Vehicle on-route quantity determination method, device, equipment and storage medium

Abstract

The application relates to a vehicle in-transit quantity determination method, device, equipment and storage medium, and relates to the technical field of intelligent transportation. The method comprises the following steps: dividing roads included in a target region into urban expressways and urban ordinary roads, and acquiring road condition data of the urban expressways and monitoring data of the urban ordinary roads; determining a first in-transit quantity of the urban ordinary roads based on the monitoring data of the urban ordinary roads; determining a second in-transit quantity of the urban expressways based on the road condition data of the urban expressways; and determining a target in-transit quantity of the target region based on the first in-transit quantity of the urban ordinary roads and the second in-transit quantity of the urban expressways. The application is used for accurately determining the in-transit quantity of vehicles.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent transportation, and particularly relates to a vehicle in-transit quantity determination method and device, equipment and a storage medium. BACKGROUND

[0002] In order to measure the degree of urban traffic load, determining the vehicle in-transit quantity in a city area is a common method. The vehicle in-transit quantity is used to indicate the number of vehicles driving on the road. Specifically, the vehicle in-transit quantity of the area can be determined by the congestion density, free-flow speed, average speed of vehicles, road length and number of lanes of each road in the area.

[0003] However, the number of intersections and traffic lights in different roads in the city area is different, and the accuracy of determining the vehicle in-transit quantity by using the above method is poor. Therefore, how to accurately determine the vehicle in-transit quantity is a technical problem to be solved. SUMMARY

[0004] The present application provides a vehicle in-transit quantity determination method, device, equipment and storage medium to accurately determine the vehicle in-transit quantity. The technical solution of the present application is as follows:

[0005] In a first aspect, a vehicle in-transit quantity determination method is provided, which comprises: dividing roads included in a target area into urban expressways and urban ordinary roads, and acquiring road condition data of the urban expressways and monitoring data of the urban ordinary roads, the monitoring data being vehicle passing data collected by a monitoring device, the monitoring device comprising any one of the following: a geomagnetic device and a turret device; determining a first in-transit quantity of the urban ordinary roads based on the monitoring data of the urban ordinary roads, the in-transit quantity being used to indicate the number of vehicles driving on the road; determining a second in-transit quantity of the urban expressways based on the road condition data of the urban expressways; and determining a target in-transit quantity of the target area based on the first in-transit quantity of the urban ordinary roads and the second in-transit quantity of the urban expressways.

[0006] In a possible implementation, the first in-transit quantity of the urban common road is determined based on monitoring data of the urban common road, including: determining a first urban common road and a second urban common road from the urban common road, and determining an effective device set corresponding to the first urban common road from the monitoring devices, the monitoring devices included in the first urban common road having a distribution density greater than a preset density value, the monitoring devices included in the first urban common road having a device operation quality satisfying a preset quality, the monitoring devices included in the second urban common road having a distribution density less than or equal to the preset density value, the monitoring devices included in the second urban common road having a device operation quality not satisfying the preset quality, and the effective device set including a plurality of normally operating monitoring devices; determining a third in-transit quantity of the first urban common road based on monitoring data collected by the effective device set corresponding to the first urban common road; determining a fourth in-transit quantity of the second urban common road based on a predetermined in-transit quantity threshold range, a traffic index range, and a correction coefficient, the correction coefficient being a coefficient determined based on a weather condition; and determining the first in-transit quantity of the urban common road as a sum of the third in-transit quantity of the first urban common road and the fourth in-transit quantity of the second urban common road.

[0007] In a possible implementation, the monitoring devices are a plurality of geomagnetic devices; the third in-transit quantity of the first urban common road is determined based on monitoring data collected by the effective device set corresponding to the first urban common road, including: dividing the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban common road into a plurality of categories of geomagnetic devices based on a distribution density of the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban common road; determining, for each category of geomagnetic devices in the plurality of categories of geomagnetic devices, a vehicle average travel duration corresponding to each category of geomagnetic devices in the plurality of categories of geomagnetic devices based on distances between the geomagnetic devices and an average speed of a vehicle; and determining the third in-transit quantity of the first urban common road based on a number of first vehicles passing through each category of geomagnetic devices in the plurality of categories of geomagnetic devices within a vehicle average travel duration of each category of geomagnetic devices before a current time.

[0008] In a possible implementation, the monitoring device is a plurality of kiosk devices, and the monitoring data includes historical monitoring data and real-time monitoring data; the third in-transit quantity of the first urban ordinary road is determined based on the monitoring data collected by the effective device set corresponding to the first urban ordinary road, including: determining, based on the historical monitoring data of the first urban ordinary road, a vehicle in-transit probability in each unit time period included in a target time period, the vehicle in-transit probability being used to indicate a probability that a vehicle passes through other kiosk devices again within the target time period after passing through any kiosk device of the plurality of kiosk devices, the other kiosk devices being the kiosk devices other than the any kiosk device; determining a second vehicle number passing through the plurality of kiosk devices in the target time period before the current time, and determining a third vehicle number passing through each kiosk device of the plurality of kiosk devices in each unit time period included in the target time period; and determining the third in-transit quantity of the first urban ordinary road based on the third vehicle number passing through each kiosk device of the plurality of kiosk devices and the vehicle in-transit probability.

[0009] In a possible implementation, the first urban ordinary road and the second urban ordinary road are determined from the urban ordinary roads, including: obtaining device distribution information of the monitoring devices in the urban ordinary roads, the device distribution information including at least one of the following: device position information, device quantity information, and device running quality, the device running quality including at least one of the following: data transmission quality, data accuracy, and device running stability; and dividing the urban ordinary roads into the first urban ordinary road and the second urban ordinary road based on the device distribution information in the urban ordinary roads.

[0010] In a possible implementation, the effective device set corresponding to the first urban ordinary road is determined from the monitoring devices, including: constructing a vehicle flow variation law graph corresponding to the first urban ordinary road based on historical monitoring data of the first urban ordinary road, the vehicle flow variation law graph being used to indicate a variation of vehicle flow in the first urban ordinary road in a historical time period, one monitoring device corresponding to one vehicle flow variation law graph; and determining the effective device set corresponding to the first urban ordinary road from the monitoring devices based on real-time monitoring data of the first urban ordinary road and the vehicle flow variation law graph.

[0011] In a possible implementation, the road condition data includes at least one of the following: road length, lane quantity, average speed of a vehicle, and vehicle flow; and the second in-transit quantity of the urban expressway is determined based on the road condition data of the urban expressway, including: determining a traffic flow density corresponding to the urban expressway based on the average speed of the vehicle and the vehicle flow corresponding to the urban expressway; and determining the second in-transit quantity of the urban expressway based on the traffic flow density corresponding to the urban expressway, the road length, and the lane quantity.

[0012] In a possible implementation, the method further includes: determining, based on at least one of the second in-traffic quantity of the urban expressway and the third in-traffic quantity of the first urban ordinary road, a range of the in-traffic quantity threshold value corresponding to the second urban ordinary road and a range of the traffic index corresponding to the second urban ordinary road, the range of the in-traffic quantity threshold value including a lower in-traffic quantity and an upper in-traffic quantity, and the range of the traffic index including a lower traffic index and an upper traffic index; and determining the traffic index of the second urban ordinary road based on the free-flow speed corresponding to the second urban ordinary road and the average speed of the vehicle corresponding to the second urban ordinary road.

[0013] In a second aspect, a vehicle in-traffic quantity determination apparatus is provided, which includes a processing unit and a determination unit. The processing unit is configured to divide roads included in a target region into urban expressways and urban ordinary roads, and to obtain road condition data of the urban expressways and monitoring data of the urban ordinary roads. The average speed of a vehicle traveling in the urban expressways is greater than a preset speed, and the average speed of a vehicle traveling in the urban ordinary roads is less than or equal to the preset speed. The monitoring data is vehicle passing data collected by a monitoring device, and the monitoring device includes any one of a geomagnetic device and a loop device. The determination unit is configured to determine a first in-traffic quantity of the urban ordinary roads based on the monitoring data of the urban ordinary roads, the in-traffic quantity being used to indicate the number of vehicles traveling in the roads. The determination unit is further configured to determine a second in-traffic quantity of the urban expressways based on the road condition data of the urban expressways. The determination unit is further configured to determine a target in-traffic quantity of the target region based on the first in-traffic quantity of the urban ordinary roads and the second in-traffic quantity of the urban expressways.

[0014] In a possible implementation, the determination unit is specifically configured to: determine a first urban ordinary road and a second urban ordinary road from the urban ordinary roads, and determine an effective device set corresponding to the first urban ordinary road from the monitoring devices. The distribution density of the monitoring devices included in the first urban ordinary road is greater than a preset density value, and the device operation quality of the monitoring devices included in the first urban ordinary road meets a preset quality. The distribution density of the monitoring devices included in the second urban ordinary road is less than or equal to the preset density value, and the device operation quality of the monitoring devices included in the second urban ordinary road does not meet the preset quality. The effective device set includes a plurality of normally-operating monitoring devices. The determination unit is further configured to determine a third in-traffic quantity of the first urban ordinary road based on the monitoring data collected by the effective device set corresponding to the first urban ordinary road. The determination unit is further configured to determine a fourth in-traffic quantity of the second urban ordinary road based on a range of the in-traffic quantity threshold value, a range of the traffic index, and a correction coefficient, the correction coefficient being a coefficient determined based on a weather condition. The determination unit is further configured to determine the first in-traffic quantity of the urban ordinary roads by summing the third in-traffic quantity of the first urban ordinary road and the fourth in-traffic quantity of the second urban ordinary road.

