An automatic parking system and method based on wireless signal field guidance

Abstract

The application relates to an automatic parking system and method based on wireless signal field guidance, belonging to the technical field of parking lot management, which comprises a control module and a wireless positioning module which are electrically connected with each other, the control module is previously input with a grid constituted by parking lot paths as a basic grid, the basic grid in the control module is previously input with parking space positions, the wireless positioning module is used for uploading the positions of each vehicle in the parking lot to the control module, and the control module is used for mapping the positions of each vehicle in the parking lot to the basic grid; the control module is used for planning a path for each vehicle entering the parking lot by using an A-star algorithm, the control module periodically judges whether there is an obstacle on the path of each vehicle, and the control module plans a local path for bypassing the obstacle by using a Dlite algorithm when the judgment result is yes; the application has the characteristics of considering both the calculation speed and dynamic adaptability.

Description

Technical Field

[0001] This invention belongs to the field of parking management technology, specifically relating to an automatic parking system and method based on wireless signal field guidance. Background Technology

[0002] With my country's economic development, the number and ownership rate of private cars are constantly increasing. The increasing number of private cars requires parking lots with larger capacity. In addition to the volume of the parking lot itself, the navigation efficiency of the parking lot also affects the efficiency of the parking lot. For example, when vehicles are misguided or congested in the parking lot, even if there are empty spaces, they cannot park. Therefore, parking lot guidance systems are needed to provide parking and wayfinding guidance.

[0003] Traditional parking lot navigation relies on manual or fixed signage for finding parking spaces, which is inefficient and prone to congestion. Traditional automated guidance systems rely on vehicle sensors, are highly susceptible to environmental interference, and are costly. To address this, Chinese patent CN109859525B discloses a parking space navigation method based on the A* algorithm. This method divides the parking lot into a grid, with each grid cell considered a vertex. The starting point is placed in set A, and set B is left empty. Then, the vertices in A are sorted in ascending order of their cost values, and the first vertex Vi is placed in B. It is then determined whether Vi is the destination; if so, navigation ends; otherwise, Vi's child vertices Vj are expanded. If Vj is not in either A or B, it is placed in A, and its pointer is set to its parent vertex Vi. If Vj exists in A, the cost value of Vj in set A is updated, and its pointer is set to Vi. If Vj exists in B, this vertex is not considered. This process is repeated until navigation ends. This invention solves the problem that existing parking space navigation methods cannot quickly and effectively find the shortest path. This invention can be used for parking space management.

[0004] The above-mentioned scheme uses the A* algorithm to achieve relatively accurate vehicle positioning and path planning. However, individual algorithms have limitations. For example, while the A* algorithm is fast, it is mainly suitable for static or low-frequency dynamic environments. However, vehicles in parking lots may park or leave at any time, and in some cases, they may face high-frequency dynamic changes. Temporary obstacles may also appear, making it difficult for a single A* algorithm to handle such situations. Other algorithms adapted to high-frequency dynamic environments require greater computing power and are slower, increasing the cost and power consumption of the computing terminal. Therefore, a wireless signal-guided automatic parking system and method that balances computing speed and dynamic adaptability is needed. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides an automatic parking system and method based on wireless signal field guidance, which features both computational speed and dynamic adaptability.

[0006] The object of the present application can be achieved by the following technical solutions:

[0007] The automatic parking system based on wireless signal field guidance comprises a control module and a wireless positioning module which are electrically connected to each other, the control module has a grid of parking lot paths as a basic grid input in advance, the basic grid in the control module has a parking space position input in advance, the wireless positioning module is used to upload the position of each vehicle in the parking lot to the control module, and the control module is used to map the position of each vehicle in the parking lot to the basic grid.

[0008] The control module is used to plan a path for each vehicle entering the parking lot by using an A-star algorithm, the control module is used to periodically determine whether there is an obstacle on the path of each vehicle, and the control module is used to plan a local path to bypass the obstacle by using a Dlite algorithm when the determination result is yes.

[0009] As a preferred technical solution of the present application, the control module is used to periodically determine whether there is an obstacle on the path of each vehicle, and the control module is used to create a temporary planning space around the obstacle in the basic grid and plan a path to bypass the obstacle in the temporary planning space by using a Dlite algorithm when the determination result is yes.

