CN111867052B - Vehicle parking spot positioning method and device and service platform - Google Patents
Vehicle parking spot positioning method and device and service platform Download PDFInfo
- Publication number
- CN111867052B CN111867052B CN201911408189.7A CN201911408189A CN111867052B CN 111867052 B CN111867052 B CN 111867052B CN 201911408189 A CN201911408189 A CN 201911408189A CN 111867052 B CN111867052 B CN 111867052B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- parking spot
- parking
- information
- user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Theoretical Computer Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- General Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Computational Biology (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Navigation (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a method, a device and a service platform for positioning a vehicle parking point, wherein the method comprises the following steps: when receiving the returning confirmation information, acquiring the wireless signal information of the vehicle; inputting the wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; and if the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value, allowing the vehicle to park at the current position. The invention can judge whether the current position of the vehicle returning is in the parking spot area or not more accurately under the environment that the GPS signal is weak or the GPS signal is interfered, thereby restraining and reminding a user to return the vehicle at a fixed point and reducing the phenomenon of disordered parking.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a device for positioning a vehicle parking spot and a service platform.
Background
With the popularization of sharing economy and the increasing deterioration of the environment, in order to meet the requirements of users for the last kilometer, a plurality of sharing bicycles for providing convenience for green travel appear on the market. With the increase of capital investment and users, some problems of sharing a bicycle are gradually reflected. For example, shared bicycles are parked randomly, which tends to hinder normal traffic.
Currently, parking spot positioning is generally performed by a global positioning system GPS to guide a user to park a vehicle in a virtual parking spot area.
However, the GPS signal is easily interfered by buildings, for example, in an urban area with high floors, the GPS signal is affected by multipath effect, and a positioning deviation is generated, thereby causing a vehicle not to be accurately parked in a parking spot area.
Disclosure of Invention
The invention provides a method, a device and a service platform for positioning a vehicle parking spot, which are used for accurately judging whether the current position of a vehicle returning is located in a parking spot area or not in an environment that a GPS signal is weak or the GPS signal is interfered, so that a user can be restrained and reminded to return the vehicle at a fixed point.
In a first aspect, an embodiment of the present invention provides a method for locating a vehicle parking spot, including:
when receiving the returning confirmation information, acquiring the wireless signal information of the vehicle;
inputting the wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area;
and if the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value, allowing the vehicle to park at the current position.
In one possible design, the acquiring wireless signal information of the vehicle includes:
receiving a wifi signal list obtained by scanning a wireless module of a vehicle, wherein the wifi signal list comprises: the wifi signal name near the current location, and the corresponding wifi signal strength.
In one possible design, before inputting the wireless signal information into the target learning model, the method further includes:
constructing a training data set, the training data set comprising: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area;
performing feature extraction on the data in the training data set to obtain feature data;
inputting the characteristic data into an initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle stops in a parking spot region, and obtaining the target learning model.
In one possible design, further comprising:
and if the probability that the current position of the vehicle is located in the parking spot area is not greater than the preset threshold value, feeding back reminding information to the user to prompt the user to search the parking spot area again.
In one possible design, further comprising:
acquiring the GPS signal intensity of the vehicle;
if the GPS signal intensity of the vehicle is not greater than the preset intensity, prompting a user to drive to an open area;
if the GPS signal intensity of the vehicle is greater than the preset intensity, acquiring the position information of the vehicle;
and recommending the parking spot closest to the user according to the position information.
In one possible design, after the reminding information is fed back to the user, the method further includes:
receiving a parking question fed back by a vehicle, the parking question comprising: the vehicle returning cannot be carried out in the parking spot area, and the wireless signal information acquisition fails;
and checking the parking problem, and recording the serial number and the position information of the vehicle if the checking is passed.
In one possible design, further comprising:
and sending the serial number and the position information of the vehicle to a terminal of a maintenance worker, so that the maintenance worker can maintain the vehicle.
In one possible design, further comprising:
if the probability that the current position of the vehicle is located in the parking spot area is not larger than a preset threshold value and the returning success information is received, recording the self-increment of the number of wrong parking times of the user by 1;
and adjusting the price of the vehicle used by the user next time according to the wrong parking times of the user.
In a second aspect, an embodiment of the present invention provides a device for locating a vehicle parking spot, including:
the acquisition module is used for acquiring wireless signal information of the vehicle when the vehicle returning confirmation information is received;
the processing module is used for inputting the wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area;
the parking module is used for allowing the vehicle to park at the current position when the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value.
