CN112950932A

CN112950932A - Method and device for merging area units and electronic equipment

Info

Publication number: CN112950932A
Application number: CN202110104532.XA
Authority: CN
Inventors: 曾彬炜; 郑重
Original assignee: Alibaba Group Holding Ltd
Current assignee: Alibaba Group Holding Ltd
Priority date: 2021-01-26
Filing date: 2021-01-26
Publication date: 2021-06-11
Anticipated expiration: 2041-01-26
Also published as: CN112950932B

Abstract

The disclosure provides a merging method and a merging device of area units and electronic equipment, wherein the method comprises the following steps: acquiring position information of a plurality of original area units; the original area units are areas obtained by splitting a preset area according to road network data; acquiring traffic data of a target vehicle, which is acquired by road monitoring equipment in the preset area within a historical statistical time period, and a traffic track generated by the preset area within the historical statistical time period; and combining the plurality of original area units in the historical statistical time period according to the position information, the traffic data and the traffic track of the plurality of original area units to obtain at least one traffic cell corresponding to the historical statistical time period.

Description

Method and device for merging area units and electronic equipment

Technical Field

The present disclosure relates to the field of travel technologies, and in particular, to a method and an apparatus for merging area units, an electronic device, and a computer-readable storage medium.

Background

The road network data includes information on road sections and intersections. In the prior art, the vehicle traveling situation can be researched through road network partitions. Specifically, a plurality of directed edges may be generated by using road network data in a preset area; forming a polygon with a plurality of directed edges; and forming a plurality of original area units by using the polygons to realize the partition of the preset area.

However, due to the existing partitioning method, the road monitoring equipment in the preset area is too sparse, so that the vehicle flow rule in the original area unit cannot be restored.

Therefore, in order to more accurately determine the area where the vehicle enters when the vehicle disappears in the bayonet monitoring range of the preset area after passing through the road monitoring equipment, a technical scheme of combining area units is provided.

Disclosure of Invention

An object of the embodiments of the present disclosure is to provide a new technical solution for merging area units.

According to a first aspect of the present disclosure, there is provided a merging method of region units, including:

acquiring position information of a plurality of original area units; the original area units are areas obtained by splitting a preset area according to road network data;

acquiring traffic data of a target vehicle, which is acquired by road monitoring equipment in the preset area within a historical statistical time period, and a traffic track generated by the preset area within the historical statistical time period;

and combining the plurality of original area units in the historical statistical time period according to the position information, the traffic data and the traffic track of the plurality of original area units to obtain at least one traffic cell corresponding to the historical statistical time period.

Optionally, the merging the multiple original area units within the historical statistics time period according to the location information, the traffic data, and the traffic trajectory of the multiple original area units to obtain at least one traffic cell corresponding to the historical statistics time period includes:

determining a first probability that each target vehicle enters each original area unit within the historical statistical time period according to the traffic data and the traffic track;

and combining the plurality of original area units in the historical statistical time period according to the position information of the plurality of original area units and the first probability that each target vehicle enters each original area unit in the historical statistical time period to obtain at least one traffic cell corresponding to the historical statistical time period.

Optionally, the determining, according to the traffic data and the traffic trajectory, a first probability that each of the target vehicles enters each of the origin regional units within the historical statistical time period includes:

determining a second probability that each target vehicle disappears in a bayonet monitoring range of the preset area after passing through each road monitoring device according to the traffic data;

determining a third probability that a vehicle disappears in a bayonet monitoring range of the preset area and enters each original area unit after passing through each road monitoring device according to the traffic track;

and determining a first probability that each target vehicle enters each original region unit within the historical statistical time period according to the second probability and the third probability.

Optionally, the determining, according to the traffic data, a second probability that each target vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device includes:

determining a first number of times that each target vehicle is monitored by each road monitoring device according to the traffic data;

and determining a second probability that each target vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device according to the first number of times that each target vehicle is monitored by each road monitoring device.

Optionally, the determining, according to the first number of times that each target vehicle is monitored by each road monitoring device, a second probability that each target vehicle disappears in a checkpoint monitoring range of the preset area after passing through each road monitoring device includes:

acquiring a first number of the road monitoring devices in the preset area;

traversing the target vehicle;

determining the sum of the first times monitored by each road monitoring device of the currently traversed target vehicle as a second time corresponding to the currently traversed target vehicle;

and for each road monitoring device, obtaining a second probability that the currently traversed target vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device according to the second times corresponding to the currently traversed target vehicle, the first number of the road monitoring devices and the first times monitored by the corresponding road monitoring device.

Optionally, the determining, according to the traffic track, a third probability that a vehicle disappears in a checkpoint monitoring range of the preset area and enters each original area unit after passing through each road monitoring device includes:

determining a second number of traffic tracks which disappear from the checkpoint monitoring range of the preset area after passing through each road monitoring device and enter each original area unit;

and determining a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area and enters each original area unit after passing through each road monitoring device according to the second number of the traffic tracks which disappear in the checkpoint monitoring range of the preset area and enter each original area unit after passing through each road monitoring device.

Optionally, the determining, according to the second number of the traffic tracks which disappear in the checkpoint monitoring range of the preset area and enter each original area unit after passing through each road monitoring device, a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area and enters each original area unit after passing through each road monitoring device includes:

determining the sum of a second quantity of the traffic tracks which disappear from the corresponding road monitoring equipment in the bayonet monitoring range of the preset area and enter all the original area units as a corresponding third quantity for each road monitoring equipment;

and for each road monitoring device, obtaining a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enters each original area unit according to the corresponding third number and the second number of the traffic tracks which disappear in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enter each original area unit.

Optionally, the determining, according to the second probability and the third probability, a first probability that each of the target vehicles enters each of the original area units within the historical statistical period includes:

traversing the target vehicle;

traversing the original area unit;

for each road monitoring device, obtaining a fourth probability corresponding to the road monitoring device according to a second probability that a target vehicle traversed at present disappears in a checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device, and a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enters a current traversed original area unit;

and summing the fourth probabilities of all the road monitoring devices to obtain a first probability that the currently traversed target vehicle enters the currently traversed original region unit within the historical statistical time period.