[0015] In a possible implementation, the monitoring devices are a plurality of geomagnetic devices; the determination unit is specifically configured to: divide the plurality of normally-operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road into a plurality of categories of geomagnetic devices based on the distribution density of the plurality of normally-operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road; for each category of geomagnetic devices in the plurality of categories of geomagnetic devices, determine the average vehicle travel duration corresponding to each category of geomagnetic devices in the plurality of categories of geomagnetic devices based on the distance between the geomagnetic devices and the average speed of the vehicle; and determine the third quantity of vehicles in transit of the first urban ordinary road based on the number of first vehicles passing through each category of geomagnetic devices in the plurality of categories of geomagnetic devices within the average vehicle travel duration of each category of geomagnetic devices in the plurality of categories of geomagnetic devices before the current time.

[0016] In a possible implementation, the monitoring devices are a plurality of tollgate devices, and the monitoring data includes historical monitoring data and real-time monitoring data; and the determination unit is specifically configured to: determine the probability of a vehicle in transit on the first urban ordinary road in each unit time period included in a target time period based on the historical monitoring data of the first urban ordinary road, the probability of a vehicle in transit being used to indicate the probability of the vehicle passing through other tollgate devices again within the target time period after passing through any tollgate device in the plurality of tollgate devices, the other tollgate devices being the tollgate devices other than the any tollgate device in the plurality of tollgate devices; determine the number of second vehicles passing through the plurality of tollgate devices within the target time period before the current time, and determine the number of third vehicles passing through each tollgate device in the plurality of tollgate devices in each unit time period included in the target time period; and determine the third quantity of vehicles in transit of the first urban ordinary road based on the number of third vehicles passing through each tollgate device in the plurality of tollgate devices and the probability of a vehicle in transit.

[0017] In a possible implementation, the determination unit is specifically configured to: obtain device distribution information of the monitoring devices in the urban ordinary road, the device distribution information including at least one of the following: device location information, device quantity information, and device operation quality, the device operation quality including at least one of the following: data transmission quality, data accuracy, and device operation stability; and divide the urban ordinary road into the first urban ordinary road and the second urban ordinary road based on the device distribution information in the urban ordinary road.

[0018] In a possible implementation, the determination unit is specifically configured to: construct a vehicle flow variation pattern diagram corresponding to the first urban ordinary road based on the historical monitoring data of the first urban ordinary road, the vehicle flow variation pattern diagram being used to indicate the variation of the vehicle flow in the first urban ordinary road in a historical time period, one monitoring device corresponding to one vehicle flow variation pattern diagram; and determine the effective device set corresponding to the first urban ordinary road from the monitoring devices based on the real-time monitoring data of the first urban ordinary road and the vehicle flow variation pattern diagram.

[0019] In a possible implementation, the road condition data comprises at least one of the following: road length, number of lanes, average speed of vehicles, vehicle flow; and the determining unit is specifically configured to: determine the traffic flow density corresponding to the urban expressway based on the average speed of vehicles and the vehicle flow corresponding to the urban expressway; and determine the second in-transit quantity of the urban expressway based on the traffic flow density corresponding to the urban expressway, the road length, and the number of lanes.

[0020] In a possible implementation, the determining unit is further configured to: determine the in-transit quantity threshold range corresponding to the second urban ordinary road and the traffic index range corresponding to the second urban ordinary road based on at least one of the following: the second in-transit quantity of the urban expressway and the third in-transit quantity of the first urban ordinary road, wherein the in-transit quantity threshold range comprises a lower in-transit quantity and an upper in-transit quantity, and the traffic index range comprises a lower traffic index and an upper traffic index; and determine the traffic index of the second urban ordinary road based on the free-flow speed corresponding to the second urban ordinary road and the average speed of vehicles corresponding to the second urban ordinary road.

[0021] In a third aspect, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method of the first aspect and any possible implementation thereof.

[0022] In a fourth aspect, a computer-readable storage medium / computer program product is provided, when computer-executable instructions stored in the computer-readable storage medium / computer program product are executed by a processor of an electronic device, the electronic device is enabled to perform the method of the first aspect and any possible implementation thereof.

[0023] The embodiments of the present application provide the technical solutions of the first aspect, which bring at least the following beneficial effects: in the prior art, the vehicle in-transit quantity of a region is usually determined according to the congestion density of each road in the region, the free flow speed, the average speed of vehicles, the road length and the number of lanes, but due to different numbers of intersections and signal lights in different roads, the vehicle in-transit quantity cannot be accurately determined by using the method. In the present application, the roads included in the target region are divided into urban expressways and urban ordinary roads, and based on the monitoring data of the urban ordinary roads, the first in-transit quantity of the urban ordinary roads is determined. Based on the road condition data of the urban expressways, the second in-transit quantity of the urban expressways is determined. Further, based on the first in-transit quantity of the urban ordinary roads and the second in-transit quantity of the urban expressways, the target in-transit quantity of the target region is determined. The present application takes into account the different average speeds of vehicles caused by different numbers of intersections and signal lights in different roads, divides the roads included in the target region into urban expressways and urban ordinary roads, respectively determines the first in-transit quantity of the urban ordinary roads and the second in-transit quantity of the urban expressways, and thus the vehicle in-transit quantity of the target region can be accurately determined.

[0024] It should be noted that the technical effects brought by any one of the implementation manners of the second aspect to the fourth aspect can refer to the technical effects brought by the corresponding implementation manners in the first aspect, which will not be repeated here.

[0025] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0026] The accompanying drawings, which are incorporated into and form part of the specification, illustrate an embodiment consistent with the present application and, together with the specification, serve to explain the principles of the present application, and do not constitute an undue limitation on the present application.

[0027] Figure 1 is a structural schematic diagram of a vehicle in-transit quantity determination system according to an exemplary embodiment;

[0028] Figure 2 is a flowchart of a vehicle in-transit quantity determination method according to an exemplary embodiment;

[0029] Figure 3 is a flowchart of another vehicle in-transit quantity determination method according to an exemplary embodiment;

[0030] Figure 4 is a flowchart of another vehicle in-transit quantity determination method according to an exemplary embodiment;

[0031] Figure 5 is a flowchart of another vehicle in-transit quantity determination method according to an exemplary embodiment;

[0032] Figure 6 is a flow chart of still another vehicle in-transit quantity determination method according to an example embodiment;

[0033] Figure 7 is a flow chart of still another vehicle in-transit quantity determination method according to an example embodiment;

[0034] Figure 8 is a flow chart of still another vehicle in-transit quantity determination method according to an example embodiment;

[0035] Figure 9 is a block diagram of a vehicle in-transit quantity determination apparatus according to an example embodiment;

[0036] Figure 10 is a block diagram of an electronic device according to an example embodiment. DETAILED DESCRIPTION

[0037] In order to make the ordinary person skilled in the art better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings.

[0038] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0039] Before the vehicle in-transit quantity determination method provided by the present application is described in detail, the implementation environment (implementation architecture) involved in the present application will be briefly introduced.

[0040] The vehicle in-transit quantity determination method provided by the embodiments of the present application can be applied to a vehicle in-transit quantity determination system. Figure 1 A structural schematic diagram of the vehicle in-transit quantity determination system is shown. As shown in Figure 1 The vehicle in-transit quantity determination system 10 includes a vehicle in-transit quantity determination apparatus 11 and an electronic device 12. The vehicle in-transit quantity determination apparatus 11 is connected with the electronic device 12. The connection between the vehicle in-transit quantity determination apparatus 11 and the electronic device 12 can be wired or wireless, which is not limited by the embodiments of the present application.

[0041] The vehicle in-traffic quantity determining apparatus 11 can be configured to acquire the road condition data of the urban expressway and the monitoring data of the urban ordinary road from the electronic device 12.

[0042] The vehicle in-traffic quantity determining apparatus 11 can be further configured to process the acquired road condition data of the urban expressway and the monitoring data of the urban ordinary road, for example, determine a first in-traffic quantity of the urban ordinary road based on the monitoring data of the urban ordinary road; determine a second in-traffic quantity of the urban expressway based on the road condition data of the urban expressway; and determine a target in-traffic quantity of a target region based on the first in-traffic quantity of the urban ordinary road and the second in-traffic quantity of the urban expressway.

[0043] The vehicle in-traffic quantity determining apparatus 11 can be further configured to send the determined target in-traffic quantity of the target region to the electronic device 12.

[0044] Optionally, the electronic device can be a physical machine, for example, a desktop computer, a mobile phone, a tablet computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), or the like, and the electronic device can also be a server or a server group composed of multiple servers.

[0045] Optionally, the vehicle in-traffic quantity determining apparatus 11 can also be implemented by a virtual machine (VM) deployed on a physical machine to realize the functions of the vehicle in-traffic quantity determining apparatus 11.

