CN111325986B - Abnormal parking monitoring method and device, electronic equipment and storage medium - Google Patents

Abnormal parking monitoring method and device, electronic equipment and storage medium Download PDF

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Publication number
CN111325986B
CN111325986B CN201910273238.4A CN201910273238A CN111325986B CN 111325986 B CN111325986 B CN 111325986B CN 201910273238 A CN201910273238 A CN 201910273238A CN 111325986 B CN111325986 B CN 111325986B
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preset
sub
preset area
mobile terminal
value
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CN111325986A (en
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李海波
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Beijing Didi Infinity Technology and Development Co Ltd
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Beijing Didi Infinity Technology and Development Co Ltd
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
    • G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]

Abstract

The application provides an abnormal parking monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of traffic detection. According to the embodiment of the application, the running tracks of the mobile terminals in the preset area on the road are obtained, whether the running track deviation of the mobile terminals meets the preset condition is used for judging, whether abnormal parking exists in the preset area where the vehicle carrying the mobile terminals passes is judged, and therefore the fact that the running track deviation of the vehicle in the preset area can be used for judging is achieved, whether abnormal parking exists in the preset area is determined, and then areas needing monitoring in key points are determined according to the judgment result, and monitoring points can be deployed more flexibly and more accurately in a violation mode.

Description

Abnormal parking monitoring method and device, electronic equipment and storage medium
Technical Field
The application relates to the technical field of traffic monitoring, in particular to an abnormal parking monitoring method, an abnormal parking monitoring device, electronic equipment and a storage medium.
Background
At present, with the development of society and the improvement of living standard of people, vehicles are more and more on roads, but the problem that illegal parking exists on the roads is more and more, and road traffic is seriously influenced.
At present, the method for managing the illegal parking on the road generally needs to monitor vehicles parked illegally on the road by installing an electronic eye, a camera and the like at a fixed position on the road and monitoring the illegal parking on the road in a way that a traffic police patrols the road so as to take relevant treatment measures and improve the traffic management quality.
However, the existing monitoring method for vehicles which stop violating parking cannot flexibly determine the area needing monitoring according to the condition of the violating parking in the road section.
Disclosure of Invention
In view of this, an object of the embodiments of the present application is to provide an abnormal parking monitoring method, an abnormal parking monitoring device, an electronic device, and a storage medium, which can obtain a moving end with an abnormal driving track by analyzing a driving track of the moving end in a preset area on a road, and further determine that there is an abnormal parking on the road, so as to solve the problems that in the prior art, a location of the road where monitoring is not convenient to install is not located, the location where monitoring is not located is not monitored, and the efficiency of a traffic police patrol mode is low.
In a first aspect, an embodiment of the present application provides an abnormal parking monitoring method, where the method includes: acquiring m mobile terminal driving tracks in a preset area on a road, wherein m is an integer larger than 0;
judging whether the running track deviation in a preset area meets a preset condition or not according to the running tracks of the m mobile terminals;
and if the preset condition is met, determining that abnormal parking exists in the preset area.
Optionally, the obtaining m mobile terminal driving tracks in a preset area on a road includes:
acquiring a positioning coordinate point set of each mobile terminal in m mobile terminals on a road;
and obtaining m mobile terminal driving tracks according to the positioning coordinate point set of each mobile terminal.
Optionally, judging whether a running track deviation in a preset area meets a preset condition according to m running tracks of the mobile terminal, including:
dividing a preset area into a plurality of first sub-road sections according to a first preset length, and calculating and acquiring a position mean value of each first sub-road section according to a positioning coordinate point set;
calculating and acquiring a preset number of position peak values in a preset area according to the positioning coordinate point set;
and judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and a preset number of position peak values.
Optionally, judging whether the running track deviation in the preset area meets a preset condition according to a preset algorithm, the position mean values of the plurality of first sub-road sections and a preset number of position peak values, including:
calculating the position mean value of a preset area according to the position mean values of the plurality of first sub-road sections;
calculating the average value of the peak values of a preset number of positions;
judging whether the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than a preset threshold value or not;
correspondingly, if the preset condition is met, determining that abnormal parking exists in the preset area, including:
and if the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than a preset threshold value, determining that abnormal parking exists in the preset area.
Optionally, judging whether a running track deviation in a preset area meets a preset condition according to m running tracks of the mobile terminal, including:
dividing a preset area into a plurality of first sub-road sections according to a first preset length, and calculating and acquiring a position mean value of each first sub-road section according to a positioning coordinate point set;
dividing the preset area into a plurality of second sub-road sections according to a second preset length, and calculating and acquiring a preset number of position peak values in each second sub-road section according to the positioning coordinate point set, wherein the second preset length is greater than the first preset length;
judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and the preset number of position peak values of each second sub-road section;
correspondingly, if the preset condition is met, determining that abnormal parking exists in the preset area, including:
and if the running track deviation in the preset area is sufficient to the preset condition, determining that abnormal parking exists in the preset area.
Optionally, judging whether the running track deviation in the preset area meets a preset condition according to a preset algorithm, the position mean values of the plurality of first sub-road sections and a preset number of position peak values of each second sub-road section, including:
calculating the position mean value of a preset area according to the position mean values of the plurality of first sub-road sections;
the average value of the peak values of the preset number of positions in each second sub-section;
acquiring a position average value of a preset area and a difference value between the position average value and an average value of a preset number of position peak values in each second sub-road section;
determining whether a second sub-road section with the difference value larger than a preset threshold value exists;
correspondingly, if the deviation of the driving track in the preset area is sufficient to the preset condition, determining that abnormal parking exists in the preset area, including:
and if the second sub-road section with the difference value larger than the preset threshold value exists, determining that abnormal parking exists in the second sub-road section with the difference value larger than the preset threshold value.
Optionally, after determining that there is an abnormal parking in the second sub-road segment where the difference is greater than the preset threshold, the method further includes:
and acquiring a position coordinate corresponding to the position peak value according to the position peak value in the second sub-road section with the difference value larger than the preset threshold value.