[0010] As a preferred technical solution of the present application, the control module is used to obtain the number of currently driving vehicles in the parking lot, the control module is used to periodically determine whether there is an obstacle on the path of each vehicle at a frequency F, the control module is used to determine whether the number of currently driving vehicles exceeds a threshold value, and the value of F is increased when the determination result is yes.

[0011] As a preferred technical solution of the present application, the control module is used to obtain the number C of currently driving vehicles in the parking lot, the control module is used to periodically determine whether there is an obstacle on the path of each vehicle at a frequency F, wherein F=C / C0×a, C0 is a standard number input in advance, 0.2C0≤C≤2C0, and a is a correction coefficient input in advance.

[0012] As a preferred technical solution of the present application, the control module creates a temporary planning space with an area of M around the obstacle in the basic grid when the determination result is yes, the control module is used to obtain the number value of the obstacle and determine whether the number value of the obstacle exceeds a threshold value, and the value of M is increased when the number value of the obstacle or the number of currently driving vehicles exceeds the threshold value.

[0013] As a preferred technical solution of the present application, the control module is used to acquire a quantity value Z of the obstacle, and when the judgment result is yes, the control module creates a temporary planning space with an area of M around the obstacle in the basic grid, wherein M=Z / Z0x b x M0, M≤0.5T, T is the total area of the basic grid, Z0 is a reference quantity value input in advance, b is a correction coefficient input in advance, and M0 is an area reference value input in advance.

[0014] As a preferred technical solution of the present application, the wireless positioning module comprises a UWB module and a narrow wave positioning module, the narrow wave positioning module comprises a WiFi module and a Bluetooth module, and the control module calculates the position of the vehicle in the parking lot according to a weighted average of values of coordinates provided by the UWB module, the WiFi module and the Bluetooth module.

[0015] As a preferred technical solution of the present application, the control module judges whether the operating power of the WiFi module and the Bluetooth module exceeds a threshold value, and when the judgment result is yes, the control module reduces the calculation weight of the UWB module when calculating the position of the vehicle in the parking lot according to a weighted average of values of coordinates provided by the UWB module, the WiFi module and the Bluetooth module.

[0016] An automatic parking method based on wireless signal field guidance, which is suitable for the automatic parking system based on wireless signal field guidance and comprises the following steps:

[0017] Step one: the control module pre-inputs a grid constituted by parking lot paths as a basic grid;

[0018] Step two: the wireless positioning module is used to upload the position of each vehicle in the parking lot to the control module, and the control module is used to map the position of each vehicle in the parking lot to the basic grid;

[0019] Step three: the control module is used to plan a path for each vehicle entering the parking lot by using an A-star algorithm, the control module periodically judges whether there is an obstacle on the path of each vehicle, the control module creates a temporary planning space around the obstacle in the basic grid when the judgment result is yes, and a Dlite algorithm is used to plan a path bypassing the obstacle in the temporary planning space.

[0020] The present application has the following beneficial effects:

[0021] (1) by making the control module for each car into the parking lot using A star algorithm planning path, the control module periodically determines whether there is an obstacle on the path of each vehicle, the control module uses Dlite algorithm to plan the local path to bypass the obstacle when the result is yes, so according to the overall route change probability in the parking lot, only low frequency local small obstacle will appear, when planning the route for each vehicle, first use A star algorithm to plan the overall path, make A star play the characteristics of fast calculation, at the same time ensure that A star algorithm adapts to static or low frequency dynamic environment and is consistent with the overall environment of parking lot; Secondly, when there is an obstacle, the local path is re planned by using Dlite algorithm, which ensures that Dlite algorithm is more suitable for high frequency change environment, at the same time, reduces the path planning range of Dlite algorithm, and then reduces the defect of high calculation amount of Dlite algorithm to the load of system;

[0022] (2) by making the control module determine whether the number of current driving vehicles exceeds the threshold value, and increasing the frequency of obtaining obstacles when the result is yes, to ensure that in the parking lot environment, when the number of vehicles is small and the probability of obstacle generation is low, the system operation load is reduced, when the number of vehicles is large and the probability of obstacle generation is high, the frequency of obtaining obstacles is increased, to ensure the accuracy of route guidance;

