最后根据RTK经纬度数据和局部纠错编码确定车辆的纵向位置；
    c、当车辆接收到RFID数据时，首先根据RFID数据确定所处位置的RFID标签的EPC号，然后根据EPC号以及所述局部纠错编码确定最近的磁标记序列，最后根据磁标记序列确定车辆的纵向位置；
    2)车辆横向定位；
    车辆接受摄像头数据与磁标记序列数据后，根据这些数据确定车辆的横向位置；
    a、车辆通过摄像头直接测量车辆相对中心车道线之间的距离，得到车辆的横向偏差；
    b、车辆通过采集经过磁标记时的空间磁场的分布信息，来判断车辆相对于固定位置磁标记的横向距离，最终得到车辆横向偏差的大小。
  3. 根据权利要求2所述的一种基于多源信息融合的车辆定位方法，其特征在于：车辆通过传感器获取局部纠错编码，随后根据局部纠错编码数据、RTK数据、RFID数据，获取车辆纵向定位信息，所述定位信息用于辅助车辆的纵向控制。
  4. 根据权利要求2所述的一种基于多源信息融合的车辆定位方法，其特征在于：
    当车辆经过一个完整的磁标记后，通过反解码获得磁标记的编码段数据，从而更新局部纠错编码；在磁标记之间通过纵向积分获得车辆在局部纠错编码中的纵向位置；接下来，每经过一个磁标记位置就以递增的方式更新车辆的纵向定位。
  5. 根据权利要求4所述的一种基于多源信息融合的车辆定位方法，其特征在于：所述局部纠错编码由16个磁标记组成，局部纠错编码中任意连续4个磁标记形成的的编码都不相同；
    当车辆经过一个局部纠错编码时，通过结合接收到的RFID数据信息或RTK数据信息与局部纠错编码比对，确定车辆纵向初始位置。
  6. 根据权利要求5所述的一种基于多源信息融合的车辆定位方法，其特征在于：所述填充段的磁标记编码极性都相同。
  7. 根据权利要求2所述的一种基于多源信息融合的车辆定位方法，其特征在于：
    当车辆接收到磁标记序列数据，并维护磁标记序列之后，判断是否能够匹配局部纠错编码；
    若否，则在经过里程阈值与前置条件的判断后，采用磁标记序列匹配算法，根据RTK数据与RFID数据，进行局部纠错编码匹配；
    若是，则判断判定车辆的大致纵向位置，结合历史磁标记序列与线路磁标记序列匹配，最终确定车辆在全局道路上的纵向定位。
  8. 根据权利要求2所述的一种基于多源信息融合的车辆定位方法，其特征在于：
    车辆通过定位传感器采集经过磁标记时的空间磁场的分布信息时，磁传感器会受到除磁标记磁场外的环境磁场影响；电磁定位传感器包括多个磁传感单元，通过多次测量磁传感单元所在位置的磁场并获得每个磁传感单元的磁场平均值，将每个磁传感单元的磁场值减去所有磁传感单元的磁场平均值作为偏差，后续电磁定位传感器获得的每个磁场数据都减去该偏差以消除周围环境的影响。
  9. 根据权利要求8所述的一种基于多源信息融合的车辆定位方法，其特征在于：
    当车辆通过定位传感器接收到磁标记的磁场数据时，通过计算每帧的磁场数据的标准差来计算数据一致性；当磁场数据的标准差是小于等于某定值时，判断车辆通过对应的磁标记。
  10. 根据权利要求1所述的一种基于多源信息融合的车辆定位方法，其特征在于：所述布置磁标记和RFID标签在线路中心以固定间距布置成一排或多排。
PCT/CN2024/088152 2023-04-18 2024-04-17 一种基于多源信息融合的车辆定位方法 Ceased WO2024217426A1 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
MX2024008382A MX2024008382A (es) 2023-04-18 2024-07-02 Metodo de posicionamiento de vehiculos basado en la fusion de informacion de multiples fuentes.

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202310416512.5 2023-04-18
CN202310416512.5A CN116429123A (zh) 2023-04-18 2023-04-18 一种基于多源信息融合的车辆定位方法

Publications (1)

Publication Number Publication Date
WO2024217426A1 true WO2024217426A1 (zh) 2024-10-24

Family

ID=87094081

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2024/088152 Ceased WO2024217426A1 (zh) 2023-04-18 2024-04-17 一种基于多源信息融合的车辆定位方法

Country Status (3)

Country Link
CN (1) CN116429123A (zh)
MX (1) MX2024008382A (zh)
WO (1) WO2024217426A1 (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN121763206A (zh) * 2026-03-02 2026-03-31 中国电子科技集团公司第五十四研究所 一种基于多维电磁场图的无线阵列单基站定位方法及系统

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116429123A (zh) * 2023-04-18 2023-07-14 中车南京浦镇车辆有限公司 一种基于多源信息融合的车辆定位方法

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080189038A1 (en) * 2004-06-02 2008-08-07 Centre National De La Recherche Scientifique -Cnrs - Driving Assistance System for Interaction Between a Mobile Element and an Infrastructure
CN103268116A (zh) * 2013-04-17 2013-08-28 无锡普智联科高新技术有限公司 基于复合型磁钉校正的agv纠偏控制系统及方法
CN106249736A (zh) * 2016-07-13 2016-12-21 上海交通大学 一种基于磁钉地图导航的自动导引车
CN106403931A (zh) * 2015-07-31 2017-02-15 北京航天计量测试技术研究所 一种磁地标动态定位方法
CN111966104A (zh) * 2020-08-21 2020-11-20 上海电气集团智能交通科技有限公司 一种基于磁钉的融合导航车辆自动驾驶系统及方法
CN115808177A (zh) * 2022-09-13 2023-03-17 中车南京浦镇车辆有限公司 一种基于电磁标记的车辆融合定位传感器
CN116429123A (zh) * 2023-04-18 2023-07-14 中车南京浦镇车辆有限公司 一种基于多源信息融合的车辆定位方法

