CN117152990A - Automatic intelligent garage system and method based on artificial intelligence - Google Patents
Automatic intelligent garage system and method based on artificial intelligence Download PDFInfo
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/145—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas
- G08G1/146—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas where the parking area is a limited parking space, e.g. parking garage, restricted space
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Abstract
The application discloses an automatic intelligent garage system and method based on artificial intelligence, and relates to the technical field of intelligent navigation; according to the intelligent parking management method, the parking space image data of each parking space are collected, the corresponding parking space image model is built according to the parking space image data, the parking space image models are sequentially arranged, the sub-garage image models of the corresponding floors are further obtained, all the sub-garage image models are stacked according to actual scenes, the garage image models are obtained, corresponding parking spaces are matched from the garage image models according to parking requirements, the garage entrance is further taken as a starting point, the target parking space is taken as an end point, a plurality of driving paths are further built, the optimal driving paths are selected from the plurality of driving paths according to the optimal driving paths of other parking requirements, a parking strategy is generated according to the parking requirements, the optimal driving paths and the matched parking spaces, and corresponding vehicles are guided to the corresponding parking spaces according to the parking strategy.
Description
Technical Field
The application relates to the technical field of intelligent navigation, in particular to an automatic intelligent garage system and method based on artificial intelligence.
Background
With the deep town, the scale of the city is larger and larger, and the quantity of the automobile in the city is also increasing year by year. However, the problem of difficult parking is always plagued by limiting the daily life of people, and the corresponding parking space is often difficult to find due to excessive vehicles in daily travel;
the intelligent garage system is a system for realizing automatic parking and taking vehicles by utilizing an artificial intelligence technology, relates to automatic driving and automatic parking of vehicles, can cause accidents or damage to the vehicles if the safety of the system cannot be ensured, and is easy to cause vehicle blockage when the vehicles in the intelligent garage are too many, so that the problem of the prior art is solved that the vehicles are ensured to find proper parking spaces while the vehicles are ensured to normally run.
Disclosure of Invention
In order to solve the technical problems, the application aims to provide an automatic intelligent garage system and method based on artificial intelligence.
In order to achieve the above object, the present application provides the following technical solutions:
the automatic intelligent garage system based on the artificial intelligence comprises a cloud computing platform, wherein the cloud computing platform is in communication connection with a garage management module, a parking space scheduling module and a parking space guiding module;
the garage management module is used for collecting the parking space image data of each parking space, establishing corresponding parking space image models according to the parking space image data, and sequentially arranging the parking space image models to obtain a garage image model;
the parking space scheduling module is used for matching corresponding parking spaces from the garage image model according to parking requirements and establishing an optimal driving path of the parking requirements according to the optimal driving paths of other vehicles;
the parking space guiding module is used for guiding the corresponding vehicle to park according to the parking strategy.
Further, the building process of the garage image model comprises the following steps:
the garage management module is provided with a garage data acquisition unit, a garage database and a garage image model unit; the garage data acquisition unit is provided with cameras and wireless signal devices for all the parking spaces in the garage, and numbers are arranged for all the parking spaces, so that the garage data acquisition unit shoots the parking space image data of all the parking spaces through the cameras, and sends the parking space image data to the garage database after representing the numbers of the corresponding parking spaces through the wireless signal sending device;
the parking space image model unit sequentially takes out parking space image data of each layer from the garage database, and further establishes corresponding parking space image models according to the parking space image data of each parking space in proportion, and sequentially arranges each parking space image model according to the arrangement condition of each parking space in an actual scene, so as to obtain sub-garage image models of the corresponding layer, and stacks all the sub-garage image models according to the actual scene to obtain the garage image model.
Further, the sizes of all the parking space image models in the garage image model are not completely the same, the corresponding sizes of all the parking space image models are marked according to the actual parking space sizes, and the idle state and the using state of all the parking space image models in the garage image model are set.