Optionally, obtaining m mobile terminal driving tracks according to the positioning coordinate point set of each mobile terminal includes:
screening positioning coordinate points in the positioning coordinate point set of each mobile terminal according to a preset rule to obtain a screened positioning coordinate point set of each mobile terminal;
and obtaining m mobile terminal driving tracks according to the positioning coordinate point set screened by each mobile terminal.
In a second aspect, an embodiment of the present application provides an abnormal parking monitoring device, where the device includes: the device comprises an acquisition module and a judgment module;
the system comprises an acquisition module, a processing module and a control module, wherein the acquisition module is used for acquiring m mobile terminal driving tracks in a preset area on a road, and m is an integer larger than 0;
the judging module is used for judging whether the running track deviation in the preset area meets the preset condition or not according to the running tracks of the m mobile terminals; and if the preset condition is met, determining that abnormal parking exists in the preset area.
Optionally, the obtaining module is specifically configured to obtain a set of location coordinate points of each of m mobile terminals on the road;
and obtaining m mobile terminal driving tracks according to the positioning coordinate point set of each mobile terminal.
Optionally, the determining module is specifically configured to divide the preset area into a plurality of first sub-segments according to a first preset length, and calculate and obtain a position average value of each first sub-segment according to the set of positioning coordinate points;
calculating and acquiring a preset number of position peak values in a preset area according to the positioning coordinate point set;
and judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and a preset number of position peak values.
Optionally, the determining module is specifically configured to calculate a position average value of the preset area according to the position average values of the plurality of first sub-road segments; calculating the average value of the peak values of a preset number of positions; judging whether the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than a preset threshold value or not; and if the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than a preset threshold value, determining that abnormal parking exists in the preset area.
Optionally, the determining module is specifically configured to divide the preset area into a plurality of first sub-segments according to a first preset length, and calculate and obtain a position average value of each first sub-segment according to the set of positioning coordinate points; dividing the preset area into a plurality of second sub-road sections according to a second preset length, and calculating and acquiring a preset number of position peak values in each second sub-road section according to the positioning coordinate point set, wherein the second preset length is greater than the first preset length; judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and the preset number of position peak values of each second sub-road section; and if the running track deviation in the preset area is sufficient to the preset condition, determining that abnormal parking exists in the preset area.
Optionally, the determining module is specifically configured to calculate a position average value of the preset area according to the position average values of the plurality of first sub-road segments; the average value of the peak values of the preset number of positions in each second sub-section; acquiring a position average value of a preset area and a difference value between the position average value and an average value of a preset number of position peak values in each second sub-road section; determining whether a second sub-road section with the difference value larger than a preset threshold value exists; and if the second sub-road section with the difference value larger than the preset threshold value exists, determining that abnormal parking exists in the second sub-road section with the difference value larger than the preset threshold value.
Optionally, the processing module is further configured to obtain a position coordinate corresponding to the position peak according to the position peak in the second sub-road segment of which the difference is greater than the preset threshold.
Optionally, the obtaining module is specifically configured to filter the positioning coordinate points in the positioning coordinate point set of each mobile terminal according to a preset rule, so as to obtain a filtered positioning coordinate point set of each mobile terminal;
and obtaining m mobile terminal driving tracks according to the positioning coordinate point set screened by each mobile terminal.
In a third aspect, an embodiment of the present application provides an electronic device, including: the system comprises a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, when the electronic device runs, the processor and the storage medium communicate through the bus, and the processor executes the machine-readable instructions to execute the steps of the abnormal parking monitoring method according to any one of the first aspect.
In a fourth aspect, an embodiment of the present application provides a storage medium, where a computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the abnormal parking monitoring method according to any one of the first aspect are executed.
In the embodiment of the application, whether the deviation of the running track of the mobile terminal meets the preset condition or not is judged by acquiring the running tracks of the mobile terminals in the preset area on the road, and whether abnormal parking exists in the preset area through which a vehicle carrying the mobile terminal passes is judged, so that whether abnormal parking exists in the preset area or not is determined by judging the deviation of the running track of the vehicle in the preset area, and further areas needing monitoring in key points are determined according to the judgment result, and more flexible and more accurate deployment of violation monitoring points can be realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required 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 application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is a block diagram of an abnormal parking monitoring system of some embodiments of the present application;
FIG. 2 illustrates a schematic diagram of exemplary hardware and software components of an electronic device of some embodiments of the present application;
FIG. 3 is a schematic flow chart illustrating an abnormal parking monitoring method according to an embodiment of the present application;
FIG. 4 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the application;
FIG. 5 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the application;
FIG. 6 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the present application;
FIG. 7 is a schematic flow chart illustrating another abnormal parking monitoring method provided by the embodiment of the present application;
FIG. 8 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the present application;
FIG. 9 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the present application;
fig. 10 is a schematic structural diagram illustrating an abnormal parking monitoring device according to an embodiment of the present application;
fig. 11 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of protection of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.
In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In order to enable a person skilled in the art to use the present disclosure, the following embodiments are given in connection with a specific application scenario "road driving". It will be apparent to those skilled in the art that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. Although the present application is described primarily in the context of road driving, it should be understood that this is merely one exemplary embodiment. The application can be applied to any other traffic type. For example, the present application may be applied to different transportation system environments, including terrestrial, marine, or airborne, among others, or any combination thereof. The transportation means of the transportation system may comprise a taxi, a private car, a windmill, a bus, a train, a bullet train, a high speed railway, a subway, a ship, an airplane, a hot air balloon, or an unmanned vehicle, etc., or any combination thereof.
It should be noted that in the embodiments of the present application, the term "comprising" is used to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.
The Positioning technology used in the present application may be based on a Global Positioning System (GPS), a Global Navigation Satellite System (GLONASS), a COMPASS Navigation System (COMPASS), a galileo Positioning System, a Quasi-Zenith Satellite System (QZSS), a Wireless Fidelity (WiFi) Positioning technology, or the like, or any combination thereof. One or more of the above-described positioning systems may be used interchangeably in this application.
