WO2022007143A1 - 路侧车联网装置、高架桥路段识别方法及车载车联网装置 - Google Patents

路侧车联网装置、高架桥路段识别方法及车载车联网装置 Download PDF

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WO2022007143A1
WO2022007143A1 PCT/CN2020/111285 CN2020111285W WO2022007143A1 WO 2022007143 A1 WO2022007143 A1 WO 2022007143A1 CN 2020111285 W CN2020111285 W CN 2020111285W WO 2022007143 A1 WO2022007143 A1 WO 2022007143A1
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vehicle
viaduct
road
data set
coordinate value
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PCT/CN2020/111285
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English (en)
French (fr)
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张耿旭
唐侨
钟启兴
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惠州市德赛西威智能交通技术研究院有限公司
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Publication of WO2022007143A1 publication Critical patent/WO2022007143A1/zh

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/012—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/167—Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Definitions

  • the invention relates to the technical field of Internet of Vehicles, in particular to a roadside Internet of Vehicles device, an identification method for a viaduct road section, and a vehicle Internet of Vehicles device.
  • the Internet of Vehicles mainly refers to the effective use of all vehicle dynamic information in the information network platform by the on-board equipment on the vehicle through wireless communication technology, and provides different functional services during vehicle operation.
  • the main features of the Internet of Vehicles are: the Internet of Vehicles can provide a guarantee for the distance between vehicles and reduce the probability of vehicle collisions; the Internet of Vehicles can help car owners navigate in real time, and improve traffic through communication with other vehicles and network systems. operating efficiency.
  • V2X vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle to everything, information exchange between vehicles and the outside world
  • V2X Vehicle
  • V2X in the viaduct road section Since the viaduct has multi-level height plane sections, if we do not distinguish which level plane section the vehicle is driving on, there will inevitably be warning errors caused by vehicles of different height plane sections interacting with each other. report a problem. For example, vehicles at different levels of height plane sections may cross, and there is a danger of collision, but they are in different height plane sections. In fact, they will not collide. However, if the height plane sections are not distinguished, there will be collisions. False positive cross-collision warning.
  • the purpose of the present invention is to provide a roadside vehicle networking device, a viaduct section identification method that can accurately identify the viaduct section that the vehicle enters or exits, and a vehicle-mounted vehicle networking device applying the method.
  • a roadside vehicle networking device used to be installed on or near a viaduct with multiple road sections, comprising: a storage unit in which location point data sets of the multiple road sections are stored; a wireless transmission unit; and a broadcast unit , which is used to control the wireless sending unit to broadcast the location point data set at predetermined time intervals.
  • the location point data set of each road segment includes location data of a plurality of location points on the center line of the road segment.
  • the location point data set of each road segment includes two sets of data sets: an entrance data set and an exit data set, which respectively include a plurality of data sets on the centerline of the road segment when advancing from the entrance end to the exit end of the road segment.
  • Location data for the location point is two sets of data sets: an entrance data set and an exit data set, which respectively include a plurality of data sets on the centerline of the road segment when advancing from the entrance end to the exit end of the road segment.
  • M is preferably an integer greater than or equal to 2
  • the structure of the position point data set of the M road sections is preferably an integer greater than or equal to 2
  • OP x is the viaduct
  • Path M is the road section
  • Entr M is the entrance data set
  • Exit M is the exit data set
  • (Px, Py) is the coordinate value of the local coordinate system.
  • a method for identifying a viaduct road section comprising:
  • Receive broadcasts from other IoV devices and when receiving the location point datasets of the multiple road segments broadcasted by the roadside IoV device as described above, calculate the location of the vehicle and the multiple road segments according to the track record of the vehicle According to the calculated evaluation index, whether the vehicle enters or exits a certain road section of the viaduct is discriminated and stored.
  • the position data acquired in the vehicle establishing the vehicle track recording step, a certain collection period T H of the position data of the vehicle, and according to a fixed distance interval [Delta] L, the extraction position data storage into The vehicle track record is formed in the sliding queue positioning array Tra with a length of N; the storage structure of the sliding queue positioning array Tra is as follows:
  • the step of receiving the broadcast of other IoV devices it also includes receiving state information broadcast from other vehicles, and updating and storing the received information in the system of the vehicle;
  • the vehicle If the vehicle generates a collision warning with other vehicles while driving on a certain road section of the viaduct, first determine whether the vehicle and the warning vehicle are in the same road section, and if they are in the same road section, output the warning, otherwise it will be regarded as a misjudgment Warning, no action will be taken.
  • the evaluation index includes the correlation r between the position of the vehicle and the plurality of road sections, and the calculation formula is:
  • p is the X or Y coordinate value in the received position point data set of the multiple road segments
  • h is the X or Y coordinate value in the track record of the vehicle
  • It is the mean value of the X or Y coordinate values in the track record of the vehicle.
  • the correlation r X of the X coordinate value in the point data set; the Y coordinate value in the position point data set of the multiple road sections, the Y coordinate value in the track record of the vehicle are substituted into formula (1) to obtain the track record of the vehicle
  • the correlation r Y between the Y coordinate value in and the Y coordinate value in the position point data set of the plurality of road segments.
