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CN116588083A - A parking control method, device and system - Google Patents

A parking control method, device and system Download PDF

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Publication number
CN116588083A
CN116588083A CN202310597430.5A CN202310597430A CN116588083A CN 116588083 A CN116588083 A CN 116588083A CN 202310597430 A CN202310597430 A CN 202310597430A CN 116588083 A CN116588083 A CN 116588083A
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vehicle
point cloud
parked
parking
parking space
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李一鸣
金宇和
蔡金鹏
吴楠
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Beijing Tusimple Technology Co Ltd
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/06Automatic manoeuvring for parking
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/70Determining position or orientation of objects or cameras
    • G06T7/73Determining position or orientation of objects or cameras using feature-based methods
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74Image or video pattern matching; Proximity measures in feature spaces
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/70Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/762Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/56Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/56Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/586Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of parking space

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Artificial Intelligence (AREA)
  • Automation & Control Theory (AREA)
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  • Databases & Information Systems (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Mathematical Physics (AREA)
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Abstract

The embodiment of the application provides a parking control method, equipment and a system. The parking control method includes: receiving a message of a vehicle to be parked requesting parking sent by a vehicle controller; determining a parking space and sending the identification of the parking space to a vehicle controller; acquiring point cloud data of a preset monitoring area corresponding to a parking space obtained by laser radar scanning; clustering the point cloud data to obtain a point cloud set of the vehicle to be parked; calculating a point cloud set of the vehicle to be parked and a vehicle point cloud model by using an iterative closest point ICP algorithm, obtaining and sending a rotation matrix and a translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model, so that a vehicle controller controls the running direction and the running speed of the vehicle to be parked in real time according to the rotation matrix and the translation matrix and finally stops in a parking space. The parking control method provided by the application has the advantages of high automation degree, high precision and the like, and meets the requirement of realizing automatic and accurate parking in multiple types of parking spaces with narrow spaces.

Description

一种停车控制方法、设备及系统A parking control method, device and system

技术领域technical field

本申请的实施方式涉及智能交通技术领域,更具体地,本申请的实施方式涉及一种停车控制方法、设备及系统。The embodiments of the present application relate to the technical field of intelligent transportation, and more specifically, the embodiments of the present application relate to a parking control method, device and system.

背景技术Background technique

本部分旨在为权利要求书中陈述的本申请的实施方式提供背景或上下文。此处的描述不因为包括在本部分中就承认是现有技术。This section is intended to provide a background or context to the implementations of the application that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section.

随着城市化发展和乘用汽车的普及,停车问题已经成为制约很多城市发展的重要难题。为了解决这一问题,自动上锁式停车位、交叉式停车位、多层式停车位等类型的停车位应运而生,并且为了提高土地利用率和停车管理效率,每个停车位的占地面积一般会被设置成恰好容纳一辆车。然而,不论是上述各种停车位类型,还是狭小的停车位面积,都对停车的精准程度提出了较高的要求。With the development of urbanization and the popularization of passenger cars, the parking problem has become an important problem restricting the development of many cities. In order to solve this problem, types of parking spaces such as automatic locking parking spaces, cross parking spaces, and multi-storey parking spaces have emerged as the times require, and in order to improve land utilization and parking management efficiency, the area occupied by each parking space The area is generally set to accommodate exactly one car. However, whether it is the above-mentioned types of parking spaces or the small area of parking spaces, higher requirements are placed on the accuracy of parking.

发明内容Contents of the invention

为了解决车辆停车问题,现有的一些解决方案例如有:In order to solve the vehicle parking problem, some existing solutions are as follows:

(1)一些技术方案是利用车载GPS设备采集车辆位置来控制车辆停车,然而GPS设备的定位精度(一般达到米级)不能满足在停车位精准停车的要求(精度需达到厘米级),此外,城市内的停车位多位于地下停车场中,受到地上建筑及其室内设备等的影响,GPS信号很容易被遮挡导致定位失败。(1) Some technical solutions use vehicle-mounted GPS devices to collect vehicle positions to control vehicle parking. However, the positioning accuracy of GPS devices (generally up to meter level) cannot meet the requirements for precise parking in parking spaces (accuracy needs to reach centimeter level). In addition, Most of the parking spaces in the city are located in underground parking lots. Due to the influence of above-ground buildings and indoor equipment, GPS signals are easily blocked and cause positioning failure.

(2)还有一些技术方案是利用车载摄像头对停车标识线进行视觉定位来控制车辆停车,然而受到算法和算力的限制,目前这种方案还不能实现厘米级别的精准停车。(2) There are also some technical solutions that use the on-board camera to visually locate the parking marking line to control vehicle parking. However, due to the limitations of algorithms and computing power, this solution cannot achieve centimeter-level precise parking.

可见,目前常见的车辆停车方式多是通过车载定位设备或车载摄像头等对车辆和停车位进行定位,这种停车方式存在误差大、速度慢等缺点。It can be seen that the current common vehicle parking methods mostly use vehicle-mounted positioning equipment or vehicle-mounted cameras to locate vehicles and parking spaces. This parking method has disadvantages such as large errors and slow speeds.

鉴于上述问题,本申请提出了一种克服上述问题或者至少部分地解决上述问题的停车控制方法、设备及系统。In view of the above problems, the present application proposes a parking control method, device and system that overcome the above problems or at least partially solve the above problems.

在本申请实施方式的第一方面中,提供了一种应用于主控器的停车控制方法,包括:In the first aspect of the embodiment of the present application, a parking control method applied to the main controller is provided, including:

接收车辆控制器发送的待停车辆请求停车的消息;Receive the message that the vehicle to be parked requests parking sent by the vehicle controller;

确定一停车位并将所述停车位的标识发送给所述车辆控制器,以使所述车辆控制器控制所述待停车辆驶向所述停车位;determining a parking space and sending the identification of the parking space to the vehicle controller, so that the vehicle controller controls the vehicle to be parked to drive towards the parking space;

获取激光雷达扫描得到的所述停车位对应的预定监控区域的点云数据;所述预定监控区域包括所述停车位和可进入所述停车位的预设区域;Acquiring the point cloud data of the predetermined monitoring area corresponding to the parking space scanned by the laser radar; the predetermined monitoring area includes the parking space and a preset area that can enter the parking space;

对所述点云数据聚类得到所述待停车辆的点云集合;Clustering the point cloud data to obtain the point cloud set of the vehicle to be parked;

利用迭代最近点ICP算法对所述待停车辆的点云集合和车辆点云模型进行计算,得到所述待停车辆的点云集合与所述车辆点云模型之间的旋转矩阵和平移矩阵;其中,所述车辆点云模型是预先利用激光雷达扫描在所述停车位停止的车辆得到的点云集合;Utilize iterative closest point ICP algorithm to calculate the point cloud set and the vehicle point cloud model of the vehicle to be parked, obtain the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model; Wherein, the vehicle point cloud model is a set of point clouds obtained by scanning the vehicles stopped in the parking space by laser radar in advance;

发送所述旋转矩阵和平移矩阵,以使所述车辆控制器根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度并最终停止在所述停车位。Sending the rotation matrix and translation matrix, so that the vehicle controller controls the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and translation matrix, and finally stops at the parking space.

在本申请实施方式的第二方面中,提供了一种应用于车辆控制器的停车控制方法,包括:In the second aspect of the embodiment of the present application, a parking control method applied to a vehicle controller is provided, including:

发送待停车辆请求停车的消息;Send a message that the vehicle to be parked requests to park;

接收主控器返回的停车位的标识,并控制所述待停车辆驶向所述停车位;receiving the identification of the parking space returned by the main controller, and controlling the vehicle to be parked to drive towards the parking space;

接收主控器返回的待停车辆的点云集合和车辆点云模型之间的旋转矩阵和平移矩阵;其中,车辆点云模型是利用预先利用激光雷达扫描在所述停车位停止的车辆得到的点云集合;Receive the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model returned by the main controller; wherein, the vehicle point cloud model is obtained by scanning the vehicle stopped in the parking space by using the laser radar in advance collection of point clouds;

根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度,以使所述待停车辆最终停止在所述停车位。Controlling the traveling direction and speed of the vehicle to be parked in real time according to the rotation matrix and the translation matrix, so that the vehicle to be parked finally stops at the parking space.

在本申请实施方式的第三方面中,提供了一种主控器,包括第一处理器、第一存储器及存储在第一存储器上并可在第一处理器上运行的计算机程序,所述第一处理器在运行所述计算机程序时,执行前述的应用于主控器的停车控制方法中的各个步骤。In a third aspect of the embodiments of the present application, a main controller is provided, including a first processor, a first memory, and a computer program stored in the first memory and operable on the first processor, the When the first processor runs the computer program, it executes various steps in the aforementioned parking control method applied to the main controller.

在本申请实施方式的第四方面中,提供了一种车辆控制器,包括第二处理器、第二存储器及存储在第二存储器上并可在第二处理器上运行的计算机程序,所述第二处理器在运行所述计算机程序时,执行如前所述的应用于车辆控制器的停车控制方法中的各个步骤。In a fourth aspect of the embodiments of the present application, a vehicle controller is provided, including a second processor, a second memory, and a computer program stored in the second memory and operable on the second processor, the When the second processor runs the computer program, it executes various steps in the aforementioned parking control method applied to the vehicle controller.

在本申请实施方式的第五方面中,提供了一种停车控制系统,包括:如前所述的主控器,如前所述的车辆控制器,以及激光雷达。In a fifth aspect of the embodiments of the present application, a parking control system is provided, including: the aforementioned main controller, the aforementioned vehicle controller, and a laser radar.

在本申请实施方式的第六方面中,提供了一种汽车,所述汽车上装设有如前所述的车辆控制器。In a sixth aspect of the embodiments of the present application, a car is provided, and the car is equipped with the aforementioned vehicle controller.

在本申请实施方式的第七方面中,提供了一种计算机可读的存储介质,其上存储有计算机程序,所述计算机程序被处理器运行时实现如前所述的应用于主控器的停车控制方法中的各个步骤。In the seventh aspect of the embodiments of the present application, there is provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, the aforementioned computer program applied to the main controller is implemented. Various steps in the parking control method.

在本申请实施方式的第八方面中,提供了一种计算机可读的存储介质,其上存储有计算机程序,所述计算机程序被处理器运行时实现如前所述的应用于车辆控制器的停车控制方法中的各个步骤。In the eighth aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is run by a processor, the above-mentioned application to the vehicle controller is realized. Various steps in the parking control method.

借助于上述技术方案,本申请利用ICP算法计算行驶中的待停车辆到停车位的旋转量和平移量,并依据该旋转量和平移量控制待停车辆的行驶方向和速度,最终控制待停车辆精准停止在停车位,整个停车过程自动完成,可以达到厘米级别的精度,可满足高精度精准停车的需要。With the help of the above technical solution, the application uses the ICP algorithm to calculate the amount of rotation and translation of the vehicle to be parked to the parking space, and controls the direction and speed of the vehicle to be parked according to the amount of rotation and translation, and finally controls the vehicle to be parked. The vehicle stops precisely in the parking space, and the entire parking process is automatically completed, which can achieve centimeter-level accuracy, which can meet the needs of high-precision and precise parking.

附图说明Description of drawings

通过参考附图阅读下文的详细描述,本申请示例性实施方式的上述以及其他目的、特征和优点将变得易于理解。在附图中,以示例性而非限制性的方式示出了本申请的若干实施方式,其中:The above and other objects, features and advantages of the exemplary embodiments of the present application will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the present application are shown by way of illustration and not limitation, in which:

图1示意性地示出了本申请实施例提供的应用场景;Figure 1 schematically shows the application scenario provided by the embodiment of the present application;

图2示意性地示出了本申请实施例提供的停车控制方法的流程;Fig. 2 schematically shows the flow of the parking control method provided by the embodiment of the present application;

图3示意性地示出了本申请一实施例的预设区域;Fig. 3 schematically shows a preset area according to an embodiment of the present application;

图4示意性地示出了本申请又一实施例的预设区域;Fig. 4 schematically shows a preset area according to another embodiment of the present application;

图5示意性地示出了本申请实施例提供的主控器、激光雷达和预定监控区域的配置模式;Figure 5 schematically shows the configuration mode of the main controller, laser radar and predetermined monitoring area provided by the embodiment of the present application;

图6示意性地示出了本申请一实施例的初始平移矩阵的确定方式;FIG. 6 schematically shows a method of determining an initial translation matrix in an embodiment of the present application;

图7示意性地示出了本申请实施例提供的应用于主控器的停车控制方法的流程;FIG. 7 schematically shows the flow of the parking control method applied to the main controller provided by the embodiment of the present application;

图8示意性地示出了本申请实施例提供的应用于车辆控制器的停车控制方法的流程;Fig. 8 schematically shows the flow of the parking control method applied to the vehicle controller provided by the embodiment of the present application;

图9示意性地示出了本申请实施例提供的汽车;Fig. 9 schematically shows a car provided by an embodiment of the present application;

图10示意性地示出了本申请实施例提供的停车控制系统。Fig. 10 schematically shows the parking control system provided by the embodiment of the present application.

在附图中,相同或对应的标号表示相同或对应的部分。In the drawings, the same or corresponding reference numerals denote the same or corresponding parts.

具体实施方式Detailed ways

下面将参考若干示例性实施方式来描述本申请的原理和精神。应当理解,给出这些实施方式仅仅是为了使本领域技术人员能够更好地理解进而实现本申请,而并非以任何方式限制本申请的范围。相反,提供这些实施方式是为了使本公开更加透彻和完整,并且能够将本公开的范围完整地传达给本领域的技术人员。The principle and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present application, rather than to limit the scope of the present application in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

本领域技术技术人员知道,本申请的实施方式可以实现为一种系统、装置、设备、方法或计算机程序产品。因此,本公开可以具体实现为以下形式,即:完全的硬件、完全的软件(包括固件、驻留软件、微代码等),或者硬件和软件结合的形式。Those skilled in the art know that the embodiments of the present application may be implemented as a system, device, device, method or computer program product. Therefore, the present disclosure may be embodied in the form of complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

本申请附图中的任何元素数量均用于示例而非限制,以及任何命名都仅用于区分,而不具有任何限制含义。Any number of elements in the drawings of the present application is for illustration rather than limitation, and any naming is only for distinction and has no limiting meaning.

下面参考本申请的若干代表性实施方式,详细阐释本申请的原理和精神。The principle and spirit of the present application will be explained in detail below with reference to several representative implementations of the present application.

发明概述Summary of the invention

目前常见的通过车载定位设备或车载摄像头等实现车辆停车的方式存在精度低、速度慢等缺点,为了满足在各种类型且空间狭小的停车位中实现自动化精准停车的需要,本申请实施例提供一种停车控制方法,该方案首先利用激光雷达扫描已在停车位停车的车辆得到车辆点云模型,然后在待停车辆请求停车时再利用激光雷达实时扫描驶向停车位的车辆得到其点云集合,之后通过ICP算法计算待停车辆的点云集合和车辆点云模型之间的旋转矩阵和平移矩阵,由于该旋转矩阵和平移矩阵分别是行驶中的待停车辆到停车位的旋转量和平移量,因此,可以依据该旋转矩阵和平移矩阵实时控制待停车辆的行驶方向和速度,使得待停车辆精准停止在停车位。At present, the common ways of realizing vehicle parking through vehicle positioning equipment or vehicle cameras have disadvantages such as low precision and slow speed. A parking control method, the program first uses the laser radar to scan the vehicle that has parked in the parking space to obtain the vehicle point cloud model, and then uses the laser radar to scan the vehicle driving to the parking space in real time to obtain its point cloud when the vehicle to be parked requests parking After that, the rotation matrix and translation matrix between the point cloud collection of the vehicle to be parked and the vehicle point cloud model are calculated by the ICP algorithm. Since the rotation matrix and translation matrix are the rotation amount and Therefore, the driving direction and speed of the vehicle to be parked can be controlled in real time according to the rotation matrix and translation matrix, so that the vehicle to be parked can accurately stop in the parking space.