In one possible design, the obtaining module is specifically configured to:
receiving a wifi signal list obtained by scanning a wireless module of a vehicle, wherein the wifi signal list comprises: the wifi signal name near the current location, and the corresponding wifi signal strength.
In one possible design, further comprising: a training module to:
constructing a training data set, the training data set comprising: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area;
performing feature extraction on the data in the training data set to obtain feature data;
inputting the characteristic data into an initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle stops in a parking spot region, and obtaining the target learning model.
In one possible design, further comprising: a feedback module to:
and when the probability that the current position of the vehicle is located in the parking spot area is not larger than the preset threshold value, feeding back reminding information to the user to prompt the user to find the parking spot area again.
In one possible design, further comprising: a recommendation module to:
acquiring the GPS signal intensity of the vehicle;
if the GPS signal intensity of the vehicle is not greater than the preset intensity, prompting a user to drive to an open area;
if the GPS signal intensity of the vehicle is greater than the preset intensity, acquiring the position information of the vehicle;
and recommending the parking spot closest to the user according to the position information.
In one possible design, after the reminder information is fed back to the user, the processing module is further configured to:
receiving a parking question fed back by a vehicle, the parking question comprising: the vehicle returning cannot be carried out in the parking spot area, and the wireless signal information acquisition fails;
and checking the parking problem, and recording the serial number and the position information of the vehicle if the checking is passed.
In one possible design, the processing module is further configured to
And sending the serial number and the position information of the vehicle to a terminal of a maintenance worker, so that the maintenance worker can maintain the vehicle.
In one possible design, the processing module is further configured to
If the probability that the current position of the vehicle is located in the parking spot area is not larger than a preset threshold value and the returning success information is received, recording the self-increment of the number of wrong parking times of the user by 1;
and adjusting the price of the vehicle used by the user next time according to the wrong parking times of the user.
In a third aspect, an embodiment of the present invention provides a service platform, including:
a memory for storing a program;
a processor for executing the program stored by the memory, the processor being configured to perform the method of any of the first aspects when the program is executed.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including: computer program, which, when run on a computer, causes the computer to perform the method of any of the first aspects.
According to the positioning method, the positioning device and the positioning service platform of the vehicle parking spot, provided by the invention, when the vehicle returning confirmation information is received, the wireless signal information of the vehicle is obtained; inputting the wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; and if the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value, allowing the vehicle to park at the current position. Therefore, whether the current position of the vehicle returning is located in the parking spot area can be accurately judged in the environment that the GPS signal is weak or the GPS signal is interfered, so that the user can be restrained and reminded to return the vehicle at a fixed point, and the phenomenon of parking in disorder is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of an application scenario of the present invention;
FIG. 2 is a schematic diagram of a wifi signal list in an embodiment of the invention;
fig. 3 is a flowchart of a method for locating a parking spot of a vehicle according to an embodiment of the present invention;
FIG. 4 is a first schematic view of a vehicle display interface;
FIG. 5 is a second schematic view of a vehicle display interface;
fig. 6 is a flowchart of a method for locating a parking spot of a vehicle according to a second embodiment of the present invention;
fig. 7 is a schematic structural diagram of a positioning device for a vehicle parking spot according to a third embodiment of the present invention;
fig. 8 is a schematic structural diagram of a positioning device for a vehicle parking spot according to a fourth embodiment of the present invention;
fig. 9 is a schematic structural diagram of a service platform according to the fifth embodiment of the present invention.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Currently, parking spot positioning is generally performed by a global positioning system GPS to guide a user to park a vehicle in a virtual parking spot area. However, the GPS signal is easily interfered by buildings, for example, in an urban area with high floors, the GPS signal is affected by multipath effect, and a positioning deviation is generated, thereby causing a vehicle not to be accurately parked in a parking spot area.