  • the evaluation index includes the consistency between the position of the vehicle and the plurality of road sections
  • the calculation method includes: separately calculating each of the position point data sets of the plurality of road sections and the data recorded by the vehicle's track.
  • the distance of the corresponding position point Dis ⁇ dis 1 ,dis 2 ,...,dis N ⁇ ,
  • P x and P y point for the location of the plurality of sections of the received data set X coordinate value and Y coordinate value, X coordinate value or the Y-coordinate values H x and H y of the vehicle has track record;
  • the standard deviation S is used to represent the dispersion degree of the distance difference between each location point.
  • the steps of judging and storing whether the vehicle enters or leaves a certain road section of the viaduct include:
  • C R is a predetermined correlation criterion values, is determined to satisfy the relationship between the degree of correlation calculated link data and the position data of the vehicle , and start to calculate the consistency between the calculated data of the road segment and the position data of the vehicle;
  • An in-vehicle Internet of Vehicles device includes a control unit loaded with a viaduct road segment identification program, and when the viaduct road segment identification program is run, executes the above-mentioned viaduct road segment identification method.
  • the roadside vehicle networking device, the viaduct road section identification method, and the vehicle-mounted vehicle networking device of the present invention have at least the following advantages:
  • the roadside vehicle networking device of the present invention can effectively collect and broadcast the location point data of each viaduct road section.
  • the viaduct road section identification method of the present invention can accurately identify the viaduct road section that the vehicle enters or exits, effectively solves the problem of early warning and false alarms caused by the mutual influence of vehicles on various layers of the viaduct, and greatly improves the system early warning accuracy.
  • the in-vehicle Internet of Vehicles device of the present invention is loaded with a viaduct road section identification program, which can effectively ensure the operation of the viaduct road section identification program, and execute the above-mentioned viaduct road section identification method.
  • the roadside vehicle networking device in the embodiment of the present invention is installed on or near a viaduct with multiple road sections, and includes a storage unit, a wireless transmission unit and a broadcast unit; the storage unit stores the location point data of the multiple road sections of the viaduct set, the broadcasting unit controls the wireless sending unit to broadcast the above-mentioned location point data set at a predetermined time interval; the predetermined time interval is set to, for example, but not limited to, 100ms.
  • the location point data set of each road segment includes location data of a plurality of location points on the centerline of the road segment.
  • the position point data set of each road segment includes two sets of data sets: an entrance data set and an exit data set, respectively including a plurality of positions on the center line of the road segment when advancing from the entrance end to the exit end of the road segment point location data.
  • the entrance data set and exit data set of each road section of the viaduct are collected in advance, which are the position point data of the entrance and exit length of each road section, and the number of position point data of the entrance and exit is N, then the position point data
  • M is preferably an integer greater than or equal to 2
  • the location point data collection results of the M road sections are stored according to the following data structure into the vehicle system.
  • OP x is the viaduct
  • Path M is the road section
  • Entr M is the entrance data set
  • Exit M is the exit data set
  • (Px, Py) is the coordinate value of the local coordinate system.
  • the track record of the vehicle is formed in the sliding queue positioning array Tra of .
  • the storage structure of the sliding queue positioning array Tra is as follows: Tra ⁇ (Hx 1 ,Hy 1 ),(Hx 2 ,Hy 2 ),...(Hx N ,Hy N ) ⁇ , where (Hx, Hy) is the positioning coordinate value of the vehicle's local coordinate system.
  • Receive broadcasts from other IoV devices when receiving the location point data sets of multiple road segments broadcast by the roadside IoV device, calculate the vehicle location and the evaluation indicators of multiple road segments according to the track record of the vehicle; It can judge and store whether the vehicle enters or exits a certain road section of the viaduct.
  • the evaluation index includes the correlation r between the position of the vehicle and the plurality of road sections, and the calculation formula is:
  • p is the X or Y coordinate value in the received position point data set of the multiple road segments
  • h is the X or Y coordinate value in the track record of the vehicle
  • It is the mean value of the X or Y coordinate values in the track record of the vehicle.
  • the evaluation index includes the consistency between the position of the vehicle and the plurality of road sections
  • the calculation method includes:
  • P x and P y point for the location of the plurality of sections of the received data set X coordinate value and Y coordinate value, X coordinate value or the Y-coordinate values H x and H y of the vehicle has track record.
  • the standard deviation S is used to represent the dispersion degree of the distance difference between each position point. The smaller the dispersion degree, the more concentrated the distance difference between the corresponding position points.
  • the steps of judging and storing whether the vehicle enters or exits a certain road section of the viaduct include:
  • C R is a predetermined correlation criterion values, is determined to satisfy the relationship between the degree of correlation calculated link data and the position data of the vehicle , and start to calculate the consistency between the calculated data of the road segment and the position data of the vehicle.
  • C R is set according to the actual situation, optionally, C R is 0.9, i.e. r ⁇ 0.9, may be considered to satisfy the relationship between the horizontal position data of the vehicle and the road data acquired.
  • C Dis and C s are preset standard distance parameters and preset standard deviation parameters, indicating that the mean and standard deviation of the distances of each location point are within the preset range, then it is considered that the calculated viaduct is
  • C Dis is set according to the actual situation, optional, C Dis is (LN/2-0.5)*LW , where LN is the number of lanes of the road segment, and LW is the width of the lane. For example, a road segment has 3 lanes and the lane width is 3.5 meters, that is, C Dis can be selected as 3.5 meters.