Further, the process of matching the corresponding parking spaces from the garage image model according to the parking requirements includes:
sending a parking requirement to a parking space scheduling module through a mobile terminal, wherein the parking requirement comprises a vehicle size, a license plate number, a mobile terminal IP address and an expected parking time;
after the parking space scheduling module receives the parking requirement, matching a parking space image model with the parking space size being larger than or equal to the vehicle size and in an idle state to the garage image model according to the vehicle size in the parking requirement;
if the parking space image model meeting the parking requirement is matched, a temporary parking space-free prompt is sent to the mobile terminal of the corresponding user, and if the parking space image model meeting the parking requirement is matched, the number of the corresponding parking space image and the position of the corresponding parking space image in the garage image model are recorded, the number is marked as a target parking space, and the license plate number of the user is marked.
Further, the generating process of the optimal driving path includes:
taking a garage entrance as a starting point and a target parking space as an ending point, further establishing a plurality of driving paths, and marking corresponding license plate numbers and setting numbers for each driving path;
setting a standard vehicle speed, wherein the standard vehicle speed is the highest speed limit of a garage, and mapping all the corresponding generated driving paths into a garage image model when a parking space scheduling module receives a driving path of a new parking demand and the previous parking demand has selected an optimal driving path;
each vehicle image model with license plate number is driven on the corresponding optimal driving path according to the standard vehicle speed, and the vehicle image model corresponding to the latest parking requirement is driven on all driving paths in a time synchronization mode;
if the vehicle image model corresponding to the latest parking requirement is expected to collide with other vehicle image models in the driving path, corresponding collision nodes are marked in the driving path, and the corresponding collision nodes are marked in the driving path to collide with the driving path;
if the vehicle image model corresponding to the latest parking requirement does not collide with any vehicle image model in the running path, marking the running path as a smooth running path;
the standard vehicle speed is taken as the running speed of the vehicle image model, the expected running time of each unobstructed running path is obtained, the expected running time of each unobstructed running path is compared with each other, and the unobstructed running path with the smallest expected running time is marked as the optimal running path.
Further, if the latest parking requirement does not have a clear running path, selecting a collision running path with the least collision nodes from the collision running paths as an optimal running path, setting a collision label for the collision running path, and marking the collision nodes on the optimal running path.
Further, after the optimal driving path is selected from the plurality of driving paths corresponding to the parking requirement, other driving paths except the optimal driving path are removed from the garage image model, and when the parking space scheduling module receives the vehicle parking information from the parking space guiding module, the optimal driving path corresponding to the license plate number is removed from the garage image model.
Further, the process of parking the corresponding vehicle according to the parking strategy includes:
when the parking space guiding model receives the real-time position of the mobile terminal, the current position of the mobile terminal is taken as the starting position of the vehicle, the current position of the mobile terminal is mapped on the optimal driving path in the parking strategy, the optimal driving path with the real-time position of the vehicle is synchronized in real time in the garage image model of the mobile terminal, and other vehicles in parking navigation or off-position navigation are synchronously mapped in the garage image model;
if no collision label exists on the optimal driving path in the parking strategy, after the corresponding vehicle reaches the predicted parking space and the parking is completed, a camera positioned in the parking space shoots the license plate number of the corresponding vehicle in real time, a wireless signal transmitting device transmits a license plate number image to a parking space guiding model, and the parking space guiding model generates vehicle parking information according to the license plate number image and transmits the vehicle parking information to a garage management module, wherein the vehicle parking information comprises the license plate number and the parking space number;
if the optimal driving path in the parking strategy is provided with a collision label, a parking space guiding module sends a warning prompt to a mobile terminal according to the position of a collision node in the optimal driving path in a garage image model, and meanwhile, the garage image model of the mobile terminal marks a corresponding collision node, and then when a corresponding vehicle arrives at an estimated parking space, vehicle parking information is generated and sent to a garage management module;
further, the mobile terminal sends an off-position request to the parking space guiding module, the parking space guiding module sends the off-position request to the parking space scheduling module, the parking space scheduling module adopts the same method for generating the optimal driving path, the parking space is taken as the starting position, the garage outlet is taken as the end point, and the optimal off-position path is generated and sent to the parking space guiding module;
and the parking space guiding module guides the corresponding vehicle to leave the garage according to the optimal leaving path, and meanwhile generates vehicle leaving information and sends the vehicle leaving information to the parking space guiding module.