Aiming at the problems in the prior art, the invention aims to provide a method, a device and a service platform for positioning a vehicle parking spot, wherein when receiving a returning confirmation message, wireless signal information of a vehicle is acquired; inputting wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; and if the probability that the current position of the vehicle is located in the parking spot area is greater than the preset threshold value, allowing the vehicle to park at the current position. Therefore, whether the current position of the vehicle returning is located in the parking spot area can be accurately judged in the environment that the GPS signal is weak or the GPS signal is interfered, so that the user can be restrained and reminded to return the vehicle at a fixed point, and the phenomenon of parking in disorder is reduced.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
Fig. 1 is a schematic diagram of an application scenario of the present invention, as shown in fig. 1, taking a shared electric bicycle as an example, after a user clicks a return button on an operation interface of the electric bicycle 20, a service platform 10 receives corresponding return confirmation information and receives wireless signal information reported by the electric bicycle 20, where the wireless signal is a wifi signal list obtained by scanning a wireless module of the electric bicycle 20 at a current location, and the wifi signal list includes: the wifi signal name near the current location, and the corresponding wifi signal strength. Fig. 2 is a schematic diagram of a wifi signal list in an embodiment of the invention, as shown in fig. 2, when the wireless module of the electric bicycle 20 is turned on, peripheral wifi signals can be obtained through signal scanning.
The service platform 10 inputs the wireless signal information into the target learning model to obtain the probability that the current position of the electric bicycle 20 is located in the parking spot area; if the probability that the current position of the electric bicycle 20 is located in the parking spot area is greater than the preset threshold value, the electric bicycle 20 is allowed to park at the current position. The target learning model is obtained by training a training data set acquired in advance, and is used for outputting the probability that the electric bicycle 20 stops in the parking spot area. For example, if the probability value output by the target learning model is 80% and is greater than the preset threshold value 50%, it is determined that the current position of the electric bicycle 20 is within the parking spot region, and thus the user is allowed to park at the current position. It should be noted that, the specific value of the preset threshold is not limited in this embodiment, and the preset threshold may be set according to the actual model training result.
This embodiment, can be weak at the GPS signal, perhaps under the environment that the GPS signal is disturbed, judge more accurately whether the current position that the vehicle was returned the car is located the parking spot region to can retrain and remind the user to carry out the fixed point and return the car, reduce the phenomenon of parking in disorder.
The following describes the technical solutions of the present invention and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 3 is a flowchart of a method for locating a parking spot of a vehicle according to an embodiment of the present invention, and as shown in fig. 3, the method in this embodiment may include:
and S101, acquiring wireless signal information of the vehicle when the returning confirmation information is received.
In this embodiment, the service platform can receive the wifi signal list that the wireless module scanning of vehicle obtained, and the wifi signal list includes: the wifi signal name near the current location, and the corresponding wifi signal strength.
In particular, wifi signals around a parking spot tend to be fixed, each covering a certain range. Thus, the current location may be determined with the coverage of multiple wifi signals. For example, when the user clicks a return button at the location a, the wifi signal list obtained by scanning through the wireless module of the vehicle can be obtained. The service platform can receive a wifi signal list of the vehicle as a basis for data analysis.
And S102, inputting the wireless signal information into the target learning model to obtain the probability that the current position of the vehicle is located in the parking spot area.
In this embodiment, the service platform may input the wireless signal information into the target learning model to obtain the probability that the current position of the vehicle is located in the parking spot region.
Specifically, the question of whether the user parks at the parking spot can be converted into a single sample detection question in machine learning. The single-sample detection problem is concerned with the characteristics of a group of data, the group of data is concerned with the problem that the group of data is in a parking area, the accuracy judgment standard is also in the single type that the group of data is not in the parking area, and therefore the accuracy of judging whether the vehicle is parked at a parking spot can be improved by focusing the characteristics of the group of data on the single type of problem that the vehicle is parked in a parking circle or not. Thus, wireless signal information may be input into the target learning model, resulting in a probability that the current position of the vehicle is within the parking spot area.
S103, if the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value, allowing the vehicle to park at the current position.
In this embodiment, if the probability that the current position of the vehicle is located in the parking spot region is greater than the preset threshold, the vehicle is allowed to park at the current position.
Optionally, if the probability that the current position of the vehicle is located in the parking spot area is not greater than the preset threshold, feeding back a reminding message to the user to prompt the user to search for the parking spot area again.
In one possible embodiment, the GPS signal strength of the vehicle may also be acquired; if the GPS signal intensity of the vehicle is not greater than the preset intensity, prompting the user to drive to an open area; if the GPS signal intensity of the vehicle is greater than the preset intensity, acquiring the position information of the vehicle; and recommending the parking spot closest to the user according to the position information.
