CN111326015A - Method and device for recommending a parking spot - Google Patents

Abstract

The application provides a parking spot recommendation method and a parking spot recommendation device, firstly, a parking request of a target vehicle is obtained, and at least one candidate parking spot is determined according to destination information carried by the parking request; then, according to the running condition of the target vehicle, determining the predicted arrival time of the target vehicle to the candidate parking point; and finally, screening out at least one recommended parking point from the candidate parking points according to the parking space use information corresponding to the candidate parking points and the predicted arrival time. According to the method and the device, the time that the target vehicle arrives at the parking spot can be predicted, the recommended parking spot is determined according to the time that the target vehicle arrives at the parking spot and the parking space use information of the parking spot, the low parking efficiency caused by the fact that the parking spot does not have an available parking space is avoided, and the traffic environment is further improved.

Description

Method and device for recommending a parking spot

technical field

The present application relates to the field of computer technology, and in particular, to a method and device for recommending a parking spot.

Background technique

With the continuous advancement of science and technology and the rapid development of the economy, traveling by car has become one of the most extensive choices for people. Whether it is a rental car, private car, shared electric vehicle or shared car, the vehicle needs to be parked at a parking spot. However, with more and more vehicles on the road, finding a parking spot has become difficult. Due to the limited number of parking spaces at each parking spot and more and more vehicles traveling, it often happens that after the driver drives the vehicle to the parking spot, the parking spot is full and there is no parking space.

Therefore, how to recommend parking spots with available parking spaces to drivers and guide drivers to park has become an urgent problem to be solved.

SUMMARY OF THE INVENTION

In view of this, the purpose of the present application is to provide a parking spot recommendation method and device, which can predict the time when the target vehicle arrives at the parking spot, and determine the recommended parking according to the time when the target vehicle arrives at the parking spot and the parking space usage information of the parking spot. To avoid the low parking efficiency caused by the lack of available parking spaces at the parking spot, and thus improve the traffic environment.

In a first aspect, an embodiment of the present application provides a method for recommending a parking spot, the method comprising:

Obtain the parking request of the target vehicle, and determine at least one candidate parking spot according to the destination information carried by the parking request;

According to the driving situation of the target vehicle, determine the estimated time of arrival of the target vehicle to the candidate parking point;

At least one recommended parking spot is selected from the candidate parking spots according to the parking space usage information corresponding to the candidate parking spots and the estimated time of arrival.

In a possible implementation manner, the parking space usage information includes historical parking space usage information of the candidate parking spot within a preset time period;

Screening out at least one recommended parking spot from the candidate parking spots according to the parking space usage information corresponding to the candidate parking spots and the estimated time of arrival, including:

determining a plurality of target historical moments corresponding to the estimated time of arrival within the preset time period;

According to the historical parking space usage information, determine the number of available parking spaces in the candidate parking spots at each target historical moment;

At least one recommended parking spot is selected from the candidate parking spots based on the number of available parking spaces of the candidate parking spots at each of the target historical moments.

In a possible implementation manner, filtering out at least one recommended parking point from the candidate parking points based on the number of available parking spaces of the candidate parking points at each target historical moment, including:

determining the average number of available parking spaces at the multiple target historical moments of the candidate parking spots;

A candidate parking spot whose average number of available parking spaces is greater than or equal to a preset threshold is used as a recommended parking spot.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record and a current location of the target vehicle;

The determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

According to the travel time, the estimated time of arrival of the target vehicle to the candidate parking point is determined.

In a possible implementation manner, the determining the estimated time of arrival of the target vehicle to the candidate parking point according to the travel time includes:

When there are multiple target driving records, for each target driving record, determine the congestion level weight corresponding to the target driving record according to the road congestion level corresponding to the target driving record;

According to the congestion level weight corresponding to each target driving record, a weighted average value of the travel time of the target driving record is determined, and the weighted average value is used as the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking spot, and the current speed of the target vehicle;

The determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In a possible implementation manner, the driving situation of the target vehicle includes a road congestion level between the target vehicle and the candidate parking point, and a distance between the target vehicle and the candidate parking point;

The determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, and all the current speed of the target vehicle;

The determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining the first estimated time of arrival of the target vehicle to the candidate parking point according to the travel time;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate the second estimated time of arrival of the target vehicle to the candidate parking point;

According to the weight of the first estimated time of arrival and the weight of the second estimated time of arrival, the weighted average of the first estimated time of arrival and the second estimated time of arrival is calculated to obtain the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, a current location of the target vehicle, and road congestion between the target vehicle and the candidate parking point level, and the distance between the target vehicle and the candidate parking spot;

The determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a third estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a fourth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the third estimated time of arrival and the fourth estimated time of arrival, the weighted average of the third estimated time of arrival and the fourth estimated time of arrival is calculated to obtain the estimated time of arrival.

In a possible implementation, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking point, the current speed of the target vehicle, and the difference between the target vehicle and the candidate parking point. the level of road congestion between

The determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculating a fifth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a sixth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the fifth ETA and the sixth ETA, the weighted average of the fifth ETA and the sixth ETA is calculated to obtain the ETA.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, the the current speed of the target vehicle, and the road congestion level between the target vehicle and the candidate parking spot;

The determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a seventh estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate an eighth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a ninth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

Calculate the seventh ETA, the eighth ETA and the ninth ETA according to the weights of the seventh ETA, the eighth ETA and the ninth ETA The time-weighted average is obtained to obtain the estimated time of arrival.