It should be noted that the abnormal parking in the embodiment indicates that the position where the vehicle parks is at an unreasonable position, such as a normal vehicle parking in a bus lane, a vehicle parking on a highway, a vehicle parking in the center of a road, a vehicle parking on a zebra crossing, and the like.
FIG. 1 is a block diagram of an abnormal parking monitoring system of some embodiments of the present application; as shown in fig. 1, for example, the abnormal parking monitoring system may be an online transportation service platform for transportation services such as taxi cab, designated driving service, express bus, carpool, bus service, driver rental, or regular bus service, or any combination thereof. The abnormal parking monitoring system may include one or more of a server 110, a network 120, a driving position collecting terminal 130 and a database 140, and the server 110 may include a processor for executing instructions.
In some embodiments, the server 110 may be a single server or a group of servers. The set of servers can be centralized or distributed (e.g., the servers 110 can be a distributed system). In some embodiments, the server 110 may be local or remote to the terminal. For example, the server 110 may access information and/or data stored in the driving location collection end 130, or the database 140, or any combination thereof, via the network 120. As another example, the server 110 may be directly connected to at least one of the driving location collection terminal 130 and the database 140 to access stored information and/or data. In some embodiments, the server 110 may be implemented on a cloud platform; by way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud (community cloud), a distributed cloud, an inter-cloud, a multi-cloud, and the like, or any combination thereof. In some embodiments, the server 110 may be implemented on an electronic device 200 having one or more of the components shown in FIG. 2 in the present application.
In some embodiments, the server 110 may include a processor. The processor may process information and/or data related to the service request to perform one or more of the functions described herein. For example, the processor may determine the target vehicle based on a service request obtained from the driving position collection terminal 130. In some embodiments, a processor may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, a 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 (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 (Reduced Instruction Set computer), a microprocessor, or the like, or any combination thereof.
Network 120 may be used for the exchange of information and/or data. In some embodiments, one or more components of the abnormal parking monitoring system (e.g., server 110, vehicle location collection end 130, and database 140) may send information and/or data to other components. For example, the server 110 may collect the driving position information from the driving position collecting terminal 130 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or combination thereof. Merely by way of example, Network 120 may include a wired Network, a Wireless 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 Wide Area Network (WAN), a Public Switched Telephone Network (PSTN), a bluetooth Network, a ZigBee Network, a Near Field Communication (NFC) Network, or the like, or any combination thereof. In some embodiments, network 120 may include one or more network access points. For example, network 120 may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of the abnormal parking monitoring system may connect to network 120 to exchange data and/or information.
In some embodiments, the driving position acquisition end 130 may include a mobile device, a tablet computer, a laptop computer, or a built-in device in a motor vehicle, etc., or any combination thereof. In some embodiments, the mobile device may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home devices may include smart lighting devices, control devices for smart electrical devices, smart monitoring devices, smart televisions, smart cameras, or walkie-talkies, or the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, and the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a Personal Digital Assistant (PDA), a gaming device, a navigation device, or a point of sale (POS) device, or the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or augmented reality device may include various virtual reality products and the like. In some embodiments, the built-in devices in the motor vehicle may include an on-board computer, an on-board television, and the like. In some embodiments, the driving position collection end 130 may be a device having a positioning technology for locating the position of the service requester and/or the driving position collection end.
In some embodiments, database 140 may store data and/or instructions. In some embodiments, the database 140 may store data obtained from the driving position acquisition end 130. In some embodiments, database 140 may store data and/or instructions for the exemplary methods described herein. In some embodiments, the database 140 may include mass storage, removable storage, volatile Read-write Memory, or Read-Only Memory (ROM), among others, or any combination thereof. By way of example, mass storage may include magnetic disks, optical disks, solid state drives, and the like; removable memory may include flash drives, floppy disks, optical disks, memory cards, zip disks, tapes, and the like; volatile read-write Memory may include Random Access Memory (RAM); the RAM may include Dynamic RAM (DRAM), Double data Rate Synchronous Dynamic RAM (DDR SDRAM); static RAM (SRAM), Thyristor-Based Random Access Memory (T-RAM), Zero-capacitor RAM (Zero-RAM), and the like. By way of example, ROMs may include Mask Read-Only memories (MROMs), Programmable ROMs (PROMs), Erasable Programmable ROMs (PERROMs), Electrically Erasable Programmable ROMs (EEPROMs), compact disk ROMs (CD-ROMs), digital versatile disks (ROMs), and the like. In some embodiments, database 140 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, or the like, or any combination thereof.
In some embodiments, a database 140 may be connected to network 120 to communicate with one or more components in the abnormal parking monitoring system (e.g., server 110, driving location collection end 130, etc.). One or more components of the abnormal parking monitoring system may access data or instructions stored in database 140 via network 120. In some embodiments, the database 140 may be directly connected to one or more components in the abnormal parking monitoring system (e.g., the server 110, the driving position collection end 130); alternatively, in some embodiments, database 140 may also be part of server 110.
In some embodiments, one or more components of the abnormal parking monitoring system (e.g., server 110, drive location collection end 130, etc.) may have access to database 140. In some embodiments, one or more components in the abnormal parking monitoring system may read and/or modify information related to the service requester, the service provider, or the public, or any combination thereof, when certain conditions are met. For example, server 110 may read and/or modify information for one or more users after receiving a service request. As another example, the position information of the vehicle may be collected at the slave vehicle position collecting terminal 130.