In particular, although the GPS signal is easily interfered with by buildings, for example, in an urban area with high floors, the GPS signal is affected by a multipath effect, and a positioning error is generated, thereby causing a vehicle not to be accurately parked in a parking spot area. However, the positioning can be assisted by using the GPS signal, and the closest parking spot can be recommended to the user based on the positioning by the GPS signal. In the specific implementation process, the GPS signal strength may be determined first. And if the GPS signal intensity of the vehicle is greater than the preset intensity, acquiring the position information of the vehicle and recommending a parking spot with the closest distance to the user.
In another possible implementation, after the reminding information is fed back to the user, a parking question fed back by the vehicle is received, and the parking question comprises: the vehicle returning cannot be carried out in the parking spot area, and the wireless signal information acquisition fails; and checking the parking problem, and recording the serial number and the position information of the vehicle if the checking is passed.
For example, the number and the position information of the vehicle can be sent to a terminal of a maintenance person, so that the maintenance person can maintain the vehicle.
In this embodiment, since the target learning model outputs a probability value, it does not necessarily completely match the actual situation. For example, in an actual environment, a user actually drives a vehicle to a parking spot area, but a scanned wifi signal list is inconsistent with a wifi signal list used in training due to weak wireless signals of the vehicle, and a situation that the vehicle cannot be returned in the parking spot may occur. There is also a possibility that the wireless module of the vehicle itself fails and cannot scan for surrounding wireless signals. Thus, the service platform provides a question feedback window so that the user can feed back a question to the service platform.
Specifically, the user can operate on a display interface of the vehicle to submit the parking problem, then the problem is fed back to the service platform, the service platform checks the problem, and if the check is passed, the serial number and the position information of the vehicle are recorded, so that maintenance personnel can be conveniently dispatched to maintain the vehicle.
Fig. 4 is a first schematic diagram of a vehicle display interface, and fig. 5 is a second schematic diagram of the vehicle display interface, as shown in fig. 4, a question can be fed back with the display interface of the vehicle, a question description is added in a drop-down box, and after editing of the question description is completed, a user clicks to submit the question. Further, as shown in fig. 5, after the question is submitted, a prompt message indicating that the question is submitted successfully and the current status are displayed on the display interface. And if the service platform passes the audit, displaying an audit passing prompt on a display interface, wherein a vehicle returning key appears on the vehicle display interface at the moment. After the user clicks and confirms the car returning, the car returning can be completed at the current position.
In another possible implementation manner, if the probability that the current position of the vehicle is located in the parking spot area is not greater than the preset threshold value and the returning success information is received, recording the self increment of the number of wrong parking times of the user by 1; and adjusting the price of the vehicle used by the user next time according to the wrong parking times of the user.
In this embodiment, although the service platform feeds back the reminding information, some users still force parking in the non-parking spot area, and at this time, the service platform can track the user information of the vehicle used and record the number of times of the user mistakenly parking. And adjusting the price of the vehicle used by the user next time according to the wrong parking times of the user. Thereby restricting the user from completing the car return as much as possible in the parking spot area.
In the embodiment, when the returning confirmation information is received, the wireless signal information of the vehicle is acquired; inputting wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; and if the probability that the current position of the vehicle is located in the parking spot area is greater than the preset threshold value, allowing the vehicle to park at the current position. Therefore, whether the current position of the vehicle returning is located in the parking spot area can be accurately judged in the environment that the GPS signal is weak or the GPS signal is interfered, so that the user can be restrained and reminded to return the vehicle at a fixed point, and the phenomenon of parking in disorder is reduced.
Fig. 6 is a flowchart of a method for locating a vehicle parking spot according to a second embodiment of the present invention, and as shown in fig. 6, the method in this embodiment may include:
s201, constructing a training data set, and performing iterative training on the initial learning model to obtain a target learning model.
In this embodiment, the service platform may further construct a training data set, where the training data set includes: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area; performing feature extraction on the data in the training data set to obtain feature data; inputting the characteristic data into the initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle parks in the parking spot region, so as to obtain the target learning model.
Specifically, the training data set may be constructed by collecting a large number of WiFi lists that the user parks within the parking circle at a time. Then, the data of parking in the parking circle is subjected to feature learning, and the problem that whether the user parks at the parking spot is converted into a single sample detection problem in machine learning; no matter wifi assistance-localization or GPS positioning mode is pursuit single point positioning accuracy, and then whether the parking area is in is judged.