Optionally, the merging, within the historical statistics time period, the multiple original region units according to the position information of the multiple original region units and the first probability that each target vehicle enters each original region unit within the historical statistics time period to obtain at least one traffic cell corresponding to the historical statistics time period includes:

selecting a first original area unit and a second original area unit from the original area units;

determining a logical distance between the first original area unit and the second original area unit according to a first probability that each target vehicle enters the first original area unit within the historical statistical time period and a first probability that each target vehicle enters the second original area unit within the historical statistical time period; wherein the logical distance reflects a similarity of entering a target vehicle between the first raw area cell and the second raw area cell;

determining a geographical distance between the first original area unit and the second original area unit according to the position information of the first original area unit and the position information of the second original area unit;

and under the condition that the logical distance is greater than or equal to a first preset distance and the geographic distance is less than or equal to a second preset distance, combining the first original area unit and the second original area unit within the historical statistical time period to obtain a corresponding traffic cell.

Optionally, the method further includes:

acquiring a preset attenuation factor;

according to the first probability that each target vehicle enters each original region unit in the historical statistical time period, obtaining the first probability that each target vehicle enters each original region unit in the target statistical time period;

and combining the plurality of original area units in the target statistical time period according to the first probability that each target vehicle enters each original area unit in the target statistical time period to obtain at least one traffic cell corresponding to the target statistical time period.

Optionally, the method further includes:

and determining the traffic cell which the target vehicle enters in the historical statistical time period according to the traffic data.

According to a second aspect of the present disclosure, there is provided a merging apparatus of a zone unit, including:

the position information acquisition module is used for acquiring the position information of a plurality of original area units; the original area units are areas obtained by splitting a preset area according to road network data;

the data track acquisition module is used for acquiring traffic data of a target vehicle acquired by road monitoring equipment in the preset area in a historical statistical time period and a traffic track generated by the preset area in the historical statistical time period;

and the area unit merging module is used for merging the plurality of original area units in the historical statistical time period according to the position information, the traffic data and the traffic track of the plurality of original area units to obtain at least one traffic cell corresponding to the historical statistical time period.

According to a third aspect of the present disclosure, there is provided an electronic device comprising:

the apparatus according to the second aspect of the present disclosure; alternatively, the first and second electrodes may be,

a processor and a memory for storing an executable computer program for controlling the processor to perform the method according to the first aspect of the present disclosure.

According to a fourth aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method according to the first aspect of the present disclosure.

According to the embodiment of the disclosure, the multiple original area units are combined in the historical statistical time period according to the position information, the traffic data and the traffic tracks of the multiple original area units, so that the traffic cell, into which the target vehicle enters in the historical statistical time period, can be accurately determined according to the traffic data of the target vehicle, the target vehicle can be conveniently subjected to migration analysis, the migration rule of the target vehicle is obtained, and then traffic control is performed according to the migration rule of the target vehicle, so that traffic jam is relieved.

Other features of the present disclosure and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.

Fig. 1 is a schematic diagram of an application scenario of a merging method of a region unit according to an embodiment of the present disclosure.

Fig. 2a is a schematic configuration diagram of an example of an electronic device according to an embodiment of the present disclosure.

Fig. 2b is a schematic configuration diagram of another example of an electronic device according to an embodiment of the present disclosure.

Fig. 3 shows a flowchart of a merging method of a zone unit of an embodiment of the present disclosure.

Fig. 4 shows a flowchart of the steps of determining the second probability in an embodiment of the present disclosure.

FIG. 5 shows a flowchart of the steps of determining a first probability according to an embodiment of the present disclosure.

Fig. 6 shows a flowchart of one example of a merging method of a zone unit of the embodiment of the present disclosure.

Fig. 7 shows a block diagram of a merging device of a zone unit of an embodiment of the present disclosure.

Fig. 8 shows a block diagram of an electronic device of an embodiment of the disclosure.

Detailed Description

Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.

Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

Road monitoring equipment can be arranged on roads or at junctions in the preset area. The road monitoring equipment adopts advanced photoelectric technology, image processing technology and pattern recognition technology to take images of each passing automobile, automatically recognizes license plates of the automobiles in the images, and acquired information data of the automobiles can be stored in a server database. The traffic data of the target vehicle collected by the road monitoring device may be a captured image of the vehicle, or license plates of all vehicles passing through the corresponding road monitoring device obtained according to the image of the vehicle, and the number of times that the vehicle of each license plate is captured.

A driver of a vehicle traveling in a preset area may navigate through a map application, and thus, a traffic track generated in the preset area may be obtained through a server of the map application. The map application may be installed on the target vehicle or on a terminal device carried by the driver.

The target vehicle may be provided with a positioning device, and the positioning device may report the position of the target vehicle to a server of the map application according to a set frequency and store the position of the target vehicle in the server of the map application, so that the server of the map application may generate a traffic track of the target vehicle.

Fig. 1 is a schematic diagram of an application scenario of a merging method of area units according to an embodiment of the present disclosure.

As shown in fig. 1, the electronic device 1000 executing the method of the present embodiment may acquire traffic data of a target vehicle collected during a historical statistical period from the road monitoring device 2000 set in a preset area. The electronic device 1000 may also acquire a traffic track generated in a historical statistical period in a preset area from the server 3000 of the map application.

The electronic device 1000 may further acquire position information of an original area unit from another electronic device 4000, where the original area unit is an area obtained by splitting a preset area by the other electronic device 4000 according to road network data. In one example, the raw area unit may be a minimum granularity area bounded by roads. For example, there may be regions corresponding to each of the smallest polygons as in fig. 1.

The location information of the raw area unit may be location information indicating a boundary of the corresponding raw area unit, and may include, for example, a geographical location of a plurality of boundary points of the corresponding raw area unit.

In this embodiment, the electronic device 1000 and the other electronic devices 4000 may be provided by the same computer or different computers.