An automatic intelligent method of an automatic intelligent garage system based on artificial intelligence comprises the following steps:
firstly, collecting parking space image data of each parking space, establishing corresponding parking space image models according to the parking space image data, sequentially arranging the parking space image models to obtain sub-garage image models of corresponding layers, and stacking all the sub-garage image models according to actual scenes to obtain garage image models;
step two, matching corresponding parking spaces from the garage image model according to parking requirements, further taking a garage entrance as a starting point and a target parking space as an end point, further establishing a plurality of running paths, and selecting an optimal running path from the plurality of running paths according to other parking requirements;
and thirdly, generating a parking strategy according to the parking requirement, the optimal driving path and the matched parking space, and guiding the corresponding vehicle to the corresponding parking space according to the parking strategy.
Compared with the prior art, the application has the beneficial effects that:
1. collecting parking space image data of each parking space, establishing corresponding parking space image models according to the parking space image data, sequentially arranging the parking space image models to obtain sub-garage image models of corresponding layers, stacking all the sub-garage image models according to actual scenes to obtain garage image models, and marking the real-time state of the parking space on the garage image models to improve the management efficiency of the parking space in the garage to a certain extent;
2. according to the parking requirements uploaded by users, matching the corresponding parking spaces from the garage image model, further taking a garage entrance as a starting point, taking a target parking space as an end point, further establishing a plurality of driving paths, selecting the optimal driving paths from the plurality of driving paths according to the optimal driving paths corresponding to the parking requirements of other users, generating a parking strategy according to the parking requirements, the optimal driving paths and the matching parking spaces, further guiding the corresponding vehicles to the corresponding parking spaces according to the parking strategy, and simultaneously establishing the optimal leaving paths by adopting the same method, thereby effectively improving the flexibility and adaptability of the vehicles in the garage in the process of driving to the parking spaces.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for those skilled in the art.
Fig. 1 is a schematic diagram of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail below. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, based on the examples herein, which are within the scope of the application as defined by the claims, will be within the scope of the application as defined by the claims.
As shown in fig. 1, an automated intelligent garage system based on artificial intelligence comprises a cloud computing platform, wherein the cloud computing platform is in communication connection with a garage management module, a parking space scheduling module and a parking space guiding module;
the garage management module is provided with a garage data acquisition unit, a garage database and a garage image model unit;
the garage data acquisition unit is provided with a plurality of cameras which are respectively positioned at each parking space and each corner of the garage and used for acquiring the parking space image data of each parking space;
specifically, cameras and wireless signal devices are arranged on each parking space in the garage, and the parking spaces are provided with numbers, for example, S 1，1 、S 1，2 、……、S n，m Wherein S is n，m The m-th parking space of the n-th garage is represented, n and m are natural numbers larger than 0;
the garage data acquisition unit shoots the parking space image data of each parking space through the camera, and sends the parking space image data to the garage database after representing the number of the corresponding parking space through the wireless signal sending device;
the garage database is used for storing the parking space image data from the garage data acquisition unit, and meanwhile, the parking space image data are classified and stored by taking the layer number as a classification item according to the layer number of the garage where each parking space is located;
the garage image model unit is used for establishing a garage image model according to the image data of each parking space in the parking space database, so as to establish the garage image model;
specifically, the parking space image model unit sequentially takes out parking space image data of each layer from the garage database, and further establishes corresponding parking space image models according to the parking space image data of each parking space in proportion, and sequentially arranges each parking space image model according to the arrangement condition of each parking space in an actual scene, so as to obtain sub-garage image models of the corresponding layer, and stacks all the sub-garage image models according to the actual scene to obtain a garage image model;
further, the sizes of the parking space image models in the garage image model are not completely the same, and the parking space image models are marked with corresponding sizes according to the actual parking space sizes, for example, the number is S 1，2 The parking spaces of the vehicle are marked with 2.4m5.3m;
the method comprises the steps that idle states and using states are set for all parking space image models in a garage image model, corresponding user information is marked on the parking space image model in the using state, and vehicle image models are added on the parking space image model;
and when the garage management module receives the vehicle parking information or the vehicle departure information from the parking space guiding module, the garage management module sends the vehicle parking information or the vehicle departure information to the garage image model unit, and the garage image model unit updates the corresponding parking space image model state in the garage image model.