本申请提出的停车控制方法具有自动化程度高,精度高等优点,可以达到厘米级别的精度,满足在多类型且空间狭小的停车位中实现自动化精准停车的需要。The parking control method proposed in this application has the advantages of high automation and high precision, and can achieve centimeter-level precision, meeting the needs of automatic and precise parking in multiple types of parking spaces with small spaces.

应用场景总览Overview of application scenarios

本申请实施例提供一种应用场景示意,如图1所示,停车位的上方设置有激光雷达,该激光雷达与主控器连接,主控器获取激光雷达扫描得到的点云数据。The embodiment of the present application provides a schematic diagram of an application scenario. As shown in FIG. 1 , a laser radar is installed above the parking space, and the laser radar is connected to a main controller, and the main controller acquires point cloud data scanned by the laser radar.

车辆控制器发出待停车辆请求停车的消息,主控器获取该消息后,为待停车辆分配一停车位,随后在待停车辆驶向该停车位的过程中,主控器利用激光雷达获取的点云数据聚类得到行驶中的待停车辆的点云集合,并利用ICP算法计算待停车辆的点云集合与该停车位对应的车辆点云模型之间的旋转矩阵和平移矩阵,车辆控制器根据该旋转矩阵和平移矩阵实时控制待停车辆的行驶方向和速度,以使待停车辆精准停止在该停车位。The vehicle controller sends a message that the vehicle to be parked requests parking. After obtaining the message, the main controller allocates a parking space for the vehicle to be parked. Then, when the vehicle to be parked is driving towards the parking space, the main controller uses the laser radar to acquire The point cloud data clustering of the vehicle to be parked is obtained by clustering the point cloud set of the vehicle to be parked, and the ICP algorithm is used to calculate the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model corresponding to the parking space. The controller controls the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and the translation matrix, so that the vehicle to be parked can accurately stop at the parking space.

需要注意的是,图1所示的应用场景仅是为了便于理解本申请的精神和原理而示出,本申请的实施方式在此方面不受任何限制。相反,本申请的实施方式可以应用于适用的任何场景。It should be noted that the application scenario shown in FIG. 1 is only shown to facilitate understanding of the spirit and principle of the present application, and the implementation of the present application is not limited in this regard. On the contrary, the embodiments of the present application can be applied to any applicable scene.

示例性方法exemplary method

下面结合图1的应用场景,参考图2来描述本申请实施例提供的停车控制方法。The following describes the parking control method provided by the embodiment of the present application with reference to FIG. 2 in combination with the application scenario of FIG. 1 .

如图2所示,本申请实施例提供一种停车控制方法,包括:As shown in Figure 2, the embodiment of the present application provides a parking control method, including:

步骤S100,车辆控制器发送待停车辆请求停车的消息。In step S100, the vehicle controller sends a message that the vehicle to be parked requests parking.

具体实施时,车辆控制器和主控器之间可以通过WIFI、V2X、基站等无线通信方式收发消息,本申请对此不做严格限定。考虑到信号的稳定性,主控器和车辆控制器之间可以通过V2X技术收发消息。在一些实施例中,车辆控制器可以通过待停车辆上装设的V2X设备广播待停车辆请求在停车位停车的消息。During specific implementation, messages can be sent and received between the vehicle controller and the main controller through wireless communication methods such as WIFI, V2X, and base station, which is not strictly limited in this application. Considering the stability of the signal, the main controller and the vehicle controller can send and receive messages through V2X technology. In some embodiments, the vehicle controller may broadcast a message that the vehicle to be parked requests to park in a parking space through a V2X device installed on the vehicle to be parked.

在一些实施例中,车辆控制器可以在判断预定条件满足时才发出消息,例如可以是:In some embodiments, the vehicle controller may send a message only when it judges that a predetermined condition is met, for example, it may be:

(1)车辆控制器判断待停车辆进入停车场之后发出消息;或,(1) The vehicle controller sends a message after judging that the vehicle to be parked enters the parking lot; or,

(2)车辆控制器接收到预设的触发信号(如由停车场入口处设置的路卡设备发出的触发信号)之后发出消息。(2) The vehicle controller sends a message after receiving a preset trigger signal (such as a trigger signal sent by a road card device installed at the entrance of the parking lot).

在一些实施例中,车辆控制器发出的消息中可以包含如下一些信息中的一种或多种:In some embodiments, the message sent by the vehicle controller may contain one or more of the following information:

(1)待停车辆的车辆标识;(1) The vehicle identification of the vehicle to be parked;

(2)待停车辆的车辆型号;(2) The vehicle model of the vehicle to be parked;

(3)待停车辆的车载定位设备采集的定位数据;(3) The positioning data collected by the on-board positioning equipment of the vehicle to be parked;

(4)通信连接标识。(4) Communication connection identification.

其中,通信连接标识包括但不限于是车辆控制器的MAC地址、车辆控制器连接的V2X通信设备的MAC地址中的一种或两种。Wherein, the communication connection identifier includes, but is not limited to, one or both of the MAC address of the vehicle controller and the MAC address of the V2X communication device connected to the vehicle controller.

步骤S200,主控器接收车辆控制器发送的待停车辆请求停车的消息。In step S200, the main controller receives a message from the vehicle controller that the vehicle to be parked requests parking.

在一些实施例中,主控器可以通过V2X设备接收车辆控制器发出的消息。In some embodiments, the main controller can receive the message sent by the vehicle controller through the V2X device.

步骤S300,主控器确定一停车位并将该停车位的标识发送给车辆控制器。Step S300, the main controller determines a parking space and sends the identification of the parking space to the vehicle controller.

为确保主控器和车辆控制器之间建立稳定的通信连接,在一些实施例中,在步骤S300之前,主控器从车辆控制器发出的消息中解析出通信连接标识;并通过该通信连接标识与车辆控制器建立通信连接。在一些实施例中,通信连接标识可以但不限于是车辆控制器的MAC地址,和/或,车辆控制器连接的V2X通信设备的MAC地址。To ensure that a stable communication connection is established between the main controller and the vehicle controller, in some embodiments, before step S300, the main controller parses out the communication connection identifier from the message sent by the vehicle controller; and through the communication connection The identification establishes a communication connection with the vehicle controller. In some embodiments, the communication connection identifier may be, but not limited to, the MAC address of the vehicle controller, and/or the MAC address of the V2X communication device connected to the vehicle controller.

在一些实施例中,主控器可以用于管理一个或多个停车位(如整个停车场中的所有停车位)的车辆停车业务,主控器可以在本地存储自身管理的所有停车位的标识和是否被占用的状态(即是否已经有车辆停止在停车位上),当主控器收到车辆控制器发送的待停车辆期待停车的请求时,主控器可以从其管理的全部停车位中确定一空闲的停车位,并将其标识发送给车辆控制器。In some embodiments, the main controller can be used to manage the vehicle parking business of one or more parking spaces (such as all parking spaces in the entire parking lot), and the main controller can locally store the identifications of all the parking spaces managed by itself and the status of whether it is occupied (that is, whether there is a vehicle parked on the parking space), when the main controller receives the request from the vehicle controller to wait for the vehicle to be parked, the main controller can start from all the parking spaces it manages Determine a free parking space in the system and send its identification to the vehicle controller.

步骤S400,车辆控制器根据主控器发来的停车位的标识确定停车位,并控制待停车辆驶向该停车位。Step S400, the vehicle controller determines the parking space according to the parking space identification sent by the main controller, and controls the vehicle to be parked to drive to the parking space.

在一些实施例中,停车位的标识可以是停车位的编号和/或位置信息。例如,停车位的编号可以是1,2,3之类的序号,也可以是M-N(表示该停车位位于停车场的M排N列),停车位的位置信息可以是经纬度坐标,也可以是M排N列(表示该停车位位于停车场的M排N列)等,本申请对此不作具体限定。In some embodiments, the identification of the parking space may be the number and/or location information of the parking space. For example, the number of the parking space can be a serial number such as 1, 2, 3, or M-N (indicating that the parking space is located in the M row N of the parking lot), and the location information of the parking space can be latitude and longitude coordinates, or M rows and N columns (indicating that the parking space is located in M rows and N columns of the parking lot), etc., which are not specifically limited in this application.

步骤S500,主控器获取激光雷达扫描得到的该停车位对应的预定监控区域的点云数据;其中,预定监控区域包括该停车位和可进入该停车位的预设区域。Step S500, the main controller acquires the point cloud data of the predetermined monitoring area corresponding to the parking space scanned by the laser radar; wherein, the predetermined monitoring area includes the parking space and a preset area that can enter the parking space.

在一些实施例中,激光雷达一直处于扫描状态,主控器向车辆控制器发送停车位的标识之后,便立即开始按照一预设的频率获取激光雷达扫描得到的点云数据。In some embodiments, the lidar is always in the scanning state, and after the main controller sends the identification of the parking space to the vehicle controller, it immediately starts to acquire the point cloud data scanned by the lidar at a preset frequency.

为了达到计算行驶中的待停车辆到停车位的旋转量和平移量的目的,预定监控区域应包括停车位和可进入该停车位的预设区域。In order to achieve the purpose of calculating the amount of rotation and translation of the moving vehicle to be parked to the parking space, the predetermined monitoring area should include the parking space and the preset area that can enter the parking space.

在一些实施例中,预设区域可以是从停车位的各个边界向外扩展一定距离所覆盖的区域,如图3所示,预设区域(虚线所示)为该停车位的各个边界向外5米所覆盖的区域。In some embodiments, the preset area can be the area covered by a certain distance from each boundary of the parking space. As shown in FIG. The area covered by 5 meters.

在一些实施例中,预设区域可以是连接停车位的车道中与该停车位相接的矩形区域(即车辆驶入停车位之前在车道内行驶经过的区域),该矩形区域的长度可自行设定,宽度与车道同宽。如图4所示,预设区域(虚线所示)连接停车位的车道中与该停车位相接的矩形区域,其长度为15米,宽度为7米。In some embodiments, the preset area can be a rectangular area connected to the parking space in the lane connecting the parking space (that is, the area that the vehicle drives in the lane before entering the parking space), and the length of the rectangular area can be adjusted by itself. Set the width to be the same width as the lane. As shown in FIG. 4 , the preset area (shown by a dotted line) is connected to a rectangular area in the driveway of the parking space and connected to the parking space, and its length is 15 meters and its width is 7 meters.

在一些实施例中,主控器会对激光雷达实时扫描得到的点云数据进行预处理,例如激光雷达的扫描范围大于预定监控区域,则可以根据预定监控区域所在的位置,将预定监控区域以外的区域的点云数据删除,只保留预定监控区域的点云数据。In some embodiments, the main controller will preprocess the point cloud data obtained by the real-time scanning of the laser radar. The point cloud data in the area will be deleted, and only the point cloud data in the scheduled monitoring area will be kept.

主控器、激光雷达作为两种独立设备,二者之间存在多种连接模式,预定监控区域和停车位之间存在一一对应的关系。考虑到以上因素,具体实施时,主控器、激光雷达和预定监控区域(停车位)可以有如图5所示的多种配置模式:The main controller and the laser radar are two independent devices, and there are multiple connection modes between them, and there is a one-to-one correspondence between the predetermined monitoring area and the parking space. Considering the above factors, during specific implementation, the main controller, laser radar and predetermined monitoring area (parking space) can have multiple configuration modes as shown in Figure 5:

(a)一个主控器只连接一个激光雷达,一个激光雷达只负责一个停车位对应的预定监控区域的扫描工作;(a) One main controller is only connected to one laser radar, and one laser radar is only responsible for scanning the predetermined monitoring area corresponding to one parking space;

(b)一个主控器只连接一个激光雷达,一个激光雷达负责至少两个停车位对应的预定监控区域的扫描工作;(b) One main controller is only connected to one laser radar, and one laser radar is responsible for scanning the predetermined monitoring area corresponding to at least two parking spaces;

(c)一个主控器连接至少两个激光雷达,一个激光雷达只负责一个停车位对应的预定监控区域的扫描工作;(c) A main controller is connected to at least two laser radars, and one laser radar is only responsible for scanning the predetermined monitoring area corresponding to a parking space;

(d)一个主控器连接至少两个激光雷达,一个激光雷达负责至少两个停车位对应的预定监控区域的扫描工作。(d) A main controller is connected with at least two laser radars, and one laser radar is responsible for scanning the predetermined monitoring areas corresponding to at least two parking spaces.

具体实施时,可根据激光雷达的线数和扫描范围等信息综合决定采用哪种配置模式,本申请实施例对此不作具体限定。During specific implementation, which configuration mode to adopt may be comprehensively determined based on information such as the number of lines of the lidar and the scanning range, which is not specifically limited in this embodiment of the present application.

鉴于主控器、激光雷达和停车位之间有多种配置模式,为了便于主控器确定负责扫描停车位对应的预定监控区域的激光雷达,在一些实施例中,主控器在为待停车辆确定空闲的停车位之后,根据激光雷达、停车位之间的配置关系,确定用于扫描该停车位对应的预定监控区域的激光雷达,从而获取该激光雷达扫描得到的点云数据。In view of the fact that there are multiple configuration modes between the main controller, the laser radar and the parking space, in order to facilitate the main controller to determine the laser radar responsible for scanning the predetermined monitoring area corresponding to the parking space, in some embodiments, the main controller After the vehicle determines the free parking space, according to the configuration relationship between the laser radar and the parking space, determine the laser radar used to scan the predetermined monitoring area corresponding to the parking space, so as to obtain the point cloud data scanned by the laser radar.

步骤S600,主控器对点云数据聚类得到待停车辆的点云集合。Step S600, the main controller clusters the point cloud data to obtain a point cloud set of the vehicle to be parked.

具体的,当待停车辆行驶并进入激光雷达的扫描范围内时,激光束会射到待停车辆上并返回被激光雷达接收,扫描得到的点云数据中就会存在待停车辆所对应的点云,通过对点云数据进行聚类就可以提取出待停车辆的点云集合。Specifically, when the vehicle to be parked is driving and enters the scanning range of the laser radar, the laser beam will hit the vehicle to be parked and return to be received by the laser radar. Point cloud, by clustering the point cloud data, the point cloud collection of the vehicles to be parked can be extracted.

该步骤可采用目前常用于对任意形状聚类的算法,例如:WaveCluster、ROCK、CURE、K-Prototypes、DENCLUE、DBSCAN等等。In this step, algorithms commonly used for clustering arbitrary shapes can be used, for example: WaveCluster, ROCK, CURE, K-Prototypes, DENCLUE, DBSCAN, etc.

由于预定监控区域可能会覆盖停车场内的公共区域(如停车位共用的车道)或者其他停车位,获取的点云数据中可能会同时存在多个车辆所对应的点云(例如将要在其他停车位停车的车辆,或者在其他停车位上停止的车辆),这种情况下,对点云数据进行聚类就可能会得到多个车辆(包括待停车辆以及其他车辆)的点云集合,考虑到这点,为了便于主控器从点云数据中聚类得到待停车辆的点云集合,本申请实施例提供了如下几种处理方式:Since the predetermined monitoring area may cover the public area in the parking lot (such as the shared lane of the parking space) or other parking spaces, the point cloud data corresponding to multiple vehicles may exist in the acquired point cloud data (for example, it will be parked in other parking spaces) parking spaces, or vehicles parked in other parking spaces), in this case, clustering the point cloud data may result in a collection of point clouds of multiple vehicles (including vehicles to be parked and other vehicles), considering Up to this point, in order to facilitate the main controller to obtain the point cloud set of the vehicle to be parked by clustering from the point cloud data, the embodiment of the present application provides the following processing methods:

(1)在一些实施例中,主控器对点云数据聚类得到一个或多个车辆的点云集合,将这些点云集合中对应于行驶状态的车辆的点云集合确定为所述待停车辆的点云集合。(1) In some embodiments, the main controller clusters the point cloud data to obtain point cloud sets of one or more vehicles, and determines the point cloud set of the vehicle corresponding to the driving state in these point cloud sets as the to-be Point cloud collection of parked vehicles.

