A cloud platform-based vehicle flow monitoring method and system

Abstract

The present disclosure provides a kind of cloud platform-based vehicle flow monitoring method and system, it is related to flow monitoring technical field, the method comprises: obtaining the preset destination of target vehicle;Collect the real-time position information of target vehicle;According to preset destination and real-time position information, travel path planning is carried out, obtains preset planning path, and preset planning path includes multiple paths;Extract the first path of preset planning path, carry out path decomposition to first path, obtain the decomposition section set;According to the first decomposition section set, extract first decomposition section, and carry out vehicle flow collection to first decomposition section, obtain first traffic data;According to first traffic data and preset planning path, path optimization is carried out, obtains optimal travel path, and is sent to target vehicle, by the present application, the accuracy of vehicle flow monitoring can be improved, the effect of improving vehicle path planning efficiency is realized.

Description

Technical Field

[0001] This disclosure relates to the field of traffic flow monitoring technology, specifically to a vehicle traffic flow monitoring method and system based on a cloud platform. Background Technology

[0002] Route planning is a crucial step in vehicle operation, primarily involving the automatic planning of a path from the starting point to the destination within a given area. Existing route planning methods rely on manually counting vehicles on a road segment to determine congestion levels, which can sometimes fail to accurately assess the degree of congestion.

[0003] In summary, existing technologies suffer from low efficiency in vehicle route planning due to the low accuracy of vehicle traffic monitoring. Summary of the Invention

[0004] This disclosure provides a cloud-based vehicle traffic monitoring method and system to solve the technical problem of low vehicle route planning efficiency due to low accuracy of vehicle traffic monitoring in the prior art.

[0005] According to a first aspect of this disclosure, a cloud-based vehicle traffic monitoring method is provided, comprising: acquiring a preset destination of a target vehicle; collecting real-time location information of the target vehicle; performing driving route planning based on the preset destination and the real-time location information to obtain a preset planned route, the preset planned route including multiple routes; extracting a first route of the preset planned route, decomposing the first route to obtain a set of decomposed road segments; extracting a first decomposed road segment based on the set of decomposed road segments, and collecting vehicle traffic data on the first decomposed road segment to obtain first traffic traffic data; performing path optimization based on the first traffic traffic data and the preset planned route to obtain an optimal driving route, and sending it to the target vehicle.

[0006] According to a second aspect of this disclosure, a cloud-based vehicle traffic monitoring system is provided, comprising: a destination acquisition module for acquiring a preset destination of a target vehicle; a location acquisition module for collecting real-time location information of the target vehicle; a route planning acquisition module for planning a driving route based on the preset destination and the real-time location information to obtain a preset planned route, the preset planned route including multiple paths; a road segment set acquisition module for extracting a first path of the preset planned route, decomposing the first path to obtain a set of decomposed road segments; a traffic flow data acquisition module for extracting a first decomposed road segment based on the set of decomposed road segments, collecting vehicle flow data on the first decomposed road segment to obtain first traffic flow data; and a driving route acquisition module for optimizing a route based on the first traffic flow data and the preset planned route to obtain an optimal driving route, and sending it to the target vehicle.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: According to this disclosure, by obtaining a preset destination of a target vehicle; collecting real-time location information of the target vehicle; performing route planning based on the preset destination and the real-time location information to obtain a preset planned route, the preset planned route including multiple routes; extracting a first route from the preset planned route; decomposing the first route to obtain a set of decomposed road segments; extracting a first decomposed road segment from the set of decomposed road segments and collecting vehicle traffic flow data from the first decomposed road segment to obtain first traffic flow data; and performing route optimization based on the first traffic flow data and the preset planned route to obtain the optimal driving route, and sending it to the target vehicle, the accuracy of vehicle traffic flow monitoring can be improved, achieving the technical effect of improving vehicle route planning efficiency.