  • C s is set according to the actual situation.
  • C s is 0.5 meters, that is, S ⁇ 0.5 meters, it is considered that the standard deviation of the distance between the position data of the road and the vehicle meets the requirements.
  • the road segment data is entry data, it is considered that the vehicle enters the road segment, and if the road segment data is exit data, the vehicle is considered to have exited the road segment. And when the vehicle enters the above-mentioned viaduct section determined to be consistent, it is marked in the vehicle system, and the information on the viaduct section where the vehicle is located is broadcast to the outside through the in-vehicle Internet of Vehicles device mounted on the vehicle.
  • this step also includes receiving the status information broadcasted by other vehicles and the location point data of the entrance and exit of each road section of the viaduct, and updating and storing the received information in the system of the vehicle; if the vehicle is in a certain part of the viaduct.
  • Relevant warnings (such as collision warnings with other vehicles) are generated during driving on the road section. First determine whether the vehicle and the warning vehicle are in the same road section. If they are in the same road section, the warning will be output. Otherwise, it will be regarded as a misjudgment warning, and no corresponding deal with.
  • Another key point of this method is how to solve the problem of consistency evaluation between the position point of the vehicle's own motion trajectory and the position point data of each plane section of the viaduct.
  • the correlation calculation is firstly performed on the X and Y values of the vehicle itself and the position point data of the road section, so as to determine whether there is a correlation between the vehicle itself and the position point data of the road section, and the degree of the correlation.
  • the correlation since the correlation only reflects the correlation of the data, it cannot guarantee the consistency of the data, so on the basis of the correlation, the error of the data (that is, the distance between the location points) is evaluated. The error and the standard deviation of the error are evaluated.
  • the standard deviation is a measure of the degree of dispersion of the data, which is used in this method to reflect the degree of dispersion of the distance between the location points; if the calculated average distance is 0, but the standard deviation is large, it means that the distance between each corresponding location point is between There are large differences, so the data cannot be considered consistent. Similarly, if the average distance is large, but the standard deviation is small, it means that the difference between the distances between each corresponding location point is small, but the overall error is large, and the data cannot be considered consistent. Only by comprehensively considering the correlation between the data, the average error and the dispersion of the error, can the evaluation conclusion of the data consistency be given more accurately.