In some embodiments, the exchange of information by one or more components in the abnormal parking monitoring system may be accomplished by requesting service. The object of the service request may be any product. In some embodiments, the product may be a tangible product or a non-physical product. Tangible products may include food, pharmaceuticals, commodities, chemical products, appliances, clothing, automobiles, homes, or luxury goods, and the like, or any combination thereof. The non-material product may include a service product, a financial product, a knowledge product, an internet product, or the like, or any combination thereof. The internet product may include a stand-alone host product, a network product, a mobile internet product, a commercial host product, an embedded product, or the like, or any combination thereof. The internet product may be used in software, programs, or systems of the mobile terminal, etc., or any combination thereof. The mobile terminal may include a tablet, a laptop, a mobile phone, a Personal Digital Assistant (PDA), a smart watch, a Point of sale (POS) device, a vehicle-mounted computer, a vehicle-mounted television, a wearable device, or the like, or any combination thereof. The internet product may be, for example, any software and/or application used in a computer or mobile phone. The software and/or applications may relate to social interaction, shopping, transportation, entertainment time, learning, or investment, or the like, or any combination thereof. In some embodiments, the transportation-related software and/or applications may include travel software and/or applications, vehicle dispatch software and/or applications, mapping software and/or applications, and the like. In the vehicle scheduling software and/or application, the vehicle may include a horse, a carriage, a human powered vehicle (e.g., unicycle, bicycle, tricycle, etc.), an automobile (e.g., taxi, bus, privatege, etc.), a train, a subway, a ship, an airplane (e.g., airplane, helicopter, space shuttle, rocket, hot air balloon, etc.), etc., or any combination thereof.
FIG. 2 illustrates a schematic diagram of exemplary hardware and software components of an electronic device of some embodiments of the present application; as shown in fig. 2, for example, a processor may be used on the electronic device 200 and to perform the functions in the present application.
The electronic device 200 may be a general purpose computer or a special purpose computer, both of which may be used to implement the abnormal parking monitoring method of the present application. Although only a single computer is shown, for convenience, the functions described herein may be implemented in a distributed fashion across multiple similar platforms to balance processing loads.
For example, the electronic device 200 may include a network port 210 connected to a network, one or more processors 220 for executing program instructions, a communication bus 230, and a different form of storage medium 240, such as a disk, ROM, or RAM, or any combination thereof. Illustratively, the computer platform may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The method of the present application may be implemented in accordance with these program instructions.
For ease of illustration, only one processor is depicted in the electronic device 200. However, it should be noted that the electronic device 200 in the present application may also comprise a plurality of processors, and thus the steps performed by one processor described in the present application may also be performed by a plurality of processors in combination or individually. For example, if the processor of the electronic device 200 executes steps a and B, it should be understood that steps a and B may also be executed by two different processors together or separately in one processor. For example, a first processor performs step a and a second processor performs step B, or the first processor and the second processor perform steps a and B together.
FIG. 3 is a schematic flow chart illustrating an abnormal parking monitoring method according to an embodiment of the present application; as shown in fig. 3, the abnormal parking monitoring method provided by the present application includes:
s101, acquiring m mobile terminal driving tracks in a preset area on a road.
According to the position coordinates, the traffic information and the like of the road, a preset area can be selected in advance in the road, and the running track of the mobile terminal passing through the preset area is collected. If m driving tracks are acquired, m vehicles are considered to pass through the road section. Wherein m is an integer greater than 0.
The mobile terminal may be a vehicle-mounted device of a vehicle passing through the preset area, or may be a handheld terminal (e.g., a mobile phone, a tablet computer, etc.) of a user in the vehicle.
S102, judging whether the running track deviation in the preset area meets the preset condition or not according to the running tracks of the m mobile terminals.
If the preset condition is satisfied, S103 is executed.
S103, determining that abnormal parking exists in the preset area.
Judging the collected running tracks of the plurality of mobile terminals, judging whether each running track has abnormal deviation, and if the abnormal deviation exists, judging that the vehicle deviates in a preset area, namely, abnormal parking exists in the preset area; if the obtained running tracks of the vehicles do not obviously deviate, the abnormal parking in the preset area is indicated, wherein the abnormal deviation is the running track of the vehicles in a certain distance continuously deviates.
For example, a preset area which needs to monitor whether abnormal parking exists is divided in a road, a running track of a vehicle passing through the area is obtained, the running track of the vehicle is analyzed, if the running track of the vehicle has obvious deviation, the vehicle is indicated to have abnormal deviation in the preset area, namely the vehicle is indicated to have abnormal parking in the preset area; if no obvious deviation occurs in the acquired running track of the vehicle, the abnormal parking does not exist in the preset area.
It should be noted that the deviation of the driving track may be determined according to a position deviation between coordinate points in the driving track, and the like, and if the deviation is large, it indicates that the deviation of the driving track is obvious, and may indicate that the vehicle has an obvious avoidance behavior in the process of passing through the preset area, because there may be an abnormal parking, such as an illegal lane occupation parking, and the like.
According to the abnormal parking monitoring method provided by the embodiment, the running tracks of the plurality of mobile terminals in the preset area on the road are obtained, whether the deviation of the running tracks of the mobile terminals meets the preset condition is used for judging, whether abnormal parking exists in the preset area where the vehicle carrying the mobile terminals passes is judged, and therefore the fact that whether abnormal parking exists in the preset area is determined through the deviation of the running tracks of the vehicles in the preset area is achieved, and further areas needing monitoring are determined according to the judgment result, and monitoring points can be deployed more flexibly and more accurately in a violation mode.
Optionally, fig. 4 shows a schematic flow chart of another abnormal parking monitoring method provided in the embodiment of the present application; as shown in fig. 4, the obtaining of the m mobile terminal driving tracks in the preset area on the road includes:
s201, acquiring a positioning coordinate point set of each mobile terminal in m mobile terminals on a road.
The positioning coordinate point in the application can be positioning coordinate information acquired according to the positioning function of the mobile terminal, such as a GPS point, a Beidou coordinate point and the like, and is not limited herein.
Specifically, a preset area to be monitored is selected in advance in a road, positioning coordinate points of each mobile terminal passing through the preset area are obtained within a period of time, and when m vehicles pass through the preset area within a period of time, a set of the positioning coordinate points of the m mobile terminals is obtained.
In practical application, a user drives a vehicle and simultaneously a mobile terminal on the vehicle runs taxi taking software, navigation software or other software with a positioning function, when the user drives the vehicle to pass through the preset area, the mobile terminal sends positioning coordinate points to a server, and the server receives and stores the positioning coordinate points.