In a possible implementation, the method further includes:

The recommended parking spot is pushed to the client terminal corresponding to the target vehicle, so as to provide a reference for the user corresponding to the client terminal to select a parking spot.

In a second aspect, an embodiment of the present application further provides a parking spot recommendation device, the device comprising:

an acquisition module, configured to acquire the parking request of the target vehicle, and determine at least one candidate parking point according to the destination information carried by the parking request;

a determining module, configured to determine the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle;

The screening module is configured to screen out at least one recommended parking spot from the candidate parking spots according to the parking space usage information corresponding to the candidate parking spots and the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record and a current location of the target vehicle;

The determining module is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

According to the travel time, the estimated time of arrival of the target vehicle to the candidate parking point is determined.

In a possible implementation manner, when the determining module determines the estimated time of arrival of the target vehicle to the candidate parking point according to the travel time, the determining module is specifically configured to:

When there are multiple target driving records, for each target driving record, determine the congestion level weight corresponding to the target driving record according to the road congestion level corresponding to the target driving record;

According to the congestion level weight corresponding to each target driving record, a weighted average value of the travel time of the target driving record is determined, and the weighted average value is used as the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking spot, and the current speed of the target vehicle;

The determining module is specifically used for:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In a possible implementation manner, the driving situation of the target vehicle includes a road congestion level between the target vehicle and the candidate parking point, and a distance between the target vehicle and the candidate parking point;

The determining module is specifically used for:

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, and all the current speed of the target vehicle;

The determining module is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining the first estimated time of arrival of the target vehicle to the candidate parking point according to the travel time;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate the second estimated time of arrival of the target vehicle to the candidate parking point;

According to the weight of the first estimated time of arrival and the weight of the second estimated time of arrival, the weighted average of the first estimated time of arrival and the second estimated time of arrival is calculated to obtain the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, a current location of the target vehicle, and road congestion between the target vehicle and the candidate parking point level, and the distance between the target vehicle and the candidate parking spot;

The determining module is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a third estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a fourth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the third estimated time of arrival and the fourth estimated time of arrival, the weighted average of the third estimated time of arrival and the fourth estimated time of arrival is calculated to obtain the estimated time of arrival.

In a possible implementation, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking point, the current speed of the target vehicle, and the difference between the target vehicle and the candidate parking point. the level of road congestion between

The determining module is specifically used for:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculating a fifth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a sixth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the fifth ETA and the sixth ETA, the weighted average of the fifth ETA and the sixth ETA is calculated to obtain the ETA.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, the the current speed of the target vehicle, and the road congestion level between the target vehicle and the candidate parking spot;

The determining module is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a seventh estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate an eighth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a ninth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

Calculate the seventh ETA, the eighth ETA and the ninth ETA according to the weights of the seventh ETA, the eighth ETA and the ninth ETA The time-weighted average is obtained to obtain the estimated time of arrival.

In a possible implementation manner, the parking space usage information includes historical parking space usage information of the candidate parking spot within a preset time period;

The screening module is specifically used for:

determining a plurality of target historical moments corresponding to the estimated time of arrival within the preset time period;

According to the historical parking space usage information, determine the number of available parking spaces in the candidate parking spots at each target historical moment;

At least one recommended parking spot is selected from the candidate parking spots based on the number of available parking spaces of the candidate parking spots at each of the target historical moments.

In a possible implementation manner, when the screening module selects at least one recommended parking spot from the candidate parking spots based on the number of available parking spaces of the candidate parking spots at each target historical moment, Specifically for:

determining the average number of available parking spaces at the multiple target historical moments of the candidate parking spots;

A candidate parking spot whose average number of available parking spaces is greater than or equal to a preset threshold is used as a recommended parking spot.

In a possible implementation, the device further includes:

A push module is configured to push the recommended parking spot to a client corresponding to the target vehicle, so as to provide a reference for a user corresponding to the client to select a parking spot.

In a third aspect, embodiments of the present application further provide an electronic device, including: a processor, a memory, and a bus, where the memory stores machine-readable instructions executable by the processor, and when the electronic device runs, the processing The processor and the memory communicate via a bus, and the machine-readable instructions, when executed by the processor, execute the steps of the above-mentioned method for recommending a parking spot.

In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program executes the steps of the above parking spot recommendation method when the computer program is run by a processor.

The method and device for recommending parking spots provided by the embodiments of the present application first obtain a parking request of a target vehicle, and determine at least one candidate parking spot according to the destination information carried in the parking request; then, according to the driving conditions of the target vehicle , determine the expected arrival time of the target vehicle to the candidate parking spot; finally, according to the parking space usage information corresponding to the candidate parking spot and the expected arrival time, filter out at least one recommendation from the candidate parking spot parking spot. The application can predict the time when the target vehicle arrives at the parking spot, and determine the recommended parking spot according to the time when the target vehicle arrives at the parking spot and the parking space usage information of the parking spot, so as to avoid low parking efficiency caused by the lack of available parking spaces at the parking spot, and further Improve the traffic environment.