[0023] (3) by making the control module increase the size of the temporary planning space when the obstacle or the number of current driving vehicles exceeds the threshold value, so that when the number or probability of obstacle generation is high, the temporary planning space cannot cover the possible bypass route, the range of temporary planning space is expanded, to ensure the accuracy of route guidance, when the number or probability of obstacle generation is low, the temporary planning space has a large probability to cover the possible bypass route, the range of temporary planning space is reduced, to reduce the transportation load;

[0024] (4) by calculating the weighted average of the values of the coordinates provided by the UWB module, WiFi module and Bluetooth module when the running power of WiFi module and Bluetooth module exceeds the threshold value, to calculate the position of the vehicle in the parking lot, to reduce the calculation weight of UWB module, to reduce the weight of UWB in coordinate calculation when the interference probability of WiFi module and Bluetooth module to UWB module is large and the positioning accuracy of UWB is low, to improve the accuracy of route guidance, when the interference probability of WiFi module and Bluetooth module to UWB module is small, to increase the weight of UWB module, to make full use of the characteristics of UWB module to a greater extent, to improve the accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to facilitate the understanding of those skilled in the art, the present application will be further described below with reference to the drawings.

[0026] Figure 1 The control loop diagram of the present application. DETAILED DESCRIPTION

[0027] To further clarify the technical means and effects taken by the present application to achieve the predetermined inventive purpose, the specific embodiments, structures, features and effects thereof according to the present application are described in detail below in combination with the drawings and preferred embodiments.

[0028] Referring to Figure 1 An automatic parking system based on wireless signal field guidance comprises a control module and a wireless positioning module which are electrically connected to each other, the control module has a grid of parking lot paths pre-input as a basic grid, the basic grid in the control module has a parking space position pre-input, the wireless positioning module is used to upload the position of each vehicle in the parking lot to the control module, and the control module is used to map the position of each vehicle in the parking lot to the basic grid.

[0029] The control module is used to plan a path for each vehicle entering the parking lot by using an A-star algorithm, the control module is used to periodically determine whether there is an obstacle on the path of each vehicle, and the control module is used to plan a local path bypassing the obstacle by using a Dlite algorithm when the determination result is yes.

[0030] As to the wireless positioning module, the wireless positioning module comprises a UWB module, a WiFi module and a Bluetooth module.

[0031] As to the UWB module, the UWB module comprises a UWB anchor point and a plurality of UWB tags, the plurality of UWB tags are respectively arranged on the plurality of vehicles, the vehicles are captured by the UWB anchor point when the vehicles enter the parking lot, each UWB tag has a unique identification code, and the UWB module distinguishes the plurality of vehicles according to the identification code.

[0032] In the basic grid, each multi-route intersection point, such as a T-shaped intersection and a cross-shaped intersection, is a node, after each vehicle enters the parking lot, a starting point is first determined according to the entrance of the vehicle, then the control module selects a unique empty parking space corresponding to the vehicle, the empty parking space is determined as the end point of the vehicle, and then the A-star algorithm is used to calculate the total cost of each node for driving to the end point.

[0033] In the formula, F(n) is the total cost, G(n) is the actual moving cost from the starting point to the current node n, and H(n) is the heuristic estimated cost from the current node n to the end point.

[0034] Specifically, as to the calculation process, the calculation process of a typical A-star algorithm can be referred to, and in the present embodiment, the following steps are included.

[0035] Step one: firstly, put the starting point into set A and set B empty; then arrange the nodes in set A according to the value from small to large, and put the first node in the arrangement into set B;

[0036] Step two: then judge whether the node newly put into set B is the terminal point; if yes, the path generation is completed, if not, take this node as the parent node, the adjacent node of the parent node as the child node, and take the path distance between the nodes as the cost, and calculate the G(n) value of each child node,

[0037] Step three: judge whether the child node is in set A or set B, if in set A, replace the value of the parent node with the value of the node, and return to step two;

[0038] For the design of heuristic function H(n), since the parking lot can be regarded as a grid map, the calculation method is Manhattan distance, that is, H(n) = |xn-xgoal|+|yn-ygoal|, wherein xgoal and ygoal are the coordinates of the target position, and xn and yn are the coordinates of the node to be calculated;