The electronic device 1000 may perform merging processing on the original area units within a historical statistical period according to the position information, traffic data, and traffic tracks of the original area units.

< hardware configuration >

Fig. 2a and 2b are block diagrams of a hardware configuration of an electronic device 1000 that can be used to implement the merging method of the zone unit of any embodiment of the present disclosure.

In one embodiment, as shown in FIG. 2a, the electronic device 1000 may be a server 1100.

The server 1100 provides a process, database, computer or cluster of computers for communication facilities. The server 1100 can be a unitary server or a distributed server across multiple computers or computer data centers. The server may be of various types, such as, but not limited to, a web server, a news server, a mail server, a message server, an advertisement server, a file server, an application server, an interaction server, a database server, or a proxy server. In some embodiments, each server may include hardware, software, or embedded logic components or a combination of two or more such components for performing the appropriate functions supported or implemented by the server. For example, a server, such as a blade server, a cloud server, etc., or may be a server group consisting of a plurality of servers, which may include one or more of the above types of servers, etc.

In this embodiment, the server 1100 may include a processor 1110, a memory 1120, an interface device 1130, a communication device 1140, a display device 1150, and an input device 1160, as shown in fig. 2 a.

In this embodiment, the server 1100 may also include a speaker, a microphone, and the like, which are not limited herein.

The processor 1110 may be a dedicated server processor, or may be a desktop processor, a mobile version processor, or the like that meets performance requirements, and is not limited herein. The memory 1120 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 1130 includes various bus interfaces such as a serial bus interface (including a USB interface), a parallel bus interface, and the like. The communication device 1140 is capable of wired or wireless communication, for example. The display device 1150 is, for example, a liquid crystal display panel, an LED display panel touch display panel, or the like. Input devices 1160 may include, for example, a touch screen, a keyboard, and the like.

In this embodiment, the memory 1120 of the server 1100 is configured to store instructions for controlling the processor 1110 to operate at least to perform the merging method of the zone units according to any embodiment of the present disclosure. The skilled person can design the instructions according to the disclosed solution of the present disclosure. How the instructions control the operation of the processor is well known in the art and will not be described in detail herein.

Although a number of devices of server 1100 are shown in fig. 2a, the present disclosure may refer to only some of the devices, e.g., server 1100 refers to only memory 1120 and processor 1110.

In one embodiment, the electronic device 1000 may be a terminal device 1200 such as a PC, a notebook computer, or the like used by an operator, which is not limited herein.

In this embodiment, referring to fig. 2b, the terminal device 1200 may include a processor 1210, a memory 1220, an interface 1230, a communication device 1240, a display device 1250, an input device 1260, a speaker 1270, a microphone 1280, and the like.

The processor 1210 may be a mobile version processor. The memory 1220 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 1230 includes, for example, a USB interface, a headphone interface, and the like. The communication device 1240 may be capable of wired or wireless communication, for example, the communication device 1240 may include a short-range communication device, such as any device that performs short-range wireless communication based on short-range wireless communication protocols, such as the Hilink protocol, WiFi (IEEE 802.11 protocol), Mesh, bluetooth, ZigBee, Thread, Z-Wave, NFC, UWB, LiFi, and the like, and the communication device 1240 may also include a long-range communication device, such as any device that performs WLAN, GPRS, 2G/3G/4G/5G long-range communication. The display device 1250 is, for example, a liquid crystal display, a touch display, or the like. The input device 1260 may include, for example, a touch screen, a keyboard, and the like. A user can input/output voice information through the speaker 1270 and the microphone 1280.

In this embodiment, the memory 1220 of the terminal device 1200 is configured to store instructions for controlling the processor 1210 to operate at least to perform a method of merging zone units according to any of the embodiments of the present disclosure. The skilled person can design the instructions according to the disclosed solution of the present disclosure. How the instructions control the operation of the processor is well known in the art and will not be described in detail herein.

Although a plurality of means of the terminal device 1200 are shown in fig. 2b, the disclosure may only relate to a part of the means therein, e.g. the terminal device 1200 only relates to the memory 1220 and the processor 1210 and the display device 1250.

< method examples >

Fig. 3 is a schematic flow chart of a merging method of zone units according to an embodiment of the present disclosure.

In one example, the merging method of the area units shown in fig. 3 may be implemented by only the server or the terminal device, or may be implemented by both the server and the terminal device. In one embodiment, the terminal device may be the terminal device 1200 as shown in fig. 2b and the server may be the server 1100 as shown in fig. 2 a.

As shown in fig. 3, the merging method of the area units of the present embodiment includes the following steps S1000 to S3000:

step S1000, obtaining position information of a plurality of original area units, where the plurality of original area units are areas obtained by splitting a preset area according to road network data.

In one example, the raw area unit may be a minimum granularity area bounded by roads.

The preset area in this embodiment may be an area that is selected by a user in advance according to an application scenario or a specific requirement. For example, the preset area may be a city, an administrative area, etc.

The step of splitting the preset area according to the road network data to obtain a plurality of original area units may be performed by the electronic device of this embodiment, or may be performed by another electronic device.

The location information of the primitive region unit may be pre-stored in the electronic device 1000; the information may also be stored in other electronic devices, for example, may be stored in a map server and obtained by the electronic device 1000 from other electronic devices.

Step S2000, acquiring traffic data of the target vehicle collected by the road monitoring equipment in the preset area in the historical statistical time period, and acquiring traffic tracks generated by the preset area in the historical statistical time period.

The historical statistic time period in this embodiment may be set in advance according to an application scenario or a specific requirement, for example, the historical statistic time period may be one week in the past.

Road monitoring equipment can be arranged on roads or at junctions in the preset area. The road monitoring equipment adopts advanced photoelectric technology, image processing technology and pattern recognition technology to take images of each passing automobile, automatically recognizes license plates of the automobiles in the images, and acquired information data of the automobiles can be stored in a server database. The traffic data of the target vehicle collected by the road monitoring equipment can be the shot vehicle image, and the license plate numbers of all vehicles passing through the corresponding road monitoring equipment and the shooting times of the vehicles of each license plate number can be obtained according to the vehicle image.