  • the in-vehicle Internet of Vehicles device in the embodiment of the present invention includes a control unit, the control unit is loaded with a viaduct road segment identification program, and when the viaduct road segment identification program is run, executes the above-mentioned viaduct road segment identification method.
  • the present invention provides a roadside vehicle networking device that can effectively collect and broadcast the position point data of each viaduct section; A road segment identification method and an in-vehicle vehicle networking device applying the method.
  • the viaduct road section identification method in the embodiment of the present invention can accurately identify the viaduct road section that the vehicle enters or exits, effectively solves the problem of early warning and false alarms caused by the mutual influence of vehicles on various layers of the viaduct, and greatly improves the system. Accuracy of warnings.
  • the broadcast frequency of the broadcasting unit of the roadside vehicle networking device may be adjusted as required.
  • a step of collecting location data of the vehicle, the vehicle setup time period T H of the recording track may be replaced 50ms, 100ms, 150ms, 200ms, etc. integer number of cycles, but not limited to the above-mentioned time period.

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Abstract

一种路侧车联网装置、高架桥路段识别方法及车载车联网装置；所述路侧车联网装置包括存储单元、无线发送单元和广播单元，用于收集和广播各高架桥路段的位置点数据；所述高架桥路段识别方法包括采集本车的位置数据，建立本车航迹记录；接收其它车联网装置的广播，当接收到路侧车联网装置广播的多个路段的位置点数据集时，根据本车航迹记录计算本车位置与所述多个路段的评价指标；并根据所计算的评价指标，对本车是否进入或驶出高架桥的某一路段进行判别和存储。所述车载车联网装置包括控制单元，所述控制单元中加载有高架桥路段识别程序，所述高架桥路段识别程序被运行时，执行上述的高架桥路段识别方法。

Description

路侧车联网装置、高架桥路段识别方法及车载车联网装置 技术领域
本发明涉及车联网技术领域，具体涉及一种路侧车联网装置、高架桥路段识别方法及车载车联网装置。
背景技术
车联网主要指：车辆上的车载设备通过无线通信技术，对信息网络平台中的所有车辆动态信息进行有效利用，在车辆运行中提供不同的功能服务。车联网的主要特征是：车联网能够为车与车之间的间距提供保障，降低车辆发生碰撞事故的几率；车联网可以帮助车主实时导航，并通过与其它车辆和网络系统的通信，提高交通运行的效率。V2X(vehicle to everything，车对外界的信息交换)，是车联网发展的关键领域之一，主要包括以下几种互联类型：车与车V2V(Vehicle to Vehicle)、车与基础设施V2I(Vehicle to Infrastructure)、车与人V2P(Vehicle to Pedestrian)和车与互联网(Vehicle to Network)。V2X通过车与万物互联，能够使车辆获得实时的路况信息、道路信息和行人信息等一系列交通信息，从而提高驾驶安全性、减少拥堵、提高交通效率等。
V2X在高架桥路段所面临的问题：由于高架桥存在多层高度平面的路段，如果我们没有区分车辆是在哪层高度平面路段行驶，那么势必会出现不同高度平面路段的车辆互相影响而导致的预警误报问题。例如不同层次高度平面路段的车辆存在交叉行驶，且运动趋势存在碰撞的危险，但是他们在不同的高度平面路段，实际上他们是不会存在碰撞可能的，然而若没有区分高度平面路段，就会误报交叉碰撞预警。
现有技术中，针对车辆在高架桥路段预警误报的问题，一般通过以下方式解决：
1)利用导航卫星定位系统提供的高度数据来作为本车与目标车是否在同一平面路段的判断。这种方案最为简单和直接，也是最为经济的一种方法；然而，由于目前导航卫星定位系统提供的高度数据误差无法保证，使得同一平面判断存在一定的错误概率，错误的预警不仅会给驾驶员产生干扰和误导，从体验上和驾驶安全上都是不可接受的。