[0046] It should be noted that the vehicle in-traffic quantity determining apparatus 11 and the electronic device 12 can be independent devices or integrated into the same device, and the present disclosure does not make a specific limitation thereon.

[0047] When the vehicle in-traffic quantity determining apparatus 11 and the electronic device 12 are integrated into the same device, the communication mode between the vehicle in-traffic quantity determining apparatus 11 and the electronic device 12 is the communication between the internal modules of the device. In this case, the communication process between the two is the same as the communication process between the vehicle in-traffic quantity determining apparatus 11 and the electronic device 12 when they are independent of each other.

[0048] In the following embodiments provided by the present disclosure, the vehicle in-traffic quantity determining apparatus 11 and the electronic device 12 are taken as examples for illustration.

[0049] For ease of understanding, the vehicle in-traffic quantity determining method provided by the present disclosure is specifically introduced below with reference to the accompanying drawings.

[0050] Figure 2 is a flow chart of a vehicle in-traffic quantity determination method according to an exemplary embodiment. The method can be applied to an electronic device, and can also be applied to a vehicle in-traffic quantity determination apparatus connected with the electronic device. Meanwhile, the method can also be applied to devices similar to the electronic device or the vehicle in-traffic quantity determination apparatus. Hereinafter, the method is described by taking the method applied to the electronic device as an example. As shown in Figure 2 the vehicle in-traffic quantity determination method includes the following steps:

[0051] S201, the electronic device divides roads included in a target region into urban expressways and urban ordinary roads.

[0052] As a possible implementation manner, the electronic device divides the roads included in the target region into the urban expressways and the urban ordinary roads according to speed limits of the roads included in the target region and the number of intersections.

[0053] S202, the electronic device acquires road condition data of the urban expressways and monitoring data of the urban ordinary roads.

[0054] The monitoring data is vehicle passing data collected by a monitoring device, and the monitoring device includes any one of the following: a geomagnetic device, a loop device.

[0055] As a possible implementation manner, the electronic device acquires the road condition data of the urban expressways, and the road condition data of the urban expressways includes: road length, number of lanes, average speed of vehicles, and vehicle flow. The electronic device acquires vehicle passing data collected by the geomagnetic device and the loop device in the urban ordinary roads.

[0056] S203, the electronic device determines a first in-traffic quantity of the urban ordinary roads based on the monitoring data of the urban ordinary roads.

[0057] The in-traffic quantity is used to indicate the number of vehicles driving on the road.

[0058] As a possible implementation manner, the electronic device determines a first urban ordinary road and a second urban ordinary road from the urban ordinary roads, determines a third in-traffic quantity of the first urban ordinary road based on monitoring data corresponding to the first urban ordinary road. The electronic device determines a fourth in-traffic quantity of the second urban ordinary road based on a pre-determined in-traffic quantity threshold range, a traffic index range, and a correction coefficient.

[0059] Further, the electronic device determines a sum of the third in-traffic quantity of the first urban ordinary road and the fourth in-traffic quantity of the second urban ordinary road as the first in-traffic quantity of the urban ordinary roads.

[0060] The specific implementation of this step can refer to the subsequent description of the embodiments of the present application, which will not be repeated here.

[0061] In S204, the electronic device determines a second quantity of vehicles on the urban expressway based on the road condition data of the urban expressway.

[0062] In some embodiments, the road condition data comprises at least one of the following: road length, number of lanes, average speed of vehicles, vehicle flow, and in order to determine the second quantity of vehicles on the urban expressway, the above S204 can be implemented in the following manner:

[0063] In S2041, the electronic device determines a traffic flow density corresponding to the urban expressway based on the average speed of vehicles and the vehicle flow corresponding to the urban expressway.

[0064] As a possible implementation manner, the electronic device inputs the average speed of vehicles and the vehicle flow of the urban expressway into a preset formula one based on the obtained road condition data of the urban expressway, to obtain the traffic flow density corresponding to the urban expressway. The formula one can be as follows:

[0065] k i =q i / v i Formula one

[0066] wherein i is the i-th urban expressway, k i is the traffic flow density of the i-th urban expressway, q i is the vehicle flow of the i-th urban expressway, and v i is the average speed of vehicles of the i-th urban expressway.

[0067] In S2042, the electronic device determines the second quantity of vehicles on the urban expressway based on the traffic flow density corresponding to the urban expressway, the road length, and the number of lanes.

[0068] As a possible implementation manner, the electronic device inputs the traffic flow density corresponding to the urban expressway, the road length, and the number of lanes into a preset formula two, to obtain the second quantity of vehicles on the urban expressway. The formula two can be expressed as follows:

[0069]

[0070] wherein CarNum1 is the second quantity of vehicles on the urban expressway, n is the total number of urban expressways, i is the i-th urban expressway, k i is the traffic flow density of the i-th urban expressway, L i is the road length of the i-th urban expressway, and LaneNum i is the number of lanes of the i-th urban expressway.

[0071] S205, the electronic device determines the target in-traffic quantity of the target region based on the first in-traffic quantity of the urban ordinary road and the second in-traffic quantity of the urban expressway.

[0072] As a possible implementation manner, the electronic device determines the target in-traffic quantity of the target region as a sum of the first in-traffic quantity of the urban ordinary road and the second in-traffic quantity of the urban expressway.

[0073] It can be understood that in the prior art, the in-traffic quantity of a region is generally determined according to the congestion density, free-flow speed, average speed of vehicles, road length and number of lanes of each road in the region, but due to different numbers of intersections and signal lights in different roads, the in-traffic quantity of vehicles cannot be accurately determined by using this method. In the present application, the roads included in the target region are divided into urban expressways and urban ordinary roads, the first in-traffic quantity of the urban ordinary road is determined based on the monitoring data of the urban ordinary road, the second in-traffic quantity of the urban expressway is determined based on the road condition data of the urban expressway, and further, the target in-traffic quantity of the target region is determined based on the first in-traffic quantity of the urban ordinary road and the second in-traffic quantity of the urban expressway. The present application takes into account the different average speeds of vehicles caused by different numbers of intersections and signal lights in different roads, divides the roads included in the target region into urban expressways and urban ordinary roads, respectively determines the first in-traffic quantity of the urban ordinary road and the second in-traffic quantity of the urban expressway, and thus can accurately determine the in-traffic quantity of vehicles in the target region.

[0074] In some embodiments, in order to determine the first in-traffic quantity of the urban ordinary road, as shown in Figure 3 S203 can be implemented in the following manner:

[0075] S2031, the electronic device determines a first urban ordinary road and a second urban ordinary road from the urban ordinary road.

[0076] Among them, the distribution density of the monitoring device included in the first urban ordinary road is greater than a preset density value, and the device running quality of the monitoring device included in the first urban ordinary road meets a preset quality, the distribution density of the monitoring device included in the second urban ordinary road is less than or equal to the preset density value, and the device running quality of the monitoring device included in the second urban ordinary road does not meet the preset quality.

[0077] As a possible implementation manner, the electronic device obtains the distribution density of the monitoring device of the urban ordinary road and the device running quality of the monitoring device, and determines the urban ordinary road with the distribution density of the monitoring device greater than the preset density value and the device running quality of the monitoring device meeting the preset quality as the first urban ordinary road, and determines the urban ordinary road with the distribution density of the monitoring device less than or equal to the preset density value or the device running quality of the monitoring device not meeting the preset quality as the second urban ordinary road.

[0078] The specific implementation of this step can refer to the subsequent description of the embodiments of the present application, and will not be described here.

[0079] S2032, the electronic device determines the effective device set corresponding to the first urban ordinary road from the monitoring device.

[0080] Among the effective device set, a plurality of normally operating monitoring devices are included.

[0081] As a possible implementation manner, the electronic device obtains historical monitoring data and real-time monitoring data corresponding to the first urban ordinary road based on the determined first urban ordinary road. The electronic device constructs a vehicle flow change rule graph based on the historical monitoring data, and determines the effective device set corresponding to the first urban ordinary road based on the obtained real-time monitoring data and the vehicle flow change rule graph.

[0082] The specific implementation of this step can refer to the subsequent description of the embodiments of the present application, and will not be described here.

[0083] S2033, the electronic device determines the third in-transit quantity of the first urban ordinary road based on the monitoring data collected by the effective device set corresponding to the first urban ordinary road.

[0084] As a possible implementation manner, in the case that the monitoring device is a geomagnetic device, the electronic device obtains monitoring data collected by the effective device corresponding to the first urban ordinary road, and the distribution density of a plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road.

[0085] Further, the electronic device divides the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road into a plurality of types of geomagnetic devices, and determines the number of first vehicles passing through each type of geomagnetic device within the average driving time of vehicles before the current time, to determine the third in-transit quantity of the first urban ordinary road.

[0086] As another possible implementation manner, in the case that the monitoring device is a geomagnetic device, the electronic device obtains monitoring data collected by the effective device corresponding to the first urban ordinary road, and the monitoring data includes real-time monitoring data and historical monitoring data. The electronic device determines the vehicle in-transit probability corresponding to the first urban ordinary road based on the historical monitoring data of the first urban ordinary road. The electronic device determines the third vehicle number passing through each of the plurality of portal devices based on the real-time monitoring data.