A driver of a vehicle traveling in a preset area may navigate through a map application, and thus, a traffic track generated in the preset area may be obtained through a server of the map application. The target vehicle may be provided with a positioning device, and the positioning device may report the position of the target vehicle to a server of the map application according to a set frequency and store the position of the target vehicle in the server of the map application, so that the server of the map application may generate a traffic track of the target vehicle.

Each traffic track in this embodiment may be a spatial position sequence for recording a trip process of a corresponding vehicle. The spatial position sequence comprises a plurality of points, and each point can comprise longitude and latitude position information. Therefore, according to the longitude and latitude information contained in each point in the spatial position sequence of the sampling track, each traffic track can be matched to a specific road according to the sequence of the traffic track in the spatial position sequence.

The electronic device 1000 executing the method of the present embodiment may acquire traffic data of the target vehicle collected during the historical statistical period from the road monitoring device set in the preset area. The electronic device 1000 may further obtain a traffic track generated in a historical statistical time period in a preset area from a server of the map application.

In one example, the traffic track generated in the preset area may be a traffic track whose end point is located in the preset area. Then, the traffic track generated in the historical statistical time period in the preset area may be the traffic track with the parking time in the historical statistical time period and the end point located in the preset area.

Step S3000, combining the multiple original area units in the historical statistical time period according to the position information, the traffic data and the traffic tracks of the multiple original area units to obtain at least one traffic cell corresponding to the historical statistical time period.

Each traffic cell may include at least one raw area cell.

In the embodiment, the multiple original area units are combined in the historical statistical time period according to the position information, the traffic data and the traffic tracks of the multiple original area units, so that the traffic cells, into which the target vehicles enter in the historical statistical time period, can be accurately determined according to the traffic data of the target vehicles, the target vehicles can be conveniently migrated and analyzed, the migration rules of the target vehicles are obtained, and then traffic control is performed according to the migration rules of the target vehicles, so that traffic congestion is relieved.

In an embodiment of the present disclosure, merging the multiple primitive area units within the historical statistics time period according to the location information, the traffic data, and the traffic trajectory of the multiple primitive area units, and obtaining at least one traffic cell corresponding to the historical statistics time period may include steps S3100 to S3200 as follows:

step S3100, determining a first probability that each target vehicle enters each original area unit within a historical statistical time period according to the traffic data and the traffic track.

The target vehicle in this embodiment may be a plurality of vehicles captured by road monitoring equipment provided in a preset area.

In one embodiment of the present disclosure, determining a first probability of each target vehicle entering each raw zone cell within the historical statistical period based on the traffic data and the traffic trajectory may include steps S3110-S3130 as shown below:

and S3110, determining a second probability that each target vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device according to the traffic data.

In any embodiment of the present disclosure, after the target vehicle passes through the target road monitoring device, the target vehicle disappears within the checkpoint monitoring range of the preset area, that is, it indicates that any road monitoring device in the preset area does not capture the target vehicle again within the preset time after the target vehicle is captured by the target road monitoring device. The preset time may be preset according to an application scenario or a specific requirement, for example, two hours. The target road monitoring device may be any road monitoring device disposed in a preset area and providing the collected traffic data of the target vehicle to the electronic device 1000.

In one embodiment of the present disclosure, determining, according to the traffic data, a second probability that each target vehicle disappears within the checkpoint monitoring range of the preset area after passing through each road monitoring device includes steps S3111 to S3112 as follows:

step S3111, determining a first number of times that each target vehicle is monitored by each road monitoring device according to the traffic data.

In the case that the traffic data is an image acquired by the road monitoring device, the license plate of the target vehicle in the image acquired by each road monitoring device may be identified, and for the vth target vehicle and the kth road monitoring device, the number of images acquired by the kth road monitoring device in the image identifying the license plate of the vth target vehicle may be determined as the first number of times that the vth target vehicle is monitored by the kth road monitoring device.

In the case that the traffic data includes the license plates of all vehicles passing through the corresponding road monitoring device and the number of times that the vehicle of each license plate is photographed, the vehicle corresponding to the license plate included in the traffic data may be used as the target vehicle, and the first number of times that each target vehicle is monitored by each road monitoring device may be determined through the traffic data.

Step S3112, determining a second probability that each target vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device according to the first number of times that each target vehicle is monitored by each road monitoring device.

In an embodiment of the present disclosure, determining the second probability that each target vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device according to the first number of times that each target vehicle is monitored by each road monitoring device may include steps S3112-1 to S3112-5 as shown in fig. 4:

step S3112-1, a first number of road monitoring devices in a preset area is obtained.

Specifically, the first number may be the number of road monitoring devices that acquired the traffic data in step S2000.

The first number K may be set in advance according to an actual scene, or may be obtained by counting the number of the road monitoring devices that acquire the traffic data in step S2000 by the electronic device 1000 that executes the embodiment of the present disclosure.

Step S3112-2, traverse the target vehicle.

And S3112-3, determining the sum of the first times monitored by each road monitoring device of the currently traversed target vehicle as a second time corresponding to the currently traversed target vehicle.

When the currently traversed target vehicle is the vth target vehicle, the first time number of the vth target vehicle monitored by the kth road monitoring device may be represented as n_v,kThen, the second number corresponding to the currently traversed target vehicle may be represented as

And S3112-4, for each road monitoring device, obtaining, according to the second number of times corresponding to the currently traversed target vehicle, the first number of road monitoring devices, and the first number of times that the currently traversed target vehicle is monitored by the corresponding road monitoring device, a second probability that the currently traversed target vehicle disappears in a checkpoint monitoring range of a preset area after passing through the corresponding road monitoring device.