2)增加高精度的高度传感器来获取车辆的海拔高度。这种方案一方面需要增加额外的硬件成本，设想所有安装有V2X系统的车辆都需要加装该传感器的话，成本总量将很难承受；另一方面，传感器的接入将增加系统的复杂性和不稳定性，且增加系统功耗；另外，V2X的最远预警范围可达几百米，那么不同环境的因素(如温度)也会对高度传感器带来一定的误差，存在误判风险。
发明内容
本发明的目的在于提供一种路侧车联网装置、一种可准确识别本车所驶入或驶出的高架桥路段的高架桥路段识别方法及应用该方法的车载车联网装置。
为实现上述目的，本发明采用的技术方案如下：
一种路侧车联网装置，用于安装在具有多个路段的高架桥上或附近，其包括：存储单元，其内存储有所述多个路段的位置点数据集；无线发送单元；以及广播单元，其用于控制所述无线发送单元以预定时间间隔广播所述位置点数据集。
较佳地，每个路段的位置点数据集均包括该路段的中心线上的多个位置点的位置数据。
较佳地，每个路段的位置点数据集均包括两套数据集：入口数据集和出口数据集，分别包括了从该路段入口端向出口端前进时的该路段的中心线上的多个位置点的位置数据。
较佳地，假设所述高架桥的路段数为M，为保证高架桥所收集位置数据的准确性和完整性，优选M为大于或等于2的整数，则该M个路段的位置点数据集的结构如下：
Figure PCTCN2020111285-appb-000001
其中，OP x为所述高架桥，Path M为路段，Entr M为入口数据集，Exit M为出口数据集，(Px,Py)为地方坐标系的坐标值。
一种高架桥路段识别方法，其特征在于，包括，
采集本车的位置数据，建立本车航迹记录；
接收其它车联网装置的广播，当接收到如上所述的路侧车联网装置广播的所述多个路段的位置点数据集时，根据本车航迹记录计算本车位置与所述多个路段的评价指标；并根据所计算的评价指标，对本车是否进入或驶出高架桥的某一路段进行判别和存储。
较佳地，在所述采集本车的位置数据，建立本车航迹记录步骤中，以一定的周期T H采集本车的位置数据，并按照固定的距离间隔ΔL，抽取位置数据，存储进长度为N的滑动队列定位数组Tra中形成所述本车航迹记录；所述滑动队列定位数组Tra的存储结构如下：
Tra{(Hx 1,Hy 1),(Hx 2,Hy 2),…(Hx N,Hy N)}，其中(Hx,Hy)为本车地方坐标系的定位坐标值。
较佳地，在所述接收其它车联网装置的广播步骤中，还包括接收来自其它车辆广播的状态信息，并将所接收的信息更新存储到本车系统中；
如果本车在所述高架桥的某一路段行驶过程中产生与其他车辆的碰撞预警，先判断本车和预警车辆是否处于同路段，如果处于同路段，则输出该预警，否则视为误判的预警，不做相应处理。
较佳地，所述评价指标包括本车位置与所述多个路段的相关性r，其计算公式为：
公式(一)：
Figure PCTCN2020111285-appb-000002
其中-1≤r≤1,r越大则相关性越强；
p为接收到的所述多个路段的位置点数据集中的X或Y坐标值，h为本车航迹记录中的X或Y坐标值，
Figure PCTCN2020111285-appb-000003
为所述多个路段的位置点数据集中的X或Y坐标值的均值，
Figure PCTCN2020111285-appb-000004
为本车航迹记录中的X或Y坐标值的均值。
将所述多个路段的位置点数据集中的X坐标值、本车航迹记录中的X坐标值代入公式(一)得到本车航迹记录中的X坐标值和所述多个路段的位置点数据集中的X坐标值的相关性r X；将所述多个路段的位置点数据集中的Y坐标值、本车航迹记录中的Y坐标值代入公式(一)得到本车航迹记录中的Y坐标值和所述多个路段的位置点数据集中的Y坐标值的相关性r Y。
较佳地，所述评价指标包括本车位置与所述多个路段的一致性，其计算方法包括：分别计算所述多个路段的位置点数据集和本车航迹记录的数据中每个对应位置点的距离：Dis{dis 1,dis 2,…,dis N}，
Figure PCTCN2020111285-appb-000005
P x和P y为接收到的所述多个路段的位置点数据集中的X坐标值和Y坐标值，H x和H y为本车航迹记录中的X坐标值或Y坐标值；
计算上述得出的位置点距离的均值
Figure PCTCN2020111285-appb-000006
和标准差S：
Figure PCTCN2020111285-appb-000007
用标准差S表示各位置点距离差距的离散程度。
较佳地，所述对本车是否进入或驶出高架桥的某一路段进行判别和存储的步骤包括：
如果r Y≥C R且r X≥C R，0＜C R≤1，C R为预设相关性标准值，则判断所计算的该路段数 据和本车的位置数据之间满足相关关系程度，开始计算所计算的该路段数据和本车的位置数据之间的一致性；
如果
Figure PCTCN2020111285-appb-000008
且S＜C s，其中C Dis和C s为预设标准距离参数和预设标准差参数，则认为所计算的该高架桥路段位置点数据集和本车航迹记录是一致的，不再进行其它路段的计算；以及当本车进入上述被判断为一致的该高架桥路段时，在本车系统中进行标记，并通过本车搭载的车载车联网装置对外广播本车所处的高架路段信息。
一种车载车联网装置，包括控制单元，所述控制单元中加载有高架桥路段识别程序，所述高架桥路段识别程序被运行时，执行如上所述的高架桥路段识别方法。
本发明的路侧车联网装置、高架桥路段识别方法及车载车联网装置至少具有如下优点：
1、本发明的路侧车联网装置，可有效的收集和广播各高架桥路段的位置点数据。
2、本发明的高架桥路段识别方法可准确识别本车所驶入或驶出的高架桥路段，有效地解决了因高架桥各层路段车辆互相影响而导致的预警误报问题，大大的提高了系统预警的准确性。
3、本发明的车载车联网装置，加载有高架桥路段识别程序，可有效的保证高架桥路段识别程序的运行，执行如上所述的高架桥路段识别方法。
具体实施方式
下面将结合具体实施例对本发明的路侧车联网装置、高架桥路段识别方法及车载车联网装置作进一步详细描述。
本发明实施例中的路侧车联网装置安装在具有多个路段的高架桥上或附近，包括存储单元、无线发送单元和广播单元；所述存储单元内存储有该高架桥多个路段的位置点数据集，所述广播单元控制无线发送单元以预定时间间隔广播上述位置点数据集；预定时间间隔设置为例如但不限于100ms。
每个路段的位置点数据集均包括该路段的中心线上的多个位置点的位置数据。优选地，每个路段的位置点数据集均包括两套数据集：入口数据集和出口数据集，分别包括了从该路段入口端向出口端前进时的该路段的中心线上的多个位置点的位置数据。
高架桥的每个路段的入口数据集和出口数据集均为预先采集，为每个路段的入口和出口长度为L的位置点数据，入口和出口的位置点数据个数都为N，则位置点数据之间为相同的距离间隔
Figure PCTCN2020111285-appb-000009