[0087] Further, the electronic device determines the third in-transit quantity of the first urban ordinary road based on the third vehicle number passing through each of the plurality of portal devices and the vehicle in-transit probability.

[0088] The specific implementation of this step can refer to the subsequent description of the embodiments of the present application, and will not be described here.

[0089] In S2034, the electronic device determines the fourth OD of the second urban ordinary road based on the predetermined OD threshold range, the traffic index range and the correction coefficient.

[0090] The OD threshold range includes a lower OD limit and an upper OD limit, the traffic index range includes a lower traffic index limit and an upper traffic index limit, and the correction coefficient is a coefficient determined based on the weather condition.

[0091] As a possible implementation, the electronic device obtains the traffic index at the current time, and determines the fourth OD of the second urban ordinary road based on the traffic index at the current time, the predetermined OD threshold range, the traffic index range, the correction coefficient and Formula 3.

[0092] Formula 3 can be as follows:

[0093]

[0094] wherein CarNum2 is the fourth OD of the second urban ordinary road, CarNum max is the upper OD limit in the OD threshold range, CarNum min is the lower OD limit in the OD threshold range, TSI max is the upper traffic index limit in the traffic index range, TSI min is the lower traffic index limit in the traffic index range, TSI t is the traffic index corresponding to the current time t, and γ is the correction coefficient.

[0095] For example, the correction coefficient can be as shown in Table 1:

[0096] Table 1: Correction coefficient

[0097] Rainy Heavy rain Moderate rain Light rain Correction factor 0.83 0.86 0.91 Snowy Heavy snow Moderate snow Light snow Correction factor 0.8 0.85 0.88

[0098] In S2035, the electronic device determines the first OD of the urban ordinary road as the sum of the third OD of the first urban ordinary road and the fourth OD of the second urban ordinary road.

[0099] It can be understood that, according to the distribution density of the corresponding monitoring device in the urban ordinary road and the device operation quality of the monitoring device, the urban ordinary road is divided into the first urban ordinary road and the second urban ordinary road, and the third in-transit quantity of the first urban ordinary road and the fourth in-transit quantity of the second urban ordinary road are determined. In this way, the first in-transit quantity of the urban ordinary road can be accurately determined by making full use of the monitoring device, so as to accurately determine the vehicle in-transit quantity of the target area. Meanwhile, the correction coefficient is a coefficient determined based on the weather condition, so that the fourth in-transit quantity of the second urban ordinary road determined based on the correction coefficient takes into account the weather condition, so that the vehicle in-transit quantity of the target area determined subsequently is more accurate.

[0100] In some embodiments, in the case where the monitoring device is a plurality of geomagnetic devices, in order to determine the third in-transit quantity of the first urban ordinary road, as shown in S2033, the above S2033 can be implemented in the following manner: Figure 4

[0101] S301, the electronic device divides the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road into a plurality of categories of geomagnetic devices based on the distribution density of the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road.

[0102] As a possible implementation manner, the electronic device obtains device position information and device quantity information of the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road, and performs kernel density analysis to obtain a kernel density analysis result. The electronic device divides the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road into a plurality of categories of geomagnetic devices (for example, the plurality of categories of geomagnetic devices can be 3 categories) based on the kernel density analysis result and the natural break method.

[0103] S302, the electronic device determines, for each category of geomagnetic devices in the plurality of categories of geomagnetic devices, a vehicle average driving time corresponding to each category of geomagnetic devices based on the distance between the geomagnetic devices and the average speed of the vehicle.

[0104] As a possible implementation manner, the electronic device determines, for each category of geomagnetic devices in the plurality of categories of geomagnetic devices, at least one group of geomagnetic devices in each category of geomagnetic devices based on the obtained device position information and device quantity information of the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road, and each group of geomagnetic devices includes two geomagnetic devices with connectivity.

[0105] ​Further, the electronic device determines a distance between each group of geomagnetic devices in at least one group of geomagnetic devices in each type of geomagnetic device, and averages the distance between each group of geomagnetic devices in at least one group of geomagnetic devices in each type of geomagnetic device to obtain a distance average value. The electronic device determines the distance average value as the distance average value of each type of geomagnetic device.

[0106] The electronic device obtains an average speed of a vehicle of each type of geomagnetic device, and determines an average driving duration of a vehicle corresponding to each type of geomagnetic device in the plurality of types of geomagnetic devices based on the distance average value of each type of geomagnetic device and the average speed of the vehicle of each type of geomagnetic device.

[0107] S303, the electronic device determines a third quantity of vehicles on the first urban ordinary road based on a first quantity of vehicles passing through the first urban ordinary road within the average driving duration of the vehicle of each type of geomagnetic device in the plurality of types of geomagnetic devices before the current time.

[0108] As a possible implementation manner, the electronic device obtains real-time monitoring data of each type of geomagnetic device within the average driving duration of the vehicle of each type of geomagnetic device in the plurality of types of geomagnetic devices before the current time, and the real-time monitoring data includes a real-time time and a quantity of vehicles corresponding to the real-time time. The electronic device sums the quantity of vehicles corresponding to the real-time time in the real-time monitoring data within the average driving duration of the vehicle of each type of geomagnetic device before the current time to obtain the first quantity of vehicles passing through the first urban ordinary road within the average driving duration of the vehicle of each type of geomagnetic device before the current time.

[0109] Further, the electronic device determines a distance between each group of geomagnetic devices in at least one group of geomagnetic devices in each type of geomagnetic device, and averages the distance between each group of geomagnetic devices in at least one group of geomagnetic devices in each type of geomagnetic device to obtain a distance average value. The electronic device determines the distance average value as the distance average value of each type of geomagnetic device.

[0110] It can be understood that, according to the average driving duration of the vehicle corresponding to each type of geomagnetic device in the plurality of types of geomagnetic devices, the third quantity of vehicles on the first urban ordinary road is determined, the vehicle passing data collected by the geomagnetic device is fully utilized, and the third quantity of vehicles on the first urban ordinary road can be accurately determined, so that the quantity of vehicles on the way in the target region can be accurately determined.

[0111] In some embodiments, in the case that the monitoring device is a plurality of geomagnetic devices, the monitoring data includes historical monitoring data and real-time monitoring data. In order to determine the third quantity of vehicles on the first urban ordinary road, as shown in Figure 5 The above S2033 can also be implemented in the following manner:

[0112] S304, the electronic device determines a probability of a vehicle on the first urban ordinary road in each unit time period included in a target time period based on the historical monitoring data of the first urban ordinary road.

[0113] The vehicle-in-transit probability is used to indicate a probability that the vehicle passes through other camera devices again within a target time period after passing through any camera device of the plurality of camera devices, the other camera devices being camera devices other than the any camera device of the plurality of camera devices.

[0114] As a possible implementation, the electronic device obtains historical monitoring data of any camera device of the plurality of camera devices within a target time period (e.g., 30 minutes) before the historical time, the historical monitoring data including a plurality of historical monitoring times, a number of vehicles corresponding to each historical monitoring time, and a license plate identification of each vehicle. The electronic device performs data preprocessing on the obtained historical monitoring data of any camera device of the plurality of camera devices within the target time period before the historical time, to retain the historical monitoring data corresponding to the same vehicle and closest to the historical time.

[0115] Thus, the electronic device sums up the number of vehicles corresponding to each historical monitoring time in the historical monitoring data of any camera device of the plurality of camera devices within the target time period before the historical time, to obtain a first total number of vehicles passing through the any camera device of the plurality of camera devices within the target time period before the historical time.

[0116] Further, the electronic device divides the target time period into a plurality of unit time periods (e.g., 5 minutes), and determines a second total number of vehicles passing through other camera devices other than the any camera device of the plurality of camera devices again within each unit time period of the plurality of unit time periods included in the target time period after the plurality of vehicles pass through the any camera device of the plurality of camera devices. Taking any vehicle as an example, assuming that the any vehicle passes through the any camera device of the plurality of camera devices at the historical monitoring time, the electronic device determines a number of times that the any vehicle passes through other camera devices other than the any camera device of the plurality of camera devices again within the plurality of unit time periods included in the target time period after the historical monitoring time.

[0117] Thus, the electronic device determines, based on the first total number of vehicles passing through the any camera device of the plurality of camera devices within the target time period before the historical time and the second total number of vehicles, a vehicle-in-transit probability corresponding to each unit time period of the plurality of unit time periods included in the target time period after the historical time, in sequence.

[0118] Further, the electronic device can also calculate an average value of all vehicle-in-transit probabilities determined within a preset time period (e.g., one month), to further improve the accuracy of determining the vehicle-in-transit probability.

[0119] For example, at a historical time of 8:00, a target time period of 30 minutes, and a unit time period of 5 minutes, the electronic device obtains historical monitoring data of the A-catch device in the 30 minutes before the historical time of 8:00 (i.e., the time period between 7:30 and 8:00), where the A-catch device is any of the plurality of catch devices, and the historical monitoring data includes a plurality of historical monitoring times, a number of vehicles corresponding to each historical monitoring time, and a license plate identifier of each vehicle. The electronic device performs data preprocessing on the obtained historical monitoring data of the A-catch device in the 30 minutes before 8:00, to retain the historical monitoring data corresponding to the same vehicle and obtained closest to the historical time.