In one embodiment, for the vth target vehicle and the kth road monitoring device, the second probability p that the vth target vehicle disappears in the checkpoint monitoring range of the preset area after passing through the kth road monitoring device can be determined by the following formula (one)_v,k：

In another embodiment of the present disclosure, determining, according to the first number of times that each target vehicle is monitored by each road monitoring device, a second probability that each target vehicle disappears within the checkpoint monitoring range of the preset area after passing through each road monitoring device may further include:

traversing the target vehicle; determining the sum of the first times monitored by each road monitoring device of the currently traversed target vehicle as a second time corresponding to the currently traversed target vehicle; and for each road monitoring device, determining the ratio of the second time corresponding to the currently traversed target vehicle to the first time monitored by the corresponding road monitoring device of the currently traversed target vehicle, and obtaining a second probability that the currently traversed target vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device.

Step S3112-5, determining whether the target vehicle is traversed and ended, if so, ending the process; if not, the process continues to step S3112-2.

And S3120, determining a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area and enters each original area unit after passing through each road monitoring device according to the traffic track.

In this embodiment, when the vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device, the vehicle may enter one of the original area units. The traffic track can record the complete track of the vehicle in the driving process, so that the third probability that the vehicle disappears in the checkpoint monitoring range of the preset area and enters each original area unit after passing through each road monitoring device can be obtained by analyzing the traffic track.

The vehicle in step S3120 generally refers to any vehicle that can travel in the target area, and does not have directivity.

In an embodiment of the present disclosure, determining, according to the traffic trajectory, that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device and enters each original area unit may include steps S3121 to S3122 as follows:

and S3121, determining a second number of traffic tracks which disappear from the checkpoint monitoring range of the preset area after passing through each road monitoring device and enter each original area unit.

The traffic track may reflect a moving route of the vehicle. According to the geographical position of each road monitoring device, a second number of traffic tracks which disappear into the intersection monitoring range of the preset area after passing through each road monitoring device and enter each original area unit can be determined.

And S3122, determining a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area and enters each original area unit after passing through each road monitoring device according to the second number of tracks which disappear in the checkpoint monitoring range of the preset area and enter each original area unit after passing through each road monitoring device.

In an embodiment of the present disclosure, determining that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device and enters each original area unit according to the second number of traffic tracks of each original area unit and disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device may include steps S3122-1 to S3122-2 as follows:

and S3122-1, determining, for each road monitoring device, a sum of a second number of traffic tracks which disappear within the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enter all the original area units, as a corresponding third number.

For example, for the k-th road monitoring device, the second number of traffic tracks which disappear in the checkpoint monitoring range of the preset area after passing through the k-th road monitoring device and enter the q-th original area unit can be represented as n_k,q. Correspondingly, the sum of the second number of the traffic tracks which disappear in the checkpoint monitoring range of the preset area after passing through the kth road monitoring device and enter all the original area units, that is, the third number corresponding to the kth road monitoring device can be expressed as

Wherein Q is the total number of original area units for which the position information is acquired in step S1000.

And S3122-2, for each road monitoring device, obtaining a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enters each original area unit according to the corresponding third number and the second number of the traffic tracks which disappear in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enter each original area unit.

Specifically, for the k-th road monitoring device, the third probability p that the vehicle disappears in the checkpoint monitoring range of the preset area and enters the q-th original area unit after passing through the k-th road monitoring device may be determined by the following formula (two)_k,q：

Step S3130, determining a first probability that each target vehicle enters each raw zone unit within the historical statistical period, according to the second probability and the third probability.

In one embodiment of the present disclosure, determining the first probability that each target vehicle enters each raw zone unit within the historical statistical period according to the second probability and the third probability may include steps S3131 to S3136 as shown in fig. 5:

step S3131, traverse the target vehicle.

Step S3132, traverse the primitive region unit.

Step S3133, for each road monitoring device, obtaining a fourth probability of the corresponding road monitoring device according to a second probability that the currently traversed target vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device, and a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enters the currently traversed original area unit.

Under the condition that the currently traversed target vehicle is the v-th target vehicle and the currently traversed original region unit is the q-th original region unit, the fourth probability p corresponding to the k-th road monitoring device_v,q,kCan be determined by the following formula (three):

p_v,q,k＝p_v,k*p_k,qformula (III)

Wherein p is_v,kThe situation that the v-th target vehicle disappears in the checkpoint monitoring range of the preset area after passing through the k-th road monitoring equipment is shownSecond probability of p_k,qAnd the third probability that the vehicle disappears in the bayonet monitoring range of the preset area and enters the q-th original area unit after passing through the k-th road monitoring device is represented.

Step S3134, summing the fourth probabilities of each road monitoring device, to obtain a first probability that the currently traversed target vehicle enters the currently traversed original area unit within the historical statistical time period.

Under the condition that the currently traversed target vehicle is the nth target vehicle and the currently traversed original region unit is the qth original region unit, the first probability p that the vth target vehicle enters the qth original region unit in the historical statistical time period_v,qCan be determined by the following equation (four):

step S3135, determining whether the original area unit is finished traversing, if so, performing step S3136; if not, the step S3132 is continued.

Step S3136, determining whether the target vehicle is traversed and ended, if so, ending the process; if not, the step S3131 is continued.

Step S3200, according to the position information of the plurality of original area units and the first probability that each target vehicle enters each original area unit within the historical statistical time period, merge the plurality of original area units within the historical statistical time period to obtain at least one traffic cell corresponding to the historical statistical time period.

In an embodiment of the present disclosure, merging the multiple original area units within the historical statistics time period according to the location information of the multiple original area units and the first probability that each target vehicle enters each original area unit within the historical statistics time period to obtain at least one traffic cell corresponding to the historical statistics time period may include steps S3210 to S3240 as follows:

in step S3210, a first original area unit and a second original area unit are selected from the original area units.

In the embodiment of the present disclosure, all the original area units may be combined two by two to obtain a plurality of area unit combinations. Traversing the area unit combination, respectively taking the original area units in the currently traversed area unit combination as the first original area unit and the second original area unit, and executing the subsequent steps S3220-S3240.

Step S3220 determines a logical distance between the first original region unit and the second original region unit according to a first probability that each target vehicle enters the first original region unit within the historical statistical period and a first probability that each target vehicle enters the second original region unit within the historical statistical period.

