CN112289041B

CN112289041B - Intelligent parking lot management method based on hotspot positioning and information sharing and cloud platform

Info

Publication number: CN112289041B
Application number: CN202011151113.3A
Authority: CN
Inventors: 储美红
Original assignee: Shanghai Urban Construction Digital Industry Group Co ltd; Shanghai Intelligent Transportation Co ltd
Current assignee: SHANGHAI INTELLIGENT TRANSPORTATION Co.,Ltd.; Shanghai urban construction digital industry group Co., Ltd
Priority date: 2020-10-25
Filing date: 2020-10-25
Publication date: 2021-12-03
Anticipated expiration: 2040-10-25
Also published as: CN113470377A; CN113470378A; CN112289041A

Abstract

The invention relates to a smart parking lot management method and a cloud platform based on hotspot positioning and information sharing. So, can correspond the focus location and the information sharing of vehicle with the wisdom parking area and carry out integrated analysis to the jam condition in wisdom parking area is confirmed fast, accurately, and then realizes managing and dispatching the interior management of field in wisdom parking area according to real-time vehicle position shared information, avoids or reduces the jam of parking and getting out of bus, ensures the smooth and easy operation in wisdom parking area.

Description

Intelligent parking lot management method based on hotspot positioning and information sharing and cloud platform

Technical Field

The application relates to the technical field of hotspot sharing and intelligent parking, in particular to an intelligent parking lot management method and a cloud platform based on hotspot positioning and information sharing.

Background

With the improvement of living standard, the possession proportion of private cars is increasing year by year. The proliferation of the number of large urban vehicles has also led to a series of "big urban diseases". The 'parking difficulty' is a more serious problem in the current large cities. During rush hours or holidays, large-area and long-time congestion often occurs in each large parking lot, so that the schedule arrangement of people is delayed, and traffic accidents are easily caused. Therefore, how to solve or improve the congestion of the parking lot is a technical problem which needs to be considered at present.

Disclosure of Invention

The first aspect of the application discloses an intelligent parking lot management method based on hotspot positioning and information sharing, the method comprises the following steps:

acquiring first traffic track information and second traffic track information of the intelligent parking lot in the operation process, wherein the first traffic track information and the second traffic track information are traffic track information corresponding to a traffic area of the intelligent parking lot in the operation process;

obtaining a comparison result of hotspot locating distribution of the first traffic track information and the second traffic track information, wherein the comparison result of the hotspot locating distribution represents hotspot locating differences of vehicle-mounted controllers between corresponding parking areas between the first traffic track information and the second traffic track information; converting the comparison result of the hotspot locating distribution into a hotspot sharing locating list, wherein the hotspot sharing locating list comprises sharing parking time intervals corresponding to a plurality of parking areas;

according to the parking reservation information of the parking area in the hotspot sharing positioning list, determining the congestion condition of the intelligent parking lot during operation in the operation time period from the first traffic track information to the second traffic track information; and issuing a sharing instruction of vehicle position information to a target terminal based on the congestion condition, and carrying out parking scheduling according to the real-time vehicle position sharing information fed back by the target terminal.

Optionally, the obtaining of the comparison result of the hotspot locating distributions of the first traffic track information and the second traffic track information includes:

determining first vehicle running track information corresponding to the first traffic track information and second vehicle running track information corresponding to the second traffic track information;

comparing the first vehicle running track information with the second vehicle running track information according to the same hotspot activation time period to obtain a comparison result of hotspot positioning distribution; the comparison result of the hotspot locating distribution is expressed in the form of an information list, and the information list comprises hotspot longitude and latitude coordinates corresponding to hotspot locating differences of the vehicle-mounted controllers between the parking areas.

Optionally, the converting the comparison result of the hotspot locating distribution into a hotspot sharing locating list includes:

acquiring the hotspot longitude and latitude coordinates in the information list corresponding to the comparison result of the hotspot positioning distribution;

acquiring a hot spot positioning updating queue according to the hot spot longitude and latitude coordinates and parking reservation information of a vehicle corresponding to the hot spot longitude and latitude coordinates, and extracting queue elements in the hot spot updating queue according to a time sequence; wherein the queue elements comprise a plurality of real-time longitude and latitude coordinates; determining the area label weight of each real-time longitude and latitude coordinate of the queue element, and determining the number of the real-time longitude and latitude coordinates of which the area label weight is less than or equal to the preset label weight according to the area label weight of each real-time longitude and latitude coordinate;

calculating the current occupation ratio of the real-time longitude and latitude coordinate number in the total real-time longitude and latitude coordinate number of the queue element to obtain the dynamic hot spot occupation ratio of the queue element; determining the average longitude and latitude coordinates of the queue elements; determining a time-staggered parking statistical result of the queue elements according to the dynamic hotspot occupation ratio of the queue elements and the average longitude and latitude coordinates of the queue elements; according to the corresponding relation between a pre-stored parking period indication list and a hotspot sharing index, determining the hotspot sharing index corresponding to the parking period indication list where the staggered parking statistical result of the queue element is located, and obtaining the hotspot sharing positioning list based on the hotspot sharing index and the corresponding parking space number information in the parking reservation information.

Optionally, the determining, according to the parking reservation information of the parking area in the hotspot-sharing positioning list, a congestion condition of the intelligent parking lot during operation in an operation time period between the first traffic trajectory information and the second traffic trajectory information includes:

determining the maximum traffic congestion degree of a corresponding parking area according to the parking reservation information in the hotspot sharing positioning list; and in response to the fact that the maximum traffic congestion degree is larger than a set congestion degree, determining that congestion exists in the intelligent parking lot during operation in the operation time period from the first traffic trajectory information to the second traffic trajectory information.