假设所述高架桥的路段数为M，为保证高架桥所收集位置数据的准确性和完整性，优选M为大于或等于2的整数，则该M个路段的位置点数据采集结果按照 如下数据结构存储到本车系统中。
Figure PCTCN2020111285-appb-000010
其中，OP x为所述高架桥，Path M为路段，Entr M为入口数据集，Exit M为出口数据集，(Px,Py)为地方坐标系的坐标值。
本发明实施例中高架桥路段识别方法的具体实施步骤如下：
步骤一：
采集本车的位置数据，建立本车航迹记录；以例如但不限于100ms为一个时间周期T H采集本车的位置数据，并按照固定的距离间隔ΔL，抽取位置数据，存储进长度为N的滑动队列定位数组Tra中形成本车航迹记录；滑动队列定位数组Tra的存储结构如下：Tra{(Hx 1,Hy 1),(Hx 2,Hy 2),…(Hx N,Hy N)}，其中(Hx,Hy)为本车地方坐标系的定位坐标值。
步骤二：
接收其它车联网装置的广播，当接收到路侧车联网装置广播的多个路段的位置点数据集时，根据本车航迹记录计算本车位置与多个路段的评价指标；并根据所计算的评价指标，对本车是否进入或驶出高架桥的某一路段进行判别和存储。
1、在该步骤中，评价指标包括本车位置与所述多个路段的相关性r，其计算公式为：
公式(一)：
Figure PCTCN2020111285-appb-000011
其中-1≤r≤1，r越大则相关性越强；
p为接收到的所述多个路段的位置点数据集中的X或Y坐标值，h为本车航迹记录中的X或Y坐标值，
Figure PCTCN2020111285-appb-000012
为所述多个路段的位置点数据集中的X或Y坐标值的均值，
Figure PCTCN2020111285-appb-000013
为本车航迹记录中的X或Y坐标值的均值。将所述多个路段的位置点数据集中的X坐标值、本车航迹记录中的X坐标值代入公式(一)得到本车航迹记录中的X坐标值和所述多个路段的位置点数据集中的X坐标值的相关性r X；将所述多个路段的位置点数据集中的Y坐标值、本车航迹 记录中的Y坐标值代入公式(一)得到本车航迹记录中的Y坐标值和所述多个路段的位置点数据集中的Y坐标值的相关性r Y。
2、在该步骤中，评价指标包括本车位置与所述多个路段的一致性，其计算方法包括：
分别计算所述多个路段的位置点数据集和本车航迹记录的数据中每个对应位置点的距离：Dis{dis 1,dis 2,…,dis N}，
Figure PCTCN2020111285-appb-000014
P x和P y为接收到的所述多个路段的位置点数据集中的X坐标值和Y坐标值，H x和H y为本车航迹记录中的X坐标值或Y坐标值。
计算上述得出的位置点距离的均值
Figure PCTCN2020111285-appb-000015
和标准差S：
Figure PCTCN2020111285-appb-000016
用标准差S表示各位置点距离差距的离散程度，离散程度越小，表示各对应位置点的距离差距越集中。
3、所述对本车是否进入或驶出高架桥的某一路段进行判别和存储的步骤包括：
如果r Y≥C R且r X≥C R，0＜C R≤1，C R为预设相关性标准值，则判断所计算的该路段数据和本车的位置数据之间满足相关关系程度，开始计算所计算的该路段数据和本车的位置数据之间的一致性。其中，C R根据实际情况进行设定，可选的，C R为0.9，即r≥0.9，可认为该路段数据和本车所采集的位置数据之间满足相关关系水平。
如果
Figure PCTCN2020111285-appb-000017
且S＜C s，其中C Dis和C s为预设标准距离参数和预设标准差参数，表示各位置点距离的均值和标准差都在预设的范围内，则认为所计算的该高架桥路段位置点数据集和本车航迹记录是一致的，不再进行其它路段的计算；其中，C Dis根据实际情况进行设定，可选的，C Dis为(LN/2-0.5)*LW，其中LN为路段的车道数，LW为车道的宽度，例如某路段为3车道，车道宽度为3.5米，即C Dis可选为3.5米。C s根据实际情况进行设定，可选的，C s为0.5米，即S＜0.5米，则认为道路和本车的位置数据距离的标准差符合要求。
如果该路段数据是入口数据，则认为车辆进入该路段，如果该路段数据是出口数据，则认为车辆驶出该路段。以及当本车进入上述被判断为一致的该高架桥路段时，在本车系统中进行标记，并通过本车搭载的车载车联网装置对外广播本车所处的高架路段信息。
4、在该步骤中还包括接收来自其它车辆广播的状态信息和高架桥各路段入口和出口的位置点数据，并将所接收的信息更新存储到本车系统中；如果本车在高架桥的某一路段行驶过程中产生相关预警(如与其他车辆的碰撞预警)，先判断本车和预警车辆是否处于同路段， 如果处于同路段，则输出该预警，否则视为误判的预警，不做相应处理。
本发明所提出的高架桥路段识别方法的原理：
从背景技术可知，我们需要识别车辆在高架桥的某个平面路段行驶，才能避免不同平面路段预警的误报问题。现有的技术中，由于导航卫星定位系统提供的高度数据精度无法保证，增加精密高度传感器的可行性也不高。当下，V2X技术在国家层面正在大力推动，数字交通、智慧城市是未来的趋势，该方法正是数据交通的一个实现方案，所以借助V2X技术，把预先采集的高架桥各平面路段的入口和出口的位置点数据广播给周围的车辆，让车辆根据自身的位置运动轨迹和接收到的高架桥各平面路段的位置数据进行匹配，从而达到车辆识别自身处于某个高架平面路段行驶的目的。
本方法另外一个关键点，是如何解决车辆自身运动轨迹位置点和高架桥各平面路段位置点数据的一致性评价问题。方法中，先通过对车辆自身和路段位置点数据的X和Y值，分别进行相关性计算，从而判别出车辆自身和路段位置点数据之间是否存在相关性，其相关性的程度有多大。但是，由于相关性只反映数据的相关性，却无法保证数据的一致性，所以在相关性的基础上，再对数据的误差(即位置点之间的距离)情况进行评价，数据误差通过平均误差和误差的标准差来进行评价。标准差是衡量数据的离散程度，在本方法中用于反映位置点距离的离散程度；如果计算得出的平均距离为0，但是标准差很大，意味着每个对应的位置点距离之间存在很大差异，所以不能认为数据是一致的。类似的，如果平均距离很大，但是标准差很小，意味着每个对应的位置点距离之间差异小，但是整体的误差很大，也不能认为数据是一致的。只有综合考虑数据间的相关性、平均误差和误差的离散情况，才能更加准确得给出数据一致性的评价结论。
本发明实施例中的车载车联网装置，包括控制单元，所述控制单元中加载有高架桥路段识别程序，所述高架桥路段识别程序被运行时，执行如上所述的高架桥路段识别方法。
由以上实施例可知，本发明提供了一种可有效的收集和广播各高架桥路段的位置点数据的路侧车联网装置；一种可准确识别本车所驶入或驶出的高架桥路段的高架桥路段识别方法及应用该方法的车载车联网装置。