Wherein the logical distance may reflect a similarity of the target vehicle entering between the first raw area cell and the second raw area cell.

The larger the logical distance is, the higher the similarity of the target vehicle entering between the first and second origin region units is represented; the smaller the logical distance, the lower the similarity of the target vehicle entering between the first and second primitive region units.

The first probability of the i-th target vehicle entering the first original area unit p1 within the historical statistical period is p_p1, _vi, the first probability that the ith target vehicle enters the second original area unit p2 within the historical statistical period is p_p2,vin the case of i, the logical distance d between the first original region unit p1 and the second original region unit p2 may be determined by the following formula (five)_p1,p2：

Where n represents the number of all target vehicles. In this embodiment, the target vehicle may be distinguished by a license plate of the target vehicle. In the case where the ith target vehicle does not enter the first original area unit p1 within the history statistical period, it may beTo estimate the first probability p_p1,viLabeled 0, the first probability p may be assigned in the event that i target vehicles do not enter the second original area cell p2 within the historical statistical period_p2,viThe flag is 0.

In an embodiment of the present disclosure, since the number of target vehicles is large, in order to save calculation time and reduce the memory occupied by executing the method of the present embodiment, for each original area unit, the target vehicles may be sorted in a descending order according to the first probability, and the sorting value of each target vehicle is recorded; and selecting a first probability corresponding to the target vehicle with the ranking value within a set range to calculate the logical distance between the original area unit and other original area units. The setting range may be set in advance according to an application scenario or a specific requirement, and for example, the setting range may be [1,1000 ].

Step S3230, determining a geographical distance between the first primitive region unit and the second primitive region unit according to the location information of the first primitive region unit and the location information of the second primitive region unit.

In this embodiment, the geographic distance between the first original area unit and the second original area unit may be a distance between a first boundary point in the first original area unit closest to the second original area unit and a second boundary point in the second original area unit closest to the first original area unit, that is, a shortest distance between the first original area unit and the second original area unit.

Step S3240, under the condition that the logical distance is greater than or equal to the first preset distance and the geographic distance is less than or equal to the second preset distance, combining the first original area unit and the second original area unit within the historical statistical time period to obtain the corresponding traffic cell.

The first preset distance and the second preset distance may be set according to an application scenario or a specific requirement, respectively. For example, the first preset distance may be 0.5 and the second preset distance may be 10 m.

In this embodiment, when the logical distance is greater than or equal to the first preset distance and the geographic distance is less than or equal to the second preset distance, the first original area unit and the second original area unit are merged in the historical statistical time period, and the first original area unit and the second original area unit are divided into the same traffic cell in the historical statistical time period.

And under the condition that the logical distance is smaller than the first preset distance or the geographic distance is larger than the second preset distance, the first original area unit and the second original area unit are not merged in the historical statistical time period, namely the first original area unit and the second original area unit are not divided into the same traffic cell in the historical statistical time period.

In this embodiment, according to the combination result in all the area unit combinations, at least one traffic cell in the historical statistical period may be obtained, each traffic cell may include at least one original area unit, and the number of the finally obtained traffic cells is less than or equal to the number of the original area units.

In one embodiment of the present disclosure, after performing step S3000, the method may further include:

and determining the traffic cell which the target vehicle enters within the historical statistical time period according to the traffic data.

By the method, the original area units are combined in the historical statistical time period to obtain the traffic cells corresponding to the historical statistical time period, and then the traffic cells where the target vehicles enter in the historical statistical time period are determined according to the traffic data, so that the certainty of the areas where the target vehicles enter can be improved.

On the basis of the embodiment, under the condition that the traffic cell into which the target vehicle enters within the historical statistical time period is obtained, the target vehicle can be subjected to migration analysis to obtain the migration rule of the target vehicle, and then traffic control is performed according to the migration rule of the target vehicle to relieve traffic jam.

In one embodiment of the present disclosure, after step S3000 is performed, the method may further include steps S4100 to S4300 as shown below:

in step S4100, a preset attenuation factor is obtained.

In an embodiment of the present disclosure, the attenuation factor may be set in advance according to an application scenario or a specific requirement, may be set according to experimental data or experience of an engineer, and may be predicted according to a machine learning model trained in advance. For example, the attenuation factor may be 0.8.

Step S4200, obtaining a first probability that each target vehicle enters each original region unit within the target statistical time period according to the first probability that each target vehicle enters each original region unit within the historical statistical time period.

The target statistical period in this embodiment may be a statistical period after the time of the historical statistical period, and the target statistical period and the historical statistical period may have the same duration.

In the case where the target statistical period is the t-th statistical period after the history statistical period, a first probability that the v-th target vehicle enters the q-th original area unit within the history statistical period may be represented as p_v,qThen, the v-th target vehicle enters the first probability of the q-th original zone unit within the target statistical period

Can be determined by the following equation (six):

in the formula (six), α is an attenuation factor.

Step S4300, according to the first probability that each target vehicle enters each original area unit in the target counting time period, combining the plurality of original area units in the target counting time period to obtain at least one traffic cell corresponding to the target counting time period.

In step S4300, according to the first probability that each target vehicle enters each original area unit within the target statistics time period, combining the plurality of original area units within the target statistics time period to obtain a specific manner of obtaining at least one traffic cell corresponding to the target statistics time period, refer to step S3000 described above, which is not described herein again.

In the present embodiment, by determining the first probability that each target vehicle enters each original area unit within the target statistical period by iterating the first probability that each target vehicle enters each original area unit within the historical statistical period, it is possible to quickly perform the merging process on a plurality of original area units within the target statistical period, and also to reduce the data processing amount.

< example >

Fig. 6 is a schematic diagram of an example of a merging method of a region unit according to an embodiment of the present disclosure.

As shown in fig. 6, the method includes steps S6001 to S6023:

step S6001, obtaining location information of a plurality of original region units, where the plurality of original region units are regions obtained by splitting a preset region according to road network data.