[0008] It should be understood that the description in this section is not intended to highlight key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0010] Figure 1A schematic flowchart illustrating a cloud-based vehicle traffic monitoring method provided in this embodiment of the present disclosure;

[0011] Figure 2 This is a schematic diagram of the process for obtaining a set of decomposed road segments in a cloud-based vehicle traffic monitoring method according to an embodiment of this disclosure;

[0012] Figure 3 This is a schematic diagram of the process for obtaining first traffic flow data in a cloud-based vehicle traffic flow monitoring method according to an embodiment of this disclosure;

[0013] Figure 4 This is a schematic diagram of the structure of a cloud-based vehicle traffic monitoring system provided in an embodiment of this disclosure.

[0014] Explanation of reference numerals in the attached diagram: Destination acquisition module 11, Location acquisition module 12, Planned route acquisition module 13, Road segment set acquisition module 14, Traffic flow data acquisition module 15, Driving route acquisition module 16. Detailed Implementation

[0015] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0016] To address the technical problem of low vehicle route planning efficiency due to low accuracy of vehicle traffic monitoring in existing technologies, the inventors of this disclosure, through creative work, have obtained a vehicle traffic monitoring method and system based on a cloud platform:

[0017] Example 1

[0018] Figure 1 A vehicle traffic monitoring method based on a cloud platform is provided for embodiments of this application. The method includes:

[0019] Step S100: Obtain the preset destination of the target vehicle;

[0020] Specifically, the target vehicle is the vehicle to be monitored for traffic flow. Further, the preset destination of the target vehicle is obtained. This preset destination is a randomly set final destination to which the target vehicle will arrive. Further, the method for obtaining the preset destination of the target vehicle can be a preset target parking area. Based on the preset target parking area, parking spaces are randomly selected as target parking spaces, thereby obtaining the preset destination of the target vehicle.

[0021] Step S200: Collect the real-time location information of the target vehicle;

[0022] Specifically, a map of a preset target parking area is obtained. This map shows the locations of all parking spaces within the preset target parking area. For example, the preset target parking area map may include a mobile navigation map, a display board map of the preset target parking area, etc. Further, a vehicle locator is obtained. This vehicle locator is a device used to locate the target vehicle and determine its real-time location information within the preset target parking area. For example, the vehicle locator may include mobile navigation, vehicle GPS, etc.

[0023] Furthermore, based on the vehicle locator and the preset target parking area map, the location of the target vehicle is determined, and the real-time location information of the target vehicle and the real-time location relationship between the target vehicle and the preset destination within the preset target parking area are determined.

[0024] Step S300: Based on the preset destination and the real-time location information, a driving route is planned to obtain a preset planned route, which includes multiple routes;

[0025] Specifically, based on a preset destination and real-time location information, a driving route for the target vehicle is planned. The real-time location of the target vehicle is used as the starting point, and the preset destination within a preset target parking area is used as the ending point. Further, based on a map of the preset target parking area, a driving route is planned between the starting point and the ending point to obtain a preset planned route. This preset planned route includes the distance from the target vehicle's real-time location to the preset destination, as well as other route information. The distance and route information are correlated.

[0026] Furthermore, the preset planned path includes multiple paths. The path information is traversed to obtain the corresponding distances associated with each path. Specifically, a preset range for the distance values ​​is established. All distances are extracted and compared sequentially with the preset range. If a distance does not meet the preset range, it is added to the preset planned path. If a distance meets the preset range, it is removed from the preset planned path.

[0027] Step S400: Extract the first path of the preset planned path, decompose the first path, and obtain a set of decomposed road segments;

[0028] Specifically, based on a preset planned path, a path is randomly extracted as the first path. This first path is then segmented to obtain multiple segmented road segments. A preset road corner threshold is used; based on the path information, it is sequentially determined whether the road corners of the multiple segmented road segments meet the threshold. If not, the segment is segmented using its road corner as the cutting point to obtain multiple secondary segmented road segments. Further, the secondary segmented road segments are further evaluated and segmented to obtain multiple tertiary segmented road segments. This process ultimately yields a set of decomposed road segments.