S202, obtaining m mobile terminal running tracks according to the positioning coordinate point set of each mobile terminal.
And acquiring a set of positioning coordinate points of each mobile terminal passing through the preset area, wherein the set of positioning coordinate points forms a running track which can represent the running of the vehicle in the preset area, and when m vehicles pass through the preset area, acquiring the set of positioning coordinate points of the m mobile terminals, namely obtaining the running track of the m vehicles in the preset area.
It should be noted that, when a vehicle passes through the preset area, a plurality of continuous positioning coordinate points are obtained, and a track formed by the continuous positioning coordinate points is a running track of the vehicle in the preset area.
FIG. 5 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the application; as shown in fig. 5, the above determining whether the deviation of the driving track in the preset area meets the preset condition according to the driving tracks of the m mobile terminals includes:
s301, dividing the preset area into a plurality of first sub-road sections according to a first preset length, and calculating and acquiring a position average value of each first sub-road section according to the positioning coordinate point set.
In order to better obtain whether abnormal parking exists in a preset area, the preset area is divided into a plurality of sections according to a certain length to obtain a plurality of first sub-sections, then correspondingly, the track information formed by the positioning coordinate points in the preset area is also divided into a plurality of corresponding sections, and the position mean value of the positioning coordinate points forming the track information in each first sub-section is respectively calculated.
For example, a vehicle travels in a preset area to obtain a travel track on which the vehicle travels, and if the vehicle travels straight along a certain lane of a road, the offset amount of the travel track of the vehicle is 0, and if the vehicle is offset to the left with reference to the lane coordinates, the offset amount of the travel track of the vehicle is a positive number, and the offset amount is larger as the distance by which the vehicle is offset to the left is larger, and if the vehicle is offset to the right with reference to the lane coordinates, the offset amount of the travel track of the vehicle is a negative number, and the absolute value of the offset amount is larger as the distance by which the vehicle is offset to the right is larger. For example, when a vehicle travels in a predetermined area, the vehicle is offset to the left by 3 meters, the offset of the vehicle is denoted as 3, and when the vehicle is offset to the right by 4 meters, the offset of the vehicle is denoted as-4.
S302, calculating and acquiring a preset number of position peak values in a preset area according to the positioning coordinate point set.
After the driving track of the vehicle in the preset area is obtained, the deviation peak values of a preset number of vehicles can be obtained.
It should be noted that, the driving track of the vehicle is expressed by using the offset, an offset chart of the driving track in the preset area is drawn according to the offset of the driving track in the preset area, and then the peak values of the offset in the preset number are extracted according to the offset chart; the method for extracting the preset number of peaks is not particularly limited herein.
And S303, judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and a preset number of position peak values.
Optionally, after obtaining the average value of the offset of each first sub-section and the peak values of the preset number of offsets in the whole preset area, judging whether abnormal parking occurs in the preset area according to a preset algorithm, the average value of the offset of each first sub-section and the peak values of the preset number of offsets in the whole preset area.
FIG. 6 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the present application; as shown in fig. 6, an alternative determination process may include:
s401, calculating the position mean value of a preset area according to the position mean values of the plurality of first sub-road sections.
And obtaining the average value of the offset of each first sub-section in the preset area, and calculating the average value of the overall offset in the preset area according to the average value of the offset of each first sub-section.
S402, calculating the average value of the peak values of the preset number of positions.
And calculating to obtain the peak value of the offset of the whole preset area according to the obtained preset number of peak values in the preset area.
S403, judging whether the difference value between the position average value of the preset area and the average value of the preset number of position peak values is larger than a preset threshold value or not.
Correspondingly, if the preset condition is met, determining that abnormal parking exists in the preset area, including: and if the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than a preset threshold value, determining that abnormal parking exists in the preset area.
Specifically, a mean value of the overall offset in the preset area and a peak value of the overall preset area offset are obtained, a calculation result obtained by subtracting the peak value of the overall preset area offset from the mean value of the overall offset in the preset area is used for calculating an absolute value of the calculation result, the absolute value of the calculation result is used for comparing with a preset threshold, if the absolute value of the obtained calculation result is greater than the preset threshold, abnormal parking in the preset area is indicated, and if the absolute value of the obtained calculation result is not greater than the preset threshold, abnormal parking in the preset area is indicated, wherein the preset threshold can be set according to experience and actual needs of workers, and is not limited herein.
For example, when the preset area is a road section of 50 meters, the road section of 50 meters is averagely divided into a road section of 10 meters and a total of five road sections, and the average offset of the first road section is 2, the average offset of the second road section is 3, the average offset of the third road section is 8, the average offset of the fourth road section is 3, and the average offset of the fifth road section is 2, then the average offset of the preset area of 50 meters is 3.6; the 5 threshold offsets of the 50-meter preset area are respectively: 5.6, 7, 8, 9; the average peak value of the preset area of 50 meters is 7, the absolute value of the obtained calculation result is 3.4, the preset threshold value is 2, and if the absolute value of the calculation result is greater than the preset threshold value, it indicates that abnormal parking occurs in the preset area of 50 meters.
FIG. 7 is a schematic flow chart illustrating another abnormal parking monitoring method provided by the embodiment of the present application; as shown in fig. 7, the determining whether the deviation of the driving track in the preset area meets the preset condition according to the driving tracks of the m mobile terminals includes:
s501, dividing the preset area into a plurality of first sub-road sections according to a first preset length, and calculating and obtaining the position average value of each first sub-road section according to the positioning coordinate point set.
In order to better obtain whether abnormal parking exists in a preset area, the preset area is divided into a plurality of sections according to a certain length to obtain a plurality of first sub-sections, then correspondingly, the track information formed by the positioning coordinate points in the preset area is also divided into a plurality of corresponding sections, and the position mean value of the positioning coordinate points forming the track information in each first sub-section is respectively calculated.
S502, dividing the preset area into a plurality of second sub-road sections according to a second preset length, and calculating and acquiring a preset number of position peak values in each second sub-road section according to the positioning coordinate point set.