In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the preferred embodiments are exemplified below, and are described in detail as follows in conjunction with the accompanying drawings.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present application more clearly, the following drawings will briefly introduce the drawings that need to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore do not It should be regarded as a limitation of the scope, and for those of ordinary skill in the art, other related drawings can also be obtained according to these drawings without any creative effort.

FIG. 1 shows a flowchart of a parking spot recommendation method provided by an embodiment of the present application;

FIG. 2 shows a schematic structural diagram of a parking spot recommendation device provided by an embodiment of the present application;

FIG. 3 shows a schematic structural diagram of another parking spot recommendation device provided by an embodiment of the present application;

FIG. 4 shows a schematic structural diagram of an electronic device provided by an embodiment of the present application.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. The drawings are only for the purpose of illustration and description, and are not used to limit the protection scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented in accordance with some embodiments of the application. It should be understood that the operations of the flowcharts may be performed out of order and that steps without logical context may be performed in reverse order or concurrently. In addition, those skilled in the art can add one or more other operations to the flowchart, and can also remove one or more operations from the flowchart under the guidance of the content of the present application.

In addition, the described embodiments are only some of the embodiments of the present application, but not all of the embodiments. The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Thus, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the application as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

In order to enable those skilled in the art to use the content of the present application, the following embodiments are given in combination with the specific application scenario "recommending parking spots for vehicles". For those skilled in the art, the general principles defined herein may be applied to other embodiments and application scenarios without departing from the spirit and scope of the present application. While this application is primarily described around the configuration of incentive resources in a service site, it should be understood that this is only an exemplary embodiment.

It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared later, but does not exclude the addition of other features.

It is worth noting that, before this application is filed, the existing parking spot recommendation method recommends parking spots to users according to the usage of parking spaces in the parking spots when the vehicle initiates a parking request. This method has certain drawbacks. When the user drives to the recommended parking spot, the usage of the parking spaces in the parking spot may have changed, which often leads to the situation that there is no available parking space at the parking spot after the user arrives at the recommended parking spot. Users continue to look for other parking spots, reducing the travel efficiency of users, which in turn leads to worse traffic conditions and waste of public resources.

Based on this, the present application provides a parking spot recommendation method to avoid low parking efficiency caused by no available parking spaces at the parking spot, thereby improving the traffic environment.

Please refer to FIG. 1 , which is a flowchart of a method for recommending a parking spot provided by an embodiment of the present application. As shown in FIG. 1 , the execution body of the parking spot recommendation method provided by the embodiment of the present application may be a server, and the method includes:

S101. Acquire a parking request of a target vehicle, and determine at least one candidate parking point according to destination information carried in the parking request.

In this step, the server may receive a parking request sent by a client corresponding to the target vehicle, and the parking request may carry current location information, driving speed, destination information and the like of the target vehicle. After receiving the parking request, the server may determine a plurality of candidate parking points within a preset distance from the destination according to the destination information carried in the parking request.

For example, the preset distance can be set to a shorter distance such as 500 meters and 200 meters.

The destination information may be determined by the client's satellite positioning system, and the destination information may include coordinates, place names, building names, and street names.

Here, the target vehicle may be a shared bicycle, a shared electric vehicle, a shared car, a four-wheeled vehicle, or the like. The parking spot may be a parking lot corresponding to the target vehicle type. For example, for a shared electric vehicle, the parking spot is the designated parking spot for the shared electric vehicle; for a four-wheeled vehicle, the parking spot can be an underground parking lot, a surface parking lot, etc.

In this step, the server may also determine the candidate parking lot according to the road conditions near the candidate destination at the same time. For example, if the congestion level of the road segment leading to a certain parking lot at the destination is higher than the preset level, the parking lot will not be set as a candidate parking lot.

The client corresponding to the target vehicle may be a mobile device, such as a smart home device, a wearable device, a smart mobile device, a virtual reality device, or an augmented reality device, etc., or a tablet computer, a laptop computer, or a Built-in equipment in motor vehicles, etc. The client can communicate with the server through the network. The server may include a processor. The processor may process information and/or data related to the service request to perform one or more functions described herein. For example, a processor may determine a service order based on a service request obtained from a client. In some embodiments, a processor may include one or more processing cores (eg, a single-core processor (S) or a multi-core processor (S)). By way of example only, the processor may include a central processing unit (CPU), an application specific integrated circuit (ASIC), an application specific instruction-set processor (ASIP), a graphics processing unit ( Graphics Processing Unit (GPU), Physical Processing Unit (PPU), Digital Signal Processor (DSP), Field Programmable Gate Array (FPGA), Programmable Logic Device (Programmable Logic Device) , PLD), controller, microcontroller unit, Reduced Instruction Set Computing (RISC), or microprocessor, etc., or any combination thereof.

S102. Determine the estimated time of arrival of the target vehicle at the candidate parking point according to the driving situation of the target vehicle.

In this step, after determining the candidate parking point, the server may obtain the driving condition of the target vehicle, and determine the estimated time of arrival of the target vehicle to the at least one candidate parking point according to the driving condition of the target vehicle.

Wherein, the driving situation of the target vehicle may include the current location of the target vehicle, the current driving situation, the historical driving situation, and the road congestion level of the road section where the current target vehicle is located. The server may determine the time required for the target vehicle to arrive at each candidate parking point according to the information of the above one or more dimensions, and then determine the time for the target vehicle to arrive at the candidate parking point.