[0039] For the process of periodically judging whether there is an obstacle on the path of each vehicle by the control module, specifically, the control module is electrically connected with a plurality of obstacle scanners, and the plurality of obstacle scanners are arranged on the path of the parking lot, covering all the paths of the parking lot, periodically capturing all the objects on the path which are higher than the road surface and have a volume greater than a set value, and the set value is determined by the operator according to the demand, and when the judgment of the obstacle is more strict, the set value is set to a lower level;

[0040] For the judgment of the obstacle, any object with a speed lower than 5km / h scanned by the scanner is judged as an obstacle;

[0041] The control module periodically judges whether there is an obstacle on the path of each vehicle, and the control module creates a temporary planning space around the obstacle in the basic grid when the judgment result is yes, and uses the Dlite algorithm to plan a path around the obstacle in the temporary planning space;

[0042] Specifically, the control module periodically judges whether there is an obstacle on the path of each vehicle at a frequency F, and when the judgment result is yes, the control module draws a region in the basic grid as a temporary planning space, the boundary of the temporary planning space intersects with two points of the original path, and then updates the local path in the temporary planning space by using the D Lite algorithm, the updated local path bypasses the obstacle, and ensures that it is connected with the two intersection points of the boundary of the temporary planning space and the original path respectively, completes the local path update, and bypasses the obstacle;

[0043] Since the A-star algorithm has the characteristics of fast speed but is not suitable for dynamic environment, it is more suitable for static or low-frequency dynamic environment, and the overall path of the parking lot is fixed, and the obstacles will not appear or disappear frequently, therefore, using the A-star algorithm to calculate the overall path can make full use of the advantages of the A-star algorithm and avoid the shortcomings of the A-star algorithm, and since the Dlite algorithm consumes more computing power when used for long-distance path planning, but it is more suitable for dynamic environment, therefore, using the Dlite algorithm to update the local path can reduce the defect that the Dlite algorithm consumes more computing power, and it is more efficient than the pure A-star algorithm to plan the bypass path;

[0044] Therefore, by using the control module to plan the path for each vehicle entering the parking lot using the A-star algorithm, the control module periodically determines whether there is an obstacle on the path of each vehicle, and the control module uses the Dlite algorithm to plan a local path to bypass the obstacle when the determination result is yes, so that according to the characteristics of the overall route in the parking lot with low change probability and only low-frequency small local obstacles, when planning the route for each vehicle, first, the overall path is planned using the A-star algorithm, which ensures that the A-star algorithm is adapted to the static or low-frequency dynamic environment and is consistent with the overall environment of the parking lot; second, the local path is re-planned using the Dlite algorithm when there is an obstacle, which ensures that the Dlite algorithm is more suitable for high-frequency changing environment, reduces the path planning range of the Dlite algorithm, and further reduces the influence of the high computational amount of the Dlite algorithm on the system.

[0045] The control module is configured to obtain the number of currently driving vehicles in the parking lot, and the control module is configured to determine whether the number of currently driving vehicles exceeds a threshold value, and increase the value of F when the determination result is yes.

[0046] Specifically, the control module is configured to obtain the number C of currently driving vehicles in the parking lot, and the control module is configured to periodically determine whether there is an obstacle on the path of each vehicle at a frequency F, wherein F=C / C0×a, C0 is a standard number input in advance, 0.2C0≤C≤2C0, and a is a correction coefficient input in advance.

[0047] When the number C is greater than C0, it represents that there are more vehicles, and the probability of obstacle generation is higher, at this time, the frequency F is higher, the frequency of obtaining obstacles is increased, and the accuracy of route guidance is ensured;

[0048] When C is less than C0, it represents that there are fewer vehicles, and the probability of obstacle generation is lower, the system operation load is reduced;

[0049] The control module judges whether the current number of vehicles is greater than a threshold value, and increases the frequency of obtaining obstacles when the result is yes, so as to ensure that when the number of vehicles is small and the probability of obstacle generation is low in a parking lot environment, the system operation load is reduced, and when the number of vehicles is large and the probability of obstacle generation is high, the frequency of obtaining obstacles is increased, so as to ensure the accuracy of route guidance;

