Traffic state prediction method and device, computer equipment, storage medium and program product

Abstract

The invention relates to a traffic state prediction method and device, computer equipment, a storage medium and a program product. The method comprises the steps of obtaining traffic public opinion information collected in a preset time period, and performing state prediction on a traffic state of a target area where a geographic position is located according to the traffic public opinion information to obtain the traffic state of the target area where the geographic position is located, the traffic public opinion information comprises geographic positions and description information corresponding to historical traffic questions. According to the method, the traffic state of the region where each geographic position is located is predicted through the historical traffic public opinion information of each geographic position, and the traffic state prediction result of each region is obtained, so that clear traffic management guidance is provided for a traffic management department before a traffic problem occurs, and traffic accidents are avoided to a certain extent.

Description

Technical Field

[0001] The present application relates to the field of big data processing technology, and in particular to a traffic status prediction method, device, computer equipment, storage medium and program product. Background Art

[0002] With the acceleration of urbanization, problems such as traffic congestion and road safety are becoming more and more serious. The traditional model of traffic management based on experience can no longer meet the increasingly demanding management needs of modern traffic.

[0003] At present, traffic problems are generally managed based on the evaluation and opinions of the public on traffic facilities, traffic management, traffic congestion, traffic safety, etc., expressed through the Internet or by calling landlines. However, the above-mentioned traffic problem handling mode has a time lag, that is, the traffic problem is handled after it occurs, which may lead to significant economic, life and property losses.

[0004] Therefore, how to predict the traffic status of a road before a traffic problem occurs has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] Based on this, it is necessary to provide a traffic status prediction method, device, computer equipment, storage medium and program product that can predict the traffic status of a road in advance in order to solve the above technical problems.

[0006] In a first aspect, the present application provides a method for predicting traffic conditions, comprising:

[0007] Obtain traffic public opinion information collected within a preset time period; traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0008] The traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0009] The above method predicts the traffic status of each geographical location through the historical traffic public opinion information of each geographical location, and obtains the traffic status prediction results of each area, so as to provide clear traffic management guidance to the traffic management department before traffic problems occur, and avoid the occurrence of traffic accidents to a certain extent.

[0010] In one embodiment, the traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located, including:

[0011] Input traffic public opinion information into a preset traffic status prediction model for prediction, and obtain the traffic status of the geographical location within a preset time period;

[0012] The probability that all geographical locations in the target area are in abnormal traffic conditions is counted, and the traffic conditions of the target area are determined based on the probability that all geographical locations are in abnormal traffic conditions.

[0013] The method for determining the traffic status of the target area provided in the embodiment of the present application obtains the traffic status of the target area by statistically analyzing the traffic public opinion information of each geographical location within a preset time period, thereby providing a basis for the management of traffic problems in the target area and maintaining the stability of traffic order.

[0014] In one embodiment, the method further comprises:

[0015] Obtaining a preset ground area distribution map, and dividing the preset ground area distribution map into regions to obtain boundary information of each region;

[0016] According to the geographical location and the boundary information of each area, the target area where each geographical location is located is determined.

[0017] The method for determining the target area provided in the embodiment of the present application first divides the preset ground area into regions to obtain boundary information of each region, and then determines the target area where each geographical location is located based on the geographical location and the boundary information of each region, thereby providing a data basis for subsequently determining the traffic status of the target area.

[0018] In one embodiment, the above-mentioned inputting of traffic public opinion information into a preset traffic status prediction model for prediction to obtain the traffic status of the geographical location within a preset time period includes:

[0019] Extracting geographic location and corresponding description information from traffic public opinion information; the description information is used to describe traffic problems and traffic status under traffic problems;

[0020] Convert the coordinates of the geographical location to obtain the target longitude and latitude coordinates corresponding to the geographical location;

[0021] The target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0022] The method for obtaining the traffic status of a geographical location provided in the embodiment of the present application extracts the geographical location and description information in the traffic public opinion information, and determines the traffic status of the geographical location in combination with a preset traffic status prediction model, thereby improving the prediction accuracy of the traffic status of each geographical location, and further improving the prediction accuracy of the traffic status of the target area where each geographical location is located.