在这类实施例中,待停车辆请求的停车位相邻的其他停车位可能已经被占用,因此聚类得到的点云集合中,只有一个是对应于行驶状态的车辆,其他都是对应于静止状态的车辆,则这些静止状态的车辆可能是已经停止在其他停车位的车辆,这种情况下,无需关注将这类点云集合,而只需关注对应于行驶状态的车辆的点云集合。In this type of embodiment, other parking spaces adjacent to the parking space requested by the vehicle to be parked may have been occupied, so in the point cloud set obtained by clustering, only one is corresponding to the vehicle in the driving state, and the others are corresponding to Vehicles in a stationary state, these stationary vehicles may be vehicles that have stopped in other parking spaces. In this case, there is no need to pay attention to the collection of such point clouds, but only the collection of point clouds corresponding to vehicles in the driving state .

(2)在一些实施例中,车辆控制器在发出的消息中包含待停车辆的车载定位设备采集的定位数据,主控器对点云数据聚类得到一个或多个车辆的点云集合,将这些点云集合中包含上述定位数据的点云集合确定为待停车辆的点云集合。(2) In some embodiments, the message sent by the vehicle controller includes the positioning data collected by the on-board positioning device of the vehicle to be parked, and the main controller obtains the point cloud collection of one or more vehicles by clustering the point cloud data, The point cloud set containing the above positioning data in these point cloud sets is determined as the point cloud set of the vehicle to be parked.

在这类实施例中,不同车辆的车载定位设备采集的定位数据分别是不同车辆的位置信息,通过该定位数据即可区分不同的车辆,因此,包含待停车辆的车载定位设备采集的定位数据的点云集合即为待停车辆的点云集合。In this type of embodiment, the positioning data collected by the on-board positioning equipment of different vehicles are the position information of different vehicles, and different vehicles can be distinguished through the positioning data. The point cloud set of is the point cloud set of the vehicle to be parked.

具体实施时,车载定位设备可以是全球定位系统GPS定位设备、载波相位差分RTK定位设备、北斗卫星定位系统定位设备、GLONASS定位系统定位设备、Galileo定位系统定位设备、全球导航卫星系统GNSS定位设备等。During specific implementation, the on-vehicle positioning equipment can be Global Positioning System GPS positioning equipment, carrier phase difference RTK positioning equipment, Beidou satellite positioning system positioning equipment, GLONASS positioning system positioning equipment, Galileo positioning system positioning equipment, global navigation satellite system GNSS positioning equipment, etc. .

(3)在一些实施例中,车辆控制器在发出的消息中包含待停车辆的车载定位设备采集的定位数据,主控器在点云数据中截取上述定位数据对应的位置及其周围预设长度内的区域所对应的点云数据,并对截取的点云数据聚类得到待停车辆的点云集合。(3) In some embodiments, the message sent by the vehicle controller includes the positioning data collected by the on-board positioning device of the vehicle to be parked, and the main controller intercepts the position corresponding to the above positioning data and its surrounding presets in the point cloud data. Point cloud data corresponding to the area within the length, and cluster the intercepted point cloud data to obtain the point cloud set of the vehicle to be parked.

在这类实施例中,待停车辆的车载定位设备采集的定位数据对应于待停车辆的位置信息,主控器根据上述定位数据可以确定待停车辆的位置,但由于上述定位数据对应的位置是点位置,不能代表整个车身各处的位置,因此,可以根据大多数车辆的车身长度确定一预设长度,进而确定上述定位数据对应的位置及其周围该预设长度内的区域,该区域便可以涵盖整个车身。主控器在点云数据中截取该区域对应的点云数据,其中必然包括待停车辆对应的点云,对其聚类即可得到待停车辆的点云集合。In this type of embodiment, the positioning data collected by the on-board positioning equipment of the vehicle to be parked corresponds to the position information of the vehicle to be parked, and the main controller can determine the position of the vehicle to be parked according to the above positioning data. It is a point position and cannot represent the position of the entire vehicle body. Therefore, a preset length can be determined according to the body length of most vehicles, and then the position corresponding to the above positioning data and the area within the preset length around it can be determined. The area It can cover the entire body. The main controller intercepts the point cloud data corresponding to the area in the point cloud data, which must include the point cloud corresponding to the vehicle to be parked, and clusters it to obtain the point cloud set of the vehicle to be parked.

(4)在一些实施例中,车辆控制器在发出的消息中包含待停车辆所处车道的编号,主控器根据待停车辆所处车道的编号,以及已知的各个车道与激光雷达的相对位置,在点云数据中截取待停车辆所处车道的点云数据;对点云数据聚类得到一个或多个车辆的点云集合;将所述一个或多个车辆的点云集合中与待停车辆所处车道的点云数据存在交集的点云集合确定为待停车辆的点云集合。(4) In some embodiments, the vehicle controller includes the number of the lane where the vehicle to be parked is located in the message sent, and the main controller is based on the number of the lane where the vehicle to be parked is located, and the known relationship between each lane and the laser radar. Relative position, intercepting the point cloud data of the lane where the vehicle to be parked is located in the point cloud data; clustering the point cloud data to obtain the point cloud collection of one or more vehicles; The point cloud set that intersects with the point cloud data of the lane where the vehicle to be parked is determined to be the point cloud set of the vehicle to be parked.

在这类实施例中,当激光雷达的位置确定,各个车道与激光雷达的相对位置即可确定并作为已知信息存储于主控器本地;主控器根据待停车辆所处车道的编号可确定待停车辆在哪个车道上行驶;结合各个车道与激光雷达的相对位置关系,主控器可在点云数据中截取待停车辆所处车道的点云数据;主控器对点云数据聚类得到一个或多个车辆的点云集合之后,找到其中与待停车辆所处车道的点云数据存在交集的点云集合,该点云集合即为待停车辆的点云集合。In this type of embodiment, when the position of the laser radar is determined, the relative position of each lane and the laser radar can be determined and stored locally in the main controller as known information; Determine which lane the vehicle to be parked is driving on; combined with the relative positional relationship between each lane and the laser radar, the master controller can intercept the point cloud data of the lane where the vehicle to be parked is located in the point cloud data; the master controller aggregates the point cloud data After the class obtains the point cloud collection of one or more vehicles, it finds the point cloud collection that intersects with the point cloud data of the lane where the vehicle is to be parked, and this point cloud collection is the point cloud collection of the vehicle to be parked.

(5)在一些实施例中,车辆控制器在发出的消息中包含待停车辆所处车道的编号,主控器根据待停车辆所处车道的编号,以及已知的各个车道与激光雷达的相对位置,在点云数据中截取待停车辆所处车道的点云数据,并对截取的点云数据聚类得到待停车辆的点云集合。(5) In some embodiments, the message sent by the vehicle controller includes the number of the lane where the vehicle to be parked is located. Relative to the position, the point cloud data of the lane where the vehicle to be parked is intercepted in the point cloud data, and the point cloud collection of the vehicle to be parked is obtained by clustering the intercepted point cloud data.

在这类实施例中,当激光雷达的位置确定,各个车道与激光雷达的相对位置即可确定并作为已知信息存储于主控器本地;主控器根据待停车辆所处车道的编号可确定待停车辆在哪个车道上行驶;结合各个车道与激光雷达的相对位置关系,主控器可在点云数据中截取待停车辆所处车道的点云数据。In this type of embodiment, when the position of the laser radar is determined, the relative position of each lane and the laser radar can be determined and stored locally in the main controller as known information; Determine which lane the vehicle to be parked is driving on; combined with the relative positional relationship between each lane and the lidar, the master controller can intercept the point cloud data of the lane where the vehicle to be parked is located in the point cloud data.

(6)在一些实施例中,车辆控制器在发出的消息中包含待停车辆的车载定位设备采集的定位数据及其所处车道的编号;主控器根据待停车辆所处车道的编号,以及已知的各个车道与激光雷达的相对位置,在点云数据中截取待停车辆所处车道的点云数据;主控器对点云数据聚类得到一个或多个车辆的点云集合,将这些点云集合中包含上述定位数据且与截取的待停车辆所处车道的点云数据存在交集的点云集合确定为待停车辆的点云集合。(6) In some embodiments, the message sent by the vehicle controller includes the positioning data collected by the on-board positioning device of the vehicle to be parked and the number of the lane in which it is located; As well as the known relative positions of each lane and the lidar, the point cloud data of the lane where the vehicle to be parked is intercepted in the point cloud data; the master controller clusters the point cloud data to obtain the point cloud collection of one or more vehicles, Among these point cloud sets, the point cloud set that contains the above positioning data and has an intersection with the intercepted point cloud data of the lane where the vehicle to be parked is determined as the point cloud set of the vehicle to be parked.

在这类实施例中,不同车辆的车载定位设备采集的定位数据分别是不同车辆的位置信息,一般情况下,通过该定位数据即可区分不同的车辆,但是考虑到车载定位设备获取的定位数据存在一定的误差,且相邻的车道可能相距较近,为了区分定位数据接近但处于不同车道上的车辆,可将包含上述定位数据且与截取的待停车辆所处车道的点云数据存在交集的点云集合确定为待停车辆的点云集合。In this type of embodiment, the positioning data collected by the on-board positioning equipment of different vehicles are the position information of different vehicles. Generally, different vehicles can be distinguished through the positioning data. However, considering the positioning data acquired by the on-vehicle positioning equipment There is a certain error, and the adjacent lanes may be relatively close to each other. In order to distinguish vehicles whose positioning data are close but in different lanes, the point cloud data containing the above positioning data and intercepting the lane where the vehicle is to be parked can be intersected. The point cloud set of is determined as the point cloud set of the vehicle to be parked.

步骤S700,主控器利用ICP算法对待停车辆的点云集合和车辆点云模型进行计算,得到并发送待停车辆的点云集合与车辆点云模型之间的旋转矩阵和平移矩阵;其中,车辆点云模型是预先对在停车位停车的车辆扫描得到的点云集合。Step S700, the main controller uses the ICP algorithm to calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model, and obtains and sends the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model; wherein, The vehicle point cloud model is a collection of point clouds obtained by pre-scanning vehicles parked in a parking space.

ICP算法可用于计算不同点集之间的平移矩阵和旋转矩阵,待停车辆的点云集合是行驶中的待停车辆对应的点集,而车辆点云模型是精准停止在停车位的车辆的点集,因此利用ICP算法对上述两种点集进行计算可以得到行驶中的待停车辆与精准停止在停车位的车辆之间的平移矩阵和旋转矩阵。并且,由于车辆点云模型是精准停止在停车位的车辆的点集,因此,待停车辆的点云集合与车辆点云模型之间的旋转矩阵和平移矩阵分别对应于待停车辆到停车位的旋转量和平移量。The ICP algorithm can be used to calculate the translation matrix and rotation matrix between different point sets. The point cloud set of the vehicle to be parked is the point set corresponding to the vehicle to be parked in motion, and the vehicle point cloud model is the vehicle accurately parked in the parking space. Therefore, using the ICP algorithm to calculate the above two point sets can obtain the translation matrix and rotation matrix between the vehicle waiting to be parked and the vehicle accurately stopped in the parking space. Moreover, since the vehicle point cloud model is the point set of the vehicle accurately parked in the parking space, the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model correspond to the distance between the vehicle to be parked and the parking space the amount of rotation and translation.

考虑到车辆会有不同的车辆型号,激光雷达对不同型号的车辆扫描得到的点云集合也是不同的,因此,在一些实施例中,可预先利用激光雷达对在停车位停车的多个不同车辆型号的车辆扫描所得到的多个车辆点云模型,并将这些车辆点云模型存储在一模型库中,且步骤S700按照如下过程执行:主控器确定待停车辆的车辆型号,在模型库中选择与待停车辆的车辆型号相匹配的车辆点云模型,并利用ICP算法对待停车辆的点云集合和与待停车辆的车辆型号相匹配的车辆点云模型进行计算。Considering that vehicles have different vehicle models, the point cloud sets obtained by laser radar scanning for different types of vehicles are also different. Therefore, in some embodiments, laser radar can be used in advance to detect multiple different vehicles parked in a parking space. A plurality of vehicle point cloud models obtained by vehicle scanning of models, and store these vehicle point cloud models in a model library, and step S700 is executed according to the following process: the main controller determines the vehicle model of the vehicle to be parked, and stores the vehicle point cloud models in the model library Select the vehicle point cloud model that matches the vehicle model of the vehicle to be parked, and use the ICP algorithm to calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model that matches the vehicle model of the vehicle to be parked.

例如,模型库包括多个车辆点云模型a、b、c、d、e、f、g,这些车辆点云模型对应的车辆型号分别为A、B、C、D、E、F、G,当待停车辆的车辆型号为F时,主控器通过匹配可确定与待停车辆的车辆型号相匹配的车辆点云模型为f,然后可利用ICP算法将待停车辆的点云集合与f进行计算。For example, the model library includes multiple vehicle point cloud models a, b, c, d, e, f, g, and the vehicle models corresponding to these vehicle point cloud models are A, B, C, D, E, F, G, When the vehicle model of the vehicle to be parked is F, the main controller can determine that the vehicle point cloud model matching the vehicle model of the vehicle to be parked is f through matching, and then the point cloud set of the vehicle to be parked can be combined with f by using the ICP algorithm Calculation.

考虑到对于有些车辆型号,模型库中可能没有存储与其匹配的车辆点云模型,在一些实施例中,本申请实施例提供的停车控制方法还包括:判断模型库中是否包含与待停车辆的车辆型号相匹配的车辆点云模型;若不包含,则从模型库中选取一个已有的车辆点云模型确定为与该待停车辆的车辆型号相匹配的车辆点云模型,并在该待停车辆停止在停车位之后,利用激光雷达扫描该待停车辆并将扫描得到的点云集合存入模型库中。经过这种处理,当再次有相同车辆型号的车辆期望在该停车位停车时,模型库中就可以找到与其相匹配的车辆点云模型了。Considering that for some vehicle models, there may not be a matching vehicle point cloud model stored in the model library, in some embodiments, the parking control method provided by the embodiment of the present application further includes: judging whether the model library contains The vehicle point cloud model that matches the vehicle model; if not included, select an existing vehicle point cloud model from the model library to determine the vehicle point cloud model that matches the vehicle model of the waiting vehicle, and After the parking vehicle stops in the parking space, the lidar is used to scan the vehicle to be parked and the scanned point cloud collection is stored in the model library. After this processing, when a vehicle of the same vehicle model expects to park in the parking space again, the matching vehicle point cloud model can be found in the model library.

在一些实施例中,车辆控制器在发送的消息中包含待停车辆的车辆型号,主控器就可以通过解析接收到消息后从其中解析出待停车辆的车辆型号。In some embodiments, the message sent by the vehicle controller includes the vehicle model of the vehicle to be parked, and the main controller can parse the received message to obtain the vehicle model of the vehicle to be parked.

在一些实施例中,主控器可以先获取待停车辆的车辆标识,并根据已知的车辆标识与车辆型号的对应关系来确定待停车辆的车辆型号。其中,车辆标识可以是车牌号码。In some embodiments, the main controller may first obtain the vehicle identification of the vehicle to be parked, and determine the vehicle model of the vehicle to be parked according to the known correspondence between the vehicle identification and the vehicle model. Wherein, the vehicle identification may be a license plate number.

在一些实施例中,主控器可以通过拍摄待停车辆的车牌并对其识别来获取待停车辆的车辆标识。例如,主控器利用摄像头拍摄待停车辆的车牌。In some embodiments, the main controller can obtain the vehicle identification of the vehicle to be parked by photographing the license plate of the vehicle to be parked and identifying it. For example, the main controller utilizes the camera to take pictures of the license plate of the vehicle to be parked.

在一些实施例中,车辆控制器在发送的消息中包含待停车辆的车辆标识,主控器就可以在接收消息后从中解析出该车辆标识。In some embodiments, the message sent by the vehicle controller includes the vehicle identification of the vehicle to be parked, and the main controller can parse out the vehicle identification from the message after receiving the message.

ICP算法是通过迭代的方式计算待停车辆的点云集合和车辆点云模型之间的旋转矩阵和平移矩阵,在ICP算法的迭代过程中,所采用的初始旋转矩阵和初始平移矩阵对最终计算出的结果的准确性具有非常重要的影响。The ICP algorithm is to iteratively calculate the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model. The accuracy of the obtained results has a very important impact.

在一些实施例中,步骤S700按照如下过程执行:In some embodiments, step S700 is performed according to the following process:

步骤S702,确定第一平均中心和第二平均中心,其中,第一平均中心的坐标为待停车辆的点云集合中位于待停车辆的行驶方向上最前方的预设数量个点的坐标的平均值;第二平均中心的坐标为车辆点云模型中位于待停车辆的行驶方向上最前方的预设数量个点的坐标的平均值;Step S702, determining the first average center and the second average center, wherein the coordinates of the first average center are the coordinates of the preset number of points in the point cloud set of the vehicle to be parked that are located at the front in the direction of travel of the vehicle to be parked Average value; the coordinates of the second average center are the average value of the coordinates of the frontmost preset number of points in the vehicle point cloud model in the direction of travel of the vehicle to be parked;

步骤S704,确定初始旋转矩阵和初始平移矩阵;其中,初始旋转矩阵为第一平均中心旋转到第二平均中心所用的矩阵;初始平移矩阵为第一平均中心平移到第二平均中心所用的矩阵;Step S704, determining an initial rotation matrix and an initial translation matrix; wherein, the initial rotation matrix is a matrix used to rotate the first average center to the second average center; the initial translation matrix is a matrix used to translate the first average center to the second average center;

步骤S706,利用初始旋转矩阵和初始平移矩阵,对待停车辆的点云集合和车辆点云模型进行迭代计算,得到待停车辆的点云集合与车辆点云模型之间的旋转矩阵和平移矩阵。Step S706, use the initial rotation matrix and initial translation matrix to iteratively calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model to obtain the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model.

如图6所示,待停车辆的点云集合位于坐标系1中,车辆点云模型位于坐标系2中;待停车辆的点云集合中位于待停车辆的行驶方向上的最前方的n个点(由虚线框标识出)为Pi(xi,yi,zi),i=1,2,3...n,第一平均中心为 车辆点云模型中位于待停车辆的行驶方向上的最前方的n个点(由虚线框标识出)为Qi(Xi,Yi,Zi),i=1,2,3...n,第二平均中心为/> 将第一平均中心/>旋转到第二平均中心/>所用的矩阵确定为初始旋转矩阵;将第一平均中心/>平移到第二平均中心/>所用的矩阵确定为初始平移矩阵。As shown in Figure 6, the point cloud set of the vehicle to be parked is located in the coordinate system 1, and the vehicle point cloud model is located in the coordinate system 2; in the point cloud set of the vehicle to be parked, the n points (identified by the dotted line box) are P i (xi , y i , z i ), i=1, 2, 3...n, and the first mean center is The frontmost n points in the vehicle point cloud model in the direction of travel of the vehicle to be parked (marked by the dotted line box) are Q i (X i , Y i , Z i ), i=1,2,3.. .n, the second mean center is /> Center the first mean /> Rotate to second mean center /> The matrix used is determined as the initial rotation matrix; the first mean center /> Pan to second mean center /> The matrix used is determined as the initial translation matrix.

在一些实施例中,步骤S700按照如下步骤S708~S712执行:In some embodiments, step S700 is performed according to the following steps S708-S712:

步骤S708,主控器从车辆控制器发送的消息中解析待停车辆的车载定位设备采集的定位数据;Step S708, the main controller analyzes the positioning data collected by the on-board positioning device of the vehicle to be parked from the message sent by the vehicle controller;

步骤S710,分别确定初始旋转矩阵和初始平移矩阵;其中,初始旋转矩阵为定位数据对应的点旋转到参考定位点所用的矩阵;初始平移矩阵为定位数据对应的点平移到参考定位点所用的矩阵;参考定位点为确定车辆点云模型的过程中的车辆停止在停车位时其车载定位设备获取的定位数据对应的点;Step S710, determine an initial rotation matrix and an initial translation matrix respectively; wherein, the initial rotation matrix is the matrix used for the point corresponding to the positioning data to rotate to the reference positioning point; the initial translation matrix is the matrix used for the point corresponding to the positioning data to translate to the reference positioning point ; The reference positioning point is the point corresponding to the positioning data obtained by the vehicle positioning device when the vehicle stops in the parking space during the process of determining the vehicle point cloud model;

步骤S712,利用初始旋转矩阵和初始平移矩阵,对待停车辆的点云集合和车辆点云模型进行迭代计算,得到待停车辆的点云集合与车辆点云模型之间的旋转矩阵和平移矩阵。Step S712, use the initial rotation matrix and initial translation matrix to iteratively calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model to obtain the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model.

在确定车辆点云模型的过程中,所使用的车辆上装载有车载定位设备,当车辆停止在停车位时,该车辆上的车载定位设备获取的定位数据所确定的点,即为参考定位点。In the process of determining the vehicle point cloud model, the vehicle used is equipped with a vehicle-mounted positioning device. When the vehicle stops in a parking space, the point determined by the positioning data obtained by the vehicle-mounted positioning device on the vehicle is the reference positioning point. .

在这类实施例中,车载定位设备可以是GPS定位设备、RTK定位设备、北斗卫星定位系统定位设备、GLONASS定位系统定位设备、Galileo定位系统定位设备、全球导航卫星系统GNSS定位设备等。In such an embodiment, the vehicle positioning device may be a GPS positioning device, an RTK positioning device, a Beidou satellite positioning system positioning device, a GLONASS positioning system positioning device, a Galileo positioning system positioning device, a global navigation satellite system GNSS positioning device, etc.

车辆点云模型是在停车位精准停车的车辆的点集,而通过聚类得到的待停车辆的点云集合是正在行驶的待停车辆的点集,因此通过ICP算法对聚类得到的待停车辆的点云集合和车辆点云模型进行计算,即可得到正在行驶的待停车辆到停车位的旋转量和平移量。在此过程中,车辆点云模型的精准程度对最终计算结果的准确性有直接的影响。然而,目前常见的激光雷达的线数有限(如32线、64线),利用固定位置的激光雷达对静止停在停车位的车辆扫描时,受激光束的数量和发射方向的限制,激光束只能射到车辆车身的较少区域,获得的点云数据也只能体现车辆车身的较少区域,对其聚类得到的点云集合(即车辆点云模型)不能很好地体现车辆整个车身的位置,甚至于不能通过聚类算法得到车辆点云模型。The vehicle point cloud model is the point set of the vehicle accurately parked in the parking space, and the point cloud set of the vehicle to be parked obtained through clustering is the point set of the vehicle to be parked while driving. The point cloud collection of the parked vehicle and the vehicle point cloud model are calculated to obtain the rotation and translation of the moving vehicle to be parked to the parking space. In this process, the accuracy of the vehicle point cloud model has a direct impact on the accuracy of the final calculation results. However, the current common laser radar has a limited number of lines (such as 32 lines and 64 lines). It can only shoot to a small area of the vehicle body, and the obtained point cloud data can only reflect a small area of the vehicle body. The position of the vehicle body, even the vehicle point cloud model cannot be obtained through the clustering algorithm.

为了克服上述问题,在一些实施例中,车辆点云模型可按照步骤S714~S718获得:In order to overcome the above problems, in some embodiments, the vehicle point cloud model can be obtained according to steps S714-S718:

步骤S714,预先利用激光雷达扫描驶向停车位并最终在停车位停车的车辆。In step S714, the laser radar is used to scan the vehicles that are heading towards the parking space and finally parked in the parking space.

步骤S716,将车辆未到达停车位时的点云数据转换至到达停车位时的点云数据所在的坐标系中。Step S716, converting the point cloud data when the vehicle does not arrive at the parking space into the coordinate system where the point cloud data when the vehicle arrives at the parking space is located.

具体实施时,该过程可以利用ICP算法实现不同坐标系间点云数据的转换。During specific implementation, the process can use the ICP algorithm to realize the conversion of point cloud data between different coordinate systems.

步骤S718,将转换后得到的点云集合确定为车辆点云模型。Step S718, determining the converted point cloud set as the vehicle point cloud model.

步骤S714~S718中是利用激光雷达扫描运动中的车辆,这种方式可使激光束射到车辆车身的更多区域,相应的,所获得的点云数据能体现车辆车身的更多区域,所获得的车辆点云模型也能体现车辆车身的更多区域,进而更好地体现车辆整个车身的位置,满足ICP算法的需要,提高计算结果的准确性。In steps S714-S718, the laser radar is used to scan the moving vehicle. In this way, the laser beam can reach more areas of the vehicle body. Correspondingly, the obtained point cloud data can reflect more areas of the vehicle body, so The obtained vehicle point cloud model can also reflect more areas of the vehicle body, thereby better reflecting the position of the entire vehicle body, meeting the needs of the ICP algorithm, and improving the accuracy of the calculation results.

步骤S800,车辆控制器根据待停车辆的点云集合与车辆点云模型之间的旋转矩阵和平移矩阵,实时控制待停车辆的行驶方向和速度,最终使待停车辆停止在停车位。Step S800, the vehicle controller controls the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model, and finally stops the vehicle to be parked in the parking space.

在一些实施例中,车辆控制器通过控制待停车辆的转向系统、油门控制系统和制动系统来达到实时控制待停车辆的行驶方向和速度的目的。In some embodiments, the vehicle controller achieves real-time control of the driving direction and speed of the vehicle to be parked by controlling the steering system, accelerator control system and braking system of the vehicle to be parked.

由于待停车辆的点云集合与车辆点云模型之间的旋转矩阵和平移矩阵分别是行驶中的待停车辆到停车位的旋转量和平移量,因此,根据实时计算得到的旋转矩阵和平移矩阵,即可实时控制待停车辆的行驶方向和速度,使待停车辆驶入停车位。Since the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model are the rotation and translation of the vehicle to be parked in motion to the parking space, respectively, the rotation matrix and translation matrix obtained by real-time calculation The matrix can control the driving direction and speed of the vehicle to be parked in real time, so that the vehicle to be parked can enter the parking space.

在一些实施例中,步骤S600中,车辆控制器在控制待停车辆的行驶方向和速度的过程中,除了考虑待停车辆的点云集合与车辆点云模型之间的旋转矩阵和平移矩阵,还考虑了停车位周边的障碍物(例如相邻停车位上静止的车辆),以确保待停车辆的停车过程安全顺利。In some embodiments, in step S600, in the process of controlling the driving direction and speed of the vehicle to be parked, the vehicle controller, in addition to considering the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model, Obstacles around the parking spaces (such as stationary vehicles in adjacent parking spaces) are also taken into consideration to ensure a safe and smooth parking process for the vehicles to be parked.

本申请实施例提出的停车控制方法中,由于车辆点云模型是通过对精准停止在停车位的车辆扫描得到的点云集合,因此根据旋转矩阵和平移矩阵控制待停车辆的行驶方向和速度,相当于将车辆点云模型作为目标,通过对待停车辆的点云集合进行旋转和平移操作使其与车辆点云模型重合,达到待停车辆精准停止在停车位的目的。本申请实施例提出的停车控制方法具有自动化程度高,精度高等优点,适用于在自动上锁式停车位、交叉式停车位、多层式停车位等多种类型的停车位中应用,有利于解决停车不标准导致的车辆倾斜(轮胎、车门等部件容易受损)、离相邻停车位太近(车门打不开)、驶离停车位困难(耗时长,需要相邻停车位挪车)等问题。In the parking control method proposed in the embodiment of the present application, since the vehicle point cloud model is a collection of point clouds obtained by scanning the vehicle accurately parked in the parking space, the driving direction and speed of the vehicle to be parked are controlled according to the rotation matrix and translation matrix, It is equivalent to taking the vehicle point cloud model as the target, and performing rotation and translation operations on the point cloud collection of the vehicle to be parked so that it coincides with the vehicle point cloud model, so as to achieve the purpose of accurately stopping the vehicle to be parked in the parking space. The parking control method proposed in the embodiment of the present application has the advantages of high degree of automation and high precision, and is suitable for application in various types of parking spaces such as automatic locking parking spaces, cross parking spaces, and multi-storey parking spaces. Solve the vehicle tilt caused by non-standard parking (tires, doors and other components are easily damaged), too close to the adjacent parking space (the door cannot be opened), and it is difficult to drive away from the parking space (it takes a long time, and the car needs to be moved in the adjacent parking space) And other issues.

基于相同的发明思想,本申请实施例提供一种应用于主控器的停车控制方法,如图7所示,包括:Based on the same inventive idea, the embodiment of the present application provides a parking control method applied to the main controller, as shown in FIG. 7 , including:

步骤A100,接收车辆控制器发送的待停车辆请求停车的消息;Step A100, receiving the message that the vehicle to be parked requests parking sent by the vehicle controller;

步骤A200,确定一停车位并将所述停车位的标识发送给所述车辆控制器,以使所述车辆控制器控制所述待停车辆驶向所述停车位;Step A200, determining a parking space and sending the identification of the parking space to the vehicle controller, so that the vehicle controller controls the vehicle to be parked to drive towards the parking space;

步骤A300,获取激光雷达扫描得到的所述停车位对应的预定监控区域的点云数据;所述预定监控区域包括所述停车位和可进入所述停车位的预设区域;Step A300, obtaining the point cloud data of the predetermined monitoring area corresponding to the parking space obtained by the laser radar scanning; the predetermined monitoring area includes the parking space and a preset area that can enter the parking space;

步骤A400,对所述点云数据聚类得到所述待停车辆的点云集合;Step A400, clustering the point cloud data to obtain a point cloud set of the vehicle to be parked;

步骤A500,利用迭代最近点ICP算法对所述待停车辆的点云集合和车辆点云模型进行计算,得到所述待停车辆的点云集合与所述车辆点云模型之间的旋转矩阵和平移矩阵;其中,所述车辆点云模型是预先利用激光雷达扫描在所述停车位停止的车辆得到的点云集合;Step A500, using the iterative closest point ICP algorithm to calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model, and obtain the rotation matrix and sum of the point cloud set of the vehicle to be parked and the vehicle point cloud model A translation matrix; wherein, the vehicle point cloud model is a collection of point clouds obtained by scanning the vehicles stopped in the parking space by laser radar in advance;

步骤A600,发送所述旋转矩阵和平移矩阵,以使所述车辆控制器根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度并最终停止在所述停车位。Step A600, sending the rotation matrix and translation matrix, so that the vehicle controller can control the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and translation matrix, and finally stop at the parking space.

在一些实施例中,接收车辆控制器发送的待停车辆请求停车的消息,包括:通过车联万物V2X设备接收车辆控制器广播的待停车辆请求停车的消息。In some embodiments, receiving the parking request message sent by the vehicle controller includes: receiving the parking request message broadcast by the vehicle controller through the V2X device.

在一些实施例中,确定一停车位之前,还包括:从所述消息中解析出通信连接标识;通过所述通信连接标识与所述车辆控制器建立通信连接。In some embodiments, before determining a parking space, the method further includes: parsing out a communication connection identifier from the message; establishing a communication connection with the vehicle controller through the communication connection identifier.

在一些实施例中,所述通信连接标识包括所述车辆控制器的MAC地址、所述车辆控制器连接的车联万物V2X通信设备的MAC地址中的一种或两种。In some embodiments, the communication connection identifier includes one or both of the MAC address of the vehicle controller and the MAC address of the V2X communication device connected to the vehicle controller.

在一些实施例中,确定一停车位,包括:从预设的多个停车位中确定一空闲的停车位。In some embodiments, determining a parking space includes: determining an idle parking space from a plurality of preset parking spaces.

在一些实施例中,所述停车位的标识包括:所述停车位的编号和/或位置信息。In some embodiments, the identification of the parking space includes: the number and/or location information of the parking space.

在一些实施例中,每个激光雷达只用于扫描一个停车位对应的预定监控区域,每个主控器只用于获取一个激光雷达扫描得到的点云数据。In some embodiments, each lidar is only used to scan a predetermined monitoring area corresponding to a parking space, and each main controller is only used to acquire point cloud data scanned by one lidar.

在一些实施例中,每个激光雷达用于扫描至少两个停车位对应的预定监控区域,每个主控器只用于获取一个激光雷达扫描得到的点云数据。In some embodiments, each lidar is used to scan predetermined monitoring areas corresponding to at least two parking spaces, and each main controller is only used to acquire point cloud data scanned by one lidar.

在一些实施例中,每个激光雷达只用于扫描一个停车位对应的预定监控区域,每个主控器用于获取至少两个激光雷达扫描得到的点云数据。In some embodiments, each laser radar is only used to scan a predetermined monitoring area corresponding to a parking space, and each main controller is used to acquire point cloud data scanned by at least two laser radars.

在一些实施例中,每个激光雷达用于扫描至少两个停车位对应的预定监控区域,每个主控器用于获取至少两个激光雷达扫描得到的点云数据。In some embodiments, each lidar is used to scan predetermined monitoring areas corresponding to at least two parking spaces, and each main controller is used to acquire point cloud data scanned by at least two lidars.

在一些实施例中,获取激光雷达扫描得到的所述停车位对应的预定监控区域的点云数据,包括:In some embodiments, obtaining the point cloud data of the predetermined monitoring area corresponding to the parking space obtained by the laser radar scanning includes:

确定用于扫描所述停车位对应的预定监控区域的激光雷达;Determining the laser radar used to scan the predetermined monitoring area corresponding to the parking space;

获取该激光雷达扫描得到的点云数据。Obtain the point cloud data scanned by the lidar.

在一些实施例中,获取激光雷达扫描得到的所述停车位对应的预定监控区域的点云数据,还包括:In some embodiments, obtaining the point cloud data of the predetermined monitoring area corresponding to the parking space obtained by scanning the lidar further includes:

判断该激光雷达的扫描范围大于所述停车位对应的预定监控区域时,对该激光雷达扫描得到的点云数据进行预处理,以得到所述停车位对应的预定监控区域的点云数据。When it is judged that the scanning range of the laser radar is larger than the predetermined monitoring area corresponding to the parking space, preprocessing is performed on the point cloud data scanned by the laser radar to obtain the point cloud data of the predetermined monitoring area corresponding to the parking space.

在一些实施例中,对所述点云数据聚类得到所述待停车辆的点云集合,包括:In some embodiments, the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, including:

对所述点云数据聚类得到一个或多个车辆的点云集合,将所述一个或多个车辆的点云集合中对应于行驶状态的车辆的点云集合确定为所述待停车辆的点云集合。Clustering the point cloud data to obtain a point cloud set of one or more vehicles, and determining the point cloud set of the vehicle corresponding to the driving state in the point cloud set of one or more vehicles as the vehicle to be parked Collection of point clouds.

在一些实施例中,对所述点云数据聚类得到所述待停车辆的点云集合,包括:In some embodiments, the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, including:

从所述消息中解析出所述待停车辆的车载定位设备采集的定位数据;Analyzing the positioning data collected by the on-board positioning device of the vehicle to be parked from the message;

对所述点云数据聚类得到一个或多个车辆的点云集合,将所述一个或多个车辆的点云集合中包含所述定位数据的点云集合确定为所述待停车辆的点云集合。Clustering the point cloud data to obtain point cloud collections of one or more vehicles, and determining the point cloud collections containing the positioning data in the point cloud collections of one or more vehicles as the points of the vehicle to be parked Cloud collection.

在一些实施例中,对所述点云数据聚类得到所述待停车辆的点云集合,包括:In some embodiments, the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, including:

从所述消息中解析出所述待停车辆的车载定位设备采集的定位数据;Analyzing the positioning data collected by the on-board positioning device of the vehicle to be parked from the message;

在所述点云数据中截取所述定位数据对应的位置及其周围预设长度内的区域所对应的点云数据,并对截取的点云数据聚类得到所述待停车辆的点云集合。Intercepting the point cloud data corresponding to the position corresponding to the positioning data and the area within the preset length around it from the point cloud data, and clustering the intercepted point cloud data to obtain the point cloud set of the vehicle to be parked .

在一些实施例中,对所述点云数据聚类得到所述待停车辆的点云集合,包括:In some embodiments, the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, including:

从所述消息中解析所述待停车辆所处车道的编号;Parsing the number of the lane where the vehicle to be parked is located from the message;

根据所述待停车辆所处车道的编号,以及已知的各个车道与所述激光雷达的相对位置,在所述点云数据中截取所述待停车辆所处车道的点云数据;According to the number of the lane where the vehicle to be parked is located, and the known relative positions of each lane and the lidar, intercept the point cloud data of the lane where the vehicle to be parked is located in the point cloud data;

对所述点云数据聚类得到一个或多个车辆的点云集合;Clustering the point cloud data to obtain point cloud collections of one or more vehicles;

将所述一个或多个车辆的点云集合中与所述待停车辆所处车道的点云数据存在交集的点云集合确定为所述待停车辆的点云集合。Determining, among the point cloud sets of the one or more vehicles, the point cloud sets that intersect with the point cloud data of the lane where the vehicle to be parked is located, as the point cloud set of the vehicle to be parked.

在一些实施例中,对所述点云数据聚类得到所述待停车辆的点云集合,包括:In some embodiments, the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, including:

从所述消息中解析所述待停车辆所处车道的编号;Parsing the number of the lane where the vehicle to be parked is located from the message;

根据所述待停车辆所处车道的编号,以及已知的各个车道与所述激光雷达的相对位置,在所述点云数据中截取所述待停车辆所处车道的点云数据,并对截取的点云数据聚类得到所述待停车辆的点云集合。According to the number of the lane where the vehicle to be parked is located, and the known relative positions of each lane and the lidar, the point cloud data of the lane where the vehicle to be parked is intercepted from the point cloud data, and The intercepted point cloud data is clustered to obtain the point cloud set of the vehicle to be parked.

在一些实施例中,对所述点云数据聚类得到所述待停车辆的点云集合,包括:In some embodiments, the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, including:

从所述消息中解析所述待停车辆的车载定位设备采集的定位数据和所述待停车辆所处车道的编号;Parsing the positioning data collected by the vehicle-mounted positioning device of the vehicle to be parked and the number of the lane where the vehicle to be parked is located from the message;

根据所述待停车辆所处车道的编号,以及已知的各个车道与所述激光雷达的相对位置,在所述点云数据中截取所述待停车辆所处车道的点云数据;According to the number of the lane where the vehicle to be parked is located, and the known relative positions of each lane and the lidar, intercept the point cloud data of the lane where the vehicle to be parked is located in the point cloud data;

对所述点云数据聚类得到一个或多个车辆的点云集合,将所述一个或多个车辆的点云集合中包含所述定位数据且与所述待停车辆所处车道的点云数据存在交集的点云集合确定为所述待停车辆的点云集合。Clustering the point cloud data to obtain point cloud collections of one or more vehicles, including the positioning data in the point cloud collections of the one or more vehicles and matching the point cloud of the lane where the vehicle to be parked The set of point clouds whose data intersects is determined as the set of point clouds of the vehicle to be parked.

在一些实施例中,利用ICP算法对所述待停车辆的点云集合和车辆点云模型进行计算,包括:In some embodiments, the point cloud collection and the vehicle point cloud model of the vehicle to be parked are calculated using the ICP algorithm, including:

确定所述待停车辆的车辆型号;Determine the vehicle model of the vehicle to be parked;

在模型库中选择与所述待停车辆的车辆型号相匹配的车辆点云模型;Select the vehicle point cloud model matching the vehicle model of the vehicle to be parked in the model library;

利用ICP算法对所述待停车辆的点云集合和与所述待停车辆的车辆型号相匹配的车辆点云模型进行计算;其中,所述模型库包括预先利用激光雷达对在所述停车位停车的多个不同车辆型号的车辆扫描所得到的多个车辆点云模型。Use the ICP algorithm to calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model that matches the vehicle model of the vehicle to be parked; Multiple vehicle point cloud models obtained from vehicle scans of multiple different vehicle models parked.

在一些实施例中,确定所述待停车辆的车辆型号,包括:从所述消息中解析出所述待停车辆的车辆型号。In some embodiments, determining the vehicle model of the vehicle to be parked includes: parsing out the vehicle model of the vehicle to be parked from the message.

在一些实施例中,确定所述待停车辆的车辆型号,包括:从所述消息中解析出所述待停车辆的车辆标识,并根据已知的车辆标识与车辆型号的对应关系来确定所述待停车辆的车辆型号。In some embodiments, determining the vehicle model of the vehicle to be parked includes: parsing the vehicle identification of the vehicle to be parked from the message, and determining the corresponding relationship between the vehicle identification and the vehicle model. State the vehicle model of the vehicle to be parked.

在一些实施例中,本申请实施例提供的应用于主控器的停车控制方法,还包括:In some embodiments, the parking control method applied to the main controller provided in the embodiment of the present application further includes:

判断所述模型库中是否包含与所述待停车辆的车辆型号相匹配的车辆点云模型;Judging whether the model library contains a vehicle point cloud model matching the vehicle model of the vehicle to be parked;

若不包含,则从所述模型库中选取一个已有的车辆点云模型确定为与所述待停车辆的车辆型号相匹配的车辆点云模型,并在所述待停车辆停止在所述停车位之后,利用所述激光雷达扫描所述待停车辆并将扫描得到的点云集合存入所述模型库中。If it does not contain, then select an existing vehicle point cloud model from the model library to be determined as a vehicle point cloud model that matches the vehicle model of the vehicle to be parked, and when the vehicle to be parked stops at the After the parking space, the lidar is used to scan the vehicle to be parked, and the scanned point cloud set is stored in the model library.

在一些实施例中,利用ICP算法对所述待停车辆的点云集合和车辆点云模型进行计算,得到所述待停车辆的点云集合与所述车辆点云模型之间的旋转矩阵和平移矩阵,包括:In some embodiments, the point cloud set of the vehicle to be parked and the vehicle point cloud model are calculated using the ICP algorithm to obtain the rotation matrix and the rotation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model Translation matrix, including:

确定第一平均中心和第二平均中心,其中,所述第一平均中心的坐标为所述待停车辆的点云集合中位于所述待停车辆的行驶方向上最前方的预设数量个点的坐标的平均值;所述第二平均中心的坐标为所述车辆点云模型中位于所述待停车辆的行驶方向上最前方的所述预设数量个点的坐标的平均值;Determining a first average center and a second average center, wherein the coordinates of the first average center are a preset number of points in the point cloud set of the vehicle to be parked that are located at the forefront in the direction of travel of the vehicle to be parked The average value of the coordinates of the second average center; the coordinates of the second average center are the average value of the coordinates of the preset number of points located at the forefront in the direction of travel of the vehicle to be parked in the vehicle point cloud model;

确定初始旋转矩阵,所述初始旋转矩阵为所述第一平均中心旋转到所述第二平均中心所用的矩阵;determining an initial rotation matrix, where the initial rotation matrix is the matrix used to rotate the first mean center to the second mean center;

确定初始平移矩阵,所述初始平移矩阵为所述第一平均中心平移到所述第二平均中心所用的矩阵;determining an initial translation matrix, where the initial translation matrix is a matrix used to translate the first average center to the second average center;

利用所述初始旋转矩阵和所述初始平移矩阵,对所述待停车辆的点云集合和所述车辆点云模型进行迭代计算,得到所述待停车辆的点云集合与所述车辆点云模型之间的旋转矩阵和平移矩阵。Using the initial rotation matrix and the initial translation matrix, iteratively calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model to obtain the point cloud set of the vehicle to be parked and the vehicle point cloud Rotation matrix and translation matrix between models.

在一些实施例中,利用ICP算法对所述待停车辆的点云集合和车辆点云模型进行计算,得到所述待停车辆的点云集合与所述车辆点云模型之间的旋转矩阵和平移矩阵,包括:In some embodiments, the point cloud set of the vehicle to be parked and the vehicle point cloud model are calculated using the ICP algorithm to obtain the rotation matrix and the rotation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model Translation matrix, including:

从所述消息中解析所述待停车辆的车载定位设备采集的定位数据;Analyzing the positioning data collected by the on-board positioning device of the vehicle to be parked from the message;

确定初始旋转矩阵,所述初始旋转矩阵为所述定位数据对应的点旋转到参考定位点所用的矩阵,所述参考定位点为确定车辆点云模型的过程中的车辆停止在所述停车位时其车载定位设备获取的定位数据对应的点;Determine an initial rotation matrix, the initial rotation matrix is the matrix used by the point corresponding to the positioning data to rotate to a reference positioning point, and the reference positioning point is when the vehicle stops in the parking space during the process of determining the vehicle point cloud model The points corresponding to the positioning data acquired by the vehicle positioning equipment;

确定初始平移矩阵,所述初始平移矩阵为所述定位数据对应的点平移到所述参考定位点所用的矩阵;determining an initial translation matrix, where the initial translation matrix is a matrix used to translate the point corresponding to the positioning data to the reference positioning point;

利用所述初始旋转矩阵和所述初始平移矩阵,对所述待停车辆的点云集合和所述车辆点云模型进行迭代计算,得到所述待停车辆的点云集合与所述车辆点云模型之间的旋转矩阵和平移矩阵。Using the initial rotation matrix and the initial translation matrix, iteratively calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model to obtain the point cloud set of the vehicle to be parked and the vehicle point cloud Rotation matrix and translation matrix between models.

在一些实施例中,所述车辆点云模型按照如下方式确定:In some embodiments, the vehicle point cloud model is determined as follows:

预先利用激光雷达扫描驶向所述停车位并最终在所述停车位停车的车辆;Using lidar to scan in advance the vehicles driving towards the parking space and finally parking in the parking space;

将所述车辆未到达所述停车位时的点云数据转换至到达所述停车位时的点云数据所在的坐标系中;Converting the point cloud data when the vehicle does not arrive at the parking space into the coordinate system where the point cloud data when the vehicle arrives at the parking space;

将转换后得到的点云集合确定为所述车辆点云模型。The converted point cloud set is determined as the vehicle point cloud model.

图7所示的应用于主控器的停车控制方法与图2所示的停车控制方法基于相同的发明思想实现,且有相同的非限制性实施方式,具体可参照前述对图2所示的停车控制方法的介绍,此处不再赘述。The parking control method applied to the main controller shown in FIG. 7 is realized based on the same inventive idea as the parking control method shown in FIG. 2 , and has the same non-limiting implementation. The introduction of the parking control method will not be repeated here.

基于相同的发明思想,本申请还提供一种应用于车辆控制器的停车控制方法,如图8所示,包括:Based on the same inventive idea, the present application also provides a parking control method applied to a vehicle controller, as shown in FIG. 8 , including:

步骤B100,发送待停车辆请求停车的消息;Step B100, sending a message that the vehicle to be parked requests parking;

步骤B200,接收主控器返回的停车位的标识,并控制所述待停车辆驶向所述停车位;Step B200, receiving the identification of the parking space returned by the main controller, and controlling the vehicle to be parked to drive towards the parking space;

步骤B300,接收主控器返回的待停车辆的点云集合和车辆点云模型之间的旋转矩阵和平移矩阵;其中,车辆点云模型是利用预先利用激光雷达扫描在所述停车位停止的车辆得到的点云集合;Step B300, receiving the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model returned by the main controller; wherein, the vehicle point cloud model is stopped in the parking space by using the laser radar scan in advance The point cloud collection obtained by the vehicle;

步骤B400,根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度,以使所述待停车辆最终停止在所述停车位。Step B400, control the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and translation matrix, so that the vehicle to be parked finally stops in the parking space.

在一些实施例中,发送待停车辆请求在停车位停车的消息,包括:通过车联万物V2X设备广播待停车辆请求在停车位停车的消息。In some embodiments, sending the message that the vehicle to be parked requests to park in the parking space includes: broadcasting the message that the vehicle to be parked requests to park in the parking space through the V2X device of the Internet of Things.

在一些实施例中,所述消息中包含如下信息中的任意一项或多项:In some embodiments, the message contains any one or more of the following information:

所述待停车辆的车辆标识;the vehicle identification of the vehicle to be parked;

所述待停车辆的车辆型号;the vehicle model of the vehicle to be parked;

所述待停车辆的车载定位设备采集的定位数据;The positioning data collected by the on-board positioning equipment of the vehicle to be parked;

通信连接标识。Communication connection identification.

在一些实施例中,所述通信连接标识包括所述车辆控制器的MAC地址、所述车辆控制器连接的车联万物V2X通信设备的MAC地址中的一种或两种。In some embodiments, the communication connection identifier includes one or both of the MAC address of the vehicle controller and the MAC address of the V2X communication device connected to the vehicle controller.

在一些实施例中,发送待停车辆请求停车的消息,包括:In some embodiments, sending a message that the vehicle to be parked requests parking includes:

判断所述待停车辆进入停车场之后发出所述消息;或,Sending the message after judging that the vehicle to be parked enters the parking lot; or,

接收到预设的触发信号之后发出所述消息。The message is sent after receiving a preset trigger signal.

在一些实施例中,根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度,包括:根据所述旋转矩阵和平移矩阵,通过控制所述待停车辆的转向系统、油门控制系统和制动系统来实时控制所述待停车辆的行驶方向和速度。In some embodiments, controlling the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and translation matrix includes: controlling the steering system and accelerator of the vehicle to be parked according to the rotation matrix and translation matrix The control system and the braking system are used to control the driving direction and speed of the vehicle to be stopped in real time.

图8所示的应用于车辆控制器的停车控制方法与图2所示的停车控制方法基于相同的发明思想实现,且有相同的非限制性实施方式,具体可参照前述对图2所示的停车控制方法的介绍,此处不再赘述。The parking control method applied to the vehicle controller shown in FIG. 8 is realized based on the same inventive concept as the parking control method shown in FIG. 2 , and has the same non-limiting implementation. The introduction of the parking control method will not be repeated here.

基于相同的发明思想,本申请实施例还提供一种计算机可读的存储介质,其上存储有计算机程序,该计算机程序被处理器运行时本申请实施例提供的应用于主控器的停车控制方法中的各个步骤。该计算机可读的存储介质例如可以但不限于是电、磁、光、电磁、红外线、或半导体的系统、装置或器件,或者任意以上的组合。在一些实施例中,该计算机可读的存储介质可以是:具有一个或多个导线的电连接、便携式盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。Based on the same inventive idea, the embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by the processor, the parking control provided by the embodiment of the present application is applied to the master steps in the method. The computer-readable storage medium may be, for example but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. In some embodiments, the computer readable storage medium may be: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read only memory (ROM), an erasable Programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.

基于相同的发明思想,本申请实施例还提供一种计算机可读的存储介质,其上存储有计算机程序,该计算机程序被处理器运行时本申请实施例提供的应用于车辆控制器的停车控制方法中的各个步骤。该计算机可读的存储介质例如可以但不限于是电、磁、光、电磁、红外线、或半导体的系统、装置或器件,或者任意以上的组合。在一些实施例中,该计算机可读的存储介质可以是:具有一个或多个导线的电连接、便携式盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。Based on the same inventive idea, the embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is run by the processor, the parking control provided by the embodiment of the present application is applied to the vehicle controller. steps in the method. The computer-readable storage medium may be, for example but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. In some embodiments, the computer readable storage medium may be: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read only memory (ROM), an erasable Programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.

示例性设备exemplary device

基于相同的发明思想,本申请实施例还提供一种主控器,该主控器包括第一处理器、第一存储器及存储在第一存储器上并可在第一处理器上运行的计算机程序,第一处理器在运行计算机程序时,执行图7的应用于主控器的停车控制方法。Based on the same inventive concept, the embodiment of the present application also provides a master controller, which includes a first processor, a first memory, and a computer program stored in the first memory and operable on the first processor , the first processor executes the parking control method applied to the main controller in FIG. 7 when running the computer program.

第一存储器中的计算机程序被运行时所执行的方法与图2所示的停车控制方法基于相同的发明思想实现,且有相同的非限制性实施方式,具体可参照前面示例性方法中对图2所示的停车控制方法的介绍,此处不再赘述。The method executed when the computer program in the first memory is executed is based on the same inventive concept as the parking control method shown in FIG. The introduction of the parking control method shown in 2 will not be repeated here.

可选地,本申请中,第一处理器可以通过电路、芯片或其他电子部件来实现。例如,第一处理器还可以包括一个或多个微控制器、一个或多个现场可编程门阵列(FPGA)、一个或多个专用电路(ASIC)、一个或多个数字信号处理器(DSP)、一个或多个集成电路等。Optionally, in this application, the first processor may be implemented by a circuit, chip or other electronic components. For example, the first processor may also include one or more microcontrollers, one or more field programmable gate arrays (FPGAs), one or more application specific circuits (ASICs), one or more digital signal processors (DSP ), one or more integrated circuits, etc.

可选地,本申请中,第一存储器可以通过电路、芯片或其他电子部件来实现。例如,第一存储器可以包括一个或多个只读存储器(ROM)、随机存取存储器(RAM)、闪速存储器、电可编程存储器(EPROM)、电可编程和可擦除存储器(EEPROM)、嵌入式多媒体卡(eMMC)、硬盘驱动器或任何易失性或非易失性介质等。Optionally, in this application, the first memory may be implemented by a circuit, chip or other electronic components. For example, the first memory may include one or more of read only memory (ROM), random access memory (RAM), flash memory, electrically programmable memory (EPROM), electrically programmable and erasable memory (EEPROM), Embedded Multimedia Card (eMMC), hard drive or any volatile or non-volatile media, etc.

本申请实施例中,主控器可以是工控机、服务器、PC机、便携式电脑、平板电脑、PDA、iMac等形式的计算机设备。In the embodiment of the present application, the main controller may be computer equipment in the form of industrial computer, server, PC, portable computer, tablet computer, PDA, iMac, and the like.

基于相同的发明思想,本申请实施例还提供一种车辆控制器,该车辆控制器包括第二处理器、第二存储器及存储在第二存储器上并可在第二处理器上运行的计算机程序,第二处理器在运行计算机程序时,执行图8的应用于车辆控制器的停车控制方法。Based on the same inventive idea, the embodiment of the present application also provides a vehicle controller, which includes a second processor, a second memory, and a computer program stored in the second memory and operable on the second processor , the second processor executes the parking control method applied to the vehicle controller in FIG. 8 when running the computer program.

第二存储器中的计算机程序被运行时所执行的方法与图2所示的停车控制方法基于相同的发明思想实现,且有相同的非限制性实施方式,具体可参照前面示例性方法中对图2所示的停车控制方法的介绍,此处不再赘述。The method executed when the computer program in the second memory is executed is based on the same inventive concept as the parking control method shown in FIG. The introduction of the parking control method shown in 2 will not be repeated here.

可选地,本申请中,第二处理器可以通过电路、芯片或其他电子部件来实现。例如,第二处理器还可以包括一个或多个微控制器、一个或多个现场可编程门阵列(FPGA)、一个或多个专用电路(ASIC)、一个或多个数字信号处理器(DSP)、一个或多个集成电路等。Optionally, in this application, the second processor may be implemented by a circuit, chip or other electronic components. For example, the second processor may also include one or more microcontrollers, one or more field programmable gate arrays (FPGAs), one or more application specific circuits (ASICs), one or more digital signal processors (DSP ), one or more integrated circuits, etc.

可选地,本申请中,第二存储器可以通过电路、芯片或其他电子部件来实现。例如,第二存储器可以包括一个或多个只读存储器(ROM)、随机存取存储器(RAM)、闪速存储器、电可编程存储器(EPROM)、电可编程和可擦除存储器(EEPROM)、嵌入式多媒体卡(eMMC)、硬盘驱动器或任何易失性或非易失性介质等。Optionally, in this application, the second memory may be implemented by circuits, chips or other electronic components. For example, the secondary memory may include one or more of read only memory (ROM), random access memory (RAM), flash memory, electrically programmable memory (EPROM), electrically programmable and erasable memory (EEPROM), Embedded Multimedia Card (eMMC), hard drive or any volatile or non-volatile media, etc.

本申请实施例中,车辆控制器可以是DSP(Digital Signal Processing,数字信号处理器)、FPGA(Field-Programmable Gate Array,现场可编程门阵列)控制器、工业电脑、行车电脑、ECU(Electronic Control Unit,电子控制单元)、ARM或者VCU(Vehicle ControlUnit,整车控制器)等,本申请对此不做具体限定。In the embodiment of the present application, the vehicle controller can be DSP (Digital Signal Processing, digital signal processor), FPGA (Field-Programmable Gate Array, field programmable gate array) controller, industrial computer, driving computer, ECU (Electronic Control Unit, electronic control unit), ARM or VCU (Vehicle Control Unit, vehicle controller), etc., which are not specifically limited in this application.

基于相同的发明思想,本申请实施例还提供一种汽车,如图9所示,该汽车上装设有车辆控制器。其中,该车辆控制器用于发送待停车辆请求停车的消息,接收主控器返回的停车位的标识,并控制待停车辆驶向该停车位;接收主控器返回的待停车辆的点云集合和车辆点云模型之间的旋转矩阵和平移矩阵;并根据所述旋转矩阵和平移矩阵实时控制待停车辆的行驶方向和速度,以使待停车辆最终停止在该停车位。Based on the same inventive idea, the embodiment of the present application also provides a car, as shown in FIG. 9 , the car is equipped with a vehicle controller. Wherein, the vehicle controller is used to send the message that the vehicle to be parked requests parking, receive the identification of the parking space returned by the main controller, and control the vehicle to be parked to drive to the parking space; receive the point cloud of the vehicle to be parked returned by the main controller A rotation matrix and a translation matrix between the set and the vehicle point cloud model; and control the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and the translation matrix, so that the vehicle to be parked finally stops at the parking space.

在一些实施例中,该车辆控制器连接汽车的转向系统、油门控制系统和制动系统。即,车辆控制器通过控制汽车的转向系统、油门控制系统和制动系统间接达到实时控制待停车辆的行驶方向和速度的目的。In some embodiments, the vehicle controller is connected to the vehicle's steering system, throttle control system and braking system. That is, the vehicle controller indirectly achieves the purpose of real-time control of the driving direction and speed of the vehicle to be parked by controlling the steering system, accelerator control system and braking system of the vehicle.

在一些实施例中,该汽车上还装设有与该车辆控制器连接的车联万物V2X设备。In some embodiments, the car is also equipped with a V2X device connected to the vehicle controller.

该汽车可以是由人类驾驶的传统车辆(如家用轿车、工程车、消防车、救护车、车辆等),也可以是自动驾驶车,可以是消耗汽油、柴油等传统能源的车辆,也可以是消耗电能、太阳能等新能源的车辆。其中,自动驾驶车是指利用自动驾驶技术实现的具有载人(如家用轿车、公共汽车等类型)、载货(如普通货车、厢式货车、封闭货车、罐式货车、平板货车、集装厢车、自卸货车、特殊结构货车等类型)或者特殊救援功能(如消防车、救护车等类型)的车辆。The car can be a traditional vehicle driven by humans (such as a family car, engineering vehicle, fire engine, ambulance, vehicle, etc.), or it can be a self-driving car, which can be a vehicle that consumes traditional energy such as gasoline and diesel, or it can be a Vehicles that consume new energy sources such as electric energy and solar energy. Among them, the self-driving vehicle refers to the vehicle that uses self-driving technology to carry people (such as family cars, buses, etc.), cargo (such as ordinary trucks, vans, closed trucks, tank trucks, flatbed Vans, dump trucks, trucks with special structures, etc.) or vehicles with special rescue functions (such as fire trucks, ambulances, etc.).

示例性系统exemplary system

基于相同的发明思想,本申请实施例还提供一种停车控制系统,如图10所示,包括:主控器,车辆控制器,以及激光雷达。Based on the same inventive concept, the embodiment of the present application also provides a parking control system, as shown in FIG. 10 , including: a main controller, a vehicle controller, and a laser radar.

该停车控制系统的工作原理可参考如图2所示的停车控制方法,此处不再赘述。For the working principle of the parking control system, reference may be made to the parking control method shown in FIG. 2 , which will not be repeated here.

该停车控制系统中,激光雷达可以选用16线、32线或64线型,激光线束越多,扫描得到的点云数据就越容易覆盖被扫车辆的整个车身,相应的,成本也会越高;主控器和车辆控制器的硬件组成结构已在示例性设备中进行了描述,此处不再赘述;In the parking control system, the laser radar can be 16-line, 32-line or 64-line. The more laser beams, the easier it is for the scanned point cloud data to cover the entire body of the scanned vehicle, and the higher the cost accordingly. ; The hardware composition structure of the main controller and the vehicle controller has been described in the exemplary device, and will not be repeated here;

该停车控制系统与图2所示的停车控制方法基于相同的发明思想实现,且有相同的非限制性实施方式,具体可参照前面示例性方法中对图2所示的停车控制方法的介绍,此处不再赘述。The parking control system and the parking control method shown in FIG. 2 are implemented based on the same inventive idea, and have the same non-limiting implementation. For details, refer to the introduction of the parking control method shown in FIG. 2 in the previous exemplary method, I won't repeat them here.

为了实现激光雷达扫描预定监控区域(包括停车位和可驶入停车位的预设区域)的目的,具体实施时可以将激光雷达安装于停车场的天花板、墙上、机械设备或专业支撑架上。In order to achieve the purpose of scanning the predetermined monitoring area (including the parking space and the preset area that can be driven into the parking space) by the laser radar, the laser radar can be installed on the ceiling, wall, mechanical equipment or professional support frame of the parking lot. .

在一些实施例中,主控器可被安装于停车场的中控室内或安装于停车场的天花板、墙上、机械设备或专业支撑架上,并连接激光雷达。In some embodiments, the main controller can be installed in the central control room of the parking lot or on the ceiling, wall, mechanical equipment or professional support frame of the parking lot, and connected to the laser radar.

在一些实施例中,车辆控制器装设于待停车辆上。In some embodiments, the vehicle controller is mounted on the vehicle to be parked.

在一些实施例中,车辆控制器是装载于待停车辆以外的设备,例如是固定装设于某地的设备,或装设于任意移动设备上的设备,这些实施例中,车辆控制器通过基站、WIFI等无线通信方式控制待停车辆的转向系统、油门控制系统和制动系统,从而间接控制待停车辆停车。In some embodiments, the vehicle controller is a device installed outside the vehicle to be parked, such as a device fixedly installed in a certain place, or a device installed on any mobile device. In these embodiments, the vehicle controller passes Base station, WIFI and other wireless communication methods control the steering system, accelerator control system and braking system of the vehicle to be parked, thereby indirectly controlling the parking of the vehicle to be parked.

在一些实施例中,如图5中的(a)所示,主控器、激光雷达和预定监控区域(停车位)被设置为如下模式:每个激光雷达只用于扫描一个预定监控区域,每个主控器只用于获取一个激光雷达扫描得到的实时点云数据。In some embodiments, as shown in (a) in Figure 5, the main controller, laser radar and predetermined monitoring area (parking space) are set to the following mode: each laser radar is only used to scan a predetermined monitoring area, Each main controller is only used to obtain real-time point cloud data scanned by a lidar.

在一些实施例中,如图5中的(b)所示,主控器、激光雷达和预定监控区域被设置为如下模式:每个激光雷达用于扫描至少两个预定监控区域,每个主控器只用于获取一个激光雷达扫描得到的实时点云数据。In some embodiments, as shown in (b) in Figure 5, the main controller, the laser radar and the predetermined monitoring area are set to the following mode: each laser radar is used to scan at least two predetermined monitoring areas, each main The controller is only used to obtain real-time point cloud data obtained by a laser radar scan.

在一些实施例中,如图5中的(c)所示,主控器、激光雷达和预定监控区域被设置为如下模式:每个激光雷达只用于扫描一个预定监控区域,每个主控器用于获取至少两个激光雷达扫描得到的实时点云数据。In some embodiments, as shown in (c) in Figure 5, the main controller, laser radar and predetermined monitoring area are set to the following mode: each laser radar is only used to scan a predetermined monitoring area, each main controller The device is used to obtain real-time point cloud data obtained by at least two lidar scans.

在一些实施例中,如图5中的(d)所示,主控器、激光雷达和预定监控区域被设置为如下模式:每个激光雷达用于扫描至少两个预定监控区域,每个主控器用于获取至少两个激光雷达扫描得到的实时点云数据。In some embodiments, as shown in (d) in Figure 5, the main controller, laser radar and predetermined monitoring area are set to the following mode: each laser radar is used to scan at least two predetermined monitoring areas, each main The controller is used to obtain real-time point cloud data obtained by at least two lidar scans.

在一些实施例中,如图10所示,该停车控制系统,还包括:与主控器连接的V2X设备,以及,与车辆控制器连接的V2X设备。In some embodiments, as shown in FIG. 10 , the parking control system further includes: a V2X device connected to the main controller, and a V2X device connected to the vehicle controller.

在一些实施例中,如图10所示,该停车控制系统,还包括:用于为主控器和/或激光雷达供电的供电设备。In some embodiments, as shown in FIG. 10 , the parking control system further includes: a power supply device for powering the main controller and/or the laser radar.

在一些实施例中,该停车控制系统,还包括:用于在上述供电设备断电时为主控器和/或激光雷达供电的不间断电源UPS。In some embodiments, the parking control system further includes: an uninterruptible power supply (UPS) for supplying power to the main controller and/or the laser radar when the above-mentioned power supply equipment is powered off.

以上对本申请的目的、技术方案和有益效果进行了详细说明,所应理解的是,以上所述仅为本申请的具体实施例而已,并不用于限定本申请的保护范围,凡在本申请的精神和原则之内,所做的任何修改、等同替换、改进等,均应包含在本申请的保护范围之内。The purpose, technical solutions and beneficial effects of the application have been described in detail above. It should be understood that the above description is only a specific embodiment of the application and is not used to limit the scope of protection of the application. Within the spirit and principles, any modifications, equivalent replacements, improvements, etc., shall be included within the scope of protection of this application.

应当注意,尽管在附图中以特定顺序描述了本申请方法的操作,但是,这并非要求或者暗示必须按照该特定顺序来执行这些操作,或是必须执行全部所示的操作才能实现期望的结果。附加地或备选地,可以省略某些步骤,将多个步骤合并为一个步骤执行,和/或将一个步骤分解为多个步骤执行。It should be noted that although operations of the methods of the present application are described in a particular order in the drawings, this does not require or imply that the operations must be performed in that particular order, or that all illustrated operations must be performed to achieve the desired results . Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution.

本领域技术人员还可以了解到本申请实施例列出的各种说明性逻辑块(illustrative logical block),单元,和步骤可以通过电子硬件、电脑软件,或两者的结合进行实现。为清楚展示硬件和软件的可替换性(interchangeability),上述的各种说明性部件(illustrative components),单元和步骤已经通用地描述了它们的功能。这样的功能是通过硬件还是软件来实现取决于特定的应用和整个系统的设计要求。本领域技术人员可以对于每种特定的应用,可以使用各种方法实现所述的功能,但这种实现不应被理解为超出本申请实施例保护的范围。Those skilled in the art can also understand that various illustrative logical blocks, units, and steps listed in the embodiments of the present application can be implemented by electronic hardware, computer software, or a combination of both. To clearly demonstrate the interchangeability of hardware and software, the various illustrative components, units and steps above have generally described their functions. Whether such functions are implemented by hardware or software depends on the specific application and overall system design requirements. Those skilled in the art may use various methods to implement the described functions for each specific application, but such implementation should not be understood as exceeding the protection scope of the embodiments of the present application.

本申请实施例中所描述的各种说明性的逻辑块,或单元,或装置都可以通过通用处理器,数字信号处理器,专用集成电路(ASIC),现场可编程门阵列或其它可编程逻辑装置,离散门或晶体管逻辑,离散硬件部件,或上述任何组合的设计来实现或操作所描述的功能。通用处理器可以为微处理器,可选地,该通用处理器也可以为任何传统的处理器、控制器、微控制器或状态机。处理器也可以通过计算装置的组合来实现,例如数字信号处理器和微处理器,多个微处理器,一个或多个微处理器联合一个数字信号处理器核,或任何其它类似的配置来实现。Various illustrative logic blocks, or units, or devices described in the embodiments of the present application can be implemented by general-purpose processors, digital signal processors, application-specific integrated circuits (ASICs), field programmable gate arrays or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to implement or operate the described functions. The general-purpose processor may be a microprocessor, and optionally, the general-purpose processor may also be any conventional processor, controller, microcontroller or state machine. A processor may also be implemented by a combination of computing devices, such as a digital signal processor and a microprocessor, multiple microprocessors, one or more microprocessors combined with a digital signal processor core, or any other similar configuration to accomplish.

本申请实施例中所描述的方法或算法的步骤可以直接嵌入硬件、处理器执行的软件模块、或者这两者的结合。软件模块可以存储于RAM存储器、闪存、ROM存储器、EPROM存储器、EEPROM存储器、寄存器、硬盘、可移动磁盘、CD-ROM或本领域中其它任意形式的存储媒介中。示例性地,存储媒介可以与处理器连接,以使得处理器可以从存储媒介中读取信息,并可以向存储媒介存写信息。可选地,存储媒介还可以集成到处理器中。处理器和存储媒介可以设置于ASIC中,ASIC可以设置于用户终端中。可选地,处理器和存储媒介也可以设置于用户终端中的不同的部件中。The steps of the method or algorithm described in the embodiments of the present application may be directly embedded in hardware, a software module executed by a processor, or a combination of both. The software modules may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM or any other storage medium in the art. Exemplarily, the storage medium can be connected to the processor, so that the processor can read information from the storage medium, and can write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and the storage medium can be set in the ASIC, and the ASIC can be set in the user terminal. Optionally, the processor and the storage medium may also be set in different components in the user terminal.

在一个或多个示例性的设计中,本申请实施例所描述的上述功能可以在硬件、软件、固件或这三者的任意组合来实现。如果在软件中实现,这些功能可以存储与电脑可读的媒介上,或以一个或多个指令或代码形式传输于电脑可读的媒介上。电脑可读媒介包括电脑存储媒介和便于使得让电脑程序从一个地方转移到其它地方的通信媒介。存储媒介可以是任何通用或特殊电脑可以接入访问的可用媒体。例如,这样的电脑可读媒体可以包括但不限于RAM、ROM、EEPROM、CD-ROM或其它光盘存储、磁盘存储或其它磁性存储装置,或其它任何可以用于承载或存储以指令或数据结构和其它可被通用或特殊电脑、或通用或特殊处理器读取形式的程序代码的媒介。此外,任何连接都可以被适当地定义为电脑可读媒介,例如,如果软件是从一个网站站点、服务器或其它远程资源通过一个同轴电缆、光纤电缆、双绞线、数字用户线(DSL)或以例如红外、无线和微波等无线方式传输的也被包含在所定义的电脑可读媒介中。所述的碟片(disk)和磁盘(disc)包括压缩磁盘、镭射盘、光盘、DVD、软盘和蓝光光盘,磁盘通常以磁性复制数据,而碟片通常以激光进行光学复制数据。上述的组合也可以包含在电脑可读媒介中。In one or more exemplary designs, the above functions described in the embodiments of the present application may be implemented in hardware, software, firmware or any combination of the three. If implemented in software, the functions can be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special computer. For example, such computer-readable media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other device that can be used to carry or store instructions or data structures and Other medium of program code in a form readable by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. In addition, any connection is properly defined as a computer-readable medium, for example, if the software is transmitted from a website site, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL) Or transmitted by wireless means such as infrared, wireless and microwave are also included in the definition of computer readable media. Disks and discs include compact discs, laser discs, optical discs, DVDs, floppy discs, and Blu-ray discs. Disks usually reproduce data magnetically, while discs usually reproduce data optically with lasers. Combinations of the above can also be contained on a computer readable medium.

Claims (44)

1.一种停车控制方法,其特征在于,包括:1. A parking control method, characterized in that, comprising: 接收车辆控制器发送的待停车辆请求停车的消息;Receive the message that the vehicle to be parked requests parking sent by the vehicle controller; 确定一停车位并将所述停车位的标识发送给所述车辆控制器,以使所述车辆控制器控制所述待停车辆驶向所述停车位;determining a parking space and sending the identification of the parking space to the vehicle controller, so that the vehicle controller controls the vehicle to be parked to drive towards the parking space; 获取激光雷达扫描得到的所述停车位对应的预定监控区域的点云数据;所述预定监控区域包括所述停车位和可进入所述停车位的预设区域;Acquiring the point cloud data of the predetermined monitoring area corresponding to the parking space scanned by the laser radar; the predetermined monitoring area includes the parking space and a preset area that can enter the parking space; 对所述点云数据聚类得到所述待停车辆的点云集合;Clustering the point cloud data to obtain the point cloud set of the vehicle to be parked; 从所述消息中解析所述待停车辆的车载定位设备采集的定位数据;Analyzing the positioning data collected by the on-board positioning device of the vehicle to be parked from the message; 确定初始旋转矩阵,所述初始旋转矩阵为所述定位数据对应的点旋转到参考定位点所用的矩阵,所述参考定位点为确定车辆点云模型的过程中的车辆停止在所述停车位时其车载定位设备获取的定位数据对应的点;Determine an initial rotation matrix, the initial rotation matrix is the matrix used by the point corresponding to the positioning data to rotate to a reference positioning point, and the reference positioning point is when the vehicle stops in the parking space during the process of determining the vehicle point cloud model The points corresponding to the positioning data acquired by the vehicle positioning equipment; 确定初始平移矩阵,所述初始平移矩阵为所述定位数据对应的点平移到所述参考定位点所用的矩阵;determining an initial translation matrix, where the initial translation matrix is a matrix used to translate the point corresponding to the positioning data to the reference positioning point; 利用所述初始旋转矩阵和所述初始平移矩阵,对所述待停车辆的点云集合和所述车辆点云模型进行迭代计算,得到所述待停车辆的点云集合与所述车辆点云模型之间的旋转矩阵和平移矩阵;其中,所述车辆点云模型是预先利用激光雷达扫描在所述停车位停止的车辆得到的点云集合;Using the initial rotation matrix and the initial translation matrix, iteratively calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model to obtain the point cloud set of the vehicle to be parked and the vehicle point cloud A rotation matrix and a translation matrix between the models; wherein, the vehicle point cloud model is a collection of point clouds obtained by scanning a vehicle stopped in the parking space by laser radar in advance; 发送所述旋转矩阵和平移矩阵,以使所述车辆控制器根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度并最终停止在所述停车位。Sending the rotation matrix and translation matrix, so that the vehicle controller controls the driving direction and speed of the vehicle to be parked in real time according to the rotation matrix and translation matrix, and finally stops at the parking space. 2.根据权利要求1所述的停车控制方法,其特征在于,接收车辆控制器发送的待停车辆请求停车的消息,包括:通过车联万物V2X设备接收车辆控制器广播的待停车辆请求停车的消息。2. The parking control method according to claim 1, characterized in that receiving the message that the vehicle to be parked requesting parking sent by the vehicle controller comprises: receiving the vehicle controller's request to park the vehicle to be parked broadcasted by the vehicle controller through the V2X device news. 3.根据权利要求1所述的停车控制方法,其特征在于,确定一停车位之前,还包括:从所述消息中解析出通信连接标识;通过所述通信连接标识与所述车辆控制器建立通信连接。3. The parking control method according to claim 1, wherein, before determining a parking space, further comprising: parsing out a communication connection identifier from the message; establishing a communication connection identifier with the vehicle controller through the communication connection identifier communication connection. 4.根据权利要求1所述的停车控制方法,其特征在于,所述通信连接标识包括所述车辆控制器的MAC地址、所述车辆控制器连接的车联万物V2X通信设备的MAC地址中的一种或两种。4. The parking control method according to claim 1, wherein the communication connection identification includes the MAC address of the vehicle controller and the MAC address of the V2X communication device connected to the vehicle controller. one or two. 5.根据权利要求1所述的停车控制方法,其特征在于,确定一停车位,包括:从预设的多个停车位中确定一空闲的停车位。5. The parking control method according to claim 1, wherein determining a parking space comprises: determining an idle parking space from a plurality of preset parking spaces. 6.根据权利要求1所述的停车控制方法,其特征在于,所述停车位的标识包括:所述停车位的编号和/或位置信息。6. The parking control method according to claim 1, wherein the identification of the parking space comprises: the number and/or location information of the parking space. 7.根据权利要求1所述的停车控制方法,其特征在于,每个激光雷达只用于扫描一个停车位对应的预定监控区域,每个主控器只用于获取一个激光雷达扫描得到的点云数据。7. The parking control method according to claim 1, wherein each laser radar is only used to scan a predetermined monitoring area corresponding to a parking space, and each main controller is only used to obtain a point scanned by a laser radar cloud data. 8.根据权利要求1所述的停车控制方法,其特征在于,每个激光雷达用于扫描至少两个停车位对应的预定监控区域,每个主控器只用于获取一个激光雷达扫描得到的点云数据。8. The parking control method according to claim 1, wherein each laser radar is used to scan predetermined monitoring areas corresponding to at least two parking spaces, and each main controller is only used to obtain the information obtained by one laser radar scan. point cloud data. 9.根据权利要求1所述的停车控制方法,其特征在于,每个激光雷达只用于扫描一个停车位对应的预定监控区域,每个主控器用于获取至少两个激光雷达扫描得到的点云数据。9. The parking control method according to claim 1, wherein each laser radar is only used to scan a predetermined monitoring area corresponding to a parking space, and each main controller is used to obtain points scanned by at least two laser radars cloud data. 10.根据权利要求1所述的停车控制方法,其特征在于,每个激光雷达用于扫描至少两个停车位对应的预定监控区域,每个主控器用于获取至少两个激光雷达扫描得到的点云数据。10. The parking control method according to claim 1, wherein each laser radar is used to scan predetermined monitoring areas corresponding to at least two parking spaces, and each main controller is used to obtain at least two laser radar scans obtained point cloud data. 11.根据权利要求1所述的停车控制方法,其特征在于,获取激光雷达扫描得到的所述停车位对应的预定监控区域的点云数据,包括:11. The parking control method according to claim 1, wherein obtaining the point cloud data of the predetermined monitoring area corresponding to the parking space obtained by laser radar scanning comprises: 确定用于扫描所述停车位对应的预定监控区域的激光雷达;Determining the laser radar used to scan the predetermined monitoring area corresponding to the parking space; 获取该激光雷达扫描得到的点云数据。Obtain the point cloud data scanned by the lidar. 12.根据权利要求11所述的停车控制方法,其特征在于,获取激光雷达扫描得到的所述停车位对应的预定监控区域的点云数据,还包括:12. The parking control method according to claim 11, wherein obtaining the point cloud data of the predetermined monitoring area corresponding to the parking space obtained by laser radar scanning also includes: 判断该激光雷达的扫描范围大于所述停车位对应的预定监控区域时,对该激光雷达扫描得到的点云数据进行预处理,以得到所述停车位对应的预定监控区域的点云数据。When it is judged that the scanning range of the laser radar is larger than the predetermined monitoring area corresponding to the parking space, preprocessing is performed on the point cloud data scanned by the laser radar to obtain the point cloud data of the predetermined monitoring area corresponding to the parking space. 13.根据权利要求1所述的停车控制方法,其特征在于,对所述点云数据聚类得到所述待停车辆的点云集合,包括:13. The parking control method according to claim 1, wherein the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, comprising: 对所述点云数据聚类得到一个或多个车辆的点云集合,将所述一个或多个车辆的点云集合中对应于行驶状态的车辆的点云集合确定为所述待停车辆的点云集合。Clustering the point cloud data to obtain a point cloud set of one or more vehicles, and determining the point cloud set of the vehicle corresponding to the driving state in the point cloud set of one or more vehicles as the vehicle to be parked Collection of point clouds. 14.根据权利要求1所述的停车控制方法,其特征在于,对所述点云数据聚类得到所述待停车辆的点云集合,包括:14. parking control method according to claim 1, is characterized in that, to described point cloud data clustering, obtains the point cloud collection of described vehicle to be parked, comprising: 从所述消息中解析出所述待停车辆的车载定位设备采集的定位数据;Analyzing the positioning data collected by the on-board positioning device of the vehicle to be parked from the message; 对所述点云数据聚类得到一个或多个车辆的点云集合,将所述一个或多个车辆的点云集合中包含所述定位数据的点云集合确定为所述待停车辆的点云集合。Clustering the point cloud data to obtain point cloud collections of one or more vehicles, and determining the point cloud collections containing the positioning data in the point cloud collections of one or more vehicles as the points of the vehicle to be parked Cloud collection. 15.根据权利要求1所述的停车控制方法,其特征在于,对所述点云数据聚类得到所述待停车辆的点云集合,包括:15. parking control method according to claim 1, is characterized in that, to described point cloud data clustering, obtains the point cloud collection of described vehicle to be parked, comprising: 从所述消息中解析出所述待停车辆的车载定位设备采集的定位数据;Analyzing the positioning data collected by the on-board positioning device of the vehicle to be parked from the message; 在所述点云数据中截取所述定位数据对应的位置及其周围预设长度内的区域所对应的点云数据,并对截取的点云数据聚类得到所述待停车辆的点云集合。Intercepting the point cloud data corresponding to the position corresponding to the positioning data and the area within the preset length around it from the point cloud data, and clustering the intercepted point cloud data to obtain the point cloud set of the vehicle to be parked . 16.根据权利要求1所述的停车控制方法,其特征在于,对所述点云数据聚类得到所述待停车辆的点云集合,包括:16. The parking control method according to claim 1, wherein the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, comprising: 从所述消息中解析所述待停车辆所处车道的编号;Parsing the number of the lane where the vehicle to be parked is located from the message; 根据所述待停车辆所处车道的编号,以及已知的各个车道与所述激光雷达的相对位置,在所述点云数据中截取所述待停车辆所处车道的点云数据;According to the number of the lane where the vehicle to be parked is located, and the known relative positions of each lane and the lidar, intercept the point cloud data of the lane where the vehicle to be parked is located in the point cloud data; 对所述点云数据聚类得到一个或多个车辆的点云集合;Clustering the point cloud data to obtain point cloud collections of one or more vehicles; 将所述一个或多个车辆的点云集合中与所述待停车辆所处车道的点云数据存在交集的点云集合确定为所述待停车辆的点云集合。Determining, among the point cloud sets of the one or more vehicles, the point cloud sets that intersect with the point cloud data of the lane where the vehicle to be parked is located, as the point cloud set of the vehicle to be parked. 17.根据权利要求1所述的停车控制方法,其特征在于,对所述点云数据聚类得到所述待停车辆的点云集合,包括:17. The parking control method according to claim 1, wherein the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, comprising: 从所述消息中解析所述待停车辆所处车道的编号;Parsing the number of the lane where the vehicle to be parked is located from the message; 根据所述待停车辆所处车道的编号,以及已知的各个车道与所述激光雷达的相对位置,在所述点云数据中截取所述待停车辆所处车道的点云数据,并对截取的点云数据聚类得到所述待停车辆的点云集合。According to the number of the lane where the vehicle to be parked is located, and the known relative positions of each lane and the lidar, the point cloud data of the lane where the vehicle to be parked is intercepted from the point cloud data, and The intercepted point cloud data is clustered to obtain the point cloud set of the vehicle to be parked. 18.根据权利要求1所述的停车控制方法,其特征在于,对所述点云数据聚类得到所述待停车辆的点云集合,包括:18. The parking control method according to claim 1, wherein the point cloud collection of the vehicle to be parked is obtained by clustering the point cloud data, comprising: 从所述消息中解析所述待停车辆的车载定位设备采集的定位数据和所述待停车辆所处车道的编号;Parsing the positioning data collected by the vehicle-mounted positioning device of the vehicle to be parked and the number of the lane where the vehicle to be parked is located from the message; 根据所述待停车辆所处车道的编号,以及已知的各个车道与所述激光雷达的相对位置,在所述点云数据中截取所述待停车辆所处车道的点云数据;According to the number of the lane where the vehicle to be parked is located, and the known relative positions of each lane and the lidar, intercept the point cloud data of the lane where the vehicle to be parked is located in the point cloud data; 对所述点云数据聚类得到一个或多个车辆的点云集合,将所述一个或多个车辆的点云集合中包含所述定位数据且与所述待停车辆所处车道的点云数据存在交集的点云集合确定为所述待停车辆的点云集合。Clustering the point cloud data to obtain point cloud collections of one or more vehicles, including the positioning data in the point cloud collections of the one or more vehicles and matching the point cloud of the lane where the vehicle to be parked The set of point clouds whose data intersects is determined as the set of point clouds of the vehicle to be parked. 19.根据权利要求1所述的停车控制方法,其特征在于,利用ICP算法对所述待停车辆的点云集合和车辆点云模型进行计算,包括:19. The parking control method according to claim 1, wherein the point cloud collection and the vehicle point cloud model of the vehicle to be parked are calculated using the ICP algorithm, including: 确定所述待停车辆的车辆型号;Determine the vehicle model of the vehicle to be parked; 在模型库中选择与所述待停车辆的车辆型号相匹配的车辆点云模型;Select the vehicle point cloud model matching the vehicle model of the vehicle to be parked in the model library; 利用ICP算法对所述待停车辆的点云集合和与所述待停车辆的车辆型号相匹配的车辆点云模型进行计算;其中,所述模型库包括预先利用激光雷达对在所述停车位停车的多个不同车辆型号的车辆扫描所得到的多个车辆点云模型。Use the ICP algorithm to calculate the point cloud set of the vehicle to be parked and the vehicle point cloud model that matches the vehicle model of the vehicle to be parked; Multiple vehicle point cloud models obtained from vehicle scans of multiple different vehicle models parked. 20.根据权利要求19所述的停车控制方法,其特征在于,确定所述待停车辆的车辆型号,包括:从所述消息中解析出所述待停车辆的车辆型号。20. The parking control method according to claim 19, wherein determining the vehicle model of the vehicle to be parked comprises: analyzing the vehicle model of the vehicle to be parked from the message. 21.根据权利要求19所述的停车控制方法,其特征在于,确定所述待停车辆的车辆型号,包括:从所述消息中解析出所述待停车辆的车辆标识,并根据已知的车辆标识与车辆型号的对应关系来确定所述待停车辆的车辆型号。21. The parking control method according to claim 19, wherein determining the vehicle model of the vehicle to be parked comprises: analyzing the vehicle identification of the vehicle to be parked from the message, and according to known The vehicle model of the vehicle to be parked is determined according to the corresponding relationship between the vehicle identification and the vehicle model. 22.根据权利要求19所述的停车控制方法,其特征在于,还包括:22. The parking control method according to claim 19, further comprising: 判断所述模型库中是否包含与所述待停车辆的车辆型号相匹配的车辆点云模型;Judging whether the model library contains a vehicle point cloud model matching the vehicle model of the vehicle to be parked; 若不包含,则从所述模型库中选取一个已有的车辆点云模型确定为与所述待停车辆的车辆型号相匹配的车辆点云模型,并在所述待停车辆停止在所述停车位之后,利用所述激光雷达扫描所述待停车辆并将扫描得到的点云集合存入所述模型库中。If it does not contain, then select an existing vehicle point cloud model from the model library to be determined as a vehicle point cloud model that matches the vehicle model of the vehicle to be parked, and when the vehicle to be parked stops at the After the parking space, the lidar is used to scan the vehicle to be parked, and the scanned point cloud set is stored in the model library. 23.根据权利要求1所述的停车控制方法,其特征在于,所述车辆点云模型按照如下方式确定:23. The parking control method according to claim 1, wherein the vehicle point cloud model is determined as follows: 预先利用激光雷达扫描驶向所述停车位并最终在所述停车位停车的车辆;Using lidar to scan in advance the vehicles driving towards the parking space and finally parking in the parking space; 将所述车辆未到达所述停车位时的点云数据转换至到达所述停车位时的点云数据所在的坐标系中;Converting the point cloud data when the vehicle does not arrive at the parking space into the coordinate system where the point cloud data when the vehicle arrives at the parking space; 将转换后得到的点云集合确定为所述车辆点云模型。The converted point cloud set is determined as the vehicle point cloud model. 24.一种停车控制方法,其特征在于,包括:24. A parking control method, comprising: 发送待停车辆请求停车的消息;Send a message that the vehicle to be parked requests to park; 接收主控器返回的停车位的标识,并控制所述待停车辆驶向所述停车位;receiving the identification of the parking space returned by the main controller, and controlling the vehicle to be parked to drive towards the parking space; 接收主控器返回的待停车辆的点云集合和车辆点云模型之间的旋转矩阵和平移矩阵;其中,车辆点云模型是利用预先利用激光雷达扫描在所述停车位停止的车辆得到的点云集合;Receive the rotation matrix and translation matrix between the point cloud set of the vehicle to be parked and the vehicle point cloud model returned by the main controller; wherein, the vehicle point cloud model is obtained by scanning the vehicle stopped in the parking space by using the laser radar in advance collection of point clouds; 根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度,以使所述待停车辆最终停止在所述停车位。Controlling the traveling direction and speed of the vehicle to be parked in real time according to the rotation matrix and the translation matrix, so that the vehicle to be parked finally stops at the parking space. 25.根据权利要求24所述的停车控制方法,其特征在于,发送待停车辆请求在停车位停车的消息,包括:通过车联万物V2X设备广播待停车辆请求在停车位停车的消息。25. The parking control method according to claim 24, wherein sending the message that the vehicle to be parked requests to park in the parking space comprises: broadcasting the message that the vehicle to be parked requests to park in the parking space through the V2X device of the Internet of Things. 26.根据权利要求24所述的停车控制方法,其特征在于,所述消息中包含如下信息中的任意一项或多项:26. The parking control method according to claim 24, wherein the message contains any one or more of the following information: 所述待停车辆的车辆标识;the vehicle identification of the vehicle to be parked; 所述待停车辆的车辆型号;the vehicle model of the vehicle to be parked; 所述待停车辆的车载定位设备采集的定位数据;The positioning data collected by the on-board positioning equipment of the vehicle to be parked; 通信连接标识。Communication connection identification. 27.根据权利要求26所述的停车控制方法,其特征在于,所述通信连接标识包括所述车辆控制器的MAC地址、所述车辆控制器连接的车联万物V2X通信设备的MAC地址中的一种或两种。27. The parking control method according to claim 26, wherein the communication connection identification includes the MAC address of the vehicle controller and the MAC address of the V2X communication device connected to the vehicle controller one or two. 28.根据权利要求24所述的停车控制方法,其特征在于,发送待停车辆请求停车的消息,包括:28. The parking control method according to claim 24, wherein sending the message that the vehicle to be parked requests parking includes: 判断所述待停车辆进入停车场之后发出所述消息;或,Sending the message after judging that the vehicle to be parked enters the parking lot; or, 接收到预设的触发信号之后发出所述消息。The message is sent after receiving a preset trigger signal. 29.根据权利要求24所述的停车控制方法,其特征在于,根据所述旋转矩阵和平移矩阵实时控制所述待停车辆的行驶方向和速度,包括:根据所述旋转矩阵和平移矩阵,通过控制所述待停车辆的转向系统、油门控制系统和制动系统来实时控制所述待停车辆的行驶方向和速度。29. The parking control method according to claim 24, wherein the real-time control of the driving direction and speed of the vehicle to be parked according to the rotation matrix and the translation matrix comprises: according to the rotation matrix and the translation matrix, by The steering system, accelerator control system and braking system of the vehicle to be stopped are controlled to control the driving direction and speed of the vehicle to be stopped in real time. 30.一种主控器,包括第一处理器、第一存储器及存储在第一存储器上并可在第一处理器上运行的计算机程序,其特征在于,所述第一处理器在运行所述计算机程序时,执行权利要求1~23任一项所述的停车控制方法中的各个步骤。30. A main controller, comprising a first processor, a first memory, and a computer program stored on the first memory and operable on the first processor, wherein the first processor runs the When the computer program is described, each step in the parking control method described in any one of claims 1 to 23 is executed. 31.一种车辆控制器,包括第二处理器、第二存储器及存储在第二存储器上并可在第二处理器上运行的计算机程序,其特征在于,所述第二处理器在运行所述计算机程序时,执行权利要求22~29任一项所述的停车控制方法中的各个步骤。31. A vehicle controller comprising a second processor, a second memory, and a computer program stored on the second memory and operable on the second processor, wherein the second processor runs the When the computer program is described, each step in the parking control method described in any one of claims 22-29 is executed. 32.一种停车控制系统,其特征在于,包括:如权利要求30所述的主控器,如权利要求33所述的车辆控制器,以及激光雷达。32. A parking control system, characterized by comprising: the master controller as claimed in claim 30, the vehicle controller as claimed in claim 33, and a laser radar. 33.根据权利要求32所述的停车控制系统,其特征在于,每个所述激光雷达只用于扫描一个停车位对应的预定监控区域,每个所述主控器只用于获取一个所述激光雷达扫描得到的点云数据。33. The parking control system according to claim 32, wherein each of the laser radars is only used to scan a predetermined monitoring area corresponding to a parking space, and each of the main controllers is only used to obtain one of the Point cloud data obtained from lidar scanning. 34.根据权利要求32所述的停车控制系统,其特征在于,每个所述激光雷达用于扫描至少两个停车位对应的预定监控区域,每个所述主控器只用于获取一个所述激光雷达扫描得到的点云数据。34. The parking control system according to claim 32, wherein each of the laser radars is used to scan predetermined monitoring areas corresponding to at least two parking spaces, and each of the main controllers is only used to obtain one of the The point cloud data obtained by the lidar scanning. 35.根据权利要求32所述的停车控制系统,其特征在于,每个所述激光雷达只用于扫描一个停车位对应的预定监控区域,每个所述主控器用于获取至少两个所述激光雷达扫描得到的点云数据。35. The parking control system according to claim 32, wherein each of the laser radars is only used to scan a predetermined monitoring area corresponding to a parking space, and each of the main controllers is used to acquire at least two of the Point cloud data obtained from lidar scanning. 36.根据权利要求32所述的停车控制系统,其特征在于,每个所述激光雷达用于扫描至少两个停车位对应的预定监控区域,每个所述主控器用于获取至少两个所述激光雷达扫描得到的点云数据。36. The parking control system according to claim 32, wherein each of the laser radars is used to scan predetermined monitoring areas corresponding to at least two parking spaces, and each of the main controllers is used to acquire at least two of the corresponding monitoring areas. The point cloud data obtained by the lidar scanning. 37.根据权利要求32所述的停车控制系统,其特征在于,还包括:与所述主控器连接的车联万物V2X设备,以及,与所述车辆控制器连接的V2X设备。37. The parking control system according to claim 32, further comprising: a V2X device connected to the main controller, and a V2X device connected to the vehicle controller. 38.根据权利要求32所述的停车控制系统,其特征在于,还包括:用于为所述主控器和/或所述激光雷达供电的供电设备。38. The parking control system according to claim 32, further comprising: a power supply device for supplying power to the main controller and/or the laser radar. 39.一种汽车,其特征在于,所述汽车上装设有如权利要求31所述的车辆控制器。39. A vehicle, characterized in that the vehicle controller according to claim 31 is mounted on the vehicle. 40.根据权利要求39所述的汽车,其特征在于,所述车辆控制器连接所述汽车的转向系统、油门控制系统和制动系统。40. The vehicle of claim 39, wherein the vehicle controller is connected to a steering system, an accelerator control system and a braking system of the vehicle. 41.根据权利要求39所述的汽车,其特征在于,所述汽车上装设有与所述车辆控制器连接的车联万物V2X设备。41. The vehicle according to claim 39, wherein the vehicle is equipped with a V2X device connected to the vehicle controller. 42.根据权利要求39所述的汽车,其特征在于,所述汽车上装设有车载定位设备。42. The vehicle according to claim 39, wherein the vehicle is equipped with a vehicle positioning device. 43.一种计算机可读的存储介质,其上存储有计算机程序,其特征在于,所述计算机程序被处理器运行时实现权利要求1~23任一项所述的停车控制方法中的各个步骤。43. A computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is run by a processor, each step in the parking control method according to any one of claims 1 to 23 is implemented . 44.一种计算机可读的存储介质,其上存储有计算机程序,其特征在于,所述计算机程序被处理器运行时实现权利要求24~29任一项所述的停车控制方法中的各个步骤。44. A computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is run by a processor, each step in the parking control method according to any one of claims 24-29 is implemented .
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