Optionally, determining the maximum traffic congestion degree of the corresponding parking area according to the parking reservation information in the hotspot sharing positioning list includes:

acquiring reservation event lists corresponding to the i pieces of parking reservation information and a historical parking record set corresponding to each reservation event list, wherein each reservation event list comprises j different event attributes, and i and j are positive integers greater than or equal to 1; determining a first period parking track corresponding to the reservation event list in a historical parking record set corresponding to the reservation event list; carrying out communication congestion detection by adopting a first time period parking track corresponding to the reservation event list to obtain a congestion influence factor of each event attribute in the reservation event list; performing track updating iteration on a first-period parking track corresponding to an appointment event list based on a congestion influence factor of each event attribute in i appointment event lists to obtain a parking track after the first-period iteration corresponding to the appointment event list; adding the parking track after the first time period iteration corresponding to the reservation event list into a historical parking record set corresponding to the reservation event list; returning and executing the step to determine a first-period parking track corresponding to the reserved event list in a historical parking record set corresponding to the reserved event list until the comprehensive congestion coefficient corresponding to the hotspot sharing positioning list is converged in a set interval, and calculating the maximum traffic congestion degree of a corresponding parking area according to the relative interval position of the comprehensive congestion coefficient in the set interval;

wherein, the determining the first-period parking trajectory corresponding to the reservation event list in the historical parking record set corresponding to the reservation event list includes: determining a second time interval parking track, a first time interval congestion feedback record and a first time interval congestion feedback record corresponding to the reservation event list based on the historical parking record set; obtaining a first parking congestion index of a first period congestion feedback record corresponding to the booking event list by comparing the first period congestion feedback record corresponding to the booking event list with a first period congestion feedback record corresponding to a target booking event list; obtaining a second parking congestion index of the first-period congestion feedback record of the reservation event list by comparing the first-period congestion feedback record corresponding to the reservation event list with a second-period parking track corresponding to the reservation event list; determining a second time period parking track corresponding to the reservation event list or a parking track corresponding to a first time period congestion feedback record corresponding to the reservation event list as a first time period parking track corresponding to the reservation event list based on the second parking congestion index and the first parking congestion index;

the obtaining of the first parking congestion index of the first period congestion feedback record corresponding to the booking event list by comparing the first period congestion feedback record corresponding to the booking event list with the first period congestion feedback record corresponding to the target booking event list includes: determining a congestion delay value of a first period congestion feedback record corresponding to the reservation event list and a congestion delay value of a first period congestion feedback record corresponding to the target reservation event list; determining the difference between the congestion delay values of the first period congestion feedback record corresponding to the reservation event list and the first period congestion feedback record corresponding to the target reservation event list according to the congestion delay value of the first period congestion feedback record corresponding to the reservation event list and the congestion delay value of the first period congestion feedback record corresponding to the target reservation event list; determining a congestion delay level of the reservation event list based on the congestion delay value difference; performing communication congestion detection by adopting a first time period congestion feedback record corresponding to the reservation event list to obtain a congestion influence factor set of the first time period of the reservation event list; acquiring modification information of the reservation event list fed back by vehicles in the intelligent parking lot when congestion degree detection is carried out on the basis of the reservation event list and the congestion influence factor combination of the first time period of the reservation event list; and determining a first parking congestion index of a first period congestion feedback record corresponding to the booking event list based on the congestion delay level of the booking event list and the modification information.

Optionally, based on the congestion condition, issuing a sharing instruction of vehicle position information to a target terminal, and performing parking scheduling according to real-time vehicle position sharing information fed back by the target terminal, including:

determining congestion index feature distribution of a congestion index data set corresponding to the congestion condition and parking space area distribution corresponding to the intelligent parking lot; dividing the congestion index feature distribution and the parking space area distribution into at least two distribution subsets according to a mapping relation; acquiring a driving delay parameter of each distribution subset and local congestion index characteristic distribution corresponding to the distribution subset, wherein the local congestion index characteristic distribution is a part of the congestion index characteristic distribution; calculating a mapping offset when each distribution subset is mapped to a distribution subset corresponding to the congestion index feature distribution according to the driving delay parameter of each distribution subset and the local congestion index feature distribution, wherein the mapping offset comprises a congestion index offset; when the congestion index offset is larger than a set offset, mapping the distribution subset to a corresponding distribution subset in the congestion index feature distribution; after the mapping of the at least two distribution subsets is completed, merging the adjacent distribution subsets to obtain off-site congestion information corresponding to the congestion index data set; the off-site congestion information is used for representing congestion information of an external road of the intelligent parking lot;

issuing a sharing instruction of vehicle position information to a target terminal corresponding to a vehicle on a target street corresponding to the congestion street distribution information based on the congestion street distribution information corresponding to the off-site congestion information;

acquiring real-time vehicle position sharing information fed back by the target terminal, and calculating first position sharing delay according to the vehicle position sharing information, wherein the first position sharing delay comprises vehicle congestion delay and street traffic light delay; acquiring traffic flow density updating data corresponding to the vehicle jam delay and lane number distribution data corresponding to the street traffic light delay; generating and storing a first scheduling strategy based on the traffic flow density updating data and the lane number distribution data; calculating a second location sharing delay; extracting a first vehicle position updating track and a second vehicle position updating track in the second position sharing delay; wherein the first vehicle location update trajectory is used to characterize a street traffic light delay of the first target street; the second vehicle position updating track is used for representing vehicle congestion delay of the first target street; obtaining a third vehicle position updating track based on the first vehicle position updating track and the second vehicle position updating track, and determining a second scheduling strategy through the third vehicle position updating track; performing strategy correlation matching on the second scheduling strategy and the prestored first scheduling strategy, and performing congestion tendency analysis on the second target street according to a matching result to obtain a congestion analysis result; the first target street and the second target street are streets corresponding to the intelligent parking lot;

generating a first parking management instruction and a second parking management instruction aiming at the intelligent parking lot according to the first scheduling strategy, the second scheduling strategy and the congestion analysis result, issuing the first parking management instruction to a first vehicle located in the intelligent parking lot, and issuing the second parking management instruction to a second vehicle located outside the intelligent parking lot.