The parking space scheduling module is used for matching a parking space with a parking requirement uploaded by a user and generating an optimal driving path, and the specific process comprises the following steps:
the parking space scheduling module sends a request for acquiring the garage image model to the garage management module, so that the garage management module sends the garage image model to the parking space scheduling module, and when the garage image model is updated, the garage management module sends the garage image model to the parking space scheduling module in real time;
the user sends a parking requirement to the parking space scheduling module through the mobile terminal, wherein the parking requirement comprises a vehicle size, a license plate number, a mobile terminal IP address, a predicted parking time and a vehicle owner name;
after the parking space scheduling module receives the parking requirement, matching a parking space image model with the parking space size being larger than or equal to the vehicle size and in an idle state to the garage image model according to the vehicle size in the parking requirement;
the method is characterized in that in the process of matching the parking spaces, the parking space scheduling models are matched sequentially from top to bottom according to the number of garage layers;
if the parking space image model which does not meet the parking requirement is matched, a 'temporary parking space free' prompt is sent to the mobile terminal of the corresponding user;
if the parking space image model meeting the parking requirement is matched, the number of the corresponding parking space image and the position of the corresponding parking space image in the garage image model are recorded, the corresponding parking space image is marked as a target parking space, and the license plate number of a user is marked;
further, an optimal driving path is established according to the target parking space, and the specific process comprises the following steps:
taking a garage entrance as a starting point and a target parking space as an ending point, further establishing a plurality of driving paths, marking corresponding license plate numbers for each driving path, and setting a number, for example, the number can be h 1 、h 2 、……、h a A is a natural number greater than 0;
setting a standard vehicle speed, wherein the standard vehicle speed is the highest speed limit of a garage;
every time the parking space scheduling module receives a new driving path of a parking requirement, and when the previous parking requirement has selected an optimal driving path, mapping all the driving paths correspondingly generated into a garage image model;
when the optimal driving path is selected from a plurality of driving paths corresponding to the parking requirement, the driving paths except the optimal driving path are removed from the garage image model, and the parking space scheduling module receives the vehicle parking information from the parking space guiding module, the optimal driving path corresponding to the license plate number is removed from the garage image model;
each vehicle image model with license plate number is driven on the corresponding optimal driving path according to the standard vehicle speed, and the vehicle image model corresponding to the latest parking requirement is driven on all driving paths in a time synchronization mode;
if the vehicle image model corresponding to the latest parking requirement is expected to collide with other vehicle image models in the driving path, corresponding collision nodes are marked in the driving path, and the corresponding collision nodes are marked in the driving path to collide with the driving path;
if the vehicle image model corresponding to the latest parking requirement does not collide with any vehicle image model in the running path, marking the running path as a smooth running path;
calculating the expected running time T of each unobstructed running path by taking the standard vehicle speed as the running speed of the vehicle image model, wherein the calculation formula of the expected running time T is as follows: t (T) b =L b /V Standard of Wherein T is b The representation number is h b Is a predicted travel time of a travel path of L b The representation number is h b B is a natural number greater than 0, and b is equal to or less than a;
comparing the estimated travel time T of each unobstructed travel path with each other, and marking the unobstructed travel path with the minimum estimated travel time T as the optimal travel path;
if the latest parking requirement does not have a clear running path, selecting a collision running path with the least collision nodes from the collision running paths as an optimal running path, setting a collision label on the optimal running path, and marking the collision nodes on the optimal running path;
further, combining the optimal driving path, the number of the predicted parking space and the parking requirement to obtain a parking strategy, and further sending the parking strategy and the garage image model to a parking space guiding module and a mobile terminal of a user, and mapping the optimal driving path in the garage image model.