[0120] Thus, the electronic device sums the number of vehicles corresponding to each historical monitoring time in the historical monitoring data of the A-catch device in the 30 minutes before 8:00, to obtain a first total number M of vehicles passing through the A-catch device in the 30 minutes before 8:00.

[0121] Further, the electronic device divides the 30 minutes into 6 time periods of 5 minutes each, and determines a second total number of vehicles passing through the other catch devices in the 6 time periods of 5 minutes each included in the 30 minutes after the plurality of vehicles pass through the A-catch device. For example, assuming that any vehicle passes through the A-catch device at 8:00 (i.e., the historical time), the electronic device needs to determine the number of times that the vehicle passes through the other catch devices in the 6 time periods of 5 minutes each included in the 30 minutes after 8:00.

[0122] Thus, the electronic device determines, based on the first total number M of vehicles passing through the A-catch device in the 30 minutes before 8:00 and the second total number N of vehicles, the vehicle-in-transit probability corresponding to each time period of 5 minutes in the 6 time periods of 5 minutes each included in the 30 minutes after 8:00.

[0123] S305, the electronic device determines a second number of vehicles passing through the plurality of catch devices in a target time period before a current time.

[0124] As a possible implementation manner, the electronic device obtains real-time monitoring data in the target time period before the current time, where the real-time monitoring data includes a plurality of real-time times, a number of vehicles corresponding to each real-time time, and a license plate identifier of each vehicle. The electronic device performs data preprocessing on the real-time monitoring data, which includes deduplication.

[0125] Further, the electronic device sums the number of vehicles corresponding to each real-time time in the real-time monitoring data after data preprocessing, to obtain the second number of vehicles passing through the plurality of catch devices in the target time period before the current time.

[0126] S306. The electronic device determines the number of third vehicles passing through each of the multiple checkpoint devices within each of the multiple unit time periods included in the target time period.

[0127] As one possible implementation, the electronic device determines, based on the second number of vehicles passing through multiple checkpoint devices within a target time period prior to the current time, the third number of vehicles passing through each of the multiple unit time periods included within the target time period prior to the current time, within each unit time period.

[0128] For example, taking a target time period of 30 minutes and a unit time period of 5 minutes as an example, the electronic device determines the third number of vehicles num2 that pass through each of the multiple checkpoint devices within each of the six 5-minute intervals included in the 30 minutes before the current time of 8:30 based on the second number of vehicles num1 that passed through multiple checkpoint devices within the 30 minutes before the current time of 8:30.

[0129] S307. Electronic devices determine the third on-the-road quantity on ordinary roads in the first city based on the number of third vehicles passing through each of the multiple checkpoint devices and the probability of vehicles being on the road.

[0130] As one possible implementation, the electronic device determines the third on-road quantity on ordinary roads in the first city based on the probability of a vehicle being on the road in each unit time period within multiple unit time periods included in the target time period, and the third vehicle count of each of the multiple checkpoint devices in each unit time period within the target time period before the current time, using Formula 4. Formula 4 can be expressed as follows:

[0131]

[0132] Where CarNum3 represents the third number of vehicles on ordinary roads in the first city, f represents the total number of checkpoint devices, q represents the number of vehicles per unit time period within the preset time period, and num represents the number of vehicles on the road. j，l Let p be the number of the third vehicle at the j-th checkpoint device within the l-th time unit. j，l Let be the probability that a vehicle is on the road during the l-th unit time period for the j-th checkpoint device.

[0133] Understandably, by determining the third number of vehicles on ordinary roads in the first city based on the probability of vehicles being on the road and the number of third vehicles passing through each of the multiple checkpoint devices, the vehicle traffic data collected by the checkpoint devices is fully utilized, which can accurately determine the third number of vehicles on the road in the first city and thus accurately determine the number of vehicles on the road in the target area.

[0134] In some embodiments, in order to determine the first urban ordinary road and the second urban ordinary road, as shown in Figure 6 The above S2031 can be implemented in the following manner:

[0135] S401: The electronic device obtains device distribution information of the monitoring device in the urban ordinary road.

[0136] The device distribution information includes at least one of the following: device position information, device quantity information, and device operation quality, wherein the device operation quality includes at least one of the following: data transmission quality, data accuracy, and device operation stability.

[0137] As a possible implementation manner, the electronic device obtains the device distribution information of the monitoring device in the urban ordinary road, and the device distribution information includes: device position information, device quantity information, data transmission quality, data accuracy, and device operation stability.

[0138] It should be noted that the data transmission quality is used to indicate the stability of data backhaul of the monitoring device, the data accuracy is used to indicate the accuracy of the valid field in the data backhaul of the monitoring device, and the device operation stability is used to indicate the stability of normal operation of the monitoring device.

[0139] S402: The electronic device divides the urban ordinary road into the first urban ordinary road and the second urban ordinary road based on the device distribution information in the urban ordinary road.

[0140] As a possible implementation manner, the electronic device determines the monitoring device distribution density of the monitoring device in the urban ordinary road based on the obtained device position information and device quantity information of the monitoring device in the urban ordinary road. The electronic device determines whether the device operation quality meets the preset quality based on the obtained data transmission quality, data accuracy, and device operation stability of the monitoring device in the urban ordinary road and the preset quality.

[0141] Further, the electronic device determines the urban ordinary road with the monitoring device distribution density greater than the preset density value and the device operation quality of the monitoring device meeting the preset quality as the first urban ordinary road, and determines the urban ordinary road with the monitoring device distribution density less than or equal to the preset density value or the device operation quality of the monitoring device not meeting the preset quality as the second urban ordinary road.

[0142] It can be understood that, according to the device distribution information of the monitoring device in the urban ordinary road, the urban ordinary road can be accurately divided into the first urban ordinary road and the second urban ordinary road, so as to accurately determine the third in-transit quantity of the first urban ordinary road and the fourth in-transit quantity of the second urban ordinary road, and further accurately determine the in-transit quantity of the vehicle in the target area.

[0143] In some embodiments, the monitoring device comprises any one of the following: a geomagnetic device, a fisheye device, in order to determine the effective device set corresponding to the first urban ordinary road, such as Figure 7 As shown in the above S2032, the above S2032 can be implemented in the following way:

[0144] S501, the electronic device constructs the vehicle flow change rule graph corresponding to the first urban ordinary road based on the historical monitoring data of the first urban ordinary road.

[0145] Among them, the vehicle flow change rule graph is used to indicate the vehicle flow change in the first urban ordinary road in the historical time period, and one monitoring device corresponds to one vehicle flow change rule graph.

[0146] As a possible implementation manner, in the case of the monitoring device being a geomagnetic device, the electronic device acquires the historical monitoring data collected by the geomagnetic device in the historical time period, and the historical monitoring data includes a plurality of historical time points and the vehicle quantity corresponding to each historical time point. The electronic device performs data preprocessing on the historical monitoring data to eliminate the historical monitoring data with error fields.

[0147] Further, the electronic device divides the historical monitoring data after data preprocessing according to a plurality of time dimensions to obtain historical monitoring data corresponding to each time dimension. The electronic device constructs a vehicle flow change rule graph corresponding to each time dimension based on the vehicle quantity corresponding to the historical time point in the historical monitoring data corresponding to each time dimension in the plurality of time dimensions, and further obtains the vehicle flow change rule graph corresponding to each time dimension of the geomagnetic device.

[0148] The electronic device refers to the above steps in turn for the geomagnetic device corresponding to the first urban ordinary road, until the vehicle flow change rule graph corresponding to the first urban ordinary road is obtained.

[0149] It should be noted that the plurality of time dimensions can be specifically working days, holidays, rainy and snowy days, and major activity days.

[0150] Exemplarily, in a case where the monitoring device is a geomagnetic device, the electronic device acquires historical monitoring data collected by the geomagnetic device in a historical 30-day period, and performs data preprocessing to eliminate historical monitoring data with erroneous fields. The electronic device divides the historical monitoring data after data preprocessing according to working days, holidays, rainy and snowy days, and major activity days, to obtain historical monitoring data corresponding to 20 working days, historical monitoring data corresponding to 3 holidays, historical monitoring data corresponding to 5 rainy and snowy days, and historical monitoring data corresponding to 2 major activity days.

[0151] Further, the electronic device constructs a vehicle flow variation rule graph of each time dimension based on the vehicle quantity corresponding to the historical time in the historical monitoring data corresponding to each time dimension in the plurality of time dimensions, and further obtains the vehicle flow variation rule graph corresponding to the geomagnetic device in the working days, the holidays, the rainy and snowy days, and the major activity days.

[0152] The electronic device sequentially performs the above steps on the geomagnetic devices corresponding to the ordinary roads in the first city, until the vehicle flow variation rule graph corresponding to the ordinary roads in the first city is obtained.