本发明实施例中高架桥路段识别方法，可准确识别本车所驶入或驶出的高架桥路段，有效地解决了因高架桥各层路段车辆互相影响而导致的预警误报问题，大大的提高了系统预警的准确性。
本领域技术人员可以理解的，其他实施例中，路侧车联网装置的广播单元广播的频率可根据需要进行调整。其他实施例中，步骤一采集本车的位置数据，建立本车航迹记录的时间周期T H可以替换为50ms、100ms、150ms、200ms等整数周期，但不限于上述时间周期。
虽然对本发明的描述是结合以上具体实施例进行的，但是，熟悉本技术领域的人员能够根据上述的内容进行许多替换、修改和变化、是显而易见的。因此，所有这样的替代、改进和变化都包括在附后的权利要求的精神和范围内。

Claims (11)

  1. 一种路侧车联网装置，用于安装在具有多个路段的高架桥上或附近，其特征在于，其包括：
    存储单元，其内存储有所述多个路段的位置点数据集；
    无线发送单元；以及
    广播单元，其用于控制所述无线发送单元以预定时间间隔广播所述位置点数据集。
  2. 根据权利要求1所述的路侧车联网装置，其特征在于，每个路段的位置点数据集均包括该路段的中心线上的多个位置点的位置数据。
  3. 根据权利要求1所述的路侧车联网装置，其特征在于，每个路段的位置点数据集均包括两套数据集：入口数据集和出口数据集，分别包括了从该路段入口端向出口端前进时的该路段的中心线上的多个位置点的位置数据。
  4. 根据权利要求3所述的路侧车联网装置，其特征在于，
    假设所述高架桥的路段数为M，M为大于或等于2的整数，则该M个路段的位置点数据集的结构如下：
    Figure PCTCN2020111285-appb-100001
    其中，OP x为所述高架桥，Path M为路段，Entr M为入口数据集，Exit M为出口数据集，(Px,Py)为地方坐标系的坐标值。
  5. 一种高架桥路段识别方法，其特征在于，包括，
    采集本车的位置数据，建立本车航迹记录；
    接收其它车联网装置的广播，当接收到如权利要求1所述的路侧车联网装置广播的所述多个路段的位置点数据集时，根据本车航迹记录计算本车位置与所述多个路段的评价指标；并根据所计算的评价指标，对本车是否进入或驶出高架桥的某一路段进行判别和存储。
  6. 根据权利要求5所述的高架桥路段识别方法，其特征在于，
    在所述采集本车的位置数据，建立本车航迹记录步骤中，以一定的周期T H采集本车的位置数据，并按照固定的距离间隔ΔL，抽取位置数据，存储进长度为N的滑动队列定位数组Tra中形成所述本车航迹记录；所述滑动队列定位数组Tra的存储结构如下：
    Tra{(Hx 1,Hy 1),(Hx 2,Hy 2),…(Hx N,Hy N)}，其中(Hx,Hy)为本车地方坐标系的定位坐标值。
  7. 根据权利要求5所述的高架桥路段识别方法，其特征在于，
    在所述接收其它车联网装置的广播步骤中，还包括接收来自其它车辆广播的状态信息，并将所接收的信息更新存储到本车系统中；
    如果本车在所述高架桥的某一路段行驶过程中产生与其他车辆的碰撞预警，先判断本车和预警车辆是否处于同路段，如果处于同路段，则输出该预警，否则视为误判的预警，不做相应处理。
  8. 根据权利要求5所述的高架桥路段识别方法，其特征在于，
    所述评价指标包括本车位置与所述多个路段的相关性r，其计算公式为：
    公式(一)：
    Figure PCTCN2020111285-appb-100002
    其中-1≤r≤1,r越大则相关性越强；
    p为接收到的所述多个路段的位置点数据集中的X或Y坐标值，h为本车航迹记录中的X或Y坐标值，
    Figure PCTCN2020111285-appb-100003
    为所述多个路段的位置点数据集中的X或Y坐标值的均值，
    Figure PCTCN2020111285-appb-100004
    为本车航迹记录中的X或Y坐标值的均值；
    将所述多个路段的位置点数据集中的X坐标值、本车航迹记录中的X坐标值代入公式(一)得到本车航迹记录中的X坐标值和所述多个路段的位置点数据集中的X坐标值的相关性r X；
    将所述多个路段的位置点数据集中的Y坐标值、本车航迹记录中的Y坐标值代入公式(一)得到本车航迹记录中的Y坐标值和所述多个路段的位置点数据集中的Y坐标值的相关性r Y。
  9. 根据权利要求8所述的高架桥路段识别方法，其特征在于，所述评价指标包括本车位置与所述多个路段的一致性，其计算方法包括：
    分别计算所述多个路段的位置点数据集和本车航迹记录的数据中每个对应位置点的距离：Dis{dis 1,dis 2,…,dis N}，
    Figure PCTCN2020111285-appb-100005
    P x和P y为接收到的所述多个路段的位置点数据集中的X坐标值和Y坐标值，H x和H y为本车航迹记录中的X坐标值或Y坐标值；
    计算上述得出的位置点距离的均值
    Figure PCTCN2020111285-appb-100006
    和标准差S：
    Figure PCTCN2020111285-appb-100007
  10. 根据权利要求9所述的高架桥路段识别方法，其特征在于，所述对本车是否进入或驶出高架桥的某一路段进行判别和存储的步骤包括：
    如果r Y≥C R且r X≥C R，0＜C R≤1，C R为预设相关性标准值，则判断所计算的该路段数据和本车的位置数据之间满足相关关系程度，开始计算所计算的该路段数据和本车的位置数据之间的一致性；
    如果
    Figure PCTCN2020111285-appb-100008
    且S＜C s，其中C Dis和C s为预设标准距离参数和预设标准差参数，则认为所计算的该高架桥路段位置点数据集和本车航迹记录是一致的，不再进行其它路段的计算；以及
    当本车进入上述被判断为一致的该高架桥路段时，在本车系统中进行标记，并通过本车搭载的车载车联网装置对外广播本车所处的高架路段信息。
  11. 一种车载车联网装置，包括控制单元，其特征在于，所述控制单元中加载有高架桥路段识别程序，所述高架桥路段识别程序被运行时，执行权利要求5至10中任一项所述的高架桥路段识别方法。
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Families Citing this family (2)

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Publication number Priority date Publication date Assignee Title