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5347456A (en) * 1991-05-22 1994-09-13 The Regents Of The University Of California Intelligent roadway reference system for vehicle lateral guidance and control
US6720920B2 (en) * 1997-10-22 2004-04-13 Intelligent Technologies International Inc. Method and arrangement for communicating between vehicles
JP4090770B2 (ja) * 2002-03-28 2008-05-28 クラリオン株式会社 車載用走行支援情報検知装置
FR2871274B1 (fr) * 2004-06-02 2007-03-16 Centre Nat Rech Scient Cnrse Systeme d'aide a la conduite pour la cooperation mobile infrastructure
CN108052107B (zh) * 2018-01-19 2020-11-24 浙江科钛机器人股份有限公司 一种融合磁条、磁钉和惯导的agv室内外复合导航系统及方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080189038A1 (en) * 2004-06-02 2008-08-07 Centre National De La Recherche Scientifique -Cnrs - Driving Assistance System for Interaction Between a Mobile Element and an Infrastructure
CN103268116A (zh) * 2013-04-17 2013-08-28 无锡普智联科高新技术有限公司 基于复合型磁钉校正的agv纠偏控制系统及方法
CN106403931A (zh) * 2015-07-31 2017-02-15 北京航天计量测试技术研究所 一种磁地标动态定位方法
CN106249736A (zh) * 2016-07-13 2016-12-21 上海交通大学 一种基于磁钉地图导航的自动导引车
CN111966104A (zh) * 2020-08-21 2020-11-20 上海电气集团智能交通科技有限公司 一种基于磁钉的融合导航车辆自动驾驶系统及方法
CN115808177A (zh) * 2022-09-13 2023-03-17 中车南京浦镇车辆有限公司 一种基于电磁标记的车辆融合定位传感器
CN116429123A (zh) * 2023-04-18 2023-07-14 中车南京浦镇车辆有限公司 一种基于多源信息融合的车辆定位方法

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN121763206A (zh) * 2026-03-02 2026-03-31 中国电子科技集团公司第五十四研究所 一种基于多维电磁场图的无线阵列单基站定位方法及系统

Also Published As

Publication number Publication date
CN116429123A (zh) 2023-07-14
MX2024008382A (es) 2024-12-06

Similar Documents

Publication Publication Date Title
US20210311490A1 (en) Crowdsourcing a sparse map for autonomous vehicle navigation
US10248124B2 (en) Localizing vehicle navigation using lane measurements
CN111380539B (zh) 车辆定位、导航方法和装置及相关系统
CN110530372B (zh) 定位方法、路径确定方法、装置、机器人及存储介质
US20220082403A1 (en) Lane mapping and navigation
CN109416256B (zh) 行驶车道推定系统
AU2022203634A1 (en) Localizing vehicle navigation using lane measurements
CN106249736B (zh) 一种基于磁钉地图导航的自动导引车
US11579628B2 (en) Method for localizing a vehicle
EP3936822B1 (en) Vehicle positioning method and apparatus, and vehicle, and storage medium
US11327155B2 (en) Radar sensor misalignment detection for a vehicle
CN115038934A (zh) 车辆定位方法和装置、存储介质及电子设备
US11499833B2 (en) Inferring lane boundaries via high speed vehicle telemetry
CN106980657A (zh) 一种基于信息融合的车道级电子地图构建方法
CN112747755B (zh) 道路线确定方法、装置、可读存储介质及地图更新系统
CN116429123A (zh) 一种基于多源信息融合的车辆定位方法
Hussain et al. Real-time relative lane and position identification of surrounding vehicles using GPS and DSRC based vehicle-to-vehicle communication
CN116027375B (zh) 自动驾驶车辆的定位方法、装置及电子设备、存储介质
CN211427151U (zh) 一种应用于封闭场地无人驾驶货运车辆上的自动引导系统
CN109883434B (zh) 限制场景下辅助无人车全局定位的场端及全局定位方法
CN111561944B (zh) 一种运梁车运行路径规划方法及自动驾驶运行控制方法
Kim et al. Development of Vision-Based Train Positioning System Using Object Detection and Kalman Filter
CN119085670B (zh) 一种轻量化多趟建图方法、装置、设备及车辆
CN115515221B (zh) 定位方法、装置、电子设备及计算机存储介质
CN120651212B (zh) 基于多特征信息的定位方法和电子设备

Legal Events

Date Code Title Description
WWE Wipo information: entry into national phase

Ref document number: MX/A/2024/008382

Country of ref document: MX

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 24792011

Country of ref document: EP

Kind code of ref document: A1

REG Reference to national code

Ref country code: BR

Ref legal event code: B01A

Ref document number: 112024012750

Country of ref document: BR

ENP Entry into the national phase

Ref document number: 112024012750

Country of ref document: BR

Kind code of ref document: A2

Effective date: 20240621

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 24792011

Country of ref document: EP

Kind code of ref document: A1