Exemplarily, the server may input the driving situation of the target vehicle into the trained prediction model to obtain the estimated time of arrival of the target vehicle at each candidate parking point.

Among them, the prediction model can be a convolutional neural network model, which is a type of feedforward neural network that includes convolutional computation and has a deep structure, and can classify features. The training of the prediction model through training samples can make The prediction model learns the relationship between the driving situation of the training samples and the time when the training samples actually arrive at the candidate parking point, and then predicts the expected arrival time of the target vehicle to the candidate parking point according to the driving situation of the target vehicle.

S103. Screen out at least one recommended parking spot from the candidate parking spots according to the parking space usage information corresponding to the candidate parking spots and the estimated time of arrival.

In this step, after determining the estimated time of arrival of the target vehicle for each candidate parking point, the server may determine whether to use the parking space for the candidate parking point according to the parking space usage information corresponding to each candidate parking point and the estimated time of arrival corresponding to the parking point. Recommended to users.

Specifically, the parking space usage information corresponding to the candidate parking spot can be determined, when the estimated arrival time is determined, the remaining available parking spaces of the candidate parking spot can be determined, and when the number of available parking spaces satisfies the preset condition, it is set as the recommended parking spot.

Wherein, the parking space usage may include the current parking space usage and historical parking space usage of the parking spot, and the current parking space usage may include the currently in use parking space, the currently vacant parking space, the estimated idle time of each parking space in use, and the historical parking space usage. The parking space usage may include information on whether each parking space was used at each moment in the past preset time period, as well as the usage time, idle time, and the parking habits of vehicles in each parking space.

Exemplarily, the server may also predict, according to the pre-trained parking space prediction model, the remaining available parking spaces of each candidate parking spot at the estimated time of arrival, and filter from multiple candidate parking spots according to the predicted remaining available parking spaces. Check out at least one recommended parking spot.

The method and device for recommending parking spots provided by the embodiments of the present application first obtain a parking request of a target vehicle, and determine at least one candidate parking spot according to the destination information carried in the parking request; then, according to the driving conditions of the target vehicle , determine the expected arrival time of the target vehicle to the candidate parking spot; finally, according to the parking space usage information corresponding to the candidate parking spot and the expected arrival time, filter out at least one recommendation from the candidate parking spot parking spot. The application can predict the time when the target vehicle arrives at the parking spot, and determine the recommended parking spot according to the time when the target vehicle arrives at the parking spot and the parking space usage information of the parking spot, so as to avoid low parking efficiency caused by the lack of available parking spaces at the parking spot, and further Improve the traffic environment.

In a possible implementation manner, the parking space usage information includes historical parking space usage information of the candidate parking spot within a preset time period;

Screening out at least one recommended parking spot from the candidate parking spots according to the parking space usage information corresponding to the candidate parking spots and the estimated time of arrival, including:

determining a plurality of target historical moments corresponding to the estimated time of arrival within the preset time period;

According to the historical parking space usage information, determine the number of available parking spaces in the candidate parking spots at each target historical moment;

At least one recommended parking spot is selected from the candidate parking spots based on the number of available parking spaces of the candidate parking spots at each of the target historical moments.

In this step, the server may determine multiple target historical moments corresponding to the expected arrival time within the preset time period. For example, if the expected arrival time is 8:20 and the preset time period is nearly one month, it may determine a near one In the month, 8:20 of each day is the target historical moment.

Here, each target historical time and the estimated time of arrival have the same attribute information, for example, the estimated time of arrival and the target historical time may belong to the same working day, the same rest day, or the same day of the week. Since the target historical time and the estimated time of arrival have the same attribute information, the corresponding traffic conditions are also similar, so the number of available parking spaces at the above time point is also similar. Furthermore, the target historical time in the historical parking space usage information can be used. The number of available parking spaces for the predicted parking spot at the estimated time of arrival.

After the target historical moment is determined, the number of available parking spaces in the candidate parking spaces can be determined when each candidate parking spot is at the target historical moment, and then at least one recommended parking spot is screened from the candidate parking spots according to the number of available parking spaces point.

In a possible implementation manner, filtering out at least one recommended parking point from the candidate parking points based on the number of available parking spaces of the candidate parking points at each target historical moment, including:

determining the average number of available parking spaces at the multiple target historical moments of the candidate parking spots;

A candidate parking spot whose average number of available parking spaces is greater than or equal to a preset threshold is used as a recommended parking spot.

In this step, the server may calculate the average number of available parking spaces of each candidate parking point at the historical target time, and use the candidate parking points whose average number of available parking spaces is greater than or equal to a preset threshold as a recommended parking point.

In this way, by calculating the average value, the accuracy of the predicted available parking spaces can be improved, and a candidate parking spot with an average available parking space greater than or equal to a preset threshold is selected as the recommended parking spot, which can ensure that the number of parking spots is large enough to improve the target The probability that the vehicle still has a parking space after reaching the candidate parking point.

In some embodiments of the present application, step S102 may include various embodiments. Various implementations are as follows:

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record and a current location of the target vehicle;

The first implementation manner of determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

According to the travel time, the estimated time of arrival of the target vehicle to the candidate parking point is determined.