[0153] As another possible implementation, in a case where the monitoring device is a loop device, the electronic device acquires historical monitoring data collected by the loop device in a historical time period, and the historical monitoring data includes a plurality of historical times, a vehicle quantity corresponding to each historical time, and a license plate identifier of each vehicle. The electronic device performs data preprocessing on the historical monitoring data, and the data preprocessing includes deduplication and elimination of historical monitoring data with erroneous fields.

[0154] Further, the electronic device divides the historical monitoring data after data preprocessing according to a plurality of time dimensions to obtain historical monitoring data corresponding to each time dimension. The electronic device constructs a vehicle flow variation rule graph corresponding to each time dimension based on the vehicle quantity corresponding to the historical time in the historical monitoring data corresponding to each time dimension in the plurality of time dimensions, and further obtains the vehicle flow variation rule graph corresponding to the loop device under the plurality of time dimensions.

[0155] The electronic device sequentially performs the above steps on the loop devices corresponding to the ordinary roads in the first city, until the vehicle flow variation rule graph corresponding to the ordinary roads in the first city is obtained.

[0156] It should be noted that the plurality of time dimensions can be working days, holidays, rainy and snowy days, and major activity days.

[0157] Exemplarily, in a case where the monitoring device is a loop device, the electronic device acquires historical monitoring data collected by the loop device in the past 30 days, the historical monitoring data including a plurality of historical time points, a vehicle quantity corresponding to each historical time point, and a license plate identifier of each vehicle. The electronic device performs data preprocessing on the historical monitoring data, the data preprocessing including deduplication and elimination of historical monitoring data with erroneous fields.

[0158] Further, the electronic device divides the historical monitoring data after data preprocessing according to working days, holidays, rainy and snowy days, and major activity days, to obtain historical monitoring data corresponding to 20 working days, historical monitoring data corresponding to 3 holidays, historical monitoring data corresponding to 5 rainy and snowy days, and historical monitoring data corresponding to 2 major activity days. The electronic device constructs a vehicle flow variation rule graph corresponding to each time dimension based on the vehicle quantity corresponding to the historical time point in the historical monitoring data corresponding to each time dimension, and further obtains a vehicle flow variation rule graph corresponding to working days, holidays, rainy and snowy days, and major activity days of the loop device.

[0159] The electronic device refers to the above steps to sequentially perform on the loop devices corresponding to the first urban ordinary road, until the vehicle flow variation rule graph corresponding to the first urban ordinary road is obtained.

[0160] S502, the electronic device determines a set of effective devices corresponding to the first urban ordinary road from the monitoring devices based on the real-time monitoring data and the vehicle flow variation rule graph of the first urban ordinary road.

[0161] As a possible implementation manner, in a case where the monitoring device is a geomagnetic device, the electronic device acquires real-time monitoring data collected by the geomagnetic device in a preset time period before the current time, the real-time monitoring data including a plurality of real-time time points and a vehicle quantity corresponding to each real-time time point. The electronic device performs data preprocessing on the real-time monitoring data and determines a time dimension in which the current time is located, the data preprocessing including elimination of real-time monitoring data with erroneous fields.

[0162] Further, the electronic device constructs a real-time vehicle flow variation rule graph of the geomagnetic device based on the vehicle quantity corresponding to the real-time time point in the real-time monitoring data after data preprocessing. The electronic device determines the geomagnetic device that matches the real-time vehicle flow variation rule graph and the vehicle flow variation rule graph of the same time dimension as an effective device.

[0163] The electronic device refers to the above steps to sequentially perform on the geomagnetic devices corresponding to the first urban ordinary road, and obtains a set of effective devices corresponding to the first urban ordinary road based on the determined effective devices.

[0164] As another possible implementation, in a case where the monitoring device is a loop device, the electronic device acquires real-time monitoring data collected by the loop device in a preset time period before the current time, the real-time monitoring data including a plurality of real-time times, a number of vehicles corresponding to each real-time time, and a license plate identification of each vehicle. The electronic device performs data preprocessing on the real-time monitoring data and determines a time dimension in which the current time is located, the data preprocessing including deduplication and elimination of real-time monitoring data having an error field.

[0165] Further, the electronic device constructs a real-time traffic flow change rule graph of the loop device based on the number of vehicles passing through corresponding to the real-time times in the real-time monitoring data after data preprocessing. The electronic device determines a loop device that matches the real-time traffic flow change rule graph and a traffic flow change rule graph of the same time dimension as an effective device.

[0166] The electronic device sequentially performs the above steps on loop devices corresponding to the first urban ordinary road, and obtains a set of effective devices corresponding to the first urban ordinary road based on the determined effective devices.

[0167] It can be understood that, according to the real-time monitoring data and the traffic flow change rule graph of the first urban ordinary road, the set of effective devices corresponding to the first urban ordinary road is determined from the monitoring devices, which can ensure the accuracy of the vehicle passing data collected by the monitoring devices, thereby improving the accuracy of the third in-transit quantity of the first urban ordinary road determined based on the set of effective devices corresponding to the first urban ordinary road, and further accurately determining the in-transit quantity of vehicles in the target region.

[0168] In some embodiments, in order to determine the fourth in-transit quantity of the second urban ordinary road, as shown in Figure 8 The vehicle in-transit quantity determination method provided by the embodiments of the present application further includes:

[0169] S601, the electronic device determines an in-transit quantity threshold range corresponding to the second urban ordinary road and a traffic index range corresponding to the second urban ordinary road based on at least one of the second in-transit quantity of the urban expressway and the third in-transit quantity of the first urban ordinary road.

[0170] The in-transit quantity threshold range includes a lower in-transit quantity and an upper in-transit quantity, and the traffic index range includes a lower traffic index and an upper traffic index.

[0171] As a possible implementation, the electronic device acquires the second in-transit quantity of the urban expressway, determines the maximum value in the second in-transit quantity of the urban expressway as the upper in-transit quantity of the in-transit quantity threshold range, and determines the minimum value in the second in-transit quantity of the urban expressway as the lower in-transit quantity of the in-transit quantity threshold range.

[0172] Further, the electronic device obtains a traffic index corresponding to the maximum of the second in-traffic quantity of the urban expressway and a traffic index corresponding to the minimum of the second in-traffic quantity of the urban expressway, and determines the traffic index corresponding to the maximum of the second in-traffic quantity of the urban expressway as an upper limit traffic index of the traffic index range, and determines the traffic index corresponding to the minimum of the second in-traffic quantity of the urban expressway as a lower limit traffic index of the traffic index range.

[0173] As another possible implementation, the electronic device obtains a third in-traffic quantity of a first urban ordinary road, determines a maximum of the third in-traffic quantity of the first urban ordinary road as an upper limit in-traffic quantity of the in-traffic quantity threshold range, and determines a minimum of the third in-traffic quantity of the first urban ordinary road as a lower limit in-traffic quantity of the in-traffic quantity threshold range.

[0174] Further, the electronic device obtains a traffic index corresponding to the maximum of the third in-traffic quantity of the first urban ordinary road and a traffic index corresponding to the minimum of the third in-traffic quantity of the first urban ordinary road, and determines the traffic index corresponding to the maximum of the third in-traffic quantity of the first urban ordinary road as an upper limit traffic index of the traffic index range, and determines the traffic index corresponding to the minimum of the third in-traffic quantity of the first urban ordinary road as a lower limit traffic index of the traffic index range.

[0175] S602, the electronic device determines a traffic index of a second urban ordinary road based on a free flow speed corresponding to the second urban ordinary road and an average speed of a vehicle corresponding to the second urban ordinary road.

[0176] As a possible implementation, the electronic device obtains a free flow speed corresponding to the second urban ordinary road at a current time and an average speed of a vehicle corresponding to the second urban ordinary road at the current time, and inputs the free flow speed corresponding to the second urban ordinary road at the current time and the average speed of the vehicle corresponding to the second urban ordinary road at the current time into a preset formula five to obtain the traffic index of the second urban ordinary road at the current time. The formula five can be expressed as follows:

[0177]

[0178] wherein t is the current time, TSI t is the traffic index corresponding to the current time t, v f is the free flow speed corresponding to the second urban ordinary road, v i is the average speed of the vehicle corresponding to the second urban ordinary road.

[0179] It can be understood that, in the case that the in-transit quantity and the traffic index are in a linear relationship, the in-transit quantity threshold range corresponding to the second urban ordinary road is determined through at least one of the second in-transit quantity of the urban expressway and the third in-transit quantity of the first urban ordinary road, which can improve the accuracy of the subsequent determination of the fourth in-transit quantity of the second urban ordinary road, and thus the in-transit quantity of the vehicle in the target region is accurately determined.

[0180] The vehicle in-transit quantity determination apparatus or the electronic device can be divided into functional modules according to the above method. For example, the vehicle in-transit quantity determination apparatus or the electronic device can include functional modules corresponding to each functional division, or two or more functions can be integrated into one processing module. The integrated module can be implemented in the form of hardware or in the form of a software functional module. It should be noted that the division of modules in the present embodiment is illustrative and is only a logical functional division. Actual implementation can have another division manner.

[0181] For example, the present embodiment also provides a vehicle in-transit quantity determination apparatus.

[0182] Figure 9 FIG. 7 is a block diagram of a vehicle in-transit quantity determination apparatus according to an exemplary embodiment. Referring to FIG. 7, Figure 9 The vehicle in-transit quantity determination apparatus 700 includes a processing unit 701 and a determination unit 702.

[0183] The processing unit 701 is configured to divide roads included in a target region into urban expressways and urban ordinary roads, and to obtain road condition data of the urban expressways and monitoring data of the urban ordinary roads. The average speed of a vehicle traveling in the urban expressways is greater than a preset speed, and the average speed of a vehicle traveling in the urban ordinary roads is less than or equal to the preset speed. The monitoring data is vehicle passing data collected by a monitoring device. The monitoring device includes any one of the following: a geomagnetic device and a turret device.

[0184] The determination unit 702 is configured to determine a first in-transit quantity of the urban ordinary roads based on the monitoring data of the urban ordinary roads. The in-transit quantity is used to indicate the number of vehicles traveling in the road.

[0185] The determination unit 702 is further configured to determine a second in-transit quantity of the urban expressways based on the road condition data of the urban expressways.

[0186] The determination unit 702 is further configured to determine a target in-transit quantity of the target region based on the first in-transit quantity of the urban ordinary roads and the second in-transit quantity of the urban expressways.

[0187] Optionally, in order to determine the first in-transit quantity of the urban ordinary roads, as Figure 9 illustrated in FIG. 7, the determination unit 702 is specifically configured to:

[0188] The first urban ordinary road and the second urban ordinary road are determined from urban ordinary roads, and an effective device set corresponding to the first urban ordinary road is determined from the monitoring devices. The monitoring devices included in the first urban ordinary road have a distribution density greater than a preset density value, and the monitoring devices included in the first urban ordinary road have a device operation quality satisfying a preset quality. The monitoring devices included in the second urban ordinary road have a distribution density less than or equal to the preset density value, and the monitoring devices included in the second urban ordinary road have a device operation quality not satisfying the preset quality. The effective device set includes a plurality of normally operating monitoring devices.

[0189] Based on the monitoring data collected by the effective device set corresponding to the first urban ordinary road, the third in-transit quantity of the first urban ordinary road is determined.

[0190] Based on a predetermined in-transit quantity threshold range, a traffic index range, and a correction coefficient, the fourth in-transit quantity of the second urban ordinary road is determined. The correction coefficient is a coefficient determined based on weather conditions.

[0191] The sum of the third in-transit quantity of the first urban ordinary road and the fourth in-transit quantity of the second urban ordinary road is determined as the first in-transit quantity of the urban ordinary road.

[0192] Optionally, in the case where the monitoring devices are a plurality of geomagnetic devices, in order to determine the third in-transit quantity of the first urban ordinary road, as shown in Figure 9 The determination unit 702 is specifically configured to:

[0193] Based on the distribution density of the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road, the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road are divided into a plurality of categories of geomagnetic devices.

[0194] For each category of geomagnetic devices in the plurality of categories of geomagnetic devices, based on the distance between the geomagnetic devices and the average speed of the vehicle, the average driving time of the vehicle corresponding to each category of geomagnetic devices in the plurality of categories of geomagnetic devices is determined.

[0195] Based on the number of first vehicles passing through within the average driving time of the vehicle of each category of geomagnetic devices in the plurality of categories of geomagnetic devices before the current time, the third in-transit quantity of the first urban ordinary road is determined.

[0196] Optionally, in the case where the monitoring devices are a plurality of geomagnetic devices, the monitoring data includes historical monitoring data and real-time monitoring data. In order to determine the third in-transit quantity of the first urban ordinary road, as shown in Figure 9 The determination unit 702 is specifically configured to:

[0197] Based on historical monitoring data of ordinary roads in the first city, the probability of a vehicle being on the road is determined for each of the multiple time units included in the target time period. The probability of a vehicle being on the road indicates the probability that a vehicle will pass through other checkpoints again within the target time period after passing through any one of the multiple checkpoints. Other checkpoints are checkpoints other than any one of the multiple checkpoints.

[0198] Determine the number of second vehicles passing through multiple checkpoint devices within the target time period prior to the current time, and determine the number of third vehicles passing through each of the multiple checkpoint devices within each of the multiple unit time periods included in the target time period.

[0199] The third on-the-road quantity on ordinary roads in the first city is determined based on the number of third vehicles passing through each of the multiple checkpoint devices and the probability of vehicles being on the road.

[0200] Optionally, to determine the ordinary roads in the first city and the ordinary roads in the second city, such as Figure 9 As shown, the aforementioned determining unit 702 is specifically used for:

[0201] Acquire the distribution information of monitoring equipment on ordinary urban roads. The equipment distribution information includes at least one of the following: equipment location information, equipment quantity information, and equipment operation quality. The equipment operation quality includes at least one of the following: data transmission quality, data accuracy, and equipment operation stability.

[0202] Based on the equipment distribution information in urban general roads, urban general roads are divided into first urban general roads and second urban general roads.

[0203] Optionally, the monitoring equipment includes any of the following: geomagnetic equipment, checkpoint equipment, etc., to determine the effective set of equipment corresponding to ordinary roads in the first city, such as... Figure 9 As shown, the aforementioned determining unit 702 is specifically used for:

[0204] Based on historical monitoring data of ordinary roads in the first city, a traffic flow change pattern map is constructed for the ordinary roads in the first city. The traffic flow change pattern map is used to indicate the changes in traffic flow on ordinary roads in the first city within a historical period. One monitoring device corresponds to one traffic flow change pattern map.

[0205] Based on real-time monitoring data and traffic flow change patterns of ordinary roads in the first city, the effective set of monitoring devices corresponding to ordinary roads in the first city is determined.

[0206] Optional, the second volume of traffic on urban expressways, such as Figure 9 As shown, the aforementioned determining unit 702 is specifically used for:

[0207] determine the traffic flow density corresponding to the urban expressway based on the average speed of the vehicle corresponding to the urban expressway and the vehicle flow.

[0208] determine the second in-transit quantity of the urban expressway based on the traffic flow density corresponding to the urban expressway, the road length, and the number of lanes.

[0209] Optionally, in order to determine the fourth in-transit quantity of the second urban ordinary road, as shown in the above determination unit 702, is further used to: Figure 9

[0210] determine the in-transit quantity threshold range corresponding to the second urban ordinary road and the traffic index range corresponding to the second urban ordinary road based on at least one of the second in-transit quantity of the urban expressway and the third in-transit quantity of the first urban ordinary road, the in-transit quantity threshold range including a lower in-transit quantity and an upper in-transit quantity, and the traffic index range including a lower traffic index and an upper traffic index.

[0211] determine the traffic index of the second urban ordinary road based on the free flow speed corresponding to the second urban ordinary road and the average speed of the vehicle corresponding to the second urban ordinary road.

[0212] As to the apparatus in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments of the method, and will not be described in detail here.

[0213] Figure 10 is a block diagram of an electronic device according to an exemplary embodiment. As shown in Figure 10 the electronic device 800 includes but is not limited to a processor 801 and a memory 802.

[0214] The memory 802 described above is used to store executable instructions of the processor 801. It can be understood that the processor 801 is configured to execute the instructions to implement the vehicle in-transit quantity determination method in the above embodiments.

[0215] It should be noted that those skilled in the art can understand that the electronic device structure shown in Figure 10 does not constitute a limitation on the electronic device, and the electronic device can include more or fewer components than Figure 10 shown, or combine certain components, or different component arrangements.

[0216] ​The processor 801 is the control center of the electronic device, connects each part of the whole electronic device by various interfaces and lines, executes various functions of the electronic device and processes data by running or executing software programs and / or modules stored in the memory 802 and calling data stored in the memory 802, thereby monitoring the whole electronic device. The processor 801 can include one or more processing units. Alternatively, the processor 801 can integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application program, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor can also not be integrated into the processor 801.

[0217] The memory 802 can be used to store software programs and various data. The memory 802 can mainly include a program storage area and a data storage area, wherein the program storage area can store the operating system, the application programs (such as processing units, determination units, etc.) required by at least one function module, etc. In addition, the memory 802 can include a high-speed random access memory, and can also include a non-volatile memory, for example, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state memory device.

[0218] In an example embodiment, a computer readable storage medium / computer program product is also provided, when the computer-executable instructions stored in the computer readable storage medium / computer program product are executed by the processor of the electronic device, the electronic device can execute the method described in the first aspect.

[0219] It should be noted that " / " represents the meaning of "or".

[0220] In an example embodiment, a computer readable storage medium including instructions is also provided, for example, the memory 802 including instructions, the above-mentioned instructions can be executed by the processor 801 of the electronic device 800 to realize the vehicle in-transit quantity determination method in the above-mentioned embodiment.

[0221] In actual implementation, Figure 9 The functions of the processing unit 701 and the determination unit 702 in the above-mentioned embodiment can be realized by the processor 801 calling the computer program stored in the memory 802. Figure 10 The specific execution process can refer to the description of the vehicle in-transit quantity determination method in the above-mentioned embodiment, which will not be repeated here.

[0222] Optionally, the computer readable storage medium can be a non-transitory computer readable storage medium, for example, the non-transitory computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0223] In the example embodiments, the embodiments of the present application also provide a computer program product comprising one or more instructions executable by the processor 801 of the electronic device to complete the vehicle in-transit quantity determination method in the above-described embodiments.

[0224] It should be noted that the instructions in the above computer readable storage medium or the one or more instructions in the computer program product are executed by the processor of the electronic device to realize each process of the above vehicle in-transit quantity determination method embodiments, and achieve the same technical effects as the above vehicle in-transit quantity determination method. To avoid repetition, it will not be described here.

[0225] Through the description of the above embodiments, those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional module is taken as an example for illustration. In actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0226] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the above-described device embodiments are only illustrative, for example, the division of modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be through some interfaces, indirect coupling or communication connection between the units or devices, which can be electrical, mechanical or other forms.

[0227] The units described as separate components can or can not be physically separate, and the components shown as units can be one physical unit or multiple physical units, that is, they can be located in one place, or they can be distributed to multiple different places. According to actual needs, part or all of the units can be selected to achieve the purpose of the present embodiment.

[0228] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0229] When the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application essentially or the parts that make contributions to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The software product is stored in a storage medium, including a plurality of instructions to make a device (which can be a single-chip microcomputer, a chip, etc.) or a processor execute all or part of the steps of the method of each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various storage program codes.

[0230] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any change or replacement within the technical scope disclosed in the present application should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of determining an on-the-road quantity of a vehicle, characterized by, The method comprises the following steps: Divide the roads included in the target area into urban expressways and urban ordinary roads, and obtain road condition data of the urban expressways and monitoring data of the urban ordinary roads, wherein the monitoring data is vehicle passing data collected by monitoring devices, and the monitoring devices include any one of the following: geomagnetic devices, turret devices; Determine a first urban ordinary road and a second urban ordinary road from the urban ordinary roads, determine a third in-traffic quantity of the first urban ordinary road based on the monitoring data corresponding to the first urban ordinary road, and determine a fourth in-traffic quantity of the second urban ordinary road based on a predetermined in-traffic quantity threshold range, a traffic index range and a correction coefficient; Determine the sum of the third in-traffic quantity of the first urban ordinary road and the fourth in-traffic quantity of the second urban ordinary road as a first in-traffic quantity of the urban ordinary roads, and determine the first in-traffic quantity of the urban ordinary roads, wherein the in-traffic quantity is used to indicate the number of vehicles driving on the roads; Determine a traffic flow density corresponding to the urban expressways based on the average speed and the vehicle flow of the vehicles corresponding to the urban expressways; Determine a second in-traffic quantity of the urban expressways based on the traffic flow density, the road length and the number of lanes corresponding to the urban expressways; Determine a target in-traffic quantity of the target area based on the first in-traffic quantity of the urban ordinary roads and the second in-traffic quantity of the urban expressways.

2. The method according to claim 1, wherein The monitoring devices include an effective device set corresponding to the first urban ordinary road in the monitoring devices, and the monitoring data is collected by the effective device set; The distribution density of the monitoring devices included in the first urban ordinary road is greater than a preset density value, the device operation quality of the monitoring devices included in the first urban ordinary road meets a preset quality, the distribution density of the monitoring devices included in the second urban ordinary road is less than or equal to the preset density value, the device operation quality of the monitoring devices included in the second urban ordinary road does not meet the preset quality, and the effective device set includes a plurality of normally operating monitoring devices.

3. The vehicle on-road quantity determination method according to claim 2, characterized by, The monitoring devices are a plurality of geomagnetic devices; The method for determining the third in-traffic quantity of the first urban ordinary road based on the monitoring data collected by the effective device set corresponding to the first urban ordinary road comprises the following steps: Divide the plurality of normally operating geomagnetic devices included in the effective device set corresponding to the first urban ordinary road into a plurality of categories of geomagnetic devices based on the distribution density of the plurality of normally operating geomagnetic devices; For each category of geomagnetic devices in the plurality of categories of geomagnetic devices, determine the average driving time of vehicles corresponding to each category of geomagnetic devices based on the distance between the geomagnetic devices and the average speed of the vehicles; Determine the third in-traffic quantity of the first urban ordinary road based on the number of first vehicles passing through within the average driving time of the vehicles before the current time for each category of geomagnetic devices in the plurality of categories of geomagnetic devices.

4. The vehicle on-road quantity determination method according to claim 2, characterized by, The monitoring devices are a plurality of portal devices, and the monitoring data includes historical monitoring data and real-time monitoring data. The third in-transit quantity of the first urban ordinary road is determined based on the monitoring data collected by the effective device set corresponding to the first urban ordinary road, and includes: The vehicle in-transit probability of the first urban ordinary road in each unit time period included in the target time period is determined based on the historical monitoring data of the first urban ordinary road, the vehicle in-transit probability being used to indicate the probability of a vehicle passing through other portal devices again within a target time period after passing through any portal device of the plurality of portal devices, the other portal devices being the portal devices other than the any portal device of the plurality of portal devices; The second vehicle number passing through the plurality of portal devices in the target time period before the current time is determined, and the third vehicle number passing through each portal device of the plurality of portal devices in each unit time period included in the target time period is determined; The third in-transit quantity of the first urban ordinary road is determined based on the third vehicle number passing through each portal device of the plurality of portal devices and the vehicle in-transit probability.

5. The vehicle on-road quantity determination method according to any one of claims 2 to 4, characterized by, The first urban ordinary road and the second urban ordinary road are determined from the urban ordinary roads, and include: Device distribution information of the monitoring devices in the urban ordinary roads is acquired, the device distribution information including at least one of device position information, device quantity information, and device operation quality, the device operation quality including at least one of data transmission quality, data accuracy, and device operation stability; The urban ordinary roads are divided into the first urban ordinary road and the second urban ordinary road based on the device distribution information in the urban ordinary roads.

6. The vehicle on-road quantity determination method according to any one of claims 2 to 4, characterized by, The effective device set corresponding to the first urban ordinary road is determined from the monitoring devices, and includes: A vehicle flow variation pattern diagram corresponding to the first urban ordinary road is constructed based on the historical monitoring data of the first urban ordinary road, the vehicle flow variation pattern diagram being used to indicate the variation of vehicle flow in the first urban ordinary road in a historical time period, one monitoring device corresponding to one vehicle flow variation pattern diagram; The effective device set corresponding to the first urban ordinary road is determined from the monitoring devices based on the real-time monitoring data of the first urban ordinary road and the vehicle flow variation pattern diagram.

7. The vehicle on-road quantity determination method according to any one of claims 1 to 3, characterized by, The method further includes: The in-transit quantity threshold range corresponding to the second urban ordinary road and the traffic index range corresponding to the second urban ordinary road are determined based on at least one of the second in-transit quantity of the urban expressway and the third in-transit quantity of the first urban ordinary road, the in-transit quantity threshold range including a lower limit in-transit quantity and an upper limit in-transit quantity, and the traffic index range including a lower limit traffic index and an upper limit traffic index; The traffic index of the second urban ordinary road is determined based on the free-flow speed corresponding to the second urban ordinary road and the average speed of the vehicles corresponding to the second urban ordinary road.

8. A vehicle on-the-move quantity determining device characterized by comprising: The vehicle in-quantity determination device comprises a processing unit and a determination unit; The processing unit is configured to divide roads included in a target region into urban expressways and urban ordinary roads, and to obtain road condition data of the urban expressways and monitoring data of the urban ordinary roads, wherein the average speed of vehicles driving on the urban expressways is greater than a preset speed, and the average speed of vehicles driving on the urban ordinary roads is less than or equal to the preset speed, and the monitoring data is vehicle passing data collected by a monitoring device, and the monitoring device comprises any one of the following: a geomagnetic device and a turret device; The determination unit is configured to determine a first urban ordinary road and a second urban ordinary road from the urban ordinary roads, to determine a third in-quantity of the first urban ordinary road based on monitoring data corresponding to the first urban ordinary road, and to determine a fourth in-quantity of the second urban ordinary road based on a predetermined in-quantity threshold range, a traffic index range and a correction coefficient; The determination unit is further configured to determine a sum of the third in-quantity of the first urban ordinary road and the fourth in-quantity of the second urban ordinary road as a first in-quantity of urban ordinary roads, and to determine the first in-quantity of the urban ordinary roads, wherein the in-quantity is used to indicate the number of vehicles driving on the roads; The determination unit is further configured to determine a traffic flow density corresponding to the urban expressways based on the average speed of vehicles and vehicle flow corresponding to the urban expressways; The determination unit is further configured to determine a second in-quantity of the urban expressways based on the traffic flow density corresponding to the urban expressways, the road length and the number of lanes; The determination unit is further configured to determine a target in-quantity of the target region based on the first in-quantity of the urban ordinary roads and the second in-quantity of the urban expressways.

9. An electronic device, comprising: Comprise: A processor; A memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method of any one of claims 1-7.

10. A computer readable storage medium / computer program product, characterized in that, When the computer-executable instructions stored in the computer-readable storage medium / computer program product are executed by the processor of the electronic device, the electronic device can perform the method of any one of claims 1-7.

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