[0029] Step S500: Extract the first decomposed road segment based on the decomposed road segment set, and collect vehicle flow data on the first decomposed road segment to obtain the first traffic flow data;

[0030] Specifically, based on the set of decomposed road segments, multiple first-level decomposed road segments are extracted, and vehicle flow data is collected for these segments. During the data collection process, multiple minimum traffic flow values ​​are extracted from the first-level decomposed road segments to determine the congestion level of each segment. Vehicle flow data collection includes vehicle quantity and vehicle speed data. Further, the vehicle flow data collection results are extracted to obtain the first-level vehicle flow data.

[0031] Step S600: Optimize the route based on the first traffic flow data and the preset planned route to obtain the optimal driving route, and send it to the target vehicle.

[0032] Specifically, based on preset planned routes, multiple first traffic flow data points for these routes are extracted. These first traffic flow data points are compared, and the first traffic flow data for congestion-free road segments is extracted. The corresponding routes for these congestion-free road segments are then obtained as the route optimization results. Furthermore, the optimal driving route from the route optimization results is extracted and sent to the target vehicle.

[0033] This embodiment can improve the accuracy of vehicle traffic monitoring and improve the efficiency of vehicle route planning.

[0034] like Figure 2 As shown, step S400 in the method provided in this application embodiment includes:

[0035] S410: Obtain the preset road segment length threshold;

[0036] S420: Based on the road segment length threshold, the first path is cut once to obtain the first cut road segment;

[0037] S430: Collect road curvature information for the first cut road segment to obtain first road curvature information;

[0038] S440: Obtain the set of decomposed road segments based on the first road curvature information.

[0039] Specifically, a preset road segment length threshold is obtained. This threshold can be preset based on unit length. For example, 100 meters or 1000 meters could be used as the preset road segment length threshold.

[0040] Furthermore, based on a road segment length threshold, the first path is divided once to obtain multiple first-cut road segments. Further, road curvature information is collected from the first-cut road segments to obtain first road curvature information. Here, road curvature is the reciprocal of the curve radius, used to describe the degree of road curvature. Further, the method for collecting road curvature information from multiple first-cut road segments is to obtain point cloud data and other information of the first-cut road segments based on a detector or scanner.

[0041] Furthermore, a preset curvature threshold is set, and the curvature information of the first road is compared with the preset curvature threshold to cut the first road segment and obtain a set of decomposed road segments.

[0042] Among them, the first path of the preset planned path is extracted, the first path is decomposed, and the set of decomposed road segments is obtained, which helps to obtain the data information of the decomposed road segments in turn.

[0043] Step S440 in the method provided in this application embodiment includes:

[0044] S441: If the curvature information of the first road does not meet the preset curvature threshold, perform corner position positioning on the first cut road segment and obtain the corner positioning result;

[0045] S442: Using the corner positioning result as the cutting point, the first cutting segment is cut a second time to obtain the first decomposed segment;

[0046] S443: Based on the corner positioning result and the preset road segment length threshold, the first path is further decomposed to obtain multiple first decomposed road segments;

[0047] S444: The set of decomposed road segments is constructed using the plurality of first decomposed road segments.

[0048] Specifically, a curvature threshold is preset based on the actual road conditions. For example, since the larger the turning angle, the greater the curvature, the curvature threshold can be preset to 0 to 1. Furthermore, if the curvature value in the first road curvature information does not meet the preset curvature threshold, the turning position of the first cut road segment is located to obtain the turning position result.

[0049] Furthermore, using the corner positioning result as the cutting point, the first segment is further segmented to obtain the first decomposed segment. This can be achieved by using point cloud data technology to segment the first segment and obtain point cloud data information for the first decomposed segment. Further, based on the corner positioning result and a preset segment length threshold, it is determined whether the first decomposed segment meets a preset curvature threshold. If so, the first path is further decomposed to obtain multiple first decomposed segments.

[0050] Among them, obtaining the set of decomposed road segments based on the curvature information of the first road helps to improve the accuracy of the data information obtained from the decomposed road segments.

[0051] like Figure 3 As shown, step S500 in the method provided in this application embodiment includes:

[0052] S510: Determine whether the first decomposed road segment contains traffic lights. If it does, set the first collection period according to the traffic light switching cycle.

[0053] S520: During the first collection period, continuously collect vehicle traffic flow data for the first decomposed road segment and obtain continuous vehicle traffic flow data collection results.

[0054] S530: Obtain the minimum traffic flow based on the continuous traffic flow collection results;

[0055] S540: Determine the first segment congestion level information of the first decomposed road segment based on the minimum traffic flow value, and use the first segment congestion level information as the first traffic flow data.

[0056] Specifically, road navigation information is obtained based on the target parking area map. This road navigation information includes traffic light information. Further, it is determined whether the first decomposed road segment contains traffic lights. If so, a first data collection period is set based on the traffic light switching cycle. The traffic light switching cycle is the time interval between a green light turning red and back to green.

[0057] Furthermore, road monitoring information is obtained based on the target parking area map. Based on the road monitoring information, continuous vehicle flow data is collected for the first decomposed road segment within the first collection period, that is, the number of vehicles passing through the road segment is collected, and continuous vehicle flow data collection results for multiple collection periods are obtained.

[0058] Furthermore, based on the continuous traffic flow data collection results, the minimum value of the traffic flow is obtained. Further, based on the minimum traffic flow value, the congestion level information of the first segment of the first decomposed road segment is determined, and this first segment congestion level information is used as the first traffic flow data.

[0059] Congestion occurring at red lights can be considered false congestion. Therefore, the influence of congestion occurring when the traffic light turns red should be eliminated, and the true level of congestion should be determined based on the decrease in traffic flow.

[0060] Step S500 in the method provided in this application embodiment further includes:

[0061] S550: If the first decomposed road segment does not contain the traffic light, take the current time as the first collection time, collect real-time vehicle flow in the first decomposed road segment, and obtain the real-time flow collection result.

[0062] S560: Extract the number of vehicles and vehicle speed based on the real-time traffic collection results;

[0063] S570: Generate congestion information for the first road segment as first traffic flow data based on the number of vehicles and vehicle speed.

[0064] Specifically, if the first decomposed road segment does not include traffic lights (i.e., excluding cases of false congestion due to red traffic lights), then the current time is used as the first data collection time to collect real-time vehicle flow data for the first decomposed road segment, obtaining the real-time flow data results. Further, a speed data collector is obtained. Based on the speed data collector and the real-time flow data results, the number of vehicles and their speeds are extracted. Further, based on the number of vehicles and their speeds, congestion level information for the first road segment is generated. This congestion level information for the first road segment is extracted as the first traffic flow data.

[0065] Among them, generating congestion information for the first road segment based on the number of vehicles and vehicle speed as the first traffic flow data helps to improve the accuracy of traffic flow monitoring.

[0066] Step S600 in the method provided in this application embodiment includes:

[0067] S610: Based on the preset planned path and the first traffic flow data, obtain multiple traffic flow data sets corresponding to the multiple paths;

[0068] S620: Based on the multiple traffic flow data sets, extract the first traffic flow data set for the first path;

[0069] S630: Calculate the average value of multiple first traffic flow data in the first traffic flow data set to obtain the congestion level of the first path;

[0070] S640: If the congestion level of the first path is less than or equal to the preset path congestion level, add the first path to the initial optimal path set;

[0071] S650: Determine the optimal driving route based on the initial optimal route set.

[0072] Specifically, based on the preset planned routes and the initial traffic flow data, the association between multiple routes and corresponding sets of traffic flow data is obtained, and multiple sets of traffic flow data corresponding to multiple routes are acquired. These multiple sets of traffic flow data are then integrated to obtain a complete set of traffic flow data.

[0073] Furthermore, based on multiple traffic flow data sets, a pre-defined planned route is randomly selected as the first route. The first traffic flow data set for the first route is extracted, and the average of multiple first traffic flow data points within this set is calculated to obtain the congestion level of the first route. Further, based on historical traffic flow data of the pre-defined planned route, the congestion level of the pre-defined route is determined. The pre-defined route congestion level is defined as a situation where vehicles are forced to travel at extremely low speeds or stop due to excessive vehicle density, traffic accidents, construction work, traffic violations, or natural disasters, resulting in significant obstruction of subsequent vehicle traffic.

[0074] Furthermore, if the congestion level of the first path is less than or equal to the preset congestion level, then the first path is an uncongested path and is added to the initial optimal path set. If the congestion level of the first path is greater than the preset congestion level, then the first path is a congested path. Using the current segment as the center and a preset radius threshold, randomly selected segments within that radius threshold are used as the first path. The congestion level of the first path is again compared to the preset congestion level. If the congestion level of the first path is less than or equal to the preset congestion level, the first path is added to the initial optimal path set. Further, based on the initial optimal path set, multiple optimal paths are extracted. The path lengths of these multiple optimal paths are compared, and the optimal path with the shortest path length is selected as the optimal driving path.

[0075] Among them, the optimal driving route is obtained by optimizing the route based on the first traffic flow data and the preset planned route, which helps to improve the accuracy of traffic flow monitoring and achieve the effect of improving the efficiency of vehicle route planning.

[0076] Step S650 in the method provided in this application embodiment includes:

[0077] S651: Extract the first initial optimal path based on the initial optimal path set;

[0078] S652: Obtain the first path length of the first initial optimal path;

[0079] S653: Compare the lengths of the first path and obtain the initial optimal path corresponding to the minimum path length as the optimal driving path.

[0080] Specifically, based on the initial optimal path set, multiple first initial optimal paths are extracted. These first initial optimal paths have no congested sections. Further, multiple first path lengths are obtained from these first initial optimal paths. These first path lengths are compared, and the first initial optimal path with the shortest path length is selected as the optimal driving path.

[0081] Among them, the optimal driving route is determined based on the initial optimal path set, thereby improving the efficiency of vehicle route planning.

[0082] Example 2

[0083] Based on the same inventive concept as the cloud-based vehicle traffic monitoring method in the foregoing embodiments, such as Figure 4 As shown, this application also provides a cloud-based vehicle traffic monitoring system, the system comprising:

[0084] Destination acquisition module 11, the destination acquisition module is used to acquire the preset destination of the target vehicle;

[0085] Location acquisition module 12, the location acquisition module is used to collect the real-time location information of the target vehicle;

[0086] The route planning module 13 is used to plan a driving route based on the preset destination and the real-time location information to obtain a preset planned route, which includes multiple routes.

[0087] The road segment set acquisition module 14 is used to extract the first path of the preset planned path, decompose the first path, and obtain the decomposed road segment set.

[0088] The traffic flow data acquisition module 15 is used to extract the first decomposed road segment according to the decomposed road segment set, and collect vehicle flow data on the first decomposed road segment to obtain the first traffic flow data.

[0089] The driving route acquisition module 16 is used to perform route optimization based on the first traffic flow data and the preset planned route, obtain the optimal driving route, and send it to the target vehicle.

[0090] Furthermore, the system also includes:

[0091] A road segment length threshold acquisition module, which is used to acquire a preset road segment length threshold;

[0092] The first cut segment acquisition module is used to cut the first path once according to the segment length threshold to obtain the first cut segment;

[0093] A curvature information acquisition module is used to collect road curvature information of the first cut road segment and obtain first road curvature information.

[0094] A decomposed road segment set acquisition module is used to acquire a decomposed road segment set based on the first road curvature information.

[0095] Furthermore, the system also includes:

[0096] A corner positioning result acquisition module is used to locate the corner position of the first cut road segment and acquire the corner positioning result if the first road curvature information does not meet the preset curvature threshold.

[0097] The first decomposed road segment acquisition module is used to perform secondary cutting on the first cut road segment using the corner positioning result as the cutting point to obtain the first decomposed road segment.

[0098] A multiple decomposed road segment acquisition module is used to further decompose the first path according to the corner positioning result and the preset road segment length threshold to obtain multiple first decomposed road segments.

[0099] A decomposed road segment set assembly module is used to assemble the decomposed road segment set using the plurality of first decomposed road segments.

[0100] Furthermore, the system also includes:

[0101] The first acquisition cycle acquisition module is used to determine whether the first decomposed road segment contains traffic lights. If it does, the first acquisition cycle is set according to the traffic light switching cycle.

[0102] The data acquisition result acquisition module is used to continuously collect vehicle traffic flow data for the first decomposed road segment within the first data acquisition period and obtain continuous vehicle traffic flow data acquisition results.

[0103] A minimum traffic flow acquisition module is used to acquire the minimum traffic flow based on the continuous traffic flow acquisition results.

[0104] The congestion level information acquisition module is used to determine the first segment congestion level information of the first decomposed road segment based on the minimum traffic flow value, and use the first segment congestion level information as the first traffic flow data.

[0105] Furthermore, the system also includes:

[0106] The traffic flow acquisition result acquisition module is used to collect real-time vehicle traffic flow in the first decomposed road segment if the traffic light is not included in the first decomposed road segment, taking the current time as the first acquisition time, and to obtain real-time traffic flow acquisition results.

[0107] A vehicle data acquisition module is used to extract the number of vehicles and the vehicle speed based on the real-time traffic collection results.

[0108] The first traffic flow data acquisition module is used to generate congestion information of the first road segment as the first traffic flow data based on the number of vehicles and vehicle speed.

[0109] Furthermore, the system also includes:

[0110] A data set acquisition module is used to acquire multiple traffic flow data sets corresponding to the multiple paths based on the preset planned path and the first traffic flow data.

[0111] The first traffic flow data set acquisition module is used to extract the first traffic flow data set of the first path based on the multiple traffic flow data sets.

[0112] The first path congestion level acquisition module is used to calculate the average of multiple first traffic flow data in the first traffic flow data set to obtain the first path congestion level.

[0113] An optimal path set acquisition module is used to add the first path to an initial optimal path set if the congestion level of the first path is less than or equal to the congestion level of a preset path.

[0114] An optimal driving route acquisition module is used to determine the optimal driving route based on the initial optimal route set.

[0115] Furthermore, the system also includes:

[0116] The first initial optimal path acquisition module is used to extract the first initial optimal path based on the set of initial optimal paths.

[0117] The first path length acquisition module is used to obtain the first path length of the first initial optimal path.

[0118] An optimal driving route update module is used to compare the length of the first path and obtain the initial optimal path corresponding to the minimum path length as the optimal driving route.

[0119] The specific example of the cloud-based vehicle traffic monitoring method in Embodiment 1 described above is also applicable to the cloud-based vehicle traffic monitoring system of this embodiment. Through the foregoing detailed description of the cloud-based vehicle traffic monitoring method, those skilled in the art can clearly understand the cloud-based vehicle traffic monitoring system of this embodiment; therefore, for the sake of brevity, it will not be described in detail here. As for the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant details can be found in the method section.

[0120] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this disclosure can be achieved, and this is not limited herein.

[0121] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A vehicle traffic flow monitoring method based on a cloud platform, characterized in that, The method includes: Obtain the target vehicle's preset destination; Collect the real-time location information of the target vehicle; Based on the preset destination and the real-time location information, a driving route is planned to obtain a preset planned route, which includes multiple routes; Extract the first path of the preset planned path, decompose the first path, and obtain a set of decomposed road segments; The first decomposed road segment is extracted from the decomposed road segment set, and vehicle flow is collected on the first decomposed road segment to obtain the first traffic flow data. Based on the first traffic flow data and the preset planned route, the optimal driving route is obtained and sent to the target vehicle; The step of extracting the first path of the preset planned path, decomposing the first path, and obtaining a set of decomposed road segments includes: Obtain the preset road segment length threshold; Based on the road segment length threshold, the first path is cut once to obtain the first cut road segment; The road curvature information of the first cut road segment is collected to obtain the first road curvature information; The decomposed road segment set is obtained based on the first road curvature information; The step of obtaining the decomposed road segment set based on the first road curvature information includes: If the curvature information of the first road does not meet the preset curvature threshold, the corner position of the first cut road segment is located and the corner positioning result is obtained. Using the corner positioning result as the cutting point, the first cutting segment is cut a second time to obtain the first decomposed segment; Based on the corner positioning result and the preset road segment length threshold, the first path is further decomposed to obtain multiple first decomposed road segments; The decomposed road segment set is constructed by using the plurality of first decomposed road segments; The step of extracting the first decomposed road segment from the decomposed road segment set and collecting vehicle flow data on the first decomposed road segment to obtain the first vehicle flow data includes: Determine whether the first decomposed road segment contains traffic lights. If it does, set a first collection period based on the traffic light switching cycle. During the first collection period, continuous vehicle flow is collected on the first decomposed road segment to obtain continuous vehicle flow collection results. The minimum traffic flow value is obtained based on the continuous traffic flow collection results. The first segment congestion level information of the first decomposed road segment is determined based on the minimum traffic flow value, and the first segment congestion level information is used as the first traffic flow data. If the traffic lights are not included in the first decomposed road segment, the current time is used as the first collection time to collect real-time vehicle flow in the first decomposed road segment and obtain the real-time flow collection result. The number of vehicles and their speed are extracted based on the real-time traffic data collection results. The first traffic flow data is generated based on the number of vehicles and their speed to determine the level of congestion on the first road segment.

2. The method as described in claim 1, characterized in that, The step of optimizing the route based on the first traffic flow data and the preset planned route to obtain the optimal driving route includes: Based on the preset planned path and the first traffic flow data, obtain multiple traffic flow data sets corresponding to the multiple paths; Based on the multiple traffic flow data sets, extract the first traffic flow data set for the first path; The average value of multiple first traffic flow data within the first traffic flow data set is calculated to obtain the congestion level of the first path. If the congestion level of the first path is less than or equal to the congestion level of the preset path, the first path is added to the initial optimal path set; The optimal driving route is determined based on the initial set of optimal routes.

3. The method as described in claim 2, characterized in that, Determining the optimal driving route based on the initial optimal route set includes: Extract the first initial optimal path based on the initial optimal path set; Obtain the first path length of the first initial optimal path; The lengths of the first path are compared, and the initial optimal path corresponding to the shortest path length is obtained as the optimal driving path.

4. A vehicle traffic flow monitoring system based on a cloud platform, characterized in that, For implementing the cloud-based vehicle traffic monitoring method according to any one of claims 1-3, the system comprises: A destination acquisition module, which is used to acquire the preset destination of the target vehicle; A location acquisition module, which is used to collect the real-time location information of the target vehicle; A route planning module is used to plan a driving route based on the preset destination and the real-time location information to obtain a preset planned route, which includes multiple routes. A road segment set acquisition module is used to extract the first path of the preset planned path, decompose the first path, and obtain a decomposed road segment set. The traffic flow data acquisition module is used to extract a first decomposed road segment based on the decomposed road segment set, and to collect vehicle flow data on the first decomposed road segment to obtain first traffic flow data. The driving route acquisition module is used to perform route optimization based on the first traffic flow data and the preset planned route, obtain the optimal driving route, and send it to the target vehicle.

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