The parking space guiding module is used for guiding the corresponding vehicle to park according to a parking strategy, and simultaneously establishing an off-site navigation route, and the specific process comprises the following steps:
after receiving the parking policy from the parking space scheduling module, the parking space guiding module sends a communication connection request to the corresponding user mobile terminal according to the IP address of the user mobile terminal in the parking policy, and after receiving and agreeing to the communication connection request, the user mobile terminal sends the actual position to the parking space scheduling module;
when the parking space guiding model receives the real-time position of the user mobile terminal, the current position of the user mobile terminal is taken as the vehicle starting position, the vehicle starting position is mapped into the optimal driving path in the parking strategy, the optimal driving path with the real-time position of the vehicle is synchronized in real time in the garage image model of the user mobile terminal, and other vehicles in parking navigation or off-position navigation are synchronously mapped in the garage image model;
if no collision label exists on the optimal driving path in the parking strategy, after the corresponding vehicle reaches the predicted parking space and the parking is completed, a camera positioned in the parking space shoots the license plate number of the corresponding vehicle in real time, a wireless signal transmitting device transmits a license plate number image to a parking space guiding model, and the parking space guiding model generates vehicle parking information according to the license plate number image and transmits the vehicle parking information to a garage management module, wherein the vehicle parking information comprises a user name, a license plate number and a parking space number;
if the optimal driving path in the parking strategy is provided with a collision label, a parking space guiding module sends a warning prompt to a user moving end according to the position of a collision node in the optimal driving path in the garage image model, and meanwhile, the garage image model of the user moving end marks a corresponding collision node, and further, when a corresponding vehicle arrives at an expected parking space, vehicle parking information is generated and sent to a garage management module;
further, the user can send an off-position request to the parking space guiding module through the mobile terminal, the parking space guiding module sends the off-position request to the parking space scheduling module, the parking space scheduling module adopts the same method for generating the optimal driving path, the parking space is taken as the starting position, the garage outlet is taken as the end point, and the optimal off-position path is generated and sent to the parking space guiding module;
and the parking space guiding module guides the corresponding vehicle to leave the garage according to the optimal leaving path, and meanwhile generates vehicle leaving information and sends the vehicle leaving information to the parking space guiding module.
The application also discloses an automatic intelligent method of the automatic intelligent garage system based on the artificial intelligence, which comprises the following steps:
firstly, collecting parking space image data of each parking space, establishing corresponding parking space image models according to the parking space image data, sequentially arranging the parking space image models to obtain sub-garage image models of corresponding layers, and stacking all the sub-garage image models according to actual scenes to obtain garage image models;
step two, matching corresponding parking spaces from the garage image model according to parking requirements, further taking a garage entrance as a starting point and a target parking space as an end point, further establishing a plurality of running paths, and selecting an optimal running path from the plurality of running paths according to the optimal running paths corresponding to other parking requirements;
and thirdly, generating a parking strategy according to the parking requirement, the optimal driving path and the matched parking space, and guiding the corresponding vehicle to the corresponding parking space according to the parking strategy.
The above embodiments are only for illustrating the technical method of the present application and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present application may be modified or substituted without departing from the spirit and scope of the technical method of the present application.
Claims (8)
1. The automatic intelligent garage system based on the artificial intelligence comprises a cloud computing platform and is characterized in that the cloud computing platform is in communication connection with a garage management module, a parking space scheduling module and a parking space guiding module;
the garage management module is used for collecting the parking space image data of each parking space, establishing corresponding parking space image models according to the parking space image data, and sequentially arranging the parking space image models to obtain a garage image model;
the parking space scheduling module is used for matching corresponding parking spaces from the garage image model according to parking requirements and establishing an optimal driving path of the parking requirements according to the optimal driving paths of other vehicles;
the parking space guiding module is used for guiding the corresponding vehicle to park according to the parking strategy.
2. The automated intelligent garage system of claim 1, wherein the process of building the garage image model comprises:
the garage management module is provided with a garage data acquisition unit, a garage database and a garage image model unit; the garage data acquisition unit is used for setting cameras and wireless signal devices for all the parking spaces in the garage, numbering the parking spaces, shooting the parking space image data of all the parking spaces through the cameras, and sending the image data to the garage database;
the parking space image model unit sequentially takes out parking space image data of each layer from the garage database, further establishes a parking space image model according to the parking space image data, sequentially arranges each parking space image model according to arrangement conditions of each parking space in an actual scene, further obtains sub-garage image models of corresponding garage floors, stacks all the sub-garage image models according to the actual scene, and obtains the garage image model.