Wherein the second preset length is greater than the first preset length.
The preset area is divided into a plurality of sections according to a certain length to obtain a plurality of second sub-sections, then the track information formed by the positioning coordinate points in the preset area is correspondingly divided into a plurality of sections, and the peak values of a preset number of offsets are obtained in each second sub-section respectively.
S503, judging whether the running track deviation in the preset area meets the preset condition or not according to a preset algorithm, the position average values of the plurality of first sub-road sections and the preset number of position peak values of each second sub-road section.
And judging whether abnormal parking occurs in the preset area or not according to a preset algorithm, the position average value of the positioning coordinate points forming the track information in the plurality of obtained first sub-road sections and the peak value of the preset number of offsets obtained in each second sub-road section.
Correspondingly, if the preset condition is met, determining that abnormal parking exists in the preset area, including: and if the running track deviation in the preset area meets the preset condition, determining that abnormal parking exists in the preset area.
FIG. 8 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the present application; as shown in fig. 8, an optional judging method includes:
s601, calculating the position mean value of the preset area according to the position mean values of the plurality of first sub-road sections.
And calculating to obtain the average value of the integral offset in the preset area according to the average value of the offsets of the plurality of first sub-road sections in the preset area.
And S602, averaging the preset number of position peaks in each second sub-section.
The preset area is divided into a plurality of second sub-road sections, a preset number of peak values of each second sub-road section are obtained, and then the average value of the peak values of each second sub-road section is obtained.
S603, obtaining the position mean value of the preset area and the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values in each second sub-road section.
And calculating the difference value between the mean value of the peak value of each second sub-section and the mean value of the integral offset in the preset area according to the obtained mean value of the integral offset in the preset area and the mean value of the peak value of each second sub-section.
And S604, determining whether a second sub-road section with the difference value larger than a preset threshold exists.
And judging whether the second sub-road section in the preset area is abnormally stopped or not according to the size relation between the difference value and the preset threshold value.
Correspondingly, if the deviation of the driving track in the preset area is sufficient to the preset condition, determining that abnormal parking exists in the preset area, including: and if the second sub-road section with the difference value larger than the preset threshold value exists, determining that abnormal parking exists in the second sub-road section with the difference value larger than the preset threshold value.
Optionally, the determining process is as follows: when the difference value between the mean value of the peak value of each second sub-section and the mean value of the overall offset in the preset region is calculated, the obtained second sub-sections, in which the difference value between the mean value of the peak value of the second sub-section and the mean value of the overall offset in the preset region is greater than a preset threshold value, are marked as regions with abnormal parking, wherein the second sub-section with the largest difference value between the mean value of the peak value of the second sub-section and the mean value of the overall offset in the preset region is a region with abnormal parking, and the specific value of the preset threshold value is determined according to actual conditions and specific conditions, and is not limited herein.
For example, when the preset area is a road section of 500 meters, the road of 50 meters is averagely divided into a road section of 100 meters and a total of five road sections, so as to obtain five first sub-road sections, and the average offset of the first road section is calculated to be 2, the average offset of the second road section is calculated to be 3, the average offset of the third road section is calculated to be 8, the average offset of the fourth road section is calculated to be 3, and the average offset of the fifth road section is calculated to be 2, so that the average offset of the preset area of 50 meters is 3.6; the 500-meter preset area is divided into 50-meter sections and 10-section roads on average to obtain ten second sub-sections, a preset number of peak values are obtained in each second sub-section respectively, and then the average value of each section of peak values is calculated to obtain the following 10 peak value offset average values: 3.6, 4.6, 7.6, 5.6, 3.6, and 3.6, wherein the difference between the average of the peak offsets of the fourth second sub-segment, the fifth second sub-segment, and the sixth second sub-segment and the average offset of the preset area is: 1. and 4, 2, if the preset threshold value is 0.5, determining that abnormal parking exists in the preset area, and determining that the abnormal parking exists in a fifth second sub-road section in the preset area of 500 meters.
FIG. 9 is a schematic flow chart of another abnormal parking monitoring method provided by the embodiment of the present application; as shown in fig. 9, optionally, after determining that there is an abnormal parking in the second sub-segment where the difference is greater than the preset threshold, the method further includes:
s701, acquiring a position coordinate corresponding to the position peak value according to the position peak value in the second sub-road section with the difference value larger than the preset threshold value.
When the abnormal parking is determined to exist in one second sub-road section in the preset area, determining a position corresponding to the peak value of the track offset of the second sub-road section in which the abnormal parking exists, and determining the coordinate of the position, wherein the position of the coordinate point is the position of the abnormal parking in the preset area.
For example, if an abnormal parking exists on a road of 500 meters after the determination result is obtained, the road of 500 meters is divided into 50 areas, 5 peak values are taken for each of the 50 areas, and an area with the maximum peak value is obtained, the area is an area where the abnormal parking occurs, then the maximum peak value of the area is obtained, the position coordinate corresponding to the maximum peak value is obtained according to the maximum peak value of the area, and the position coordinate is the position where the abnormal parking occurs.
As shown in fig. 9, optionally, obtaining m mobile terminal travel tracks according to the positioning coordinate point set of each mobile terminal includes:
s801, screening the positioning coordinate points in the positioning coordinate point set of each mobile terminal according to a preset rule to obtain the screened positioning coordinate point set of each mobile terminal.
S802, obtaining m mobile terminal running tracks according to the positioning coordinate point set screened by each mobile terminal.
Optionally, the positioning coordinate points of the mobile terminal in the preset area are obtained, the obtained positioning coordinate points are screened, some discontinuous points are deleted, the remaining points are position points generated in the motion process of the mobile terminal, and the set formed by the remaining positioning coordinate points is the driving track of the vehicle in the preset area.