[0023] In one embodiment, the method further comprises:

[0024] Extract the reported longitude and latitude coordinates corresponding to the geographical location from the traffic public opinion information;

[0025] Correct the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates;

[0026] The above-mentioned target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information are input into the preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within the preset time period, including:

[0027] The corrected target latitude and longitude coordinates and corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0028] The method for correcting longitude and latitude coordinates provided in the embodiment of the present application corrects the target longitude and latitude coordinates obtained by converting the geographic name information based on the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates, thereby improving the accuracy of the determined longitude and latitude information, and providing a basis for subsequently accurately determining the target longitude and latitude of the geographic location.

[0029] In one embodiment, determining the traffic status of the target area according to the probability of all geographical locations being in abnormal traffic status includes:

[0030] The abnormal traffic state with the largest probability value is determined as the traffic state of the target area; the abnormal traffic state includes any one of a congestion state, a violation state, an accident state, and a fault state.

[0031] The method for determining the traffic status of the target area provided in the embodiment of the present application determines the abnormal traffic status with the largest probability value as the traffic status of the target area, thereby providing a statistical method for the traffic status of the target area.

[0032] In one embodiment, the method further comprises:

[0033] The traffic status of the target area is displayed in each area of ​​the preset ground area distribution map on the current display interface, and / or the traffic status of the geographical location is displayed in each area.

[0034] The method for displaying traffic status provided in the embodiment of the present application enables users (for example, traffic management personnel) to accurately respond to traffic accidents based on the displayed traffic status, avoid traffic accidents, and reduce the loss of life and property by displaying the traffic status corresponding to each area and the traffic status of each geographical location in a preset ground area distribution map.

[0035] In a second aspect, the present application also provides a traffic status prediction device, comprising:

[0036] The acquisition module is used to obtain traffic public opinion information collected within a preset time period; the traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0037] The prediction module is used to predict the traffic status of the target area where the geographical location is located according to the traffic public opinion information, so as to obtain the traffic status of the target area where the geographical location is located.

[0038] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0039] Obtain traffic public opinion information collected within a preset time period; traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0040] The traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0041] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0042] Obtain traffic public opinion information collected within a preset time period; traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0043] The traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0044] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0045] Obtain traffic public opinion information collected within a preset time period; traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0046] The traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0047] The above-mentioned traffic status prediction method, device, computer equipment, storage medium and program product predict the traffic status of each geographical location through the historical traffic public opinion information of each geographical location, and obtain the traffic status prediction results of each area, so as to provide clear traffic management guidance to the traffic management department before traffic problems occur, and avoid the occurrence of traffic accidents to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0049] FIG1 is a diagram showing an application environment of a method for predicting traffic conditions in one embodiment;

[0050] Figure 2 is a flow chart of a method for predicting traffic status in one embodiment;

[0051] Figure 3 is a flow chart of a method for predicting traffic status in another embodiment;

[0052] Figure 4 is a flow chart of a method for predicting traffic status in another embodiment;

[0053] Figure 5 is a flow chart of a method for predicting traffic status in another embodiment;

[0054] Figure 6 is a flow chart of a method for predicting traffic status in another embodiment;

[0055] Figure 7 is a flow chart of a method for predicting traffic status in another embodiment;

[0056] Figure 8 is a flow chart of a method for predicting traffic status in another embodiment;

[0057] FIG9 is a block diagram of a traffic status prediction device according to an embodiment;

[0058] FIG. 10 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0060] With the acceleration of urbanization, problems such as traffic congestion and road safety are becoming more and more serious. The traditional model of traffic management based on experience can no longer meet the increasingly demanding management needs of modern traffic.

[0061] At present, traffic problems are generally managed based on the evaluations and opinions of the public on traffic facilities, traffic management, traffic congestion, traffic safety, etc., after receiving them through the Internet or by calling landlines. However, the above-mentioned traffic problem handling mode has a time lag, that is, the traffic problem is handled after the traffic problem occurs, which may lead to significant economic, life and property losses. Therefore, how to predict the traffic status of the road before the traffic problem occurs has become a technical problem that needs to be solved urgently. This application aims to solve this problem.