3. The automated intelligent garage system based on artificial intelligence of claim 2, wherein the sizes of the respective parking space image models in the garage image model are not identical, the respective parking space image models are labeled with the respective parking space sizes according to the actually corresponding parking space sizes, and the respective parking space image models in the garage image model are provided with an idle state and a use state.
4. The automated intelligent garage system of claim 3, wherein the process of matching respective parking spaces from the garage image model based on parking requirements comprises:
sending a parking requirement to a parking space scheduling module through a mobile terminal, wherein the parking requirement comprises a vehicle size, a license plate number, a mobile terminal IP address and an expected parking time;
according to the vehicle size in the parking requirement, matching a parking space image model with the parking space size being larger than or equal to the vehicle size and in an idle state with the garage image model;
if the parking space image model meeting the parking requirement does not exist, a temporary parking space-free prompt is sent to the mobile terminal, and if the parking space image model meeting the parking requirement is matched, the number of the corresponding parking space image model and the position of the corresponding parking space image model in the garage image model are recorded, and the number is marked as a target parking space.
5. The automated intelligent garage system of claim 4, wherein the generation of the optimal travel path comprises:
taking a garage entrance as a starting point and a target parking space as an ending point, further establishing a plurality of driving paths, marking corresponding license plate numbers for each driving path, and setting numbers;
setting a standard vehicle speed, wherein the standard vehicle speed is the highest speed limit of a garage, mapping all the corresponding generated driving paths into a garage image model when a parking space scheduling module receives a new parking demand and the previous parking demand selects an optimal driving path, and simultaneously establishing a vehicle image model and marking a license plate number;
each vehicle image model with license plate number is driven on the corresponding optimal driving path according to the standard vehicle speed, and the vehicle image model corresponding to the latest parking requirement is driven on all driving paths in a time synchronization mode;
if the vehicle image model corresponding to the latest parking requirement predicts collision between the running path and other vehicle image models, corresponding collision nodes are marked on the running path, and the corresponding collision nodes are marked as collision running paths;
if the vehicle image model corresponding to the latest parking requirement does not collide with any vehicle image model in the running path, marking the running path as a smooth running path;
the standard vehicle speed is taken as the running speed of the vehicle image model, the expected running time of each unobstructed running path is obtained, the expected running time of each unobstructed running path is compared with each other, and the unobstructed running path with the smallest expected running time is marked as the optimal running path.
6. The automated intelligent garage system of claim 5, wherein when an optimal travel path is selected from a plurality of travel paths corresponding to the parking demand, the other travel paths of the parking demand other than the optimal travel path are removed from the garage image model.
7. The automated intelligent garage system of claim 5, wherein the act of parking a respective vehicle according to a parking strategy comprises:
taking the current position of the mobile terminal as the starting position of the vehicle, mapping the current position of the mobile terminal to the optimal running path in the parking strategy, updating the optimal running path with the real-time position of the vehicle to the mobile terminal in real time, and synchronously mapping other vehicles in parking navigation to the garage image model;
when a vehicle reaches an expected parking space and is parked, a camera positioned at a corresponding parking space shoots the license plate number of the vehicle in real time, a license plate number image is sent to a parking space guiding model, the parking space guiding model generates vehicle parking information according to the license plate number image and sends the vehicle parking information to a garage management module, and the vehicle parking information comprises the license plate number and the parking space number.
8. The automated intelligent method of an artificial intelligence based automated intelligent garage system of claims 1 to 7, comprising the steps of:
firstly, collecting parking space image data of each parking space, establishing corresponding parking space image models according to the parking space image data, sequentially arranging the parking space image models to obtain sub-garage image models of corresponding layers, and stacking all the sub-garage image models according to actual scenes to obtain garage image models;
step two, matching corresponding parking spaces from the garage image model according to parking requirements, further taking a garage entrance as a starting point and a target parking space as an end point, further establishing a plurality of running paths, and selecting an optimal running path from the plurality of running paths according to other parking requirements;
and thirdly, generating a parking strategy according to the parking requirement, the optimal driving path and the matched parking spaces, and guiding the vehicle to the corresponding parking spaces according to the parking strategy.
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