And S202, acquiring the wireless signal information of the vehicle when the vehicle returning confirmation information is received.
And S203, inputting the wireless signal information into the target learning model to obtain the probability that the current position of the vehicle is located in the parking spot area.
And S204, if the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value, allowing the vehicle to park at the current position.
In this embodiment, please refer to the relevant description in steps S101 to S103 in the method shown in fig. 3 for the specific implementation process and technical principle of steps S202 to S204, which is not described herein again.
In the embodiment, when the returning confirmation information is received, the wireless signal information of the vehicle is acquired; inputting wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; and if the probability that the current position of the vehicle is located in the parking spot area is greater than the preset threshold value, allowing the vehicle to park at the current position. Therefore, whether the current position of the vehicle returning is located in the parking spot area can be accurately judged in the environment that the GPS signal is weak or the GPS signal is interfered, so that the user can be restrained and reminded to return the vehicle at a fixed point, and the phenomenon of parking in disorder is reduced.
In addition, this embodiment may further construct a training data set, where the training data set includes: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area; performing feature extraction on the data in the training data set to obtain feature data; inputting the characteristic data into the initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle parks in the parking spot region, so as to obtain the target learning model.
Fig. 7 is a schematic structural diagram of a positioning device for a vehicle parking spot according to a third embodiment of the present invention, and as shown in fig. 7, the positioning device for a vehicle parking spot according to the third embodiment may include:
the obtaining module 31 is configured to obtain wireless signal information of the vehicle when the return confirmation information is received;
the processing module 32 is used for inputting the wireless signal information into the target learning model to obtain the probability that the current position of the vehicle is located in the parking spot area;
and the parking module 33 is configured to allow the vehicle to park at the current position when the probability that the current position of the vehicle is located in the parking spot area is greater than a preset threshold.
In one possible design, the obtaining module 31 is specifically configured to:
receive the wifi signal list that the wireless module scanning of vehicle obtained, wifi signal list includes: wifi signal names near the current location, and corresponding wifi signal strengths.
In one possible design, after the reminder information is fed back to the user, the processing module 32 is further configured to:
receiving a parking question fed back by the vehicle, wherein the parking question comprises: the vehicle returning cannot be carried out in the parking spot area, and the wireless signal information acquisition fails;
and checking the parking problem, and recording the serial number and the position information of the vehicle if the checking is passed.
In one possible design, the processing module 32 is also used for
And sending the serial number and the position information of the vehicle to a terminal of a maintenance person so that the maintenance person can maintain the vehicle.
In one possible design, the processing module 32 is also used for
If the probability that the current position of the vehicle is located in the parking spot area is not larger than a preset threshold value and the returning success information is received, recording the self-increment of the number of wrong parking times of the user by 1;
and adjusting the price of the vehicle used by the user next time according to the wrong parking times of the user.
The positioning device for a vehicle parking spot in this embodiment may execute the technical solution in the method shown in fig. 3, and the specific implementation process and technical principle of the positioning device refer to the related description in the method shown in fig. 3, which is not described herein again.
In the embodiment, when the returning confirmation information is received, the wireless signal information of the vehicle is acquired; inputting wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; and if the probability that the current position of the vehicle is located in the parking spot area is greater than the preset threshold value, allowing the vehicle to park at the current position. Therefore, whether the current position of the vehicle returning is located in the parking spot area can be accurately judged in the environment that the GPS signal is weak or the GPS signal is interfered, so that the user can be restrained and reminded to return the vehicle at a fixed point, and the phenomenon of parking in disorder is reduced.
Fig. 8 is a schematic structural diagram of a positioning device for a vehicle parking spot according to a fourth embodiment of the present invention, and as shown in fig. 8, the positioning device for a vehicle parking spot according to the present embodiment may further include, on the basis of the device shown in fig. 7:
a training module 34 for:
constructing a training data set, wherein the training data set comprises: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area;
performing feature extraction on data in the training data set to obtain feature data;
inputting the characteristic data into the initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle parks in the parking spot region, so as to obtain the target learning model.
In one possible design, further comprising: a feedback module 35 configured to:
and when the probability that the current position of the vehicle is located in the parking spot area is not greater than the preset threshold value, feeding back reminding information to the user to prompt the user to search the parking spot area again.