Step S6002, acquiring traffic data of the target vehicle collected by the road monitoring device in the preset area in the historical statistical time period, and a traffic track generated by the preset area in the historical statistical time period.

Step S6003, determining a first number of times that each target vehicle is monitored by each road monitoring device according to the traffic data.

Step S6004, a first number of road monitoring devices in a preset area is obtained.

Step S6005, the target vehicle is traversed.

Step S6006, determining a sum of the first times monitored by each road monitoring device of the currently traversed target vehicle, as a second time corresponding to the currently traversed target vehicle.

Step S6007, for each road monitoring device, obtaining, according to the second number of times corresponding to the currently traversed target vehicle, the first number of road monitoring devices, and the first number of times monitored by the corresponding road monitoring device of the currently traversed target vehicle, a second probability that the currently traversed target vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device.

Step 6008, determining whether the target vehicle is traversed and ended, if so, executing step 6012; if not, the process continues to step S6005.

Step S6009, determining a second number of traffic tracks that disappear into the bayonet monitoring range of the preset area after passing through each road monitoring device and enter each original area unit.

Step S6010, for each road monitoring device, determining a sum of a second number of traffic tracks that disappear within the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enter all the original area units, as a corresponding third number.

Step S6011, for each road monitoring device, according to the corresponding third number, and the second number of traffic tracks that disappear within the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enter each original area unit, obtaining a third probability that the vehicle disappears within the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enters each original area unit.

Step S6012, the target vehicle is traversed.

Step S6013, the original area unit is traversed.

Step S6014, for each road monitoring device, a fourth probability corresponding to the road monitoring device is obtained according to a second probability that a currently traversed target vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device, and a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enters the currently traversed original area unit.

Step S6015, the fourth probabilities of each road monitoring device are summed to obtain a first probability that the currently traversed target vehicle enters the currently traversed original area unit within the historical statistical period.

Step S6016, determining whether the original area unit is traversed, if so, executing step S6013; if not, the step S6017 is continued.

Step S6017, determining whether the target vehicle is traversed and ended, if so, executing step S6018; if not, the step S6012 is continued.

Step S6018, combine every two of all the original area units to obtain a plurality of area unit combinations.

Step S6019, traverse the area unit combinations, and take the original area units in the currently traversed area unit combinations as the first original area unit and the second original area unit, respectively.

Step S6020 determines a logical distance between the first original zone unit and the second original zone unit according to a first probability that each target vehicle enters the first original zone unit within the historical statistical period and a first probability that each target vehicle enters the second original zone unit within the historical statistical period.

Step S6021, determining a geographical distance between the first original area unit and the second original area unit according to the position information of the first original area unit and the position information of the second original area unit.

Step S6022, under the condition that the logic distance is greater than or equal to the first preset distance and the geographic distance is less than or equal to the second preset distance, the first original area unit and the second original area unit are merged in the historical statistic time period to obtain the corresponding traffic cell.

Step S6023, determining whether the area unit combination is traversed and ended, if yes, executing step S6024; if not, the step S6019 is continued.

And step S6024, obtaining at least one traffic cell corresponding to the historical statistical time interval.

< apparatus >

In the present embodiment, a merging device 7000 of the area units is provided. As shown in fig. 7, the processing apparatus 7000 may include a location information acquiring module 7100, a data track acquiring module 7200, and an area unit merging module 7300.

The position information acquiring module 7100 is configured to acquire position information of a plurality of original area units; the original area units are areas obtained by splitting a preset area according to road network data.

The data track acquiring module 7200 is configured to acquire traffic data of a target vehicle acquired by a road monitoring device in a preset area in a historical statistics period and a traffic track generated by the preset area in the historical statistics period.

The area unit merging module 7300 is configured to merge the multiple original area units within the historical statistics time period according to the location information, the traffic data, and the traffic track of the multiple original area units, so as to obtain at least one traffic cell corresponding to the historical statistics time period.

In one embodiment of the present disclosure, the region unit merging module 7300 may be further configured to:

determining a first probability of each target vehicle entering each original area unit within a historical statistical time period according to the traffic data and the traffic track;

In one embodiment of the present disclosure, determining a first probability of each target vehicle entering each raw area cell within the historical statistical period based on the traffic data and the traffic trajectory comprises:

determining a second probability that each target vehicle disappears in a checkpoint monitoring range of a preset area after passing through each road monitoring device according to the traffic data;

determining a third probability that the vehicle disappears in a bayonet monitoring range of a preset area and enters each original area unit after passing through each road monitoring device according to the traffic track;

In one embodiment of the disclosure, determining, according to the traffic data, a second probability that each target vehicle disappears within the checkpoint monitoring range of the preset area after passing through each road monitoring device includes:

and determining a second probability that each target vehicle disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device according to the first times that each target vehicle is monitored by each road monitoring device.

In an embodiment of the disclosure, determining, according to the first number of times that each target vehicle is monitored by each road monitoring device, a second probability that each target vehicle disappears in a checkpoint monitoring range of a preset area after passing through each road monitoring device includes:

acquiring a first number of road monitoring devices in a preset area;

traversing the target vehicle;

In one embodiment of the disclosure, determining, according to the traffic trajectory, a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area and enters each original area unit after passing through each road monitoring device includes:

In an embodiment of the disclosure, determining that the vehicle passes through each road monitoring device and disappears in the checkpoint monitoring range of the preset area and enters each original area unit according to the second number of the traffic tracks of each original area unit and disappears in the checkpoint monitoring range of the preset area after passing through each road monitoring device comprises:

determining the sum of the second quantity of the traffic tracks which disappear in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring equipment and enter all the original area units as a corresponding third quantity for each road monitoring equipment;

In one embodiment of the present disclosure, determining a first probability that each target vehicle enters each raw zone unit within the historical statistical period based on the second probability and the third probability comprises:

traversing the target vehicle;

traversing the original area unit;

for each road monitoring device, obtaining a fourth probability corresponding to the road monitoring device according to a second probability that a target vehicle traversed at present disappears in a checkpoint monitoring range of a preset area after passing through the corresponding road monitoring device, and a third probability that the vehicle disappears in the checkpoint monitoring range of the preset area after passing through the corresponding road monitoring device and enters a currently traversed original area unit;