CN113619578A (zh) * 2021-07-28 2021-11-09 东风汽车集团股份有限公司 一种车辆防碰撞方法、防碰撞系统和计算机可读存储介质
CN116256780B (zh) * 2023-05-16 2023-09-08 智道网联科技(北京)有限公司 高架桥区域的车辆定位方法、装置及电子设备、存储介质

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2552136A1 (en) * 2011-07-28 2013-01-30 Cinterion Wireless Modules GmbH Communication method of broadcast at a localized area of a location of an infrastructure facility, communication system, communication module, localized broadcast data structure and application layer computer program
CN106157691A (zh) * 2014-09-10 2016-11-23 现代自动车美国技术研究所 避免车辆间碰撞的系统
CN107221195A (zh) * 2017-05-26 2017-09-29 重庆长安汽车股份有限公司 汽车车道预测方法及车道级地图
CN207517194U (zh) * 2017-10-23 2018-06-19 天津职业技术师范大学 基于车路协同的高速公路运行车速主动预警系统
CN207780969U (zh) * 2018-01-17 2018-08-28 成都上甲光电科技有限公司 桥梁车流量实时监测系统
CN109961634A (zh) * 2019-03-05 2019-07-02 同济大学 一种基于车联网的城市道路垂直定位系统及方法
CN111291775A (zh) * 2018-12-07 2020-06-16 北京万集科技股份有限公司 车辆定位方法、设备及系统

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1180664B1 (en) * 2000-08-09 2012-10-17 Aisin Aw Co., Ltd. Car navigation system, corresponding navigation method and storage medium
JP2003346285A (ja) * 2002-03-20 2003-12-05 Vehicle Information & Communication System Center 道路情報送信装置、道路情報送信方法、道路情報送信プログラムおよび道路情報受信装置、道路情報受信方法、道路情報受信プログラム
JP2007033434A (ja) * 2005-06-20 2007-02-08 Denso Corp 車両用現在位置検出装置、及び車両制御装置
CN103050006B (zh) * 2012-12-26 2014-12-10 福建工程学院 一种基于浮动车技术的城市高架桥识别方法
CN104157167B (zh) * 2014-08-28 2016-09-28 银江股份有限公司 一种基于协同相对定位技术的车辆防碰撞方法
EP3526097A1 (de) * 2016-12-07 2019-08-21 Siemens Mobility GmbH Verfahren, vorrichtung und bahnfahrzeug, insbesondere schienenfahrzeug, zur fahrspurerkennung im bahnverkehr, insbesondere zur gleiserkennung im schienenverkehr
CN106846908B (zh) * 2016-12-27 2020-08-07 东软集团股份有限公司 道路的危险判断方法和装置
CN109286915A (zh) * 2018-07-05 2019-01-29 惠州市德赛西威汽车电子股份有限公司 一种基于v2x的车辆位置信息获取方法
CN109756867B (zh) * 2018-12-29 2022-02-22 广州中国科学院软件应用技术研究所 一种基于lte-v的车路协同车载终端应用系统
CN109686125B (zh) * 2019-01-11 2021-05-18 重庆邮电大学 一种基于hmm的v2x车联网车辆防撞预警系统
CN110968617B (zh) * 2019-10-16 2023-04-07 北京交通大学 一种基于位置字段的路网关键路段相关性分析方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2552136A1 (en) * 2011-07-28 2013-01-30 Cinterion Wireless Modules GmbH Communication method of broadcast at a localized area of a location of an infrastructure facility, communication system, communication module, localized broadcast data structure and application layer computer program
CN106157691A (zh) * 2014-09-10 2016-11-23 现代自动车美国技术研究所 避免车辆间碰撞的系统
CN107221195A (zh) * 2017-05-26 2017-09-29 重庆长安汽车股份有限公司 汽车车道预测方法及车道级地图
CN207517194U (zh) * 2017-10-23 2018-06-19 天津职业技术师范大学 基于车路协同的高速公路运行车速主动预警系统
CN207780969U (zh) * 2018-01-17 2018-08-28 成都上甲光电科技有限公司 桥梁车流量实时监测系统
CN111291775A (zh) * 2018-12-07 2020-06-16 北京万集科技股份有限公司 车辆定位方法、设备及系统
CN109961634A (zh) * 2019-03-05 2019-07-02 同济大学 一种基于车联网的城市道路垂直定位系统及方法

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