Optionally, acquire first traffic trajectory information and second traffic trajectory information of wisdom parking area in operation process, include:

acquiring traffic flow updating information sampled according to a set time step in the operation process of the intelligent parking lot;

acquiring the first traffic track information and the second traffic track information from the traffic update information; wherein a sampling period difference value between the first traffic track information and the second traffic track information is smaller than a set period value.

Optionally, the method further includes:

acquiring a modification instruction for modifying the set time step length;

and modifying the set time step according to the modification instruction.

A second aspect of the present application discloses a cloud platform comprising a processing engine, a network module, and a memory; the processing engine and the memory communicate via the network module, and the processing engine reads the computer program from the memory and runs it to perform the method of the first aspect.

A third aspect of the present application discloses a computer-readable signal medium having stored thereon a computer program which, when executed, implements the method of the first aspect.

Compared with the prior art, the intelligent parking lot management method and the cloud platform based on hotspot positioning and information sharing provided by the embodiment of the invention have the following technical effects: the method comprises the steps of firstly obtaining different traffic flow track information of the intelligent parking lot, secondly determining a comparison result of hotspot locating distribution of the different traffic flow track information and converting the comparison result into a hotspot sharing locating list, then determining the congestion condition of the intelligent parking lot in an operation time interval between the different traffic flow track information according to parking reservation information in the hotspot sharing locating list, further issuing a sharing instruction of vehicle position information to a target terminal based on the congestion condition, and carrying out parking scheduling according to the real-time vehicle position sharing information. So, can correspond the focus location and the information sharing of vehicle with the wisdom parking area and carry out integrated analysis to the jam condition in wisdom parking area is confirmed fast, accurately, and then realizes managing and dispatching the interior management of field in wisdom parking area according to real-time vehicle position shared information, avoids or reduces the jam of parking and getting out of bus, ensures the smooth and easy operation in wisdom parking area.

In the description that follows, additional features will be set forth, in part, in the description. These features will be in part apparent to those skilled in the art upon examination of the following and the accompanying drawings, or may be learned by production or use. The features of the present application may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities and combinations particularly pointed out in the detailed examples that follow.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

The methods, systems, and/or processes of the figures are further described in accordance with the exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These exemplary embodiments are non-limiting exemplary embodiments in which reference numerals represent similar mechanisms throughout the various views of the drawings.

Fig. 1 is a block diagram of an exemplary hotspot locating and information sharing based intelligent parking lot management system according to some embodiments of the present invention.

FIG. 2 is a schematic diagram illustrating hardware and software components in an exemplary cloud platform according to some embodiments of the invention.

Fig. 3 is a flowchart illustrating an exemplary hotspot locating and information sharing based intelligent parking lot management method and/or process according to some embodiments of the present invention.

Fig. 4 is a block diagram of an exemplary intelligent parking lot management device based on hotspot locating and information sharing according to some embodiments of the present invention.

Detailed Description

In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present invention are the detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features in the embodiments and the examples of the present invention may be combined with each other without conflict.

In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant guidance. It will be apparent, however, to one skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, systems, compositions, and/or circuits have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the invention.

These and other features, functions, methods of execution, and combination of functions and elements of related elements in the structure and economies of manufacture disclosed in the present application may become more apparent upon consideration of the following description with reference to the accompanying drawings, all of which form a part of this application. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the application. It should be understood that the drawings are not to scale. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the invention. It should be understood that the drawings are not to scale.

Flowcharts are used herein to illustrate the implementations performed by systems according to embodiments of the present application. It should be expressly understood that the processes performed by the flowcharts may be performed out of order. Rather, these implementations may be performed in the reverse order or simultaneously. In addition, at least one other implementation may be added to the flowchart. One or more implementations may be deleted from the flowchart.

Fig. 1 is a block diagram illustrating an exemplary smart parking lot management system 300 based on hotspot locating and information sharing according to some embodiments of the present invention, where the smart parking lot management system 300 based on hotspot locating and information sharing may include a cloud platform 100 and a target terminal 200. The cloud platform 100 may be a big data server or an artificial intelligence platform, and the target terminal 200 may be a mobile phone, a tablet computer or a notebook computer.

In some embodiments, as shown in fig. 2, cloud platform 100 may include a processing engine 110, a network module 120, and a memory 130, processing engine 110 and memory 130 communicating through network module 120.

Processing engine 110 may process the relevant information and/or data to perform one or more of the functions described herein. For example, in some embodiments, processing engine 110 may include at least one processing engine (e.g., a single core processing engine or a multi-core processor). By way of example only, the Processing engine 110 may include a Central Processing Unit (CPU), an Application-Specific Integrated Circuit (ASIC), an Application-Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a Reduced Instruction Set Computer (RISC), a microprocessor, or the like, or any combination thereof.

Network module 120 may facilitate the exchange of information and/or data. In some embodiments, the network module 120 may be any type of wired or wireless network or combination thereof. Merely by way of example, the Network module 120 may include a cable Network, a wired Network, a fiber optic Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Public Switched Telephone Network (PSTN), a bluetooth Network, a Wireless personal Area Network, a Near Field Communication (NFC) Network, and the like, or any combination thereof. In some embodiments, the network module 120 may include at least one network access point. For example, the network 120 may include wired or wireless network access points, such as base stations and/or network access points.

The Memory 130 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 130 is used for storing a program, and the processing engine 110 executes the program after receiving the execution instruction.

It is understood that the configuration shown in fig. 2 is merely illustrative, and that cloud platform 100 may include more or fewer components than shown in fig. 2, or have a different configuration than shown in fig. 2. The components shown in fig. 2 may be implemented in hardware, software, or a combination thereof.

Fig. 3 is a flowchart illustrating an exemplary intelligent parking lot management method and/or process based on hotspot locating and information sharing according to some embodiments of the present invention, where the intelligent parking lot management method based on hotspot locating and information sharing is applied to the cloud platform 100 in fig. 1, and may specifically include the contents described in the following steps S310 to S330.

Step S310, first traffic track information and second traffic track information of the intelligent parking lot in the operation process are obtained.

For example, the first traffic track information and the second traffic track information are traffic track information corresponding to a traffic area of the intelligent parking lot in an operation process. The traffic area is an area in the intelligent parking lot, except for the parking space, where vehicles can travel. The traffic flow trajectory information is travel trajectory information of a vehicle in the smart parking lot.

Step S320, obtaining a comparison result of the hotspot locating distributions of the first traffic track information and the second traffic track information, and converting the comparison result of the hotspot locating distributions into a hotspot sharing locating list.

For example, the comparison result of the hotspot locating distribution characterizes a hotspot locating difference of the on-board controller between corresponding parking areas between the first traffic trajectory information and the second traffic trajectory information. The vehicle-mounted controller is installed in the vehicle, and the hot spot positioning difference is used for representing the positioning deviation of the vehicle-mounted controller. The hotspot sharing positioning list comprises a plurality of sharing parking time periods corresponding to parking areas, the parking areas can be understood as areas corresponding to parking spaces, and the sharing parking time periods can be uploaded by a user terminal corresponding to a vehicle or a vehicle-mounted controller.

Step S330, determining the congestion condition of the intelligent parking lot during operation in the operation time interval from the first traffic trajectory information to the second traffic trajectory information according to the parking reservation information of the parking area in the hotspot sharing positioning list; and issuing a sharing instruction of vehicle position information to a target terminal based on the congestion condition, and carrying out parking scheduling according to the real-time vehicle position sharing information fed back by the target terminal.

For example, the parking reservation information is parking space reservation information of different vehicles on a parking space corresponding to the parking area, and the parking reservation information includes which time periods to park, how long the parking time is, and the like. The jam condition is used for representing the car-crossing jam place, the car-crossing jam duration and the like of the vehicles in the intelligent parking lot in the process of entering and exiting. The target terminals may be user terminals communicating with the cloud platform, and one target terminal corresponds to one vehicle. And the sharing instruction is used for indicating the vehicle corresponding to the target terminal to share the vehicle position. The intelligent parking lot management system has the advantages that vehicles corresponding to the target terminals may not drive into the intelligent parking lot in the current time period, parking scheduling management can be conducted on the intelligent parking lot through the vehicle position sharing, and accordingly congestion caused by parking and exiting can be avoided or relieved.

It can be understood that, through the contents described in the above steps S310 to S330, different traffic flow trajectory information of the intelligent parking lot during operation is obtained first, a comparison result of hotspot locating distributions of the different traffic flow trajectory information is determined, the comparison result of the hotspot locating distributions is converted into a hotspot sharing locating list, then a congestion condition of the intelligent parking lot during operation in an operation period between the different traffic flow trajectory information is determined according to parking reservation information of a parking area in the hotspot sharing locating list, a sharing instruction of vehicle position information is issued to a target terminal based on the congestion condition, and parking scheduling is performed according to real-time vehicle position sharing information fed back by the target terminal. So, can carry out the integrated analysis with the hot spot location and the information sharing of the wisdom parking area corresponding vehicle to the jam condition in wisdom parking area is confirmed fast, accurately, and then realizes managing and dispatching the interior outer management in the scene in wisdom parking area according to the real-time vehicle position shared information that target terminal corresponds, avoids or reduces the jam of parking out of car, ensures the smooth and easy operation in wisdom parking area.

In some examples, the comparing of the hotspot locating distributions of the first traffic track information and the second traffic track information in step S320 may include the following: determining first vehicle running track information corresponding to the first traffic track information and second vehicle running track information corresponding to the second traffic track information; and comparing the first vehicle running track information with the second vehicle running track information according to the same hotspot activation time interval to obtain a comparison result of hotspot positioning distribution.

For example, the comparison result of the hotspot locating distribution is expressed in the form of an information list, and the information list includes hotspot longitude and latitude coordinates corresponding to hotspot locating differences of the vehicle-mounted controllers between the parking areas. By the design, the comparison result of the hotspot locating distribution can be determined through different vehicle running track information and hotspot activation time periods, so that the real-time performance of the comparison result of the hotspot locating distribution is ensured, and the comparison result is prevented from lagging.

In some examples, the inventors found that, in order to implement accurate conversion of the comparison result, avoid data loss during the conversion process, and further ensure the integrity of the hotspot sharing location list, in step S320, the comparison result of the hotspot location distribution is converted into the hotspot sharing location list, which may further include the following contents described in step S321 to step S323.

Step S321, acquiring the hotspot longitude and latitude coordinates in the information list corresponding to the comparison result of the hotspot locating distribution.

Step S322, acquiring a hot spot positioning updating queue according to the hot spot longitude and latitude coordinates and the parking reservation information of the corresponding vehicle, and extracting queue elements in the hot spot positioning updating queue according to the time sequence; wherein the queue elements comprise a plurality of real-time longitude and latitude coordinates; and determining the area label weight of each real-time longitude and latitude coordinate of the queue element, and determining the real-time longitude and latitude coordinate number of which the area label weight is less than or equal to the preset label weight according to the area label weight of each real-time longitude and latitude coordinate.

Step S323, calculating the current ratio of the real-time longitude and latitude coordinate number in the total real-time longitude and latitude coordinate number of the queue element to obtain the dynamic hotspot ratio of the queue element; determining the average longitude and latitude coordinates of the queue elements; determining a time-staggered parking statistical result of the queue elements according to the dynamic hotspot occupation ratio of the queue elements and the average longitude and latitude coordinates of the queue elements; according to the corresponding relation between a pre-stored parking period indication list and a hotspot sharing index, determining the hotspot sharing index corresponding to the parking period indication list where the staggered parking statistical result of the queue element is located, and obtaining the hotspot sharing positioning list based on the hotspot sharing index and the corresponding parking space number information in the parking reservation information.

It can be understood that, by executing the above steps S321 to S323, the hotspot longitude and latitude coordinates corresponding to the comparison result of the hotspot locating distribution can be analyzed, and the wrong-time parking condition is taken into account by combining the parking reservation information, so that different parking spaces, different parking periods and hotspot sharing indexes can be comprehensively considered, and then verification is performed from multiple dimensions when the comparison result is converted, thereby avoiding data loss in the conversion process, and further accurately and completely obtaining the hotspot sharing and locating list.

In a possible embodiment, the determining, according to the parking reservation information of the parking area in the hotspot-shared positioning list, that the intelligent parking lot is congested in the operation period from the first traffic track information to the second traffic track information in step S330 may further include the following steps S3311 and S3312.

Step S3311, determining the maximum traffic congestion degree of the corresponding parking area according to the parking reservation information in the hotspot sharing positioning list.

Step S3312, in response to that the maximum traffic congestion degree is greater than a set congestion degree, determining that there is congestion in the operation time period between the first traffic trajectory information and the second traffic trajectory information when the intelligent parking lot operates.

By the design, the jam condition of the intelligent parking lot in operation can be determined based on the traffic congestion degree, so that the vehicle running condition and the road condition corresponding to the intelligent parking lot are taken into consideration, the jam condition of the intelligent parking lot can be stably matched with the actual operation condition, and accurate judgment basis is provided for subsequent parking management scheduling.

Further, in another alternative embodiment, the step S3311 of determining the maximum traffic congestion degree of the corresponding parking area according to the parking reservation information in the hotspot-sharing positioning list may further include the following steps a to e.

Step a, obtaining reservation event lists corresponding to i pieces of parking reservation information respectively and historical parking record sets corresponding to each reservation event list, wherein each reservation event list comprises j different event attributes, and i and j are positive integers larger than or equal to 1.

And b, determining a first-period parking track corresponding to the reservation event list in a historical parking record set corresponding to the reservation event list.

And c, carrying out communication congestion detection by adopting the first-period parking track corresponding to the reservation event list to obtain a congestion influence factor of each event attribute in the reservation event list.

And d, performing track updating iteration on the first-period parking track corresponding to the reservation event list based on the congestion influence factor of each event attribute in the i reservation event lists to obtain the parking track after the first-period iteration corresponding to the reservation event list.

And d, adding the parking track after the first time period iteration corresponding to the reservation event list into the historical parking record set corresponding to the reservation event list.

And e, returning and executing the step to determine a first-period parking track corresponding to the reserved event list in a historical parking record set corresponding to the reserved event list until the comprehensive congestion coefficient corresponding to the hotspot sharing positioning list is converged in a set interval, and calculating the maximum traffic congestion degree of the corresponding parking area according to the relative interval position of the comprehensive congestion coefficient in the set interval.

Further, the step b of determining the parking trajectory of the first time period corresponding to the reserved event list in the historical parking record set corresponding to the reserved event list includes:

step b1, determining a second time interval parking track corresponding to the reservation event list, a first time interval congestion feedback record and a first time interval congestion feedback record corresponding to the target reservation event list based on the historical parking record set;

step b2, comparing the first period congestion feedback record corresponding to the reservation event list with the first period congestion feedback record corresponding to the target reservation event list to obtain a first parking congestion index of the first period congestion feedback record corresponding to the reservation event list;

step b3, comparing a first time interval congestion feedback record corresponding to the reservation event list with a second time interval parking track corresponding to the reservation event list to obtain a second parking congestion index of the first time interval congestion feedback record of the reservation event list;

step b4, based on the second parking congestion index and the first parking congestion index, determining a second-period parking trajectory corresponding to the reserved event list or a parking trajectory corresponding to the first-period congestion feedback record corresponding to the reserved event list as a first-period parking trajectory corresponding to the reserved event list.

Further, the step b2, obtaining the first parking congestion index of the first period congestion feedback record corresponding to the reserved event list by comparing the first period congestion feedback record corresponding to the reserved event list with the first period congestion feedback record corresponding to the target reserved event list, includes:

step b21, determining a congestion delay value of a first period congestion feedback record corresponding to the reservation event list and a congestion delay value of a first period congestion feedback record corresponding to the target reservation event list;

step b22, determining the difference between the congestion delay values of the first period congestion feedback record corresponding to the reservation event list and the first period congestion feedback record corresponding to the target reservation event list according to the congestion delay values of the first period congestion feedback record corresponding to the reservation event list and the congestion delay values of the first period congestion feedback record corresponding to the target reservation event list;

step b23, determining the congestion delay value grade of the reservation event list based on the congestion delay value difference;

b24, performing communication congestion detection by adopting a first time interval congestion feedback record corresponding to the reservation event list to obtain a congestion influence factor set of the first time interval of the reservation event list;

step b25, acquiring modification information of the reservation event list fed back by vehicles in the intelligent parking lot when congestion degree detection is carried out based on the reservation event list and the congestion influence factor combination of the first time period of the reservation event list;

and b26, determining a first parking congestion index of a first period congestion feedback record corresponding to the reservation event list based on the congestion delay level of the reservation event list and the modification information.

It can be understood that, when the contents described in the above steps a to e are applied, iterative computation can be performed on convergence of the comprehensive congestion coefficient corresponding to the hotspot sharing positioning list, so that it can be ensured that the comprehensive congestion coefficient is located in the set section, and thus both the on-site road condition and the off-site road condition of the intelligent parking lot are taken into account. By the design, the maximum traffic congestion degree can be accurately determined in real time.

In some examples, in order to implement the in-field and out-field coordinated scheduling and management of the intelligent parking lot, so as to further reduce the congestion phenomenon inside and outside the intelligent parking lot, the sharing instruction of the vehicle position information is issued to the target terminal based on the congestion condition, which is described in step S330, and the parking scheduling is performed according to the real-time vehicle position sharing information fed back by the target terminal, which may further include the contents described in steps S3321 to S3324 below.

Step S3321, determining congestion index feature distribution of a congestion index data set corresponding to the congestion condition and parking space area distribution corresponding to the intelligent parking lot; dividing the congestion index feature distribution and the parking space area distribution into at least two distribution subsets according to a mapping relation; acquiring a driving delay parameter of each distribution subset and local congestion index characteristic distribution corresponding to the distribution subset, wherein the local congestion index characteristic distribution is a part of the congestion index characteristic distribution; calculating a mapping offset when each distribution subset is mapped to a distribution subset corresponding to the congestion index feature distribution according to the driving delay parameter of each distribution subset and the local congestion index feature distribution, wherein the mapping offset comprises a congestion index offset; when the congestion index offset is larger than a set offset, mapping the distribution subset to a corresponding distribution subset in the congestion index feature distribution; after the mapping of the at least two distribution subsets is completed, merging the adjacent distribution subsets to obtain off-site congestion information corresponding to the congestion index data set; the off-site congestion information is used for representing congestion information of an external road of the intelligent parking lot.

Step S3322, based on the congestion street distribution information corresponding to the off-site congestion information, issuing a sharing instruction of vehicle position information to a target terminal corresponding to a vehicle on a target street corresponding to the congestion street distribution information.

Step S3323, acquiring real-time vehicle position sharing information fed back by the target terminal, and performing first position sharing delay calculation according to the vehicle position sharing information, wherein the first position sharing delay comprises vehicle congestion delay and street traffic light delay; acquiring traffic flow density updating data corresponding to the vehicle jam delay and lane number distribution data corresponding to the street traffic light delay; generating and storing a first scheduling strategy based on the traffic flow density updating data and the lane number distribution data; calculating a second location sharing delay; extracting a first vehicle position updating track and a second vehicle position updating track in the second position sharing delay; wherein the first vehicle location update trajectory is used to characterize a street traffic light delay of the first target street; the second vehicle position updating track is used for representing vehicle congestion delay of the first target street; obtaining a third vehicle position updating track based on the first vehicle position updating track and the second vehicle position updating track, and determining a second scheduling strategy through the third vehicle position updating track; performing strategy correlation matching on the second scheduling strategy and the prestored first scheduling strategy, and performing congestion tendency analysis on the second target street according to a matching result to obtain a congestion analysis result; the first target street and the second target street are streets corresponding to the intelligent parking lot.

Step S3324, generating a first parking management instruction and a second parking management instruction for the intelligent parking lot according to the first scheduling strategy, the second scheduling strategy and the congestion analysis result, issuing the first parking management instruction to a first vehicle located in the intelligent parking lot, and issuing the second parking management instruction to a second vehicle located outside the intelligent parking lot.

By the design, the congestion condition in the parking lot can be considered, the congestion condition outside the parking lot can be considered, and therefore a first parking management instruction and a second parking management instruction for the intelligent parking lot are generated according to the first scheduling strategy, the second scheduling strategy and the congestion analysis result, the first parking management instruction is issued to a first vehicle located in the intelligent parking lot, and the second parking management instruction is issued to a second vehicle located outside the intelligent parking lot. Like this, can realize inside and outside cooperation dispatch and management to the wisdom parking area to further reduce the jam phenomenon outside the scene of wisdom parking area.

In some examples, the obtaining of the first traffic track information and the second traffic track information of the intelligent parking lot during the operation process described in step S310 may further include the following steps S311 and S312.

And step S311, acquiring the traffic flow updating information sampled according to the set time step in the operation process of the intelligent parking lot.

Step S312, obtaining the first traffic trajectory information and the second traffic trajectory information from the traffic update information.

For example, a sampling period difference between the first traffic track information and the second traffic track information is smaller than a set period value.

Further, the basic mountain in step S311 and step S312 may further include the following: acquiring a modification instruction for modifying the set time step length; and modifying the set time step according to the modification instruction.

In an alternative embodiment, the inventor finds that, when acquiring the traffic flow update information, information compatibility between the acquisition device corresponding to the smart parking lot and the cloud platform needs to be considered, so that it can be ensured that the traffic flow update information acquired by the cloud platform is not missing. To achieve this, it is necessary to synchronously acquire device configuration parameters of the collection device to achieve compatibility adjustment, and therefore, on the basis of acquiring traffic flow update information sampled according to the set time step in the operation process of the intelligent parking lot described in step S311, the following contents described in steps S3111 to S3114 may be further included.

Step S3111, obtaining to-be-processed traffic flow information sent by a collection device corresponding to the smart parking lot and a device configuration parameter set corresponding to the collection device, and performing information iterative correction on the to-be-processed traffic flow information based on the device configuration parameter set, where at least one compatibility identifier for matching the to-be-processed traffic flow information exists in the device configuration parameter set.

Step S3112, when detecting that a first compatibility identifier exists in the device configuration parameter set during the iterative information correction process of the to-be-processed traffic information, detecting whether a first identifier heat weighted value is recorded in the first compatibility identifier; the first identification heat weighted value is recorded on the first compatibility identification when the to-be-processed traffic information is not matched with the first compatibility identification for the last time, and the first identification heat weighted value is the weighted sum of the identification heat values of the compatibility identifications of the to-be-processed traffic information when the to-be-processed traffic information is not matched for the last time.

Step S3113, when the first compatibility identifier does not have the first identifier heat weighting value, detecting whether the first compatibility identifier is a compatibility identifier for which matching requirements exist in the to-be-processed traffic information; when the first compatibility identifier is determined to be the compatibility identifier with the matching requirement of the traffic flow information to be processed, matching the traffic flow information to be processed with the first compatibility identifier, and updating a second identifier heat weighted value of the traffic flow information to be processed according to a first identifier heat value of the first compatibility identifier; when the first compatibility identifier has the first identifier heat weighted value, detecting whether the first identifier heat weighted value is the same as a second identifier heat weighted value of the to-be-processed traffic information, wherein the second identifier heat weighted value is the weighted sum of the identifier heat values of the compatibility identifiers currently possessed by the to-be-processed traffic information; when the first identification popularity weighted value is different from a second identification popularity weighted value of the traffic information to be processed, acquiring a log text in the process that the first identification popularity weighted value is changed to the second identification popularity weighted value; acquiring a second identification heat degree value which changes in the first identification heat degree weighted value according to the log text; detecting whether the first compatibility identifier meets the matching condition according to the first identifier heat value and the second identifier heat value; and when the first compatibility identifier meets the matching condition, matching the to-be-processed traffic flow information with the first compatibility identifier, and updating the second identifier heat weighted value according to the first identifier heat value.

Step S3114, performing information compatibility adjustment on the to-be-processed traffic flow information based on the first compatibility identifier matched with the to-be-processed traffic flow information, so as to obtain the traffic flow update information.

Thus, by executing the steps S3111 to S3114, the compatibility adjustment is realized by synchronously obtaining the device configuration parameters of the collection device, and the information compatibility between the collection device corresponding to the smart parking lot and the cloud platform can be considered, so that it is ensured that the traffic flow update information obtained by the cloud platform is not lost, and the cloud platform can completely obtain the traffic flow update information to determine different traffic flow track information.

Fig. 4 is a block diagram illustrating an exemplary intelligent parking lot management device 140 based on hotspot locating and information sharing according to some embodiments of the present invention, where the intelligent parking lot management device 140 based on hotspot locating and information sharing includes:

the traffic flow track obtaining module 141 is configured to obtain first traffic flow track information and second traffic flow track information of the intelligent parking lot in an operation process, where the first traffic flow track information and the second traffic flow track information are traffic flow track information corresponding to a traffic area of the intelligent parking lot in the operation process;

the hotspot sharing and converting module 142 is configured to obtain a comparison result of hotspot locating distributions of the first traffic trajectory information and the second traffic trajectory information, where the comparison result of the hotspot locating distributions represents a hotspot locating difference of the vehicle-mounted controller between corresponding parking areas between the first traffic trajectory information and the second traffic trajectory information; converting the comparison result of the hotspot locating distribution into a hotspot sharing locating list, wherein the hotspot sharing locating list comprises sharing parking time intervals corresponding to a plurality of parking areas;

the parking management scheduling module 143 is configured to determine, according to the parking reservation information of the parking area in the hotspot-sharing positioning list, a congestion condition of the intelligent parking lot during operation in an operation time period from the first traffic trajectory information to the second traffic trajectory information; and issuing a sharing instruction of vehicle position information to a target terminal based on the congestion condition, and carrying out parking scheduling according to the real-time vehicle position sharing information fed back by the target terminal.

It is understood that please refer to the description of the method shown in fig. 3 for the description of the embodiment of the apparatus, which is not repeated herein.

Based on the same inventive concept, the invention also provides an intelligent parking lot management system based on hotspot positioning and information sharing, which comprises a cloud platform and a target terminal, wherein the cloud platform and the target terminal are communicated with each other; wherein the cloud platform is to:

It is understood that please refer to the description of the method shown in fig. 3 for the description of the embodiment of the system, which is not repeated herein.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered merely illustrative and not restrictive of the broad application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific terminology to describe embodiments of the application. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the present application is included in at least one embodiment of the present application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of at least one embodiment of the present application may be combined as appropriate.

In addition, those skilled in the art will recognize that the various aspects of the application may be illustrated and described in terms of several patentable species or contexts, including any new and useful combination of procedures, machines, articles, or materials, or any new and useful modifications thereof. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as a "unit", "component", or "system". Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in at least one computer readable medium.

A computer readable signal medium may comprise a propagated data signal with computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, and the like, or any suitable combination. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code on a computer readable signal medium may be propagated over any suitable medium, including radio, electrical cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the execution of aspects of the present application may be written in any combination of one or more programming languages, including object oriented programming, such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, or similar conventional programming languages, such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages, such as Python, Ruby, and Groovy, or other programming languages. The programming code may execute entirely on the user's computer, as a stand-alone software package, partly on the user's computer, partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network format, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Additionally, the order of the process elements and sequences described herein, the use of numerical letters, or other designations are not intended to limit the order of the processes and methods unless otherwise indicated in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it should be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware means, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

It should also be appreciated that in the foregoing description of embodiments of the present application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of at least one embodiment of the invention. However, this method of disclosure is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Claims

1. An intelligent parking lot management method based on hotspot positioning and information sharing is characterized by comprising the following steps:

according to the parking reservation information of the parking area in the hotspot sharing positioning list, determining the congestion condition of the intelligent parking lot during operation in the operation time period from the first traffic track information to the second traffic track information; based on the congestion condition, issuing a sharing instruction of vehicle position information to a target terminal, and carrying out parking scheduling according to the real-time vehicle position sharing information fed back by the target terminal;

wherein the obtaining of the comparison result of the hotspot locating distribution of the first traffic track information and the second traffic track information includes: determining first vehicle running track information corresponding to the first traffic track information and second vehicle running track information corresponding to the second traffic track information; comparing the first vehicle running track information with the second vehicle running track information according to the same hotspot activation time period to obtain a comparison result of hotspot positioning distribution; the comparison result of the hotspot locating distribution is expressed in the form of an information list, and the information list comprises hotspot longitude and latitude coordinates corresponding to hotspot locating differences of the vehicle-mounted controllers among the parking areas;

wherein converting the comparison result of the hotspot locating distribution into a hotspot sharing locating list comprises: acquiring the hotspot longitude and latitude coordinates in the information list corresponding to the comparison result of the hotspot positioning distribution; acquiring a hot spot positioning updating queue according to the hot spot longitude and latitude coordinates and parking reservation information of a vehicle corresponding to the hot spot longitude and latitude coordinates, and extracting queue elements in the hot spot updating queue according to a time sequence; wherein the queue elements comprise a plurality of real-time longitude and latitude coordinates; determining the area label weight of each real-time longitude and latitude coordinate of the queue element, and determining the number of the real-time longitude and latitude coordinates of which the area label weight is less than or equal to the preset label weight according to the area label weight of each real-time longitude and latitude coordinate; calculating the current occupation ratio of the real-time longitude and latitude coordinate number in the total real-time longitude and latitude coordinate number of the queue element to obtain the dynamic hot spot occupation ratio of the queue element; determining the average longitude and latitude coordinates of the queue elements; determining a time-staggered parking statistical result of the queue elements according to the dynamic hotspot occupation ratio of the queue elements and the average longitude and latitude coordinates of the queue elements; determining a hotspot sharing index corresponding to the parking period indication list where the staggered parking statistical result of the queue element is located according to a corresponding relation between a pre-stored parking period indication list and the hotspot sharing index, and obtaining the hotspot sharing positioning list based on the hotspot sharing index and the corresponding parking space number information in the parking reservation information;

wherein, the determining, according to the parking reservation information of the parking area in the hotspot-sharing positioning list, a congestion condition of the intelligent parking lot during operation in an operation time period from the first traffic trajectory information to the second traffic trajectory information includes: determining the maximum traffic congestion degree of a corresponding parking area according to the parking reservation information in the hotspot sharing positioning list; in response to the fact that the maximum traffic congestion degree is larger than a set congestion degree, determining that congestion exists in the intelligent parking lot during operation in an operation time period from the first traffic trajectory information to the second traffic trajectory information;

determining the maximum traffic congestion degree of a corresponding parking area according to the parking reservation information in the hotspot sharing positioning list, wherein the determining comprises the following steps:

acquiring reservation event lists corresponding to the i pieces of parking reservation information and a historical parking record set corresponding to each reservation event list, wherein each reservation event list comprises j different event attributes, and i and j are positive integers greater than or equal to 1;

determining a first period parking track corresponding to the reservation event list in a historical parking record set corresponding to the reservation event list;

carrying out communication congestion detection by adopting a first time period parking track corresponding to the reservation event list to obtain a congestion influence factor of each event attribute in the reservation event list;

performing track updating iteration on a first-period parking track corresponding to an appointment event list based on a congestion influence factor of each event attribute in i appointment event lists to obtain a parking track after the first-period iteration corresponding to the appointment event list;

adding the parking track after the first time period iteration corresponding to the reservation event list into a historical parking record set corresponding to the reservation event list;

returning and executing the step to determine a first-period parking track corresponding to the reserved event list in a historical parking record set corresponding to the reserved event list until the comprehensive congestion coefficient corresponding to the hotspot sharing positioning list is converged in a set interval, and calculating the maximum traffic congestion degree of a corresponding parking area according to the relative interval position of the comprehensive congestion coefficient in the set interval;

2. The method according to claim 1, wherein issuing a sharing instruction of vehicle position information to a target terminal based on the congestion condition, and performing parking scheduling according to real-time vehicle position sharing information fed back by the target terminal comprises:

acquiring real-time vehicle position sharing information fed back by the target terminal, and calculating first position sharing delay according to the vehicle position sharing information, wherein the first position sharing delay comprises vehicle congestion delay and street traffic light delay; acquiring traffic flow density updating data corresponding to the vehicle jam delay and lane number distribution data corresponding to the street traffic light delay; generating and storing a first scheduling strategy based on the traffic flow density updating data and the lane number distribution data; calculating a second location sharing delay; extracting a first vehicle position updating track and a second vehicle position updating track in the second position sharing delay; wherein the first vehicle location update trajectory is used to characterize a street traffic light delay of a first target street; the second vehicle position updating track is used for representing vehicle congestion delay of the first target street; obtaining a third vehicle position updating track based on the first vehicle position updating track and the second vehicle position updating track, and determining a second scheduling strategy through the third vehicle position updating track; performing strategy correlation matching on the second scheduling strategy and the prestored first scheduling strategy, and performing congestion tendency analysis on a second target street according to a matching result to obtain a congestion analysis result; the first target street and the second target street are streets corresponding to the intelligent parking lot;

3. The method according to any one of claims 1 to 2, wherein the obtaining of the first traffic track information and the second traffic track information of the intelligent parking lot during operation comprises:

4. The method of claim 3, further comprising:

acquiring a modification instruction for modifying the set time step length;

and modifying the set time step according to the modification instruction.

5. A cloud platform comprising a processing engine, a network module, and a memory; the processing engine and the memory communicate through the network module, the processing engine reading a computer program from the memory and operating to perform the method of any of claims 1-4.

6. A computer-readable storage medium, on which a computer program is stored which, when executed, implements the method of any one of claims 1-4.