In one embodiment of the present disclosure, the merging the multiple original area units in the historical statistical time period according to the position information of the multiple original area units and the first probability that each target vehicle enters each original area unit in the historical statistical time period to obtain at least one traffic cell corresponding to the historical statistical time period includes:

determining a logical distance between the first original region unit and the second original region unit according to a first probability that each target vehicle enters the first original region unit within a historical statistical time period and a first probability that each target vehicle enters the second original region unit within the historical statistical time period; wherein the logical distance reflects a similarity of the target vehicle entering between the first origin region unit and the second origin region unit;

determining the geographical distance between the first original area unit and the second original area unit according to the position information of the first original area unit and the position information of the second original area unit;

and under the condition that the logical distance is greater than or equal to a first preset distance and the geographic distance is less than or equal to a second preset distance, combining the first original area unit and the second original area unit within a historical statistical time period to obtain the corresponding traffic cell.

In an embodiment of the present disclosure, the merging device 7000 of the area unit may further include:

a module for obtaining a preset attenuation factor;

a module for obtaining a first probability that each target vehicle enters each original region unit within a target statistical time period according to the first probability that each target vehicle enters each original region unit within a historical statistical time period;

and the module is used for merging the plurality of original area units in the target statistical time period according to the first probability that each target vehicle enters each original area unit in the target statistical time period to obtain at least one traffic cell corresponding to the target statistical time period.

means for determining a traffic cell into which the target vehicle entered within the historical statistical time period based on the traffic data.

It will be appreciated by those skilled in the art that the merging means 7000 of the area units can be implemented in various ways. The merging means 7000 of the area units can be implemented, for example, by an instruction configuration processor. For example, the combining means 7000 of the area unit may be implemented by storing instructions in a ROM and reading the instructions from the ROM into a programmable device when starting up the apparatus. For example, the area unit consolidation apparatus 7000 may be cured into a dedicated device (e.g., ASIC). The combining means 7000 of the area units may be divided into units independent of each other, or they may be combined together. The merging means 7000 of the area units may be implemented by one of the various implementations described above, or may be implemented by a combination of two or more of the various implementations described above.

In this embodiment, the merging device 7000 of the area unit may have various implementation forms, for example, the merging device 7000 of the area unit may be any functional module running in a software product or an application providing the function of merging the area units, or a peripheral insert, a plug-in, a patch, etc. of the software product or the application, and may also be the software product or the application itself.

< electronic apparatus >

In this embodiment, an electronic device 8000 is also provided. The electronic device 8000 may include the server 1100 shown in FIG. 2a and the terminal device 1200 shown in FIG. 2 b. The electronic device 8000 may also be the server 1100 as shown in fig. 2a, or the terminal device 1200 as shown in fig. 2 b.

In one aspect, the electronic device 8000 may include the aforementioned merging apparatus 7000 for the area unit, so as to implement the merging method of the area unit according to any embodiment of the present disclosure.

In another aspect, as shown in FIG. 8, the electronic device 8000 may also include a processor 8100 and a memory 8200, the memory 8200 for storing executable instructions; the processor 8100 is configured to operate the electronic device 8000 to perform a merging method of a zone unit according to any of the embodiments of the present disclosure according to a control of an instruction.

< computer-readable storage Medium >

In this embodiment, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the merging method of the zone units as in any of the embodiments of the present disclosure.

The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including 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 using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).

Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, by software, and by a combination of software and hardware are equivalent.

Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present disclosure is defined by the appended claims.

Claims

1. A merging method of region units, comprising:

2. The method of claim 1, wherein the merging the plurality of original area units within the historical statistical time period according to the location information, the traffic data, and the traffic trajectory of the plurality of original area units to obtain at least one traffic cell corresponding to the historical statistical time period comprises:

3. The method of claim 2, said determining, from the traffic data and the traffic trajectory, a first probability that each of the target vehicles enters each of the origin regional units within the historical statistical time period comprising:

4. The method of claim 3, wherein the determining, according to the traffic data, a second probability that each of the target vehicles disappears within a checkpoint monitoring range of the preset area after passing each of the road monitoring devices comprises:

5. The method of claim 4, wherein the determining a second probability that each target vehicle disappears within a checkpoint monitoring range of the preset area after passing each road monitoring device according to a first number of times that each target vehicle is monitored by each road monitoring device comprises:

acquiring a first number of the road monitoring devices in the preset area;

traversing the target vehicle;

6. The method of claim 3, wherein determining a third probability that a vehicle disappears within a checkpoint monitoring range of the preset area and enters each raw area unit after passing each road monitoring device according to the traffic track comprises:

7. The method of claim 6, wherein determining a third probability that a vehicle will disappear into the checkpoint monitoring area of the predetermined area and into each raw area unit after passing each road monitoring device according to the second number of traffic tracks that disappear into the checkpoint monitoring area of the predetermined area and into each raw area unit after passing each road monitoring device comprises:

8. The method of claim 3, the determining, according to the second and third probabilities, a first probability that each of the target vehicles entered each of the raw zone units within the historical statistical period comprising:

traversing the target vehicle;

traversing the original area unit;

9. The method of claim 2, wherein the merging the plurality of original area units within the historical statistical time period according to the location information of the plurality of original area units and the first probability of each target vehicle entering each original area unit within the historical statistical time period to obtain at least one traffic cell corresponding to the historical statistical time period comprises:

10. The method of claim 2, further comprising:

acquiring a preset attenuation factor;

11. The method of claim 1, further comprising:

12. A merging device of a zone unit, comprising:

13. An electronic device, comprising:

the apparatus of claim 12; alternatively, the first and second electrodes may be,

a processor and a memory for storing an executable computer program for controlling the processor to perform the method of any one of claims 1 to 11.

14. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 11.