In this step, the server can filter out one or more target driving records from the historical driving records, and the driving track in the target driving record passes through the current location of the target vehicle and the candidate parking lot, and according to the target driving record of the target vehicle The time it takes for the target vehicle to reach the candidate parking point from the current location is to predict the time it takes for the target vehicle to reach the candidate parking point from the current location during this trip.

Specifically, the target driving record may be determined according to information such as the current time, the road congestion level between the current location and the candidate parking point, and the like. For example, the driving time period corresponding to the target driving record may be consistent with the time period to which the current time belongs, and the road congestion level between the current location corresponding to the target driving record and the candidate parking point may be consistent with the current road congestion level, etc. When a record meets these conditions, it is determined as the target travel record.

After determining the travel time consumed by the target vehicle from the current location to the candidate parking point in each target travel record, the average or weighted average of these travel times can be made, and the obtained average value is used as the estimated time of arrival.

In a possible implementation manner, the determining the estimated time of arrival of the target vehicle to the candidate parking point according to the travel time includes:

When there are multiple target driving records, for each target driving record, determine the congestion level weight corresponding to the target driving record according to the road congestion level corresponding to the target driving record;

According to the congestion level weight corresponding to each target driving record, a weighted average value of the travel time of the target driving record is determined, and the weighted average value is used as the estimated time of arrival.

In this step, the road congestion level corresponding to each target driving record and the road congestion level between the current target vehicle and the candidate parking point can be determined, the ratio of the two can be used as the congestion level weight, and the obtained congestion level weight can be used. , and make a weighted average of the travel time of each target travel record to obtain the preset arrival time.

In a possible implementation manner, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking spot, and the current speed of the target vehicle;

The second implementation manner of determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In this step, the current speed of the target vehicle can be used as the average speed of the target vehicle when it travels to the candidate parking point, and the estimated time of arrival to the candidate parking point is calculated according to the distance between the target vehicle and the candidate parking point.

In a possible implementation manner, the driving situation of the target vehicle includes a road congestion level between the target vehicle and the candidate parking point, and a distance between the target vehicle and the candidate parking point;

The third implementation manner of determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In this step, different road congestion levels correspond to different estimated vehicle speeds, and the corresponding relationship between the road congestion levels and estimated vehicle speeds can be determined according to historical traffic records. The higher the road congestion level, the lower the estimated vehicle speed.

After the target estimated vehicle speed is determined, the ratio between the distance between the target vehicle and the candidate parking point and the target estimated vehicle speed can be calculated to obtain the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, and all the current speed of the target vehicle;

The fourth implementation manner of determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining the first estimated time of arrival of the target vehicle to the candidate parking point according to the travel time;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate the second estimated time of arrival of the target vehicle to the candidate parking point;

According to the weight of the first estimated time of arrival and the weight of the second estimated time of arrival, the weighted average of the first estimated time of arrival and the second estimated time of arrival is calculated to obtain the estimated time of arrival.

In this step, the estimated time of arrival can be determined in combination with the first and second embodiments of step S102 and the above-mentioned methods based on historical driving records and the distance between the target vehicle and the candidate parking point. Specifically, the first estimated time of arrival and the second estimated time of arrival may be determined according to the above-mentioned methods based on the historical driving records and the distance between the target vehicle and the candidate parking point, respectively.

After the first estimated time of arrival and the second estimated time of arrival are determined, weights can be assigned to the first estimated time of arrival and the second estimated time of arrival according to the degree of accuracy or importance of the corresponding determination methods, and the first estimated time of arrival can be calculated The weighted average of the time and the second estimated time of arrival gives the estimated time of arrival.

In this way, the determined estimated time of arrival can be made more accurate by combining the above-mentioned methods based on the historical driving records and the distance between the target vehicle and the candidate parking point.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, a current location of the target vehicle, and road congestion between the target vehicle and the candidate parking point level, and the distance between the target vehicle and the candidate parking spot;

The fifth implementation manner of determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a third estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a fourth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the third estimated time of arrival and the fourth estimated time of arrival, the weighted average of the third estimated time of arrival and the fourth estimated time of arrival is calculated to obtain the estimated time of arrival.

In this step, the first and third embodiments of step S102 may be combined to determine the third estimated time of arrival and the fourth estimated time of arrival in the manner of the first embodiment and the third embodiment, respectively, and then Calculate the weighted average of the third estimated time of arrival and the fourth estimated time of arrival according to the weight of the degree of accuracy or importance corresponding to each implementation, to obtain the estimated time of arrival.

In a possible implementation, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking point, the current speed of the target vehicle, and the difference between the target vehicle and the candidate parking point. the level of road congestion between

The sixth implementation manner of determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculating a fifth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a sixth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the fifth ETA and the sixth ETA, the weighted average of the fifth ETA and the sixth ETA is calculated to obtain the ETA.

In this step, the estimated time of arrival may be determined in combination with the second implementation manner and the third implementation manner of step S102. Specifically, the steps of the second embodiment and the third embodiment may be used to generate the fifth estimated time of arrival and the sixth estimated time of arrival, and then calculate the weight corresponding to the importance or accuracy of each embodiment. The estimated time of arrival is obtained by taking the weighted average of the fifth ETA and the sixth ETA.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, the the current speed of the target vehicle, and the road congestion level between the target vehicle and the candidate parking spot;

The seventh implementation manner of determining the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle includes:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a seventh estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate an eighth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a ninth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

Calculate the seventh ETA, the eighth ETA and the ninth ETA according to the weights of the seventh ETA, the eighth ETA and the ninth ETA The time-weighted average is obtained to obtain the estimated time of arrival.

In this step, the estimated time of arrival may be determined in combination with the first implementation manner, the second implementation manner and the third implementation manner of step S102. Specifically, the seventh estimated time of arrival, the eighth estimated time of arrival, and the ninth estimated time of arrival can be determined according to the steps of the first embodiment, the second embodiment, and the third embodiment, respectively, and then implemented according to the first embodiment. method, the weight corresponding to the importance or accuracy of the second embodiment and the third embodiment, calculate the weighted average of the seventh estimated time of arrival, the eighth estimated time of arrival and the ninth estimated time of arrival, and obtain the estimated time of arrival .

In a possible implementation, the method further includes:

The recommended parking spot is pushed to the client terminal corresponding to the target vehicle, so as to provide a reference for the user corresponding to the client terminal to select a parking spot.

In this step, the server can push the determined recommended parking spot to the client corresponding to the target vehicle in the form of text, image, sound, etc., and provide a route to the recommended parking spot, and the user corresponding to the client can select a recommended parking spot as destination and navigate to that suggested stop.

Based on the same inventive concept, the embodiment of the present application also provides a parking spot recommending device corresponding to the parking spot recommending method, because the principle of solving the problem of the parking spot recommending device in the embodiment of the present application is similar to the above-mentioned parking spot method in the embodiment of the present application , so the implementation of the device may refer to the implementation of the method, and the repeated parts will not be repeated.

Please refer to FIG. 2 , which is a schematic structural diagram of a parking spot recommending device provided by an embodiment of the present application. As shown in FIG. 2 , the parking spot recommending apparatus 200 provided by the embodiment of the present application includes:

an acquisition module 210, configured to acquire a parking request of the target vehicle, and determine at least one candidate parking point according to the destination information carried in the parking request;

A determination module 220, configured to determine the estimated time of arrival of the target vehicle to the candidate parking point according to the driving situation of the target vehicle;

The screening module 230 is configured to screen out at least one recommended parking spot from the candidate parking spots according to the parking space usage information corresponding to the candidate parking spots and the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record and a current location of the target vehicle;

The determining module 220 is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

According to the travel time, the estimated time of arrival of the target vehicle to the candidate parking point is determined.

In a possible implementation manner, when the determination module 220 determines the estimated time of arrival of the target vehicle to the candidate parking point according to the travel time, the determining module 220 is specifically configured to:

When there are multiple target driving records, for each target driving record, determine the congestion level weight corresponding to the target driving record according to the road congestion level corresponding to the target driving record;

According to the congestion level weight corresponding to each target driving record, a weighted average value of the travel time of the target driving record is determined, and the weighted average value is used as the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking spot, and the current speed of the target vehicle;

The determining module 220 is specifically used for:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In a possible implementation manner, the driving situation of the target vehicle includes a road congestion level between the target vehicle and the candidate parking point, and a distance between the target vehicle and the candidate parking point;

The determining module 220 is specifically used for:

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, the estimated time of arrival of the target vehicle to the candidate parking point is calculated.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, and all the current speed of the target vehicle;

The determining module 220 is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining the first estimated time of arrival of the target vehicle to the candidate parking point according to the travel time;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate the second estimated time of arrival of the target vehicle to the candidate parking point;

According to the weight of the first estimated time of arrival and the weight of the second estimated time of arrival, the weighted average of the first estimated time of arrival and the second estimated time of arrival is calculated to obtain the estimated time of arrival.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, a current location of the target vehicle, and road congestion between the target vehicle and the candidate parking point level, and the distance between the target vehicle and the candidate parking spot;

The determining module 220 is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a third estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a fourth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the third estimated time of arrival and the fourth estimated time of arrival, the weighted average of the third estimated time of arrival and the fourth estimated time of arrival is calculated to obtain the estimated time of arrival.

In a possible implementation, the driving situation of the target vehicle includes the distance between the target vehicle and the candidate parking point, the current speed of the target vehicle, and the difference between the target vehicle and the candidate parking point. the level of road congestion between

The determining module 220 is specifically used for:

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculating a fifth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a sixth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the weights of the fifth ETA and the sixth ETA, the weighted average of the fifth ETA and the sixth ETA is calculated to obtain the ETA.

In a possible implementation manner, the driving situation of the target vehicle includes a historical driving record of the target vehicle, the current location of the target vehicle, the distance between the target vehicle and the candidate parking point, the the current speed of the target vehicle, and the road congestion level between the target vehicle and the candidate parking spot;

The determining module 220 is specifically used for:

determining at least one target driving record passing through the current location and the candidate parking point from the historical driving records;

determining, in the target driving record, the travel time taken by the target vehicle from the current location to the candidate parking point;

determining, according to the travel time, a seventh estimated time of arrival for the target vehicle to arrive at the candidate parking point;

According to the distance between the target vehicle and the candidate parking point, and the current speed of the target vehicle, calculate an eighth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

selecting a target estimated vehicle speed from a plurality of estimated vehicle speeds according to the road congestion level between the target vehicle and the candidate parking point;

According to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point, calculating a ninth estimated time of arrival for the target vehicle to arrive at the candidate parking point;

Calculate the seventh ETA, the eighth ETA and the ninth ETA according to the weights of the seventh ETA, the eighth ETA and the ninth ETA The time-weighted average is obtained to obtain the estimated time of arrival.

In a possible implementation manner, the parking space usage information includes historical parking space usage information of the candidate parking spot within a preset time period;

The screening module 230 is specifically used for:

determining a plurality of target historical moments corresponding to the estimated time of arrival within the preset time period;

According to the historical parking space usage information, determine the number of available parking spaces in the candidate parking spots at each target historical moment;

At least one recommended parking spot is selected from the candidate parking spots based on the number of available parking spaces of the candidate parking spots at each of the target historical moments.

In a possible implementation manner, when the screening module 230 selects at least one recommended parking spot from the candidate parking spots based on the number of available parking spaces of the candidate parking spots at each target historical moment , specifically for:

determining the average number of available parking spaces at the multiple target historical moments of the candidate parking spots;

A candidate parking spot whose average number of available parking spaces is greater than or equal to a preset threshold is used as a recommended parking spot.

Please refer to FIG. 3 . FIG. 3 is another parking spot recommending device provided by an embodiment of the present application. As shown in FIG. 3 , the parking spot recommendation device 300 includes an acquisition module 310, a determination module 320, a screening module 330 and a push module 340, wherein:

The pushing module is configured to push the recommended parking spot to the client corresponding to the target vehicle, so as to provide a reference for the user corresponding to the client to select the parking spot.

Please refer to FIG. 4 , which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As shown in FIG. 4 , the electronic device 400 includes a processor 410 , a memory 420 and a bus 430 .

The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 through the bus 430, and the machine-readable instructions are executed. When executed, the processor 410 may execute the steps of the method for recommending a parking spot in the method embodiment shown in FIG. 1 above. For a specific implementation method, refer to the method embodiment, which will not be repeated here.

Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the parking spot recommendation in the method embodiment shown in FIG. 1 can be executed. For the steps of the method and the specific implementation manner, reference may be made to the method embodiment, which will not be repeated here.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. The apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces, indirect coupling or communication connection of devices or units, which may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a processor-executable non-volatile computer-readable storage medium. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program codes.

Finally, it should be noted that the above-mentioned embodiments are only specific implementations of the present application, and are used to illustrate the technical solutions of the present application, rather than limit them. The embodiments describe the application in detail, and those of ordinary skill in the art should understand that: any person skilled in the art can still modify the technical solutions described in the foregoing embodiments within the technical scope disclosed in the application. Or can easily think of changes, or equivalently replace some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions in the embodiments of the application, and should be covered in this application. within the scope of protection. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (15)

1. A parking spot recommendation method, the method comprising:

the method comprises the steps of obtaining a parking request of a target vehicle, and determining at least one candidate parking point according to destination information carried by the parking request;

determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle;

and screening out at least one recommended parking point from the candidate parking points according to the parking space use information corresponding to the candidate parking points and the predicted arrival time.

2. The method of claim 1, wherein the parking space usage information comprises historical parking space usage information of the candidate parking spot within a preset time period;

the screening of at least one recommended parking point from the candidate parking points according to the parking space use information corresponding to the candidate parking points and the predicted arrival time comprises the following steps:

determining a plurality of target historical moments corresponding to the estimated arrival time within the preset time period;

determining the number of available parking spaces in the candidate parking spots at each target historical moment according to the historical parking space use information;

and screening out at least one recommended parking point from the candidate parking points based on the available parking space number of the candidate parking points at each target historical moment.

3. The method of claim 2, wherein the screening of at least one recommended parking spot from the candidate parking spots based on the number of available parking spaces of the candidate parking spots at each of the target historical time comprises:

determining an average number of available parking spaces for the plurality of target historical times for the candidate parking spot;

and taking the candidate parking points with the average available parking space number larger than or equal to a preset threshold value as recommended parking points.

4. The method according to claim 1, wherein the traveling condition of the target vehicle includes a history of traveling records and a current location of the target vehicle;

the determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle comprises the following steps:

determining at least one target driving record passing through the current position and the candidate parking point from the historical driving records;

determining the running time of the target vehicle from the current position to the candidate parking point in the target running record;

and determining the predicted arrival time of the target vehicle to the candidate parking point according to the running time.

5. The method of claim 4, wherein said determining an estimated arrival time of the target vehicle at the candidate stop based on the travel time comprises:

when a plurality of target driving records exist, determining the congestion level weight corresponding to the entry mark driving record according to the road congestion level corresponding to the entry mark driving record aiming at each target driving record;

and determining a weighted average value of the running time of the target running record according to the congestion level weight corresponding to each target running record, and taking the weighted average value as the predicted arrival time.

6. The method according to claim 1, wherein the driving condition of the target vehicle includes a distance of the target vehicle from the candidate parking point, and a current vehicle speed of the target vehicle;

the determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle comprises the following steps:

and calculating the predicted arrival time of the target vehicle to the candidate parking point according to the distance between the target vehicle and the candidate parking point and the current vehicle speed of the target vehicle.

7. The method according to claim 1, wherein the driving condition of the target vehicle includes a road congestion level between the target vehicle and the candidate parking spot, and a distance between the target vehicle and the candidate parking spot;

the determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle comprises the following steps:

selecting a target predicted vehicle speed from a plurality of predicted vehicle speeds according to the road congestion level between the target vehicle and the candidate parking spot;

and calculating the estimated arrival time of the target vehicle to the candidate parking point according to the target estimated vehicle speed and the distance between the target vehicle and the candidate parking point.

8. The method according to claim 1, wherein the traveling condition of the target vehicle includes a history of traveling records of the target vehicle, a current location of the target vehicle, a distance of the target vehicle from the candidate parking point, and a current vehicle speed of the target vehicle;

the determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle comprises the following steps:

determining at least one target driving record passing through the current position and the candidate parking point from the historical driving records;

determining the running time of the target vehicle from the current position to the candidate parking point in the target running record;

determining a first predicted arrival time of the target vehicle to the candidate parking point according to the running time;

calculating a second predicted arrival time of the target vehicle to the candidate parking point according to the distance between the target vehicle and the candidate parking point and the current speed of the target vehicle;

and calculating a weighted average value of the first predicted arrival time and the second predicted arrival time according to the weights of the first predicted arrival time and the second predicted arrival time to obtain the predicted arrival time.

9. The method according to claim 1, wherein the travel condition of the target vehicle includes a history of travel records of the target vehicle, a current location of the target vehicle, a road congestion level between the target vehicle and the candidate parking point, and a distance between the target vehicle and the candidate parking point;

the determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle comprises the following steps:

determining at least one target driving record passing through the current position and the candidate parking point from the historical driving records;

determining the running time of the target vehicle from the current position to the candidate parking point in the target running record;

determining a third predicted arrival time of the target vehicle to the candidate parking point according to the running time;

selecting a target predicted vehicle speed from a plurality of predicted vehicle speeds according to the road congestion level between the target vehicle and the candidate parking spot;

calculating fourth predicted arrival time of the target vehicle to the candidate parking point according to the target predicted vehicle speed and the distance between the target vehicle and the candidate parking point;

and calculating a weighted average value of the third predicted arrival time and the fourth predicted arrival time according to the weights of the third predicted arrival time and the fourth predicted arrival time to obtain the predicted arrival time.

10. The method according to claim 1, wherein the travel condition of the target vehicle includes a distance of the target vehicle from the candidate parking point, a current vehicle speed of the target vehicle, and a road congestion level between the target vehicle and the candidate parking point;

the determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle comprises the following steps:

calculating a fifth predicted arrival time of the target vehicle to the candidate parking point according to the distance between the target vehicle and the candidate parking point and the current speed of the target vehicle;

selecting a target predicted vehicle speed from a plurality of predicted vehicle speeds according to the road congestion level between the target vehicle and the candidate parking spot;

calculating a sixth predicted arrival time of the target vehicle to the candidate parking point according to the target predicted vehicle speed and the distance between the target vehicle and the candidate parking point;

and calculating a weighted average of the fifth predicted arrival time and the sixth predicted arrival time according to the weights of the fifth predicted arrival time and the sixth predicted arrival time to obtain the predicted arrival time.

11. The method according to claim 1, wherein the travel condition of the target vehicle includes a history of travel records of the target vehicle, a current location of the target vehicle, a distance between the target vehicle and the candidate parking point, a current vehicle speed of the target vehicle, and a road congestion level between the target vehicle and the candidate parking point;

the determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle comprises the following steps:

determining at least one target driving record passing through the current position and the candidate parking point from the historical driving records;

determining the running time of the target vehicle from the current position to the candidate parking point in the target running record;

determining a seventh predicted arrival time of the target vehicle to the candidate parking point according to the travel time;

calculating eighth predicted arrival time of the target vehicle to the candidate parking point according to the distance between the target vehicle and the candidate parking point and the current vehicle speed of the target vehicle;

selecting a target predicted vehicle speed from a plurality of predicted vehicle speeds according to the road congestion level between the target vehicle and the candidate parking spot;

calculating ninth predicted arrival time of the target vehicle to the candidate parking point according to the target predicted vehicle speed and the distance between the target vehicle and the candidate parking point;

and calculating a weighted average of the seventh predicted arrival time, the eighth predicted arrival time and the ninth predicted arrival time according to the weights of the seventh predicted arrival time, the eighth predicted arrival time and the ninth predicted arrival time to obtain the predicted arrival time.

12. The method of claim 1, further comprising:

and pushing the recommended parking point to a client corresponding to the target vehicle to provide reference for a user corresponding to the client to select a parking point.

13. A parking spot recommendation device, the device comprising:

the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring a parking request of a target vehicle and determining at least one candidate parking point according to destination information carried by the parking request;

the determining module is used for determining the predicted arrival time of the target vehicle to the candidate parking point according to the running condition of the target vehicle;

and the screening module is used for screening out at least one recommended parking point from the candidate parking points according to the parking space use information corresponding to the candidate parking points and the predicted arrival time.

14. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the electronic device is operating, the processor executing the machine-readable instructions to perform the steps of the parking spot recommendation method according to any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the parking spot recommendation method according to any one of claims 1 to 12.

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