[0062] After introducing the background technology of the traffic status prediction method provided by the embodiment of the present application, the implementation environment involved in the traffic status prediction method provided by the embodiment of the present application will be briefly described below. The traffic status prediction method provided by the embodiment of the present application can be applied in the implementation environment shown in Figure 1. The implementation environment includes a server 104, and the server 104 can be implemented with an independent server 104 or a server cluster composed of multiple servers 104. The data storage system 102 can store the data that the server 104 needs to process. The data storage system 102 can be integrated on the server 104, or it can be placed on the cloud or other network servers. Among them, the data storage system 102 can collect and pre-store various types of public opinion information, and the server 104 can obtain the traffic public opinion information collected within a preset time period from the data storage system 102, and perform state prediction on the traffic status of the target area where the geographical location is located based on the traffic public opinion information, and obtain the traffic status of the target area where the geographical location is located.

[0063] In other possible implementations, the traffic status prediction method provided in the embodiment of the present application can also be applied to terminals, which can be, but are not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart car devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc.

[0064] After introducing the application scenarios of the traffic status prediction method provided in the embodiments of the present application, the following focuses on introducing the traffic status prediction method described in the present application.

[0065] In one embodiment, Figure 2 As shown, a traffic status prediction method is provided, which is described by taking the method applied to the server in FIG1 as an example, and includes the following steps:

[0066] S201. Obtain traffic public opinion information collected within a preset time period.

[0067] The preset time period may be a time period of the traffic state to be predicted, for example, a time period of a week, a month, a day, etc., or a time period of the traffic state to be predicted every day, for example, 7:00-9:00 every day.

[0068] Among them, traffic public opinion information refers to the opinions and emotions of the public on the transportation industry expressed through landline phones or on the Internet, including evaluations and opinions on transportation facilities, traffic management, traffic congestion, traffic safety and other aspects.

[0069] The traffic public opinion information includes the geographical location and description information corresponding to the historical traffic problems, wherein the geographical location refers to the specific location where the historical traffic problems occurred, and the description information refers to the detailed information of the historical traffic problems. For example, the traffic public opinion information can be expressed as: a traffic light failure occurred at the xx intersection in the xx district of the xx city.

[0070] It should be noted that traffic public opinion information may include traffic public opinion in one geographical location, or traffic public opinion in multiple geographical locations.

[0071] In an embodiment of the present application, when it is necessary to predict the traffic status of a certain location within a preset time period, the traffic public opinion information collected within the preset time period can be obtained in advance.

[0072] Optionally, traffic public opinion information within a preset time period can be crawled on the Internet by crawling; optionally, when the public feedbacks traffic public opinion information through landlines, the traffic public opinion information can be recorded in a traffic public opinion database based on the occurrence of traffic problems; and when it is necessary to predict the traffic status of a certain location within a preset time period, the corresponding traffic public opinion information can be directly searched from the traffic public opinion database based on the occurrence time of the traffic problem.

[0073] S202: predict the traffic status of the target area where the geographical location is located according to the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0074] In an embodiment of the present application, after the traffic public opinion information is determined as described above, the traffic status of the geographical location corresponding to the traffic public opinion information can be predicted based on the descriptive information in the traffic public opinion information; and the preset ground area can be divided into multiple areas, and the boundaries of each area can be determined, and the target area where the geographical location is located can be determined based on the boundaries of each area; then, the traffic status of the target area is statistically calculated based on the traffic status of each geographical location.

[0075] For example, during the preset time period, there are 5 traffic jams, 2 illegal parkings and 1 zombie car in various geographical locations in the target area. Since the target area has the most traffic jams during the preset time period, the traffic status of the target area is determined to be traffic congestion.

[0076] The traffic status prediction method provided in the embodiment of the present application obtains the traffic public opinion information collected within a preset time period, and predicts the traffic status of the target area where the geographical location is located based on the traffic public opinion information, thereby obtaining the traffic status of the target area where the geographical location is located, wherein the traffic public opinion information includes the geographical location and description information corresponding to the historical traffic problems. The above method predicts the traffic status of the area where each geographical location is located through the historical traffic public opinion information of each geographical location, and obtains the traffic status prediction results of each area, thereby providing clear traffic management guidance to the traffic management department before traffic problems occur, and avoiding the occurrence of traffic accidents to a certain extent.