In one possible design, further comprising: a recommendation module 36 for:
acquiring the GPS signal intensity of a vehicle;
if the GPS signal intensity of the vehicle is not greater than the preset intensity, prompting the user to drive to an open area;
if the GPS signal intensity of the vehicle is greater than the preset intensity, acquiring the position information of the vehicle;
and recommending the parking spot closest to the user according to the position information.
The positioning device for a vehicle parking spot of the present embodiment may execute the technical solutions in the methods shown in fig. 3 and fig. 6, and the specific implementation process and technical principle of the positioning device refer to the related descriptions in the methods shown in fig. 3 and fig. 6, which are not described herein again.
In the embodiment, when the returning confirmation information is received, the wireless signal information of the vehicle is acquired; inputting wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; and if the probability that the current position of the vehicle is located in the parking spot area is greater than the preset threshold value, allowing the vehicle to park at the current position. Therefore, whether the current position of the vehicle returning is located in the parking spot area can be accurately judged in the environment that the GPS signal is weak or the GPS signal is interfered, so that the user can be restrained and reminded to return the vehicle at a fixed point, and the phenomenon of parking in disorder is reduced.
In addition, this embodiment may further construct a training data set, where the training data set includes: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area; performing feature extraction on the data in the training data set to obtain feature data; inputting the characteristic data into the initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle parks in the parking spot region, thereby obtaining the target learning model.
Fig. 9 is a schematic structural diagram of a service platform provided in the fifth embodiment of the present invention, and as shown in fig. 9, the service platform 40 in this embodiment may include: a processor 41 and a memory 42.
A memory 42 for storing programs; the Memory 42 may include a volatile Memory (RAM), such as a Static Random Access Memory (SRAM), a Double Data Rate Synchronous Dynamic Random Access Memory (DDR SDRAM), and the like; the memory may also comprise a non-volatile memory, such as a flash memory. The memory 42 is used to store computer programs (e.g., applications, functional modules, etc. that implement the above-described methods), computer instructions, etc., which may be stored in one or more of the memories 42 in a partitioned manner. And the above-mentioned computer program, computer instructions, data, etc. can be called by the processor 41.
The computer programs, computer instructions, etc. described above may be stored in one or more memories 42 in partitions. And the above-described computer programs, computer instructions, data, etc. may be called by the processor 41.
A processor 41 for executing the computer program stored in the memory 42 to implement the steps of the method according to the above embodiments.
Reference may be made in particular to the description relating to the previous method embodiments.
The processor 41 and the memory 42 may be separate structures or may be integrated structures integrated together. When the processor 41 and the memory 42 are separate structures, the memory 42 and the processor 41 may be coupled by a bus 43.
The service platform of this embodiment may execute the technical solutions in the methods shown in fig. 3 and fig. 6, and the specific implementation process and technical principle of the service platform refer to the related descriptions in the methods shown in fig. 3 and fig. 6, which are not described herein again.
In addition, embodiments of the present application further provide a computer-readable storage medium, in which computer-executable instructions are stored, and when at least one processor of the user equipment executes the computer-executable instructions, the user equipment performs the above-mentioned various possible methods.
Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in user equipment. Of course, the processor and the storage medium may reside as discrete components in a communication device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (14)
1. A method of locating a vehicle parking spot, comprising:
when receiving the returning confirmation information, acquiring the wireless signal information of the vehicle; inputting the wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; the target learning model is obtained based on a constructed training data set comprising: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area;
if the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value, allowing the vehicle to park at the current position;
if the probability that the current position of the vehicle is located in the parking spot area is not larger than the preset threshold value, feeding back reminding information to the user to prompt the user to search the parking spot area again;
acquiring the GPS signal intensity of the vehicle;
if the GPS signal intensity of the vehicle is not greater than the preset intensity, prompting a user to drive to an open area;
if the GPS signal intensity of the vehicle is greater than the preset intensity, acquiring the position information of the vehicle;
and recommending the parking spot closest to the user according to the position information.
2. The method of claim 1, wherein the obtaining wireless signal information of the vehicle comprises:
receiving a wifi signal list obtained by scanning a wireless module of a vehicle, wherein the wifi signal list comprises: the wifi signal name near the current location, and the corresponding wifi signal strength.