[0050] When the number of obstacles or the probability of generation is high, and the temporary planning space cannot cover the possible detour route, even if the Dlite algorithm with higher efficiency is used, a new route cannot be generated, at this time, the temporary planning space needs to be expanded, and when the temporary planning space is too large, the Dlite algorithm consumes a large amount of calculation power and cannot reduce the calculation power consumption, therefore, the control module creates a temporary planning space with an area of M around the space of the obstacle in the basic grid when the result is yes, the control module is used to obtain the number value of the obstacle and judge whether the number value of the obstacle is greater than a threshold value, and the control module increases the value of M when the number value of the obstacle or the current number of vehicles is greater than the threshold value;

[0051] Specifically, the control module is used to obtain the number value Z of the obstacle, and the control module creates a temporary planning space with an area of M around the space of the obstacle in the basic grid when the result is yes, wherein M=Z / Z0×b×M0, M≤0.5T, T is the total area of the basic grid, Z0 is a reference number value input in advance, b is a correction coefficient input in advance, and M0 is an area reference value input in advance;

[0052] When the number value Z of the obstacle is large, the number of obstacles is high, and the temporary planning space cannot cover the possible detour route, the range of the temporary planning space needs to be expanded, at this time, the value of M=Z / Z0×b×M0 is large, and the expansion of the range of the temporary planning space is completed;

[0053] When the number value Z of the obstacle is small, the number of obstacles is low, and the temporary planning space cannot cover the possible detour route, the range of the temporary planning space needs to be expanded, at this time, the value of M=Z / Z0×b×M0 is large, and the expansion of the range of the temporary planning space is completed;

[0054] By increasing the size of the temporary planning space when the number value of the obstacle or the current number of vehicles is greater than a threshold value, the range of the temporary planning space is expanded when the number of obstacles or the probability of generation is high and the temporary planning space cannot cover the possible detour route, so as to ensure the accuracy of route guidance, and the range of the temporary planning space is reduced when the number of obstacles or the probability of generation is low and the temporary planning space has a high probability of covering the possible detour route, so as to reduce the transportation load;

[0055] Specifically, the wireless positioning module includes a UWB module and a narrow wave positioning module, the narrow wave positioning module includes a WiFi module and a Bluetooth module, and the control module calculates the position of the vehicle in the parking lot according to a weighted average of values of coordinates provided by the UWB module, the WiFi module and the Bluetooth module.

[0056] Since the frequency bands of the WiFi module and the Bluetooth module cover the working frequency band of the UWB, when the power of the WiFi module and the Bluetooth module is relatively large, the error probability of the UWB module is relatively large, and the weight needs to be appropriately reduced, the control module judges whether the running power of the WiFi module and the Bluetooth module exceeds a threshold value, and when the judgment result is yes, the control module reduces the calculation weight of the UWB module when calculating the position of the vehicle in the parking lot according to a weighted average of values of coordinates provided by the UWB module, the WiFi module and the Bluetooth module.

[0057] By reducing the calculation weight of the UWB module when calculating the position of the vehicle in the parking lot according to a weighted average of values of coordinates provided by the UWB module, the WiFi module and the Bluetooth module when the running power of the WiFi module and the Bluetooth module exceeds a threshold value, the weight of the UWB in coordinate calculation is reduced when the interference probability of the WiFi module and the Bluetooth module to the UWB module is relatively large and the positioning accuracy of the UWB is relatively low, the route guidance accuracy is improved, the weight of the UWB module is increased when the interference probability of the WiFi module and the Bluetooth module to the UWB module is relatively small, and the characteristics of the UWB module are used to the greatest extent, and the accuracy is improved.

[0058] An automatic parking method based on wireless signal field guidance, suitable for the automatic parking system based on wireless signal field guidance, further comprising the following steps:

[0059] Step one: the control module pre-inputs a grid constituted by parking lot paths as a basic grid;

[0060] Step two: the wireless positioning module is used to upload the positions of vehicles in the parking lot to the control module, and the control module is used to map the positions of the vehicles in the parking lot to the basic grid;

[0061] Step three: the control module is used to plan a path for each vehicle entering the parking lot using the A-star algorithm, the control module periodically judges whether there is an obstacle on the path of each vehicle, and the control module creates a temporary planning space around the obstacle in the basic grid when the judgment result is yes, and plans a path around the obstacle in the temporary planning space using the Dlite algorithm.

