Congestion detection method, device, system, cloud server and storage medium

Abstract

The application relates to a congestion detection method, device, system, cloud server and storage medium. The method comprises the following steps: obtaining first road condition information in a non-shielding area and second road condition information in a shielding area reported by a first roadside device in a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located in the shielding area; the first roadside device is located in the non-shielding area; and the congestion condition of the target road section is obtained according to the second road condition information and the first road condition information. The application improves the accuracy of congestion detection.

Description

Technical Field

[0001] The present application relates to the field of intelligent transportation technology, and in particular to a congestion detection method, device, system, cloud server and storage medium. Background Art

[0002] As the number of motor vehicles increases, urban traffic pressure is gradually increasing. The construction of viaducts can alleviate the traffic pressure caused by the increasing traffic volume, but during peak hours, traffic jams may also occur on and under the viaducts.

[0003] Currently, the system for detecting congestion on elevated bridges includes: multiple cameras on the bridge, multiple cameras under the bridge, a display screen / voice prompt device at the bridge entrance, and a cloud server. Each camera is used to collect images of the corresponding sub-road section and send the sub-road section images to the cloud server. The cloud server processes the images of each sub-road section to analyze and obtain the real-time road conditions of each road section, and sends the real-time road conditions to the display screen / voice prompt at the bridge entrance, which prompts each vehicle driver through the display screen / voice prompt at the bridge entrance.

[0004] However, in congestion detection, the image data volume is large, the transmission distance is long, and it consumes communication resources, which urgently needs improvement. Summary of the Invention

[0005] Based on this, it is necessary to provide a congestion detection method, device, system, cloud server and storage medium that can optimize data transmission quality and improve congestion detection accuracy to address the above technical problems.

[0006] In a first aspect, the present application provides a congestion detection method, the method comprising:

[0007] Obtaining first road condition information in a non-obstructed area and second road condition information in a blocked area reported by a first roadside device in a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located in the blocked area, and the first roadside device is located in the non-obstructed area;

[0008] The congestion condition of the target road section is obtained according to the second road condition information and the first road condition information.

[0009] In one embodiment, a target occlusion area is selected from candidate occlusion areas based on a connection relationship between a candidate roadside device and an edge cloud in a congestion detection system; wherein the candidate roadside device is located within the candidate occlusion area corresponding to the target road segment;

[0010] A data forwarding instruction is sent to the second roadside device in the target obstruction area to instruct the second roadside device to forward the second road condition information to the first roadside device.

[0011] In one embodiment, selecting a target occlusion area from candidate occlusion areas based on a connection relationship between a candidate roadside device and an edge cloud in a congestion detection system includes:

[0012] Selecting a roadside device that is not connected to the edge cloud from the candidate roadside devices as a second roadside device based on a connection relationship between the candidate roadside devices and the edge cloud in the congestion detection system;

[0013] The candidate obstruction area where the second roadside device is located is used as the target obstruction area.

[0014] In one embodiment, selecting a target occlusion area from candidate occlusion areas based on a connection relationship between a candidate roadside device and an edge cloud in a congestion detection system includes:

[0015] Selecting a roadside device that is not connected to the edge cloud from the candidate roadside devices as a second roadside device based on a connection relationship between the candidate roadside devices and the edge cloud in the congestion detection system;

[0016] The candidate occlusion area where the second roadside device is located is used as the target occlusion area

[0017] In one embodiment, obtaining the congestion condition of the target road section according to the second road condition information and the first road condition information includes:

[0018] Obtain the congestion status of the occlusion areas reported by the edge cloud corresponding to other occlusion areas; where other occlusion areas are occlusion areas in the candidate occlusion areas except the target occlusion area;

[0019] The congestion condition of the target road section is obtained according to the congestion condition of the blocked area, the second road condition information, and the first road condition information.

[0020] In one embodiment, the method further comprises:

[0021] According to the installation location of the edge cloud and the installation location of the candidate roadside equipment, the connection relationship between the candidate roadside equipment and the edge cloud in the congestion detection system is determined; wherein the installation location of the edge cloud is determined according to the historical traffic condition information of the target road section.

[0022] In a second aspect, the present application further provides a congestion detection system, the system comprising: a cloud server, a first roadside device and a second roadside device within a target road section;

[0023] The second roadside device is located in the obstruction area, and is used to obtain second road condition information in the obstruction area and send the second road condition information to the first roadside device;

[0024] The first roadside device is located in the non-obstructed area, and is used to obtain first road condition information in the non-obstructed area and second road condition information sent by the second roadside device, and report the first road condition information and the second road condition information to the cloud server;

[0025] The cloud server is used to obtain the congestion status of the target road section according to the first road condition information and the second road condition information.

[0026] In one of the embodiments, the congestion detection system further includes an edge cloud;

[0027] The second roadside device is specifically located in the target obstruction area and is used to obtain second road condition information within the target obstruction area; wherein the target obstruction area is an obstruction area selected from the candidate obstruction areas based on the connection relationship between the candidate roadside device and the edge cloud; the candidate roadside device is located in the candidate obstruction area corresponding to the target road section;

[0028] The edge cloud is used to determine the congestion status of the occlusion areas corresponding to other occlusion areas and report it to the cloud server; wherein the other occlusion areas are the occlusion areas in the candidate occlusion areas except the target occlusion area;

[0029] The cloud server is further used to obtain the congestion condition of the target road section based on the congestion condition of the blocked area, the second road condition information and the first road condition information.

[0030] In a third aspect, the present application further provides a congestion detection device, comprising:

[0031] An acquisition module is configured to acquire second road condition information within the obstructed area and first road condition information within the non-obstructed area reported by a first roadside device within the target road section; the second road condition information is obtained by the first roadside device from a second roadside device located within the obstructed area, and the first roadside device is located in the non-obstructed area;

[0032] The detection module is used to obtain the congestion condition of the target road section according to the second road condition information and the first road condition information.

[0033] In a fourth aspect, the present application further provides a cloud server, the cloud server comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0034] Obtaining first road condition information in a non-obstructed area and second road condition information in a blocked area reported by a first roadside device in a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located in the blocked area, and the first roadside device is located in the non-obstructed area;

[0035] The congestion condition of the target road section is obtained according to the second road condition information and the first road condition information.

[0036] In a fifth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0037] Obtaining first road condition information in a non-obstructed area and second road condition information in a blocked area reported by a first roadside device in a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located in the blocked area, and the first roadside device is located in the non-obstructed area;

[0038] The congestion condition of the target road section is obtained according to the second road condition information and the first road condition information.

[0039] In the above-mentioned congestion detection method, device, system, cloud server, and storage medium, the first roadside device within the target road section can not only upload the first road condition information within the corresponding detection range, but can also communicate with the obstructed second roadside device to obtain the second road condition information within the obstructed area corresponding to the second roadside device; obtaining the corresponding second road condition information through the first roadside device can reduce the loss caused by the obstruction on the transmission of the second road condition information. Subsequently, when the second road condition information is sent through the unobstructed first roadside device, there is no need to consider the impact of the obstruction factor, thereby ensuring data quality. In addition, the use of roadside devices instead of image acquisition devices (such as cameras) reduces the amount of data transmitted between the server and the device compared to traditional technologies, further ensuring the quality of data transmission and improving the accuracy of congestion detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 1 is a flow chart of a congestion detection method according to an embodiment;

[0041] Figure 2 A schematic flow chart of the step of eliminating vehicles of a set type in one embodiment;

[0042] Figure 3 A schematic diagram of a process for determining a target occlusion area in one embodiment;

[0043] Figure 4 A schematic diagram of a process for determining a congestion condition for edge cloud uploads in one embodiment;

[0044] Figure 5 is a schematic diagram of a congestion detection system in one embodiment;

[0045] Figure 6 is a structural block diagram of a congestion detection device in one embodiment;

[0046] Figure 7 This is a diagram of the internal structure of a cloud server in one embodiment. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0048] The congestion detection method provided in the embodiment of the present application can be applied to road congestion detection, especially to congestion detection of elevated bridges. Optionally, the entire set of congestion detection methods can be implemented by multiple roadside devices in conjunction with a cloud server, etc. The cloud server can be implemented as an independent server or a server cluster composed of multiple servers. Optionally, the congestion detection method of this embodiment can be executed by a cloud server. Figure 1 As shown, the congestion detection method specifically includes:

[0049] S101: Acquire first road condition information in a non-blocked area and second road condition information in a blocked area reported by a first roadside device in a target road section.

[0050] In this embodiment, the target road section is any road section that requires congestion detection with the aid of a cloud server. For example, the target road section is L, which includes the bridge section L1 and the underbridge section L2. Optionally, the same segmentation method can be used to divide the bridge section L1 and the underbridge section L2 into multiple detection areas. For example, along the extension direction of the bridge deck, a detection area is formed with the width of the bridge deck as the width, a preset length, and a preset height, and the edges of each detection area are continuous. In this case, the corresponding detection areas of the bridge section L1 are {detection area S1, detection area S2, detection area S3}; the corresponding detection areas of the underbridge section L2 are {detection area S'1, detection area S'2, detection area S'3}.

[0051] Furthermore, a roadside device is installed in each detection area, which can be used to receive vehicle status information transmitted by the on-board devices in the corresponding detection area and determine the road condition information in the detection area based on the vehicle status information. For example, for any roadside device, it can obtain the vehicle status information uploaded by each on-board device passing through the detection area corresponding to the roadside device, and determine the road condition information of the detection area based on the status information of each vehicle in the detection area and the corresponding road environment information. Exemplarily, any on-board device passing through the detection area can forward the vehicle status information to the roadside device via the V2X communication device; wherein, the vehicle status information includes but is not limited to vehicle location, braking, fuel consumption, speed, vehicle type and other information.

[0052] In one possible implementation, the detection range of any roadside device may only include the corresponding detection area (i.e., the detection range is equivalent to the detection area); in another possible implementation, the detection range of any roadside device may be larger than the corresponding detection area (e.g., detection area S1) and at least one adjacent detection area (e.g., detection area S2). In this case, when a vehicle enters the detection area S2, the roadside device can also communicate with the on-board device installed on the vehicle to obtain the vehicle status information (including vehicle location information) uploaded by the on-board device in real time, but does not upload the vehicle status information. Only when the vehicle enters the detection area S1, the roadside device uploads the vehicle status information to the cloud server. In this way, the function of each roadside device only collecting the vehicle status information entering the corresponding detection area is realized.

[0053] In this embodiment, the first and second road condition information represent the status information of each vehicle within the corresponding detection area and the corresponding road environment information, respectively. Specifically, the first road condition information refers to the road condition information within the unobstructed area, while the second road condition information refers to the road condition information within the obstructed area. The second road condition information is obtained by the first roadside device from the second roadside device located within the obstructed area. The obstructed area is the overlapping spatial area of ​​the target road segment, which is the section above and below the bridge.

[0054] It is understood that each roadside device has a corresponding installation location. When a bridge section exists above the installation location, the detection area corresponding to the roadside device is determined to be an obstructed area. Correspondingly, when no bridge section exists above the installation location, the detection area corresponding to the roadside device is determined to be an unobstructed area. Furthermore, for multi-story viaducts, such as three-story viaducts, which are divided into a first bridge section, a second bridge section, and an underbridge section, the obstructed area is determined in the same manner as described above, and so on.

[0055] In this embodiment, in the road section on the bridge and the road section under the bridge, the roadside equipment in the blocked area can be determined as the second roadside equipment, and the roadside equipment in the non-blocked area can be determined as the first roadside equipment. Both the first roadside equipment and the second roadside equipment are equipped with a cellular communication module and communicate with the cloud server through the cellular communication module; and the number of the first roadside equipment and the second roadside equipment is at least one.

[0056] It should be noted that the propagation of mobile network communication radio waves will be affected by obstructions such as man-made buildings, natural terrain and even leaves during the propagation process, and will exhibit randomness and diversity, which will reduce the quality of the radio wave signal received by the receiver; therefore, when there is an obstruction (obstacle) between the cellular communication module and the communication base station, for example, when there is a bridge section above the roadside equipment, the obstruction (bridge section) will affect the reliability of data transmission, that is, affect the data quality.

[0057] Therefore, in order to reduce the impact of obstruction factors on the data transmission quality between roadside devices and cloud servers, in this embodiment, for each first roadside device, since it is not obstructed, the first road condition information collected by the first roadside device is controlled to be sent by itself to the cloud server; and for the second roadside device that is obstructed, a corresponding first roadside device is designated for it (for example, the first roadside device closest to it can be used as the designated first roadside device), and the second road condition information collected by the second roadside device is forwarded to the designated first roadside device through the V2X communication device, and then the first roadside device uploads the second road condition information to the cloud server.

[0058] S102: Obtain a congestion condition of a target road section according to the second road condition information and the first road condition information.

[0059] In this embodiment, the congestion condition can be used to represent the degree of congestion on the target road section. Alternatively, the congestion condition can be represented by a congestion level, such as smooth traffic, light congestion, moderate congestion, or severe congestion. The congestion condition can be determined based on parameters such as vehicle speed, vehicle location, and the average travel speed of vehicles on a preset road section.

[0060] Specifically, the cloud server can generate the on-bridge congestion status of the section on the bridge and the under-bridge congestion status of the section under the bridge based on the first road condition information and the second road condition information; when a user traveling to the target section sends a request, the cloud server determines the recommended path based on the congestion status of the section on the bridge, the travel length of the section on the bridge, the congestion status of the section under the bridge, and the travel length of the section under the bridge, and returns the recommended path to the corresponding user.

[0061] For example, taking the calculation of the congestion condition of a road section on a bridge as an example, when calculating the congestion condition on the bridge, the number of vehicles passing through the road section on the bridge and the corresponding travel time of each vehicle are calculated based on each first road condition information and each second road condition information to calculate the average travel speed of the road section on the bridge; according to the average travel speed and the level classification table, the congestion level corresponding to the average travel speed is determined. Among them, the level classification table stores each average travel speed (speed range) and the corresponding congestion level. Specifically, the average travel speed The calculation process is as follows:

[0062]

[0063] in, is the average travel speed on the bridge section, in kilometers per hour (km / h); L is the length of the bridge section, excluding intersections, in kilometers (km); t i is the time it takes for vehicle i to pass through the bridge section, in hours (h); n is the number of vehicles passing through the bridge section.

[0064] Furthermore, the method for calculating the congestion condition under the bridge is the same as that for calculating the congestion condition on the bridge, and will not be described in detail in this embodiment.

[0065] When calculating the average travel speed of the section on the bridge (the section under the bridge), the section on the bridge can be divided into multiple sub-sections, and the average travel speed of each sub-section can be calculated separately to refine the congestion detection range and provide more accurate analysis results.

[0066] In the above-mentioned congestion detection method, the first roadside device within the target road section can not only upload the first road condition information within the corresponding detection range, but can also communicate with the obstructed second roadside device to obtain the second road condition information within the obstructed area corresponding to the second roadside device; obtaining the corresponding second road condition information through the first roadside device can reduce the loss caused by the obstruction on the transmission of the second road condition information. Then, when the second road condition information is sent through the unobstructed first roadside device, there is no need to consider the impact of the obstruction factor, thereby ensuring data quality (data accuracy). In addition, the use of roadside devices instead of image acquisition devices (such as cameras) reduces the amount of data transmitted between the server and the device compared to traditional technologies, further ensuring the quality of data transmission and improving the accuracy of congestion detection.

[0067] In order to accurately calculate the congestion condition of the target road condition according to the actual driving situation, in one embodiment, Figure 2 As shown, this embodiment provides an optional method for obtaining the congestion status of the target road section based on the second road condition information and the first road condition information, that is, provides a method for refining S102. The specific implementation process may include:

[0068] S201: Delete information of vehicles of a set type from the second road condition information and the first road condition information.

[0069] Among them, set types of vehicles, for example, fire trucks, ambulances, engineering rescue vehicles, sprinkler trucks, street sweepers and other special vehicles.

[0070] Specifically, the cloud server identifies information of vehicles of a set type from the first road condition information, removes the information of the vehicles of the set type, and filters out information that is weakly related to the congestion condition.

[0071] S202: Obtain the congestion status of the target road section according to the second road condition information and the first road condition information after elimination processing.

[0072] Among them, after filtering out the information of the set type of vehicles, the cloud server obtains the congestion status of the target road section based on the second road condition information and the vehicle status information corresponding to other types of vehicles in the first road condition information.

[0073] In this embodiment, information weakly related to the congestion condition is filtered out, the amount of data analysis is reduced, and the detection efficiency is improved.

[0074] In one achievable manner, each obstructed roadside device within the target road section can serve as a second roadside device. In this case, the second road condition information corresponding to the second roadside device can be forwarded through the corresponding first roadside device.

[0075] In order to further improve the data transmission quality, in another feasible method, the roadside devices that meet the screening conditions among the blocked roadside devices in the target section can be used as the second roadside devices. The screening conditions can be the communication quality between the corresponding first roadside device and the cloud server, or whether the second roadside device is matched with other forwarding devices that can further ensure the data transmission quality.

[0076] Optionally, in one embodiment, Figure 3 As shown, the congestion detection method further includes:

[0077] S301 : Select a target occlusion area from candidate occlusion areas based on a connection relationship between candidate roadside equipment and an edge cloud in a congestion detection system.

[0078] Among them, each obscured roadside equipment is a candidate roadside equipment, that is, the candidate roadside equipment is located in the candidate obscuration area corresponding to the target road section. In this case, the roadside equipment corresponding to the target obscuration area is used as the second roadside equipment, and the candidate roadside equipment includes the second roadside equipment.

[0079] Specifically, the cloud server leverages the edge cloud within the congestion detection system to offload computing resources. The edge cloud can be located within the target road section and connected to at least one candidate roadside device. Communication between the edge cloud and the cloud server can be achieved via a communication link made of various materials, such as coaxial cable, twisted pair, optical fiber, or wireless transmission via Wi-Fi or satellite.

[0080] Correspondingly, based on the connection relationship between the candidate roadside device and the edge cloud in the congestion detection system, the target occlusion area is selected from the candidate occlusion area, which may specifically include: based on the connection relationship between the candidate roadside device and the edge cloud in the congestion detection system, selecting a roadside device that is not connected to the edge cloud from the candidate roadside devices as the second roadside device, and using the candidate occlusion area where the second roadside device is located as the target occlusion area; if the candidate roadside device is connected to the edge cloud, then using the detection area corresponding to the candidate roadside device as the other occlusion area.

[0081] S302: Send a data forwarding instruction to the second roadside device in the target obstruction area to instruct the second roadside device to forward the second road condition information to the first roadside device.

[0082] In this embodiment, the data forwarding instruction may include a data forwarding path, that is, a path for the second roadside device located in the target obstruction area to send the collected road condition information to the first roadside device in the non-obstruction area.

[0083] Specifically, the cloud server sends a data forwarding instruction to the second roadside device, and the second roadside device forwards the collected second road condition information to the corresponding first roadside device based on the data forwarding path included in the data forwarding instruction.

[0084] Accordingly, the first roadside device can obtain the second traffic condition information sent by the second roadside device in the target obstruction area and forward it to the cloud server. The cloud server can then obtain the second traffic condition information in the target obstruction area reported by the first roadside device in the target road section.

[0085] Furthermore, in one embodiment, the edge cloud can also analyze the traffic information of the corresponding roadside equipment and forward the analysis results to the cloud server. The cloud server can directly use the congestion detection results to reduce the computing pressure of the cloud server; accordingly, Figure 4 As shown, this embodiment provides an optional method for obtaining the congestion status of the target road section based on the second road condition information and the first road condition information, that is, provides a method for refining S102. The specific implementation process may include:

[0086] S401: Obtain the congestion status of the blocked area reported by the edge cloud corresponding to other blocked areas.

[0087] The other occlusion regions are occlusion regions other than the target occlusion region in the candidate occlusion regions.

[0088] S402 : Obtain the congestion condition of the target road section according to the congestion condition of the blocked area, the second road condition information, and the first road condition information.

[0089] In one implementation, the edge cloud is only used to connect to roadside equipment within other obstruction areas; there is at least one other obstruction area. Specifically, the edge cloud calculates the congestion status of each obstruction area within the other obstruction areas and uploads it to the cloud server. The cloud server then determines the congestion status of the target road section based on the congestion status of each obstruction area, the second road condition information, and the first road condition information.

[0090] In another possible implementation, in addition to connecting to at least one other obstructed area, the edge cloud can also connect to non-obstructed areas adjacent to the other obstructed areas according to its installation location, forming a networking area with the installation location of the edge cloud, and the edge cloud calculates the congestion conditions of other obstructed areas and non-obstructed areas in the networking area. In this case, the first roadside device refers to a roadside device that is in the non-obstructed area and is not connected to the edge cloud. The cloud server obtains the congestion condition of the target road section based on the congestion conditions of the obstructed areas and the non-obstructed areas in the networking area, the second road condition information and the first road condition information.

[0091] In this embodiment, by configuring the edge cloud within the target road section, the computing pressure of the cloud server can be reduced; at the same time, the edge cloud can analyze the congestion conditions of other blocked areas within the target road section, ensuring the accuracy of the congestion analysis of other blocked areas.

[0092] It should be noted that if edge clouds are configured in each candidate occlusion area, a large number of edge clouds are required; in order to make the number and location of edge clouds more reasonable, in this embodiment, the installation location of the edge cloud must be planned first. Only after the location of the edge cloud is determined can it be determined which candidate roadside devices can be networked with the edge cloud; correspondingly, when determining the connection relationship between the candidate roadside device and the edge cloud, the specific implementation process may include: determining the connection relationship between the candidate roadside device and the edge cloud in the congestion detection system based on the installation location of the edge cloud and the installation location of the candidate roadside device.

[0093] The installation location of the edge cloud is determined based on the historical traffic information of the target road section. The historical traffic information of the target road condition may include the historical traffic information of multiple detection areas. The historical traffic information of each detection area not only includes the vehicle status information within the detection area, but also includes road environment information. For example, the road environment information may include road types, road intersections (intersections), etc. Specifically, a detection area with a large amount of data collected from the historical traffic information, such as a road intersection area, can be used as the installation location of the edge cloud.

[0094] Specifically, after obtaining the installation location of the edge cloud and the installation location of each candidate roadside device, the cloud server can use the transmission distance or coverage range as a screening condition to determine the candidate roadside devices that can be networked with the edge cloud. The cloud server then generates a connection task and sends the connection task to the edge cloud and the candidate roadside devices associated with the edge cloud, so that the edge cloud can communicate with the corresponding candidate roadside devices, and then determine the connection relationship between the corresponding candidate roadside devices and the edge cloud.

[0095] In this embodiment, the installation location of the edge cloud is first determined, and then the candidate roadside devices that can be networked with the edge cloud are determined based on the installation location of the edge cloud and the installation location of the candidate roadside devices, so that the edge cloud can communicate with the corresponding candidate roadside devices, thereby achieving the purpose of determining the connection relationship between the candidate roadside devices and the edge cloud in the congestion detection system.

[0096] For example, based on the above embodiment, Figure 5 As shown, this embodiment provides a congestion detection system 1 corresponding to the congestion detection method, and the congestion detection system 1 includes: a cloud server 10, a first roadside device 20 and a second roadside device 30 in a target road section;

[0097] The second roadside device 30 is located in the obstruction area, and is used to obtain second road condition information in the obstruction area and send the second road condition information to the first roadside device 20;

[0098] The first roadside device 20 is located in the non-blocked area and is used to obtain first road condition information in the non-blocked area and second road condition information sent by the second roadside device 30, and report the first road condition information and the second road condition information to the cloud server 10;

[0099] The cloud server 10 is configured to obtain a congestion condition of a target road section based on the first road condition information and the second road condition information.

[0100] In one embodiment, the congestion detection system further includes an edge cloud 40;

[0101] The second roadside device 30 is specifically located in the target obstruction area and is used to obtain second road condition information within the target obstruction area; wherein the target obstruction area is an obstruction area selected from the candidate obstruction areas based on the connection relationship between the candidate roadside device and the edge cloud 40; the candidate roadside device is located in the candidate obstruction area corresponding to the target road section;

[0102] The edge cloud 40 is used to determine the congestion status of the occlusion areas corresponding to other occlusion areas and report it to the cloud server 10; wherein the other occlusion areas are occlusion areas in the candidate occlusion areas except the target occlusion area;

[0103] The cloud server 10 is further configured to obtain the congestion condition of the target road section based on the congestion condition of the blocked area, the second road condition information, and the first road condition information.

[0104] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0105] Based on the same inventive concept, embodiments of the present application also provide a congestion detection device for implementing the aforementioned congestion detection method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more of the following congestion detection device embodiments can be found in the above-described limitations of the congestion detection method and will not be further elaborated here.

[0106] In one embodiment, Figure 6 As shown, a congestion detection device 100 is provided, comprising: an acquisition module and a detection module, wherein:

[0107] An acquisition module 110 is configured to acquire second road condition information within the obstructed area and first road condition information within the unobstructed area reported by a first roadside device within the target road section; the second road condition information is obtained by the first roadside device from a second roadside device located within the obstructed area, and the first roadside device is located within the unobstructed area;

[0108] The detection module 120 is configured to obtain a congestion condition of a target road section according to the second road condition information and the first road condition information.

[0109] In one embodiment, the congestion detection device further includes a screening module configured to select a target obstruction area from candidate obstruction areas based on a connection relationship between a candidate roadside device and an edge cloud in the congestion detection system; wherein the candidate roadside device is located within the candidate obstruction area corresponding to the target road segment;

[0110] A data forwarding instruction is sent to the second roadside device in the target obstruction area to instruct the second roadside device to forward the second road condition information to the first roadside device.

[0111] In one embodiment, the screening module includes:

[0112] a first matching submodule, configured to select, from the candidate roadside devices, a roadside device that is not connected to the edge cloud as a second roadside device based on a connection relationship between the candidate roadside devices and the edge cloud in the congestion detection system;

[0113] The second matching submodule uses the candidate occlusion area where the second roadside device is located as the target occlusion area.

[0114] In one embodiment, the detection module 120 includes:

[0115] The acquisition submodule is used to obtain the congestion status of the occlusion area reported by the edge cloud corresponding to other occlusion areas; wherein, other occlusion areas are occlusion areas in the candidate occlusion areas except the target occlusion area;

[0116] The detection submodule is used to obtain the congestion condition of the target road section according to the congestion condition of the blocked area, the second road condition information and the first road condition information.

[0117] In one embodiment, the congestion detection device further includes a partitioning module, which is configured to:

[0118] According to the installation location of the edge cloud and the installation location of the candidate roadside equipment, the connection relationship between the candidate roadside equipment and the edge cloud in the congestion detection system is determined; wherein the installation location of the edge cloud is determined according to the historical traffic condition information of the target road section.

[0119] In one embodiment, the detection module 120 is further configured to: remove information of a set type of vehicle from the second road condition information and the first road condition information;

[0120] The congestion condition of the target road section is obtained according to the second road condition information and the first road condition information after the elimination process.

[0121] Each module in the congestion detection device described above may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in hardware form, or may be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0122] In one embodiment, a computer device is provided. The computer device may be a cloud server, and its internal structure diagram may be as follows: Figure 7As shown. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data for a congestion detection method. The network interface of the computer device is used to communicate with an external terminal via a network connection. When executed by the processor, the computer program implements a congestion detection method.

[0123] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0124] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0125] Obtaining first road condition information in a non-obstructed area and second road condition information in a blocked area reported by a first roadside device in a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located in the blocked area, and the first roadside device is located in the non-obstructed area;

[0126] The congestion condition of the target road section is obtained according to the second road condition information and the first road condition information.

[0127] In one embodiment, when the processor executes the computer program, it also implements the following steps: selecting a target occlusion area from the candidate occlusion areas based on the connection relationship between the candidate roadside device and the edge cloud in the congestion detection system; wherein the candidate roadside device is located in the candidate occlusion area corresponding to the target road section; and sending a data forwarding instruction to the second roadside device in the target occlusion area to instruct the second roadside device to forward the second road condition information to the first roadside device.

[0128] In one embodiment, when the processor executes the computer program to select the target occlusion area from the candidate occlusion areas based on the connection relationship between the candidate roadside equipment and the edge cloud in the congestion detection system, the following steps are specifically implemented: based on the connection relationship between the candidate roadside equipment and the edge cloud in the congestion detection system, a roadside equipment that is not connected to the edge cloud is selected from the candidate roadside equipment as the second roadside equipment; and the candidate occlusion area where the second roadside equipment is located is selected as the target occlusion area.

[0129] In one embodiment, when the processor executes a computer program to obtain the logic of the congestion condition of the target road section based on the second road condition information and the first road condition information, the following steps are specifically implemented: obtaining the congestion conditions of the occlusion areas reported by the edge cloud corresponding to other occlusion areas; wherein the other occlusion areas are occlusion areas other than the target occlusion area in the candidate occlusion areas; and obtaining the congestion condition of the target road section based on the congestion conditions of the occlusion areas, the second road condition information and the first road condition information.

[0130] In one embodiment, when the processor executes the computer program, it also implements the following steps: determining the connection relationship between the candidate roadside equipment and the edge cloud in the congestion detection system based on the installation location of the edge cloud and the installation location of the candidate roadside equipment; wherein the installation location of the edge cloud is determined based on the historical road condition information of the target road section.

[0131] In one embodiment, when the processor executes a computer program to obtain the logic of the congestion condition of the target road section based on the second road condition information and the first road condition information, the following steps are specifically implemented: eliminating information of a set type of vehicle from the second road condition information and the first road condition information; and obtaining the congestion condition of the target road section based on the second road condition information and the first road condition information after the elimination process.

[0132] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0133] Obtaining first road condition information in a non-obstructed area and second road condition information in a blocked area reported by a first roadside device in a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located in the blocked area, and the first roadside device is located in the non-obstructed area;

[0134] The congestion condition of the target road section is obtained according to the second road condition information and the first road condition information.

[0135] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the connection relationship between the candidate roadside device and the edge cloud in the congestion detection system, a target occlusion area is selected from the candidate occlusion area; wherein the candidate roadside device is located in the candidate occlusion area corresponding to the target road section; and a data forwarding instruction is sent to the second roadside device in the target occlusion area to instruct the second roadside device to forward the second road condition information to the first roadside device.

[0136] In one embodiment, when the logic of selecting a target occlusion area from candidate occlusion areas based on the connection relationship between the candidate roadside devices and the edge cloud in the congestion detection system is executed by a processor, the following steps are specifically implemented: based on the connection relationship between the candidate roadside devices and the edge cloud in the congestion detection system, a roadside device that is not connected to the edge cloud is selected from the candidate roadside devices as the second roadside device; and the candidate occlusion area where the second roadside device is located is used as the target occlusion area.

[0137] In one embodiment, when the logic of a computer program for obtaining the congestion condition of a target road section based on the second road condition information and the first road condition information is executed by a processor, the following steps are specifically implemented: obtaining the congestion condition of the occlusion area reported by the edge cloud corresponding to other occlusion areas; wherein the other occlusion areas are occlusion areas other than the target occlusion area in the candidate occlusion areas; and obtaining the congestion condition of the target road section based on the congestion condition of the occlusion area, the second road condition information and the first road condition information.

[0138] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: based on the installation location of the edge cloud and the installation location of the candidate roadside device, the connection relationship between the candidate roadside device and the edge cloud in the congestion detection system is determined; wherein the installation location of the edge cloud is determined based on the historical road condition information of the target road section.

[0139] In one embodiment, when the logic of a computer program for obtaining the congestion condition of a target road section based on the second road condition information and the first road condition information is executed by a processor, the following steps are specifically implemented: information of a set type of vehicle is eliminated from the second road condition information and the first road condition information; and the congestion condition of the target road section is obtained based on the second road condition information and the first road condition information after the elimination process.

[0140] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0141] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0142] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0143] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A congestion detection method, characterized in that: The method comprises: Selecting, from the candidate roadside devices, a roadside device that is not connected to the edge cloud as a second roadside device based on a connection relationship between the candidate roadside devices and the edge cloud in the congestion detection system; wherein the candidate roadside device is located within a candidate obstruction area corresponding to the target road segment; using the candidate obstruction area where the second roadside device is located as the target obstruction area; Obtaining first road condition information within a non-obstructed area and second road condition information within a target obstructed area reported by a first roadside device within a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located in the non-obstructed area; Obtaining the congestion status of the occlusion areas reported by the edge cloud corresponding to other occlusion areas; wherein the other occlusion areas are occlusion areas other than the target occlusion area in the candidate occlusion areas; The congestion condition of the target road section is generated according to the congestion condition of the blocked area, the second road condition information, and the first road condition information.

2. The method according to claim 1, characterized in that The method further comprises: A data forwarding instruction is sent to a second roadside device within the target obstruction area to instruct the second roadside device to forward the second road condition information to the first roadside device.

3. The method according to claim 2, characterized in that The method further comprises: According to the installation location of the edge cloud and the installation location of the candidate roadside device, the connection relationship between the candidate roadside device and the edge cloud in the congestion detection system is determined; wherein the installation location of the edge cloud is determined according to the historical traffic condition information of the target road section.

4. The method according to claim 1, wherein The method further comprises: Eliminate information of vehicles of a set type from the second road condition information and the first road condition information; The congestion condition of the target road section is detected according to the second road condition information and the first road condition information after the elimination process.

5. A congestion detection system, characterized in that: include: An edge cloud, a cloud server, a first roadside device, and a second roadside device in a target road section; The second roadside device is located in a target obstruction area and is used to obtain second road condition information within the target obstruction area and send the second road condition information to the first roadside device; the target obstruction area is an obstruction area selected from the candidate obstruction areas based on the connection relationship between the candidate roadside devices and the edge cloud; The candidate roadside equipment is located in the candidate obstruction area corresponding to the target road section; The first roadside device is located in a non-obstructed area and is configured to obtain first road condition information in the non-obstructed area and second road condition information sent by the second roadside device, and report the first road condition information and the second road condition information to the cloud server; The edge cloud is used to determine the congestion status of the occlusion areas corresponding to other occlusion areas and report it to the cloud server; wherein the other occlusion areas are occlusion areas in the candidate occlusion areas except the target occlusion area; The cloud server is used to obtain the congestion condition of the target road section according to the congestion condition of the blocked area, the first road condition information and the second road condition information.

6. A congestion detection device, characterized in that: The device comprises: a first matching submodule, configured to select, from the candidate roadside devices, a roadside device that is not connected to the edge cloud as a second roadside device based on a connection relationship between the candidate roadside device and the edge cloud in the congestion detection system; wherein the candidate roadside device is located within a candidate occlusion area corresponding to the target road segment; A second matching submodule is configured to use the candidate occlusion area where the second roadside device is located as a target occlusion area; an acquisition module, configured to acquire second road condition information within a blocked area and first road condition information within a non-blocked area reported by a first roadside device within a target road section; the second road condition information is obtained by the first roadside device from a second roadside device located within the blocked area, and the first roadside device is located within the non-blocked area; The acquisition submodule is used to obtain the congestion status of the occlusion area reported by the edge cloud corresponding to other occlusion areas; wherein, other occlusion areas are occlusion areas in the candidate occlusion areas except the target occlusion area; The detection submodule is used to obtain the congestion condition of the target road section according to the congestion condition of the blocked area, the second road condition information and the first road condition information.

7. A cloud server comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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