3. The method of claim 1, further comprising:
performing feature extraction on the data in the training data set to obtain feature data;
inputting the characteristic data into an initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle stops in a parking spot region, and obtaining the target learning model.
4. The method of claim 1, after feeding back the reminder information to the user, further comprising:
receiving a parking question fed back by a vehicle, the parking question comprising: the vehicle returning cannot be carried out in the parking spot area, and the wireless signal information acquisition fails;
and checking the parking problem, and recording the serial number and the position information of the vehicle if the checking is passed.
5. The method of claim 4, further comprising:
and sending the serial number and the position information of the vehicle to a terminal of a maintenance worker, so that the maintenance worker can maintain the vehicle.
6. The method of any one of claims 1-5, further comprising:
if the probability that the current position of the vehicle is located in the parking spot area is not larger than a preset threshold value and the returning success information is received, recording the self-increment of the number of wrong parking times of the user by 1;
and adjusting the price of the vehicle used by the user next time according to the wrong parking times of the user.
7. A vehicle parking spot locating apparatus, comprising:
the acquisition module is used for acquiring the wireless signal information of the vehicle when the vehicle returning confirmation information is received;
a training module to: constructing a training data set, the training data set comprising: the wireless signal information is acquired when the vehicle parks in the parking spot area, and the wireless signal information is acquired when the vehicle does not park in the parking spot area;
the processing module is used for inputting the wireless signal information into a target learning model to obtain the probability that the current position of the vehicle is located in a parking spot area; the target learning model is obtained based on the training data set;
the parking module is used for allowing the vehicle to park at the current position when the probability that the current position of the vehicle is located in the parking spot area is larger than a preset threshold value;
the feedback module is used for feeding back reminding information to the user when the probability that the current position of the vehicle is located in the parking spot area is not greater than a preset threshold value so as to prompt the user to search the parking spot area again;
the recommendation module is used for acquiring the GPS signal intensity of the vehicle; if the GPS signal intensity of the vehicle is not greater than the preset intensity, prompting a user to drive to an open area; if the GPS signal intensity of the vehicle is greater than the preset intensity, acquiring the position information of the vehicle; and recommending the parking spot closest to the user according to the position information.
8. The apparatus of claim 7, wherein the obtaining module is specifically configured to:
receiving a wifi signal list obtained by scanning a wireless module of a vehicle, wherein the wifi signal list comprises: the wifi signal name near the current location, and the corresponding wifi signal strength.
9. The apparatus of claim 7, further comprising: a training module further to:
performing feature extraction on the data in the training data set to obtain feature data;
inputting the characteristic data into an initial learning model to carry out iterative training until the probability output by the trained initial learning model correctly reflects whether the vehicle stops in a parking spot region, and obtaining the target learning model.
10. The apparatus of claim 7, further comprising, after feeding back the reminder information to the user:
receiving a parking question fed back by a vehicle, the parking question comprising: the vehicle returning cannot be carried out in the parking spot area, and the wireless signal information acquisition fails;
and checking the parking problem, and recording the serial number and the position information of the vehicle if the checking is passed.
11. The apparatus of claim 10, further comprising:
and sending the serial number and the position information of the vehicle to a terminal of a maintenance worker, so that the maintenance worker can maintain the vehicle.
12. The apparatus of any one of claims 7-11, further comprising:
if the probability that the current position of the vehicle is located in the parking spot area is not larger than a preset threshold value and the returning success information is received, recording the self-increment of the wrong parking times of the user by 1;
and adjusting the price of the vehicle used by the user next time according to the wrong parking times of the user.
13. A service platform, comprising:
a memory for storing a program;
a processor for executing the program stored by the memory, the processor being configured to perform the method of any of claims 1-6 when the program is executed.