In the abnormal parking monitoring method provided by this embodiment, the multiple mobile terminal driving tracks in the preset area on the road are obtained, whether the mobile terminal driving tracks meet the preset conditions is used for judgment, and whether the vehicle carrying the mobile terminal generates abnormal parking in the preset area is directly judged, so that the driving tracks of the vehicle passing through the preset area only need to be judged, if the abnormal parking in the preset area is determined, the preset area can be divided into small areas, and the specific position of the abnormal parking in the preset area is determined by determining whether the abnormal parking occurs in each small area, so that the position of the abnormal parking is accurately determined.
Fig. 10 is a schematic structural diagram illustrating an abnormal parking monitoring device according to an embodiment of the present application; as shown in fig. 10, an abnormal parking monitoring apparatus provided in an embodiment of the present application includes: an acquiring module 901 and a judging module 902; an obtaining module 901, configured to obtain m mobile terminal driving tracks in a preset area on a road, where m is an integer greater than 0; a judging module 902, configured to judge whether a running track deviation in a preset area meets a preset condition according to m running tracks of the mobile terminals; and if the preset condition is met, abnormal parking exists in the preset area.
Optionally, the obtaining module 901 is specifically configured to obtain a set of location coordinate points of each of m mobile terminals on the road; and obtaining m mobile terminal driving tracks according to the positioning coordinate point set of each mobile terminal.
Optionally, the determining module 902 is specifically configured to divide the preset area into a plurality of first sub-segments according to a first preset length, and calculate and obtain a position average value of each first sub-segment according to the set of positioning coordinate points; calculating and acquiring a preset number of position peak values in a preset area according to the positioning coordinate point set; and judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and a preset number of position peak values.
Optionally, the determining module 902 is specifically configured to calculate a position average value of a preset area according to the position average values of the plurality of first sub-road segments; calculating the average value of the peak values of a preset number of positions; judging whether the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than a preset threshold value or not; and if the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than a preset threshold value, determining that abnormal parking exists in the preset area.
Optionally, the determining module 902 is further configured to divide the preset area into a plurality of first sub-segments according to a first preset length, and calculate and obtain a position average value of each first sub-segment according to the set of positioning coordinate points; dividing the preset area into a plurality of second sub-road sections according to a second preset length, and calculating and acquiring a preset number of position peak values in each second sub-road section according to the positioning coordinate point set, wherein the second preset length is greater than the first preset length; judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and the preset number of position peak values of each second sub-road section; and if the running track deviation in the preset area is sufficient to the preset condition, determining that abnormal parking exists in the preset area.
Optionally, the determining module 902 is further configured to calculate a position average value of the preset area according to the position average values of the plurality of first sub-road segments; the average value of the peak values of the preset number of positions in each second sub-section; acquiring a position average value of a preset area and a difference value between the position average value and an average value of a preset number of position peak values in each second sub-road section; determining whether a second sub-road section with the difference value larger than a preset threshold value exists; and if the second sub-road section with the difference value larger than the preset threshold value exists, determining that abnormal parking exists in the second sub-road section with the difference value larger than the preset threshold value.
Optionally, the method further includes a processing module 903, where the processing module 903 is configured to obtain a position coordinate corresponding to a position peak according to the position peak in the second sub-road section where the difference is greater than the preset threshold.
Optionally, the obtaining module 901 is specifically configured to filter, according to a preset rule, a positioning coordinate point in the positioning coordinate point set of each mobile terminal, so as to obtain a filtered positioning coordinate point set of each mobile terminal; and obtaining m mobile terminal driving tracks according to the positioning coordinate point set screened by each mobile terminal.
Fig. 11 is a schematic structural diagram of an electronic device provided in an embodiment of the present application; an embodiment of the present application further provides an electronic device, including: a processor 1001, a memory 1002, and a bus; the memory 1002 stores machine-readable instructions executable by the processor 1001, when the electronic device is operated, the processor 1001 and the memory 1002 communicate with each other through a bus, and the processor 1001 executes the machine-readable instructions to perform the steps of the abnormal parking monitoring method provided by the foregoing method embodiments.
Specifically, the machine readable instructions stored in the memory 1002 are the executing steps of the abnormal parking monitoring method according to the foregoing embodiment of the present application, and the processor 1001 can execute the abnormal parking monitoring method to process the request, so that the electronic device also has all the advantages of the foregoing method embodiment, and the description of the present application is not repeated.
It should be noted that the electronic device may be a general-purpose computer, a special-purpose computer, and other servers for processing data, and all of the three may be used to implement the abnormal parking monitoring method of the present application. Although the abnormal parking monitoring method is described only by the computer and the server, respectively, for convenience, the functions described in the present application may be implemented in a distributed manner on a plurality of similar platforms to balance the processing load.
For example, an electronic device may include one or more processors for executing program instructions, a communication bus, and different forms of storage media, such as a disk, ROM, or RAM, or any combination thereof. Illustratively, the computer platform may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The method of the present application may be implemented in accordance with these program instructions.
For ease of illustration, only one processor is depicted in the electronic device. However, it should be noted that the electronic device in the present application may also comprise a plurality of processors, and thus the steps performed by one processor described in the present application may also be performed by a plurality of processors in combination or individually.
In addition, the present application further provides a storage medium, where a computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the abnormal parking monitoring method in the foregoing method embodiments are executed.
In particular, the functions described in the foregoing embodiments of the present application, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (12)

1. An abnormal parking monitoring method, characterized in that the method comprises:
acquiring m mobile terminal driving tracks in a preset area on a road, wherein m is an integer larger than 0;
judging whether the running track deviation in the preset area meets a preset condition or not according to the m running tracks of the mobile terminal;
if the preset condition is met, determining that abnormal parking exists in the preset area;
the acquiring of the driving tracks of the m mobile terminals in the preset area on the road comprises the following steps:
acquiring a positioning coordinate point set of each mobile terminal in m mobile terminals on a road; obtaining m mobile terminal running tracks according to the positioning coordinate point set of each mobile terminal;
the judging whether the running track deviation in the preset area meets the preset condition or not according to the m running tracks of the mobile terminal comprises the following steps:
dividing the preset area into a plurality of first sub-road sections according to a first preset length, and calculating and acquiring a position mean value of each first sub-road section according to the positioning coordinate point set; calculating and acquiring a preset number of position peak values in the preset area according to the positioning coordinate point set; judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and the preset number of position peak values;
the judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and the preset number of position peak values comprises the following steps:
calculating the position mean value of the preset area according to the position mean values of the plurality of first sub-road sections; calculating the average value of the peak values of the preset number of positions; judging whether the difference value between the position average value of the preset area and the average value of the preset number of position peak values is larger than a preset threshold value or not;
correspondingly, if the preset condition is met, determining that the abnormal parking exists in the preset area, including:
and if the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than the preset threshold value, determining that abnormal parking exists in the preset area.