[0077] In one embodiment, Figure 2 Based on the embodiment shown, the process of obtaining the traffic status of the target area where the geographical location is located can be described as follows: Figure 3 As shown, the above S202 "predicting the traffic status of the target area where the geographical location is located according to the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located" includes:

[0078] S301: Input traffic public opinion information into a preset traffic status prediction model for prediction to obtain the traffic status of the geographical location within a preset time period.

[0079] Among them, the preset traffic state prediction model can be a pre-trained model for predicting traffic states based on traffic public opinion information. The preset traffic state prediction model can be trained based on traffic public opinion information with marked traffic state types and an initial prediction model.

[0080] In an embodiment of the present application, after the traffic public opinion information collected within the preset time period is obtained as mentioned above, the traffic public opinion information collected within the preset time period can be input into a pre-trained preset traffic status prediction model for prediction to obtain the traffic status of the geographical location in the traffic public opinion information within the preset time period.

[0081] Optionally, a training method for a preset traffic state prediction model is provided below, including:

[0082] (1) Collecting sample traffic public opinion data; the sample traffic public opinion data includes traffic public opinion data that occurred in multiple time periods and multiple geographical locations;

[0083] (2) Labeling of sample traffic public opinion data; labeling the sample traffic public opinion information collected in (1) according to the congestion state, violation state, accident state, and fault state, where the congestion state may be road congestion, the violation state may be zombie cars, nuisance to residents, illegal parking, etc., the accident state may be a car accident, and the fault state may be a signal light timing error; optionally, the meaning of the sample traffic public opinion data may be manually determined based on the text description of the sample traffic public opinion data, and the traffic public opinion data may be manually labeled based on the meaning of the sample traffic public opinion data;

[0084] (3) Data segmentation: After obtaining the labeled sample traffic public opinion data in (2), the labeled sample traffic public opinion data can be divided into a training set and a test set according to a certain ratio. For example, 70% of the labeled sample public opinion data can be determined as a training set, and the remaining 30% can be determined as a test set. The training set is used to train and fit the model and determine the parameters, and the test set is used to test the accuracy of the final model in the training set.

[0085] (4) Data preprocessing: Preprocess the labeled sample public opinion data in the training set in (3). The purpose of preprocessing is to remove invalid information in the labeled sample public opinion data, for example, to remove modal particles in the labeled sample public opinion data.

[0086] (5) Text feature extraction: After the preprocessed sample public opinion data is obtained in (4) above, in order to extract the text features of the preprocessed sample public opinion data, the preprocessed sample public opinion data may be firstly subjected to word segmentation processing. For example, the shortest path word segmentation method may be used to perform word segmentation processing on the preprocessed sample public opinion data, and feature extraction is performed based on the word segmentation processed sample public opinion data to obtain the text features of the sample public opinion data.

[0087] Next, we will introduce the shortest path word segmentation method. The shortest path word segmentation method is based on the principle that the frequency / probability of common words is definitely greater than that of rare words. It can transform the problem of solving the shortest path of the word graph into the problem of solving the maximum probability path, that is, the most likely combination of words. Calculating the probability of word occurrence, it is not enough to have only words, but also sufficient corpus. Therefore, the word segmentation task has risen from a simple "algorithm" to "modeling", that is, using statistical methods combined with big data mining to model "language". The purpose of the language model is to construct the probability of a sentence appearing. , see the following formula (1):

[0088]

[0089] in, , is a character or word, and l is the total number of characters or words.

[0090] (6) Vector / matrix conversion: After obtaining the text features of the sample public opinion data as described above, for the convenience of calculation, the text features of the sample public opinion data can be converted into vectors / matrixes to obtain the sample public opinion data after the vector / matrix conversion;

[0091] (7) Model training: input the sample public opinion data after vector / matrix conversion into the initial prediction model, train the initial prediction model, and obtain a preset traffic status prediction model.

[0092] S302: Count the probabilities that all geographical locations in the target area are in abnormal traffic conditions, and determine the traffic conditions of the target area according to the probabilities that all geographical locations are in abnormal traffic conditions.