14. A computer-readable storage medium, comprising: computer program, which, when run on a computer, causes the computer to perform the method according to any of claims 1-6.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911408189.7A CN111867052B (en) | 2019-12-31 | 2019-12-31 | Vehicle parking spot positioning method and device and service platform |
| PCT/CN2020/139958 WO2021136147A1 (en) | 2019-12-31 | 2020-12-28 | Method and system for positioning preset region of shared device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911408189.7A CN111867052B (en) | 2019-12-31 | 2019-12-31 | Vehicle parking spot positioning method and device and service platform |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111867052A CN111867052A (en) | 2020-10-30 |
| CN111867052B true CN111867052B (en) | 2022-07-08 |
Family
ID=72970782
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911408189.7A Active CN111867052B (en) | 2019-12-31 | 2019-12-31 | Vehicle parking spot positioning method and device and service platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111867052B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021136147A1 (en) * | 2019-12-31 | 2021-07-08 | 北京骑胜科技有限公司 | Method and system for positioning preset region of shared device |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109218337A (en) * | 2017-05-24 | 2019-01-15 | 上海朗尚科贸有限公司 | Control method for vehicle, server, vehicle termination and user terminal |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100313614A1 (en) * | 2009-06-12 | 2010-12-16 | Rzepecki S Ryan | Municipal bicycle sharing system |
| CN106971610B (en) * | 2017-04-28 | 2018-03-23 | 北京摩拜科技有限公司 | Determine that object is in the method, parking management equipment and system of target area |
| CN107808515B (en) * | 2017-10-20 | 2023-12-26 | 北京智汇空间科技有限公司 | Parking management method and system for shared bicycle |
| CN108008350A (en) * | 2017-11-03 | 2018-05-08 | 平安科技（深圳）有限公司 | Localization method, device and storage medium based on Random Forest model |
| CN108198122A (en) * | 2018-02-07 | 2018-06-22 | 东峡大通（北京）管理咨询有限公司 | Parking process method, server, terminal and the machine readable storage medium of vehicle |
-
2019
- 2019-12-31 CN CN201911408189.7A patent/CN111867052B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109218337A (en) * | 2017-05-24 | 2019-01-15 | 上海朗尚科贸有限公司 | Control method for vehicle, server, vehicle termination and user terminal |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111867052A (en) | 2020-10-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9111145B2 (en) | Parking lot information system using image technology for identifying available parking spaces | |
| CN109509365B (en) | Vehicle information error correction method and system and handheld mobile terminal device | |
| EP3716194A1 (en) | Method and device for processing vehicle loss assessment data and processing device | |
| CN111867052B (en) | Vehicle parking spot positioning method and device and service platform | |
| CN110774930B (en) | New energy vehicle charging management method and system | |
| CN110413731A (en) | Question searching method and device, electronic equipment and storage medium | |
| CN106846514A (en) | A kind of parking management method and device | |
| EP4186038A1 (en) | Vehicle identification number (vin)-based telematics device location tracking | |
| US10692383B1 (en) | Method for locating vehicle and electronic device employing the method | |
| JP2011013719A (en) | Automobile insurance fee determination device for transportation businesses, and automobile insurance fee determination program for transportation business | |
| CN111754261B (en) | Method and device for evaluating taxi willingness and terminal equipment | |
| CN113253278A (en) | Parking space identification method and device and computer storage medium | |
| CN106327236A (en) | Method and device for determining user action track | |
| CN114529269B (en) | Invalid operation range processing method and device, electronic equipment and storage medium | |
| CN115352435A (en) | Parking memory method, parking memory device, electronic equipment and storage medium | |
| CN115662400A (en) | Processing method, device and equipment for voice interaction data of vehicle machine and storage medium | |
| CN115329917A (en) | Enhanced contactless vehicle codes | |
| CN108536605B (en) | Method, device and system for automatically testing drawing program | |
| CN115691470A (en) | Dialect-based vehicle-mounted interaction method, device and system | |
| CN113837977A (en) | Object tracking method, multi-target tracking model training method and related equipment | |
| CN113506103A (en) | Public transport fee intelligent payment method based on digital currency | |
| CN107845002A (en) | A kind of car operation monitoring method and device | |
| CN111160817B (en) | Goods acceptance method and system, computer system and computer readable storage medium | |
| CN112733909A (en) | Duplicate removal identification method, device, medium and electronic equipment for urban cases | |
| CN107622535B (en) | Path identification system, path identification method thereof and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220803 Address after: 311199 Room 301, No. 108, Xincheng Road, Nanyuan street, Linping District, Hangzhou City, Zhejiang Province Patentee after: HANGZHOU QINGQI SCIENCE AND TECHNOLOGY Co.,Ltd. Address before: Room 203, 2 / F, building 34, yard 8, Dongbei Wangxi Road, Haidian District, Beijing 100193 Patentee before: Beijing Qisheng Technology Co.,Ltd. |
|
| TR01 | Transfer of patent right |