Multi-source fusion parking lot cooperative intelligent automobile positioning and control method

Abstract

The invention discloses a multi-source fusion parking lot cooperative intelligent automobile positioning and control method. The method comprises a parking lot end device, an automobile end device, a service end and a database. Vehicle positioning parameters are obtained according to equipment information of the field end equipment, and the equipment information is used for providing a vehicle positioning mode; vehicle positioning parameters are obtained according to the equipment information of the vehicle-end equipment, the vehicle-end equipment provides vehicle positioning information, vehicle state information and environment sensing information, and the current vehicle is confirmed and positioned based on the positioning parameters capable of being supported by the vehicle-end equipment; a vehicle driving track is planned and vehicle movement is controlled based on vehicle state information and environment perception information, parking space guidance, remote vehicle control, unmanned cruise parking and unmanned cruise receiving can be realized, the advantages of field end equipment and vehicle end equipment are developed to the greatest extent, the positioning precision is improved, the remote unmanned vehicle control distance and precision are greatly increased, and the system is suitable for large-scale popularization and application. And safe, efficient and intelligent vehicle using experience is provided for the user.

Description

Technical Field

[0001] The present invention relates to a vehicle positioning and control method, and in particular to a multi-source fusion parking lot collaborative intelligent vehicle positioning and control method, and a positioning device and control method thereof. Technical Background

[0002] Current technologies related to smart parking are generally based on single-vehicle perception, prediction, planning, and control methods. However, the poor lighting conditions in underground parking lots significantly affect feature recognition. Furthermore, the GNSS+IMU+visual positioning solution commonly used in autonomous driving cannot provide accurate positioning information in the weak GNSS signal environments of medium, large, and extra-large underground or multi-story parking lots. Limited by the inability to use GNSS positioning in densely populated underground or multi-story areas, combined with the use of an IMU solution, the cumulative error generated as distance increases leads to increasing positioning deviations. Furthermore, in multi-story underground parking lots, different parking floors have similar structures, making them difficult to distinguish using visual positioning without the aid of special markings. This makes it difficult to meet the positioning accuracy and stability requirements of unmanned smart parking systems. Therefore, designing and implementing a vehicle positioning and control method in underground or multi-story parking lots has become an urgent problem for smart cars. Summary of the Invention

[0003] In order to solve the above problems in the prior art, the present invention provides a multi-source fusion parking lot collaborative intelligent vehicle positioning and control system, and a positioning device and control method thereof.

[0004] To achieve the above-mentioned objectives, the present invention provides a multi-source fusion parking lot collaborative intelligent automobile positioning and control method, the positioning and control system includes: a field-side device, a vehicle-side device, a business end and a data end; a communication relationship is established among the field-side device, the vehicle-side device and the business end to obtain positioning parameter information; the vehicle positioning parameters are obtained according to the device information of the field-side device and the device information of the vehicle-side device, wherein the device information is used to provide a positioning mode; the field-side device provides the vehicle-side device with positioning information for controlling the movement of the vehicle; the business end provides the vehicle-side device with path planning information and behavior voting information; low-power and low-cost field-side positioning devices are evenly arranged at the field end, the vehicle-mounted device receives the coordinate parameters sent by the field-side positioning device, and obtains the absolute position information of the vehicle at the field end based on the positioning algorithm, and combines the vehicle status information and environmental information collected by the vehicle-side device to obtain the global position information of the vehicle at the field end based on the fusion positioning algorithm model.

[0005] The method comprises the following steps:

[0006] S1 obtains the location information of the vehicle-side receiving device at the same terminal based on the broadcast information of multiple terminal devices deployed at the same terminal and the first positioning mode.

[0007] S2 determines the second positioning mode based on the location information of the vehicle-side receiving device at the field end and the environmental perception information in the first positioning mode to obtain the vehicle positioning information.

[0008] S3 creates decision information based on the vehicle positioning information of the second positioning mode,

[0009] S4 builds global path planning information based on vehicle positioning information and target point of interest information.

[0010] S5 constructs a vehicle motion model and generates a vehicle control model based on the path planning information.

[0011] Furthermore, in step S1, obtaining corresponding positioning information in the first positioning mode according to the device information of the field-side device and the device information of the vehicle-side device includes:

[0012] According to the device information of the field-side devices, the three field-side devices with the strongest signal strength at the time of reception are selected. The signal strengths of the three field-side devices are recorded as RSSI1, RSSI2, and RSSI3. Then, the UUID and Address information of the three field-side devices are obtained from the field-side device broadcast message. The Address contains the three-dimensional coordinates of the location information of the field-side devices, which are recorded as (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3). The three-dimensional coordinates of the vehicle in the field-side coordinate system are recorded as (x p ,y p ,z p ) Determine the preset first positioning mode currently corresponding to the terminal device; receive broadcast messages from multiple terminal devices in the same terminal; the distances from the vehicle to the above three terminal devices in the terminal coordinate system are recorded as d1, d2, and d3 respectively, and the following set of equations can be established:

[0013]

[0014] Based on the signal strength RSSI1, RSSI2, and RSSI3 received by the vehicle from the three field devices, the distances from the vehicle to the three field devices are calculated as d1, d2, and d3 respectively. The calculation formula for the distances from the vehicle to the three field devices and the received signal strength is as follows:

[0015]

[0016] Where A represents the signal strength within a certain distance from the same type of field equipment as the signal transmitter to the vehicle-mounted equipment signal receiver, n p Indicates the field-side environmental attenuation coefficient.

[0017] You can get the first positioning mode formula:

[0018]

[0019] According to the first positioning mode formula, the positioning parameters (x p ,y p ,z p ).

[0020] Furthermore, in step S2, based on the vehicle-side receiving device's location information and environmental perception information at the field side in the first positioning mode, obtaining corresponding positioning information in the second positioning mode includes:

[0021] Determine the positioning information of the vehicle-mounted device receiving terminal in the field-side coordinate system according to the vehicle-mounted device receiving terminal;

[0022] Determine the vehicle's current corresponding environmental positioning information based on the vehicle's onboard environmental perception equipment;

[0023] Establish the calculation formula for the second positioning mode:

[0024]

[0025] The angles α, β, and γ in the relationship matrix given above correspond to the angles between the three coordinate axes of the vehicle coordinate system. The coordinate transformation matrix based on the three-dimensional coordinate axes X, Y, and Z of the terminal is:

[0026]

[0027] According to the vehicle status information and environmental perception information, the corresponding vehicle positioning parameters (x i ,y i ,z i ). Further, in the step S3, the vehicle positioning information of the second positioning mode creates behavioral decision information, including: designing the vehicle's position information in the field-side coordinate system and the scene on the field-side map, based on the vehicle's position information in the current field-side coordinate system, finding an optimal strategy under any given state S, and generating a corresponding behavioral decision. The goal selected by the behavioral decision is to achieve the optimal benefit through the current time point to the future accumulation, and adopt a dynamic programming method based on the dynamic attributes and time-space interaction relationship to establish a five-element array for solving the behavioral decision based on the state S:

[0028] The five-element array definition is:

[0029] S is the state element, A is the behavior, P is the conditional probability, P A (S i , S i+1 ), representing the vehicle in state St and behavior A, reaching the next state S t+1 probability;

[0030] R is the excitation, the excitation function R A (S i ,S i+1 ), represents the vehicle in action A, from S i Status to S i+1 The excitation of the state; k is the attenuation factor under the excitation of R, k∈(0,1), and the excitation at the next moment is attenuated according to this factor.

[0031] Create an array of action decisions based on state S:

[0032]

[0033] The array q(S t ) is the cumulative excitation of future attenuation superposition. The specific solution process can be in all possible states S t and S′ t Repeat the iterative calculation until the two converge.

[0034] Furthermore, in step S4, global path planning information is constructed based on the vehicle positioning information and the target point of interest information, including:

[0035] According to the device information of the vehicle-mounted device, obtain the current corresponding vehicle status information of the vehicle;

[0036] Obtain the vehicle's current corresponding environmental perception information based on the device information of the on-board device;

[0037] Obtain information about points of interest and planned routes based on the pre-installed on-site map service;

[0038] Based on certain planning path rules, the relationship between the path starting point and the position of the control point in the planned path is established. The current path starting point is Q i (i=1,2,…,b), the control point in the planned path is C i (i=1,2,…,n+1), according to the third-order spline curve smoothing, the smooth relationship between the path points and the control points is established as follows:

[0039]

[0040] Based on the smooth relationship between the path points and the control points, a path from the starting point Q1 to the end point Q is established. n The linear equations for :

[0041]

[0042] In addition, two more conditions need to be added: C0 = 2C1-C2 and C n+1 =2C n -C n-1 , that is, the starting point and end point of the path are C0C1, C n C n+1 Tangent.

[0043] Furthermore, in step S5, a vehicle motion model is constructed and a vehicle control model is generated based on the path planning information, including:

[0044] According to the vehicle positioning parameters (x i ,y i ,z i ), a control model of the vehicle at the field end is established based on the geometric relationship of the control object, and the vehicle model placed in the field end coordinate system is simplified. The front and rear wheel turning angles are recorded as δ f and δ r The distances from the vehicle's center of mass G to the front and rear axles are represented by L f and L r Indicates that the velocity of the center of mass is V, and the angle between the velocity direction and the X axis of the vehicle coordinate system is The vehicle's yaw rate is represented by ω, and the sine theorem is used to obtain the vehicle's L f The ratio of the trajectory radius r and the front wheel turning angle δ of the vehicle f The angle between the velocity direction and the vehicle coordinate system X Function expression relationship:

[0045]

[0046] Similarly, the vehicle's L can be obtained r The ratio of the trajectory radius r and the rear wheel turning angle δ of the vehicle r The angle between the velocity direction and the vehicle coordinate system X Function expression relationship:

[0047]

[0048] The L of the above vehicle f 、L r , front wheel angle, rear wheel angle and the angle between the velocity direction and the vehicle coordinate system X By adding and merging the two function expressions, we can get the steering trajectory motion equation:

[0049]

[0050] The wheelbase of the vehicle is represented by L, then L = L f +L r , the steering trajectory motion equation can be expressed as:

[0051]

[0052] When the radius r of the vehicle's trajectory changes slowly, the vehicle's yaw rate is expressed as ω, then ω will be equal to the vehicle's

[0053] The angular velocity of the vehicle can be obtained as:

[0054]

[0055] The vehicle motion model equation based on wheel angle and vehicle speed can be obtained:

[0056]

[0057] For a car with front-wheel steering, the rear-wheel steering angle is 0 degrees, and the above vehicle control motion model equation can be simplified to

[0058] becomes:

[0059]

[0060] If the heading angle of the vehicle is γ, the period of sending control instructions from the last moment to the current moment is recorded as Δt,

[0061] Then the heading angle γ of the vehicle can be expressed as:

[0062]

[0063] Assume that the vehicle positioning parameters of the two-dimensional coordinate plane at the current moment are recorded as (x i ,y i ), the increments of the vehicle's position in the X-axis and Y-axis directions are Δx and Δy respectively, then the vehicle control model equation is:

[0064]

[0065] According to the vehicle control model equation, vehicle control parameters are obtained, and the vehicle is remotely controlled in response to the vehicle's unmanned cruise parking and unmanned cruise pick-up.

[0066] When trajectory planning information is processed according to the positioning parameter information and the control device, control parameter information is sent to the vehicle, wherein the control parameter information is configured to terminate the execution of the current control method.

[0067] In some embodiments, the vehicle control method further includes:

[0068] In this way, the present application can also send remote control implementation status information to the user based on the vehicle control method to prompt the current vehicle status and surrounding environment information on the one hand, and on the other hand, prompt the user of the execution status and vehicle location information after completing the vehicle control task.

[0069] The positioning parameter information is obtained by establishing a communication relationship among the field-side device, the vehicle-side device and the service end.

[0070] The field-side equipment in the embodiments of the present application includes:

[0071] Bluetooth beacons, Bluetooth gateways, POE switches, routers, and LTE / 5G base stations;

[0072] The Bluetooth beacon is used to send preset positioning information, and obtain the Bluetooth beacon positioning parameters according to the preset positioning information of the field terminal device, wherein the preset positioning information is used to represent the first positioning mode of the sending module and the vehicle;

[0073] The Bluetooth gateway is used to obtain the working status information of the Bluetooth beacon;

[0074] The POE switch is used to supply power to the Bluetooth gateway and send the working status information to the router;

[0075] The router is used to receive the working status information sent by the POE switch and send the working status to the service server;

[0076] The LTE / 5G base station is used for information transmission between vehicle-side equipment, service servers and mobile phones / mobile terminals.

[0077] A control device in the present application includes:

[0078] The processor is used to obtain control parameters, vehicle status information and environmental perception information based on the device information of the field-side device and the device information of the vehicle-side device;

[0079] In this way, the present application can also establish physical communication with the vehicle-side device to facilitate the acquisition of vehicle status information and environmental perception information.

[0080] The memory is used to store a computer program, and when the computer program is executed by the processor, the computer program implements the above method.

[0081] The vehicle-side device implemented in this application includes the above-mentioned control device, and also includes:

[0082] A vehicle-mounted Bluetooth unit, configured to receive device information of the field-side device;

[0083] An onboard gateway control unit, configured to receive the positioning parameters, control parameters of the control device, vehicle status information, and environmental perception information;

[0084] In certain embodiments, the vehicle gateway control unit sends the control parameters to an actuator device to control vehicle movement;

[0085] In some embodiments, the vehicle gateway control unit sends the current vehicle positioning parameters, vehicle status information, and environment perception information to the intelligent network control unit;

[0086] In some embodiments, the intelligent connected control unit has a built-in intrusion protection mechanism that can perform data security monitoring on positioning parameters, control parameters of control devices, vehicle status information, and environmental perception information received through the vehicle gateway;

[0087] The intelligent network control unit is used to send the current vehicle positioning parameters, vehicle status information and environmental perception information to the business server.

[0088] In the implementation manner of the present application, the mobile phone / mobile terminal is used to implement remote monitoring of the above-mentioned remote control vehicle implementation method.

[0089] In the implementation manner of this application, the service end includes:

[0090] Pre-install field-side map services, positioning services, information transmission services, identity authentication and access control, and establish a security framework model;

[0091] The preset map service and the positioning service are used to provide parking space information and key point information to the vehicle-side device and the mobile phone / mobile terminal to implement the above method;

[0092] The information transmission service is used to send the vehicle positioning parameters, vehicle status information and environmental perception information to the mobile phone / mobile terminal;

[0093] Authentication, used to authenticate the identity of mobile phone / mobile terminal users;

[0094] Authentication, which is used to verify whether the user's mobile phone / mobile terminal has the right to access the smart car service system;

[0095] Access control, which is used to grant users who have established authentication relationships access to communication data of the intelligent vehicle service system;

[0096] An intrusion protection mechanism is deployed in the application layer of mobile phones / mobile terminals, which can perform security monitoring on parking space information and key point information data sent from the pre-set map service and positioning service from the business end.

[0097] In the implementation manner of the present application, the data end includes storing preset field map data, customer information data, smart car EDR data and business end data.

[0098] The vehicle in the embodiment of the present application includes the above-mentioned vehicle-side equipment.

[0099] The services implemented on the business side include:

[0100] 1. The parking lot positioning and parking guidance system services are implemented through software modules and algorithms deployed on the business-side platform server;

[0101] 2. Maintain and update pre-set site-side map information data, specifically collecting site-side building structure coordinate data and updating maintenance data;

[0102] 3. The services and information (including location data) of the key points of interest on the field side are pushed to the vehicle-side device and the user's mobile device. The specific implementation is that when the system monitors the field area and searches for the key points of interest on the field side from the vehicle or the user's mobile device

[0103] (such as elevator entrances, exits, car wash services, maintenance services, etc.), the business end will push the preset information in the platform server to;

[0104] 4. Software development for the first positioning mode and its deployment and application on vehicle-side devices;

[0105] 5. The deployment of third-party services of vehicle OEM service providers EDR (event data collection) and OTA (over-the-air upgrade) on the business side is specifically implemented by directly connecting to the field communication equipment through the business side to obtain the vehicle-side EDR and vehicle-side controller when the vehicle is idle.

[0106] OTA;

[0107] Authentication and access control of user / system administrator mobile device access services are achieved through the network service authentication algorithm deployed on the platform server.

[0108] A control device, comprising: a processor and a memory;

[0109] The processor is used to implement the described method and send the processed control parameters and the vehicle status information and environmental perception information to the vehicle-end device.

[0110] Compared with the prior art, the advantages of the present invention are as follows:

[0111] 1. Improve positioning accuracy: By combining on-site and on-board equipment to obtain positioning information based on different models, this approach addresses issues such as weak satellite positioning signals in parking lots, the similarity of different parking floors, inaccurate cross-floor positioning, increasing IMU deduction errors with increasing driving distance, and the limitations of single-vehicle perception and positioning. By leveraging the advantages of both on-site and on-board equipment, positioning accuracy in parking lots can be improved.

[0112] 2. Improve the distance and safety of remote-controlled vehicles: Field-side equipment and vehicle-side equipment, as well as the establishment of planning and control models, can achieve beyond-line-of-sight remote control of vehicles while improving the safety of vehicle control.

[0113] 3. Unmanned cruise parking and pick-up can be realized without the need for field-side high-precision maps: This invention obtains positioning information under two different positioning modes based on field-side equipment, field-side services and vehicle-side equipment, and creates decision information based on the positioning information, constructs global path planning information, and then constructs a vehicle motion model and generates a control model to realize unmanned cruise and unmanned cruise pick-up control. BRIEF DESCRIPTION OF THE DRAWINGS

[0114] The description of the implementation methods of the above-mentioned equipment and devices involved in this application in combination with the accompanying drawings will become obvious and easy to understand. The drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0115] Figure 1 This is a schematic diagram of the architecture of the multi-source fusion parking lot collaborative intelligent parking system in the implementation manner of this application;

[0116] Figure 2 This is one of the flow charts of the control method in the embodiment of the present application;

[0117] Figure 3 This is the second flow chart of the control method in the embodiment of the present application;

[0118] Figure 4 This is the third flow chart of the control method in the implementation manner of this application. DETAILED DESCRIPTION

[0119] The following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without any creative work are within the scope of protection of this application.

[0120] The terms "first," "second," and the like in the specification and claims of this application and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate so that the embodiments of the application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions, for example, a process, method, system, security, product, or server comprising a series of steps or units is not necessarily limited to those steps clearly listed, but may include other steps that are not clearly listed or inherent to these processes, methods, products, or devices.

[0121] Example

[0122] This invention proposes a method for intelligent vehicle positioning and control based on multi-source fusion parking lot collaboration. Figure 1 The multi-source fusion parking lot collaborative intelligent parking system includes multiple parking-side devices in different geographical areas or in the same geographical area. The parking-side device in each geographical area is communicatively connected with the vehicle-side devices of one or more vehicles in its corresponding geographical area.

[0123] Figure 2 A multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to one embodiment of the present invention is shown. Based on device information of multiple end devices deployed in different geographical areas or the same geographical area, it is determined whether the in-field end device in the corresponding geographical area can support a preset first positioning mode corresponding to the current one, including the following steps:

[0124] S1: Acquire positioning information corresponding to the first positioning mode based on the device information of the field-side device and the device information of the vehicle-side device, including:

[0125] According to the device information of the field-side devices, the three field-side devices with the strongest signal strength at the time of reception are selected. The signal strengths of the three field-side devices are recorded as RSSI1, RSSI2, and RSSI3. Then, the UUID and Address information of the three field-side devices are obtained from the field-side device broadcast message. The Address contains the three-dimensional coordinates of the location information of the field-side devices, which are recorded as (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3). The three-dimensional coordinates of the vehicle in the field-side coordinate system are recorded as (x p ,y p ,z p ) The preset first positioning mode currently corresponding to the terminal device is determined; from receiving broadcast messages from multiple terminal devices in the same terminal; the distances from the vehicle to the above three terminal devices in the terminal coordinate system are recorded as d1, d2, and d3 respectively,

[0126] Establish the following system of equations:

[0127]

[0128] Based on the signal strength RSSI1, RSSI2, and RSSI3 received by the vehicle from the three field devices, the distances from the vehicle to the three field devices are calculated as d1, d2, and d3, respectively. The distances from the vehicle to the three field devices and the received signal strength are calculated as follows:

[0129] Calculation formula:

[0130]

[0131] Where A represents the signal strength within a certain distance from the same type of field equipment as the signal transmitter to the vehicle-mounted equipment signal receiver, n p Indicates the field-side environmental attenuation coefficient.

[0132] You can get the first positioning mode formula:

[0133]

[0134] According to the first positioning mode formula, the positioning parameters (x p ,y p ,z p ).

[0135] Figure 3 A multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to an embodiment of the present invention is shown. Vehicle status information and environmental perception information are obtained based on the device information of the vehicle-side device. The implementation process includes:

[0136] S2: The vehicle-side receiving device in the first positioning mode receives the location information and environmental perception information of the device in the field side, and obtains the corresponding positioning information in the second positioning mode, including:

[0137] Determine the positioning information of the vehicle-mounted device receiving terminal in the field-side coordinate system according to the vehicle-mounted device receiving terminal;

[0138] Determine the vehicle's current corresponding environmental positioning information based on the vehicle's onboard environmental perception equipment;

[0139] Establish the calculation formula for the second positioning mode:

[0140]

[0141] The angles a, β, and γ in the relationship matrix given above correspond to the angles between the three coordinate axes of the vehicle coordinate system.

[0142] The coordinate transformation matrix of the three-dimensional coordinate axes X, Y, and Z is:

[0143]

[0144] According to the vehicle status information and environmental perception information, the corresponding vehicle positioning parameters (x i ,y i ,z i ).

[0145] Figure 4 A multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to an embodiment of the present application is shown. According to vehicle status information, environmental perception information and positioning parameters, the current vehicle corresponding trajectory planning information is determined to implement vehicle cruise planning and motion control. The implementation process includes the following steps:

[0146] S3: The vehicle positioning information of the second positioning mode creates behavior decision information, including:

[0147] The design is based on the vehicle's position information in the field coordinate system and the scene on the field map. Based on the vehicle's position information in the current field coordinate system, an optimal strategy is found under any given state S, and a corresponding behavioral decision is generated. The goal of the behavioral decision is to achieve the optimal benefit from the current time point to the future accumulation. Based on the dynamic attributes and the time-space interaction relationship, a dynamic programming method is used to establish the solution calculation of the behavioral decision based on the five-element array of state S:

[0148] The five-element array definition is:

[0149] S is the state element, A is the behavior, P is the conditional probability, P A (S i , S i+1 ), representing the vehicle in state S t and behavior A, reaching the next state S t+1 probability;

[0150] R is the excitation, the excitation function R A (S i ,S i+1 ), represents the vehicle in action A, from S i Status to S i+1 The excitation of the state; k is the attenuation factor under the excitation of R, k∈(0,1), and the excitation at the next moment is attenuated according to this factor.

[0151] Create an array of action decisions based on state S:

[0152]

[0153] The array q(S t ) is the cumulative excitation of future attenuation superposition. The specific solution process can be in all possible states S t and S′ t Repeat the iterative calculation until the two converge.

[0154] S4: Based on the vehicle positioning information and target point of interest information, construct global path planning information, including:

[0155] According to the device information of the vehicle-mounted device, obtain the current corresponding vehicle status information of the vehicle;

[0156] Obtain the vehicle's current corresponding environmental perception information based on the device information of the on-board device;

[0157] Obtain information about points of interest and planned routes based on the pre-installed on-site map service;

[0158] Based on certain planning path rules, the relationship between the path starting point and the position of the control point in the planned path is established. The current path starting point is Q i (i=1,2,…,n), the control point in the planned path is C i (i=1,2,…,n+1), according to the third-order spline curve smoothing, the smooth relationship between the path points and the control points is established as follows:

[0159]

[0160] Based on the smooth relationship between the path points and the control points, a path from the starting point Q1 to the end point Q is established. n The linear equations for :

[0161]

[0162] In addition, two more conditions need to be added: C0 = 2C1-C2 and C n+1 =2C n -C n-1 , that is, the starting point and end point of the path are C0C1, C n C n+1 Tangent.

[0163] S5: Based on the path planning information, a vehicle motion model is constructed and a vehicle control model is generated, including:

[0164] According to the vehicle positioning parameters (x i ,y i ,z i ), a control model of the vehicle at the field end is established based on the geometric relationship of the control object, and the vehicle model placed in the field end coordinate system is simplified. The front and rear wheel turning angles are recorded as δ fand δ r The distances from the vehicle's center of mass G to the front and rear axles are represented by L f and L r Indicates that the velocity of the center of mass is V, and the angle between the velocity direction and the X axis of the vehicle coordinate system is The vehicle's yaw rate is represented by ω, and the sine theorem is used to obtain the vehicle's L f The ratio of the trajectory radius r and the front wheel turning angle δ of the vehicle f The angle between the velocity direction and the vehicle coordinate system X Function expression relationship:

[0165]

[0166] Similarly, the vehicle's L can be obtained r The ratio of the trajectory radius r and the rear wheel turning angle δ of the vehicle r The angle between the velocity direction and the vehicle coordinate system X Function expression relationship:

[0167]

[0168] The L of the above vehicle f 、L r , front wheel angle, rear wheel angle and the angle between the velocity direction and the vehicle coordinate system X By adding and merging the two function expressions, we can get the steering trajectory motion equation:

[0169]

[0170] The wheelbase of the vehicle is represented by L, then L = L f +L r , the steering trajectory motion equation can be expressed as:

[0171]

[0172] When the radius r of the vehicle's motion trajectory changes slowly, the vehicle's yaw rate is represented by ω, then ω will be equal to the vehicle's angular velocity, and we can get:

[0173]

[0174] The vehicle motion model equation based on wheel angle and vehicle speed can be obtained:

[0175]

[0176] For a front-wheel steering vehicle, the rear wheel steering angle is 0 degrees, and the above vehicle control motion model equation can be simplified to:

[0177]

[0178] If the heading angle γ of the vehicle is denoted as Δt, and the period of sending the control command from the last moment to the current moment is denoted as Δt, then the heading angle γ of the vehicle can be expressed as:

[0179]

[0180] Assume that the vehicle positioning parameters of the two-dimensional coordinate plane at the current moment are recorded as (x i ,y i ), the increments of the vehicle's position in the X-axis and Y-axis directions are Δx and Δy respectively, then the vehicle control model equation is:

[0181]

[0182] According to the vehicle control model equation, vehicle control parameters are obtained, and the vehicle is remotely controlled in response to the vehicle's unmanned cruise parking and unmanned cruise pick-up.

[0183] Multiple field-side devices in different geographical areas or in the same geographical area establish communication connections with the business end.

[0184] In the embodiment of the present application, the business end includes a platform server and a third-party server, and can provide services including pre-set field map services, positioning services, information transmission services, identity authentication and access control.

[0185] The pre-installed map service and positioning service provide parking space (PS) information and key points of interest (POI) information to the vehicle-side device and mobile phone / mobile terminal, realizing accurate and efficient parking space recommendation service, so that users can obtain parking space-related information in advance before entering the parking lot, as well as obtain information on points of interest inside larger parking lots.

[0186] The information transmission service can send vehicle positioning parameters, vehicle status information and environmental perception information to the user's mobile phone / mobile terminal, providing customers with the ability to query vehicle location, optimal terminal global planning route, and real-time location, status and surrounding environment information during vehicle docking in an intuitive and interactive way on the user's mobile phone / mobile terminal.

[0187] Authentication means verifying and confirming the identity information of the mobile phone / mobile terminal user.

[0188] The authentication is to verify whether the user's mobile phone / mobile terminal has the right to access the smart car service system and the authority to access different services opened in the smart parking service system.

[0189] The access control is to grant users who have established an authentication relationship the right to obtain communication data of the intelligent automobile service system.

[0190] In an embodiment of the present application, the data end provides storage and interaction for the business end service desk, including storage of preset field map data, customer information data, smart car EDR data and business end data.

[0191] It should be noted that the above embodiments are not intended to limit the scope of protection of the present invention, and equivalent changes or substitutions made on the basis of the above technical solutions fall within the scope of protection of the claims of the present invention.

Claims

1. A multi-source fusion parking lot collaborative intelligent vehicle positioning and control method, characterized by: The positioning and control system includes: field-side equipment, vehicle-side equipment, business end, and data end. Communication relationships are established among the field-side equipment, vehicle-side equipment, and business end to obtain positioning parameter information. Vehicle positioning parameters are obtained based on the equipment information of the field-side equipment and the vehicle-side equipment, where the equipment information is used to provide the positioning mode. The field-side equipment provides the vehicle-side equipment with positioning information for controlling vehicle movement. The business end provides the vehicle-side equipment with path planning information and behavior voting information. The method comprises the following steps: S1 obtains the location information of the vehicle-side receiving device at the same terminal based on the broadcast information of multiple terminal devices deployed at the same terminal and the first positioning mode. S2 determines the second positioning mode based on the location information of the vehicle-side receiving device at the field end and the environmental perception information in the first positioning mode to obtain the vehicle positioning information. S3 creates decision information based on the vehicle positioning information of the second positioning mode, S4 builds global path planning information based on vehicle positioning information and target point of interest information. S5 constructs a vehicle motion model and generates a vehicle control model based on the path planning information.

2. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: In step S1, obtaining corresponding positioning information in the first positioning mode according to the device information of the field-side device and the device information of the vehicle-side device includes: According to the device information of the field-side devices, the three field-side devices with the strongest signal strength at the time of reception are selected. The signal strengths of the three field-side devices are recorded as RSSI1, RSSI2, and RSSI3. Then, the UUID and Address information of the three field-side devices are obtained from the field-side device broadcast message. The Address contains the three-dimensional coordinates of the location information of the field-side devices, which are recorded as (x1, y1, z1), (x2, y2, z2), and (x3, y3, z3). The three-dimensional coordinates of the vehicle in the field-side coordinate system are recorded as (x p ,y p ,z p ) Determine the preset first positioning mode currently corresponding to the terminal device; receive broadcast messages from multiple terminal devices in the same terminal; the distances from the vehicle to the above three terminal devices in the terminal coordinate system are recorded as d1, d2, and d3 respectively, and establish the following equation group: Based on the signal strength RSSI1, RSSI2, and RSSI3 received by the vehicle from the three field devices, the distances from the vehicle to the three field devices are calculated as d1, d2, and d3 respectively. The calculation formula for the distances from the vehicle to the three field devices and the received signal strength is as follows: Where A represents the signal strength within a certain distance from the same type of field equipment as the signal transmitter to the vehicle-mounted equipment signal receiver, n p Indicates the environmental attenuation coefficient at the field end; The first positioning mode formula: According to the first positioning mode formula, the positioning parameters (x p ,y p ,z p ).

3. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: In step S2, based on the vehicle-side receiving device's location information and environmental perception information at the field side in the first positioning mode, obtaining corresponding positioning information in the second positioning mode includes: Determine the positioning information of the vehicle-mounted device receiving terminal in the field-side coordinate system according to the vehicle-mounted device receiving terminal; Determine the vehicle's current corresponding environmental positioning information based on the vehicle's onboard environmental perception equipment; Establish the calculation formula for the second positioning mode: The angles α, α, and γ in the relationship matrix given above correspond to the angles between the three coordinate axes of the vehicle coordinate system. The coordinate transformation matrix based on the three-dimensional coordinate axes X, Y, and Z of the terminal is: According to the vehicle status information and environmental perception information, the corresponding vehicle positioning parameters (x i ,y i ,z i ).

4. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: In step S3, the vehicle positioning information of the second positioning mode creates behavior decision information, including: The design is based on the vehicle's position information in the field coordinate system and the scene on the field map. Based on the vehicle's position information in the current field coordinate system, an optimal strategy is found under any given state S, and a corresponding behavioral decision is generated. The goal of the behavioral decision is to achieve the optimal benefit from the current time point to the future accumulation. Based on the dynamic attributes and the time-space interaction relationship, a dynamic programming method is used to establish the solution calculation of the behavioral decision based on the five-element array of state S: The five-element array definition is: S is the state element, A is the behavior, P is the conditional probability, P A (S i , S i+1 ), representing the vehicle in state S t and behavior A, reaching the next state S t+1 probability; R is the excitation, the excitation function R A (S i ,S i+1 ), represents that the vehicle is in action A, from S i Status to S i+1 State incentives; k is the attenuation factor under R excitation, k∈(0,1). The excitation at the next moment is attenuated according to this factor, and the behavior decision array based on state S is established: The array q(S t ) is the cumulative excitation of future attenuation superposition. The specific solution process can be in all possible states S t and S′ t Repeat the iterative calculation until the two converge.

5. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: In step S4, global path planning information is constructed based on the vehicle positioning information and the target point of interest information, including: According to the device information of the vehicle-mounted device, obtain the current corresponding vehicle status information of the vehicle; Obtain the vehicle's current corresponding environmental perception information based on the device information of the on-board device; Obtain information about points of interest and planned routes based on the pre-installed on-site map service; Based on certain planning path rules, the relationship between the path starting point and the position of the control point in the planned path is established. The current path starting point is Q i (i=1,2,…,b), the control point in the planned path is C i (i=1,2,…,n+1), according to the third-order spline curve smoothing, the smooth relationship between the path points and the control points is established as follows: Based on the smooth relationship between the path points and the control points, a path from the starting point Q1 to the end point Q is established. n The linear equations for : In addition, two more conditions need to be added: C0 = 2C1-C2 and C n+1 =2C n -C n-1 , that is, the starting point and end point of the path are C0C1, C n C n+1 Tangent.

6. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: In the step S5, a vehicle motion model is constructed and a vehicle control model is generated according to the path planning information, including: according to the vehicle positioning parameters (x i ,y i ,z i ), a control model of the vehicle at the field end is established based on the geometric relationship of the control object, and the vehicle model placed in the field end coordinate system is simplified. The front and rear wheel turning angles are recorded as δ f and δ r The distances from the vehicle's center of mass G to the front and rear axles are represented by L f and L r Indicates that the velocity of the center of mass is V, and the angle between the velocity direction and the X axis of the vehicle coordinate system is The vehicle's yaw rate is represented by ω, and the sine theorem is used to obtain the vehicle's L f The ratio of the trajectory radius r and the front wheel turning angle δ of the vehicle f The angle between the velocity direction and the vehicle coordinate system X Function expression relationship: Similarly, the vehicle's L can be obtained r The ratio of the trajectory radius r and the rear wheel turning angle δ of the vehicle r The angle between the velocity direction and the vehicle coordinate system X Function expression relationship: The L of the above vehicle f , L r , front wheel angle, rear wheel angle and the angle between the velocity direction and the vehicle coordinate system X By adding and merging the two function expressions, we can get the steering trajectory motion equation: The wheelbase of the vehicle is represented by L, then L = L f +L r , the steering trajectory motion equation can be expressed as: When the radius r of the vehicle's motion trajectory changes slowly, the vehicle's yaw rate is represented by ω, then ω will be equal to the vehicle's angular velocity, and we can get: The vehicle motion model equation based on wheel angle and vehicle speed can be obtained: For a front-wheel steering vehicle, the rear wheel steering angle is 0 degrees, and the above vehicle control motion model equation can be simplified to: If the heading angle γ of the vehicle is denoted as Δt, and the period of sending the control command from the last moment to the current moment is denoted as Δt, then the heading angle γ of the vehicle can be expressed as: Assume that the vehicle positioning parameters of the two-dimensional coordinate plane at the current moment are recorded as (x i ,y i ), the increments of the vehicle's position in the X-axis and Y-axis directions are Δx and Δy respectively, then the vehicle control model equation is: According to the vehicle control model equation, vehicle control parameters are obtained, and the vehicle is remotely controlled in response to the vehicle's unmanned cruise parking and unmanned cruise pick-up.

7. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: Also includes: When trajectory planning information is processed according to the positioning parameter information and the control device, control parameter information is sent to the vehicle, wherein the control parameter information is configured to terminate the execution of the current control method.

8. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: The field equipment includes: Bluetooth beacons, Bluetooth gateways, POE switches, routers and LTE / 5G base stations; The Bluetooth beacon is used to send preset positioning information, and obtains Bluetooth beacon positioning parameters according to the preset positioning information of the field device, wherein the preset positioning information is used to represent the first positioning mode of the sending module and the vehicle; The Bluetooth gateway is used to obtain the working status information of the Bluetooth beacon; The POE switch is used to power the Bluetooth gateway and send working status information to the router; The router is used to receive the working status information sent by the POE switch and send the working status to the service server; the LTE / 5G base station is used for information transmission between vehicle-side equipment, service servers and mobile phones / mobile terminals.

9. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: The vehicle-side device includes a control device, a vehicle-mounted Bluetooth unit, a vehicle-mounted gateway control unit and an intelligent network control unit; The vehicle-mounted Bluetooth unit is used to receive device information of the field-side device; The vehicle gateway control unit receives positioning parameters, control parameters of the control device, vehicle status information and environmental perception information; The vehicle gateway control unit sends control parameters to the actuator device to control the vehicle movement; The vehicle gateway control unit sends the current vehicle positioning parameters, vehicle status information and environmental perception information to the intelligent network control unit; The intelligent connected control unit has a built-in intrusion protection mechanism to monitor the data security of positioning parameters, control parameters of control devices, vehicle status information and environmental perception information received through the vehicle gateway; The intelligent connected control unit sends the current vehicle positioning parameters, vehicle status information and environmental perception information to the business server.

10. The multi-source fusion parking lot collaborative intelligent vehicle positioning and control method according to claim 1 is characterized by: The services that can be implemented on the business side include pre-set site map services, positioning services, information transmission services, identity authentication and access control, and the establishment of a security framework model; Among them, the pre-installed map service and positioning service provide parking space information and key point information to vehicle-side devices and mobile phones / mobile terminals. The information transmission service sends vehicle positioning parameters, vehicle status information and environmental perception information to mobile phones / mobile terminals; Authentication means verifying the identity of the mobile phone / mobile terminal user; Authentication is to verify whether the user's mobile phone / mobile terminal has the right to access the intelligent vehicle service system; access control is to grant users who have established an authentication relationship access to the intelligent vehicle service system communication data; An intrusion protection mechanism is deployed in the mobile phone / mobile terminal application layer, which can perform security monitoring on parking space information and key point information data sent from the business end through pre-set map services and positioning services; The data side includes the stored business database, user database and map database, pre-set field map data, customer information data, smart car EDR data and business side data.

Images