[0062] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in any form. Although the present application has been disclosed with the preferred embodiments as above, it is not intended to limit the present application. Any person skilled in the art can make some changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, as long as the changes or modifications do not deviate from the technical solution of the present application. Any modification, change, equivalent change and modification of the above embodiments made according to the technical essence of the present application still belong to the scope of the technical solution of the present application.

Claims

1. An automatic parking system based on wireless signal field guidance, characterized in that: The system includes a control module and a wireless positioning module that are electrically connected to each other. The control module is pre-inputted with a grid consisting of parking lot paths as a base grid. The base grid in the control module is pre-inputted with parking space locations. The wireless positioning module is used to upload the location of each vehicle in the parking lot to the control module. The control module is used to map the location of each vehicle in the parking lot to the base grid. The control module is used to plan the path for each vehicle entering the parking lot using the A* algorithm. The control module periodically determines whether there are obstacles on the path of each vehicle. When the determination result is yes, the control module uses the Dlite algorithm to plan a local path to bypass the obstacle. The control module periodically determines whether there are obstacles on the path of each vehicle. When the determination result is yes, the control module creates a temporary planning space around the obstacle in the basic grid and uses the Dlite algorithm to plan a path around the obstacle in the temporary planning space. When the judgment result is yes, the control module creates a temporary planning space with an area of ​​M around the obstacle in the basic grid. The control module is used to obtain the number of obstacles and determine whether the number of obstacles exceeds the threshold. When the number of obstacles or the number of currently driving vehicles exceeds the threshold, the control module increases the value of M. The control module is used to obtain the number value Z of obstacles. When the judgment result is yes, the control module creates a temporary planning space with an area of ​​M around the obstacle in the basic grid, where M=Z / Z0×b×M0, M≤0.5T, T is the total area of ​​the basic grid, Z0 is the pre-input reference quantity value, b is the pre-input correction coefficient, and M0 is the pre-input area reference value.

2. The automatic parking system based on wireless signal field guidance according to claim 1, characterized in that: The control module is used to obtain the number of vehicles currently driving in the parking lot. The control module periodically determines whether there are obstacles on the path of each vehicle at a frequency F. The control module determines whether the number of vehicles currently driving exceeds a threshold, and increases the value of F when the determination result is yes.

3. The automatic parking system based on wireless signal field guidance according to claim 2, characterized in that: The control module is used to obtain the number of vehicles C currently driving in the parking lot. The control module periodically determines whether there are obstacles on the path of each vehicle at a frequency F, where F=C / C0×a, C0 is a pre-input standard number, 0.2C0≤C≤2C0, and a is a pre-input correction coefficient.

4. An automatic parking system based on wireless signal field guidance according to claim 1, characterized in that: The wireless positioning module includes a UWB module and a narrowband positioning module. The narrowband positioning module includes a WiFi module and a Bluetooth module. The control module calculates the vehicle's position in the parking lot based on the weighted average of the coordinate values ​​provided by the UWB module, WiFi module, and Bluetooth module.

5. An automatic parking system based on wireless signal field guidance according to claim 4, characterized in that: The control module determines whether the operating power of the WiFi module and Bluetooth module exceeds the threshold. If the determination result is yes, when calculating the weighted average of the coordinate values ​​provided by the UWB module, WiFi module and Bluetooth module to calculate the vehicle's position in the parking lot, the calculation weight of the UWB module is reduced.

6. An automatic parking method based on wireless signal field guidance, characterized in that: An automatic parking system based on wireless signal field guidance, applicable to any one of claims 2 to 5, further includes the following steps: Step 1: The control module pre-inputs a grid consisting of parking lot paths as the base grid; Step 2: The wireless positioning module is used to upload the location of each vehicle in the parking lot to the control module, and the control module is used to map the location of each vehicle in the parking lot to the basic grid. Step 3: The control module uses the A* algorithm to plan the path for each car entering the parking lot. The control module periodically checks whether there are obstacles on the path of each car. When the check result is yes, the control module creates a temporary planning space around the obstacle in the basic grid and uses the Dlite algorithm to plan a path around the obstacle in the temporary planning space.

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