2. The method according to claim 1, wherein the determining whether the deviation of the driving track in the preset area meets a preset condition according to the m driving tracks of the mobile terminal comprises:
dividing the preset area into a plurality of second sub-road sections according to a second preset length, and calculating and acquiring a preset number of position peak values in each second sub-road section according to the positioning coordinate point set, wherein the second preset length is greater than the first preset length;
judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of a plurality of first sub-road sections and a preset number of position peak values of each second sub-road section;
correspondingly, if the preset condition is met, determining that the abnormal parking exists in the preset area, including:
and if the running track deviation in the preset area is sufficient to a preset condition, determining that abnormal parking exists in the preset area.
3. The method according to claim 2, wherein the determining whether the deviation of the driving track in the preset area meets a preset condition according to a preset algorithm, a position average value of a plurality of the first sub-segments and a preset number of position peak values of each of the second sub-segments comprises:
calculating the position mean value of the preset area according to the position mean values of the plurality of first sub-road sections;
the average value of the peak values of the preset number of positions in each second sub-section;
acquiring the position mean value of the preset area and the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values in each second sub-section;
determining whether a second sub-road section with the difference value larger than a preset threshold value exists;
correspondingly, if the deviation of the running track in the preset area is sufficient to the preset condition, determining that the abnormal parking exists in the preset area, including:
and if the second sub-road section with the difference value larger than the preset threshold value exists, determining that abnormal parking exists in the second sub-road section with the difference value larger than the preset threshold value.
4. The method according to claim 3, wherein after determining that there is an abnormal parking in the second sub-segment where the difference value is greater than the preset threshold, the method further comprises:
and acquiring a position coordinate corresponding to the position peak value according to the position peak value in the second sub-road section with the difference value larger than a preset threshold value.
5. The method according to claim 1, wherein the obtaining m mobile terminal driving tracks according to the set of positioning coordinate points of each mobile terminal comprises:
screening positioning coordinate points in the positioning coordinate point set of each mobile terminal according to a preset rule to obtain a screened positioning coordinate point set of each mobile terminal;
and obtaining m mobile terminal running tracks according to the positioning coordinate point set screened by each mobile terminal.
6. An abnormal parking monitoring device, characterized in that the device comprises: the device comprises an acquisition module and a judgment module;
the acquisition module is used for acquiring m mobile terminal driving tracks in a preset area on a road, wherein m is an integer larger than 0;
the judging module is used for judging whether the running track deviation in the preset area meets a preset condition or not according to m running tracks of the mobile terminal; if the preset condition is met, abnormal parking exists in the preset area;
the acquisition module is specifically configured to acquire a set of positioning coordinate points of each of m mobile terminals on a road; obtaining m mobile terminal running tracks according to the positioning coordinate point set of each mobile terminal;
the judging module is specifically configured to divide the preset area into a plurality of first sub-segments according to a first preset length, and calculate and acquire a position average value of each first sub-segment according to the set of positioning coordinate points; calculating and acquiring a preset number of position peak values in the preset area according to the positioning coordinate point set; judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of the plurality of first sub-road sections and the preset number of position peak values;
the judgment module is specifically configured to calculate a position average value of the preset area according to the position average values of the plurality of first sub-road sections; calculating the average value of the peak values of the preset number of positions; judging whether the difference value between the position average value of the preset area and the average value of the preset number of position peak values is larger than a preset threshold value or not; and if the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values is larger than the preset threshold value, determining that abnormal parking exists in the preset area.
7. The apparatus according to claim 6, wherein the determining module is specifically configured to divide the preset area into a plurality of second sub-segments according to a second preset length, and calculate and obtain a preset number of position peaks in each of the second sub-segments according to the set of positioning coordinate points, where the second preset length is greater than the first preset length; judging whether the running track deviation in the preset area meets a preset condition or not according to a preset algorithm, the position mean values of a plurality of first sub-road sections and a preset number of position peak values of each second sub-road section; and if the running track deviation in the preset area is sufficient to a preset condition, determining that abnormal parking exists in the preset area.
8. The apparatus according to claim 7, wherein the determining module is specifically configured to calculate a position mean value of the preset area according to position mean values of a plurality of the first sub-segments; the average value of the peak values of the preset number of positions in each second sub-section; acquiring the position mean value of the preset area and the difference value between the position mean value of the preset area and the mean value of the preset number of position peak values in each second sub-section; determining whether a second sub-road section with the difference value larger than a preset threshold value exists; and if the second sub-road section with the difference value larger than the preset threshold value exists, determining that abnormal parking exists in the second sub-road section with the difference value larger than the preset threshold value.
9. The apparatus according to claim 8, further comprising a processing module, configured to obtain a position coordinate corresponding to the position peak according to the position peak in the second sub-segment where the difference is greater than a preset threshold.
10. The apparatus according to claim 6, wherein the obtaining module is specifically configured to filter, according to a preset rule, the positioning coordinate points in the positioning coordinate point set of each mobile terminal, so as to obtain a filtered positioning coordinate point set of each mobile terminal; and obtaining m mobile terminal running tracks according to the positioning coordinate point set screened by each mobile terminal.
11. 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 running, the processor executing the machine-readable instructions to perform the steps of the abnormal parking monitoring method according to any one of claims 1 to 5.
12. A storage medium having stored thereon a computer program for performing the steps of the abnormal parking monitoring method according to any one of claims 1 to 5 when executed by a processor.
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