[0093] Among them, abnormal traffic conditions include any one of congestion conditions, violation conditions, accident conditions, and fault conditions. The congestion condition may be road congestion, the violation condition may be zombie cars, nuisance to residents, illegal parking, etc., the accident condition may be a car accident, and the fault condition may be incorrect traffic light timing.

[0094] In the embodiment of the present application, after the traffic status of the geographical location within the preset time period is determined as mentioned above, the target area corresponding to the geographical location is determined according to the boundaries of multiple areas, the traffic status of all geographical locations within the target area within the preset time period is determined, the traffic status of all geographical locations within the target area within the preset time period is counted, the abnormal traffic status among the traffic status of all geographical locations within the target area within the preset time period is determined, and then the probabilities of multiple abnormal traffic statuses corresponding to the traffic status of all geographical locations within the target area within the preset time period are determined, and after determining the probabilities of the abnormal traffic statuses corresponding to the traffic status of all geographical locations within the target area within the preset time period, the abnormal traffic status with the highest probability among the traffic status of all geographical locations within the target area within the preset time period is determined as the traffic status of the target area.

[0095] The method for determining the traffic status of the target area provided in the embodiment of the present application obtains the traffic status of the target area by statistically analyzing the traffic public opinion information of each geographical location within a preset time period, thereby providing a basis for the management of traffic problems in the target area and maintaining the stability of traffic order.

[0096] In one embodiment, Figure 3 Based on the embodiment shown, Figure 4 As shown, the above method also includes:

[0097] S303: Obtain a preset ground area distribution map, and divide the preset ground area distribution map into regions to obtain boundary information of each region.

[0098] Among them, the preset ground area can be an area to be managed, such as xx city, xx district, xx province and other areas.

[0099] In an embodiment of the present application, a preset ground area distribution map can be retrieved from the Internet, and the retrieved preset ground area distribution map can be divided into regions to obtain multiple regions, and boundary information of each region can be obtained.

[0100] Optionally, after obtaining the preset ground area distribution map, the preset ground area distribution map can be continuously divided according to a certain latitude and longitude or ground distance according to a unified rule to form regular polygons, each of which is called a grid unit, thereby forming a hierarchical and layered multi-level grid system, realizing ground space discretization, and giving each grid unit a unified code. For example, the preset ground area can be divided into several grid units of 1km*1km (the grid size can be customized), and the grids are numbered to obtain the grid boundary information and the coordinates of the grid center point.

[0101] Furthermore, after the boundary information of each area is determined as mentioned above, each area can be encoded to obtain the coding information corresponding to each area, and the jurisdiction department can be determined for each area to obtain the area number, area boundary, area center point coordinates and area jurisdiction area corresponding to each area, and the area number, area boundary, area center point coordinates and area jurisdiction area corresponding to each area can be stored in the database.

[0102] Optionally, a method for determining the jurisdiction to which a region belongs is provided below, that is, when more than 50% of the area of ​​a region belongs to a jurisdiction, the jurisdiction to which the region belongs is considered to be that jurisdiction.

[0103] S304: Determine the target area where each geographical location is located according to the geographical location and the boundary information of each area.

[0104] In the embodiment of the present application, after the geographical location in the traffic public opinion information is obtained as described above, the target area where each geographical location is located can be determined based on the geographical location and the boundary information of each area.

[0105] Optionally, the coordinate information (for example, longitude and latitude information) corresponding to the geographic location in the traffic public opinion information may be used to obtain the area where the coordinate information corresponding to the geographic location is located using a point-in-plane geographic calculation method, and the area may be determined as the target area.

[0106] Below, we provide a method to determine whether a point is within a surface. Assuming that the area is a polygon A1A2A3...An, and the geographic location coordinates P in the traffic public opinion information, then the area of ​​the polygon It can be expressed by the following formula (2):

[0107]

[0108] in, is the area of ​​triangle PA1A2, is the area of ​​triangle PA2A3, is the area of ​​triangle PAnA1.

[0109] Then, if the geographic location coordinate P is inside the polygon A1A2A3 ... An, the sum of the areas of the triangles formed by the geographic location coordinate P and all adjacent vertices of the polygon should be equal to the actual area of ​​the polygon A1A2A3 ... An, and vice versa.

[0110] The method for determining the target area provided in the embodiment of the present application first divides the preset ground area into regions to obtain boundary information of each region, and then determines the target area where each geographical location is located based on the geographical location and the boundary information of each region, thereby providing a data basis for subsequently determining the traffic status of the target area.

[0111] In one embodiment, Figure 3 Based on the embodiment shown, a method for obtaining the traffic status of a geographical location within a preset time period can be described in detail, such as Figure 5 As shown, the above S301 "inputting traffic public opinion information into a preset traffic status prediction model for prediction to obtain the traffic status of the geographical location within a preset time period" includes:

[0112] S401. Extracting geographic location and corresponding description information from traffic public opinion information.

[0113] The geographical location may be geographical name information, and / or longitude and latitude coordinate information of a certain place, wherein the geographical name information may be the intersection of xx and yy, or zz bridge, etc.

[0114] The description information is used to describe the traffic problem and the traffic status under the traffic problem.

[0115] In an embodiment of the present application, after the traffic public opinion information is obtained as described above, a geographic location analysis tool can be called to extract the geographic location information from the traffic public opinion information, and the remaining information in the traffic public opinion information except the geographic location information is determined as the descriptive information corresponding to the traffic public opinion information.

[0116] S402: Convert the coordinates of the geographical location to obtain the target longitude and latitude coordinates corresponding to the geographical location.

[0117] In an embodiment of the present application, after the geographic location in the traffic public opinion information is obtained as described above, if the geographic location information only includes geographic name information, the geographic name information can be converted into longitude and latitude coordinates to obtain the target longitude and latitude coordinates corresponding to the geographic location.

[0118] Optionally, the geocoding interface of the map service may be used to convert the geographic name information into longitude and latitude coordinates to obtain the target longitude and latitude coordinates corresponding to the geographic location.

[0119] It should be noted that the geocoding interface service provided by the map service can resolve geographic name information (province / city / district / street / house number) into corresponding longitude and latitude coordinates. The more complete the geographic name information and the more accurate the address content, the higher the accuracy of the resolved longitude and latitude coordinates.

[0120] S403: Input the target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0121] In an embodiment of the present application, after the target latitude and longitude coordinates and corresponding description information corresponding to the geographic location are obtained as mentioned above, the target latitude and longitude coordinates and corresponding description information corresponding to the geographic location can be simultaneously input into a pre-trained preset traffic status prediction model for traffic status analysis to obtain the traffic status of the geographic location within a preset time period.

[0122] Optionally, the descriptive information in the traffic public opinion information can be first input into a pre-trained preset traffic status prediction model to perform traffic status analysis to obtain the traffic status corresponding to the descriptive information, and the descriptive information can be matched with the corresponding geographic location to obtain the traffic status corresponding to the geographic location, and after analyzing the traffic public opinion information within a preset time period, the traffic status of the geographic location within the preset time period can be obtained.

[0123] Optionally, before inputting the target latitude and longitude coordinates and corresponding description information corresponding to the geographic location into the preset traffic state prediction model, the target latitude and longitude coordinates and corresponding description information corresponding to the geographic location may be cleaned to improve the quality of the data and reduce the probability of errors in the data analysis process. It should be noted that data cleaning includes data review, data verification, redundancy processing, data filling, data correction, etc.

[0124] The method for obtaining the traffic status of a geographical location provided in the embodiment of the present application extracts the geographical location and description information in the traffic public opinion information, and determines the traffic status of the geographical location in combination with a preset traffic status prediction model, thereby improving the prediction accuracy of the traffic status of each geographical location, and further improving the prediction accuracy of the traffic status of the target area where each geographical location is located.

[0125] In one embodiment, Figure 5 Based on the embodiment shown, Figure 6 As shown, the above method also includes:

[0126] S404: extract the reported longitude and latitude coordinates corresponding to the geographic location from the traffic public opinion information.

[0127] The reported longitude and latitude coordinates are the longitude and latitude coordinates carried in the traffic public opinion information. The reported longitude and latitude coordinates may be consistent with the above-mentioned target longitude and latitude coordinates, or inconsistent with the above-mentioned target longitude and latitude coordinates. In addition, when the reported longitude and latitude coordinates are inconsistent with the above-mentioned target longitude and latitude coordinates, the target longitude and latitude coordinates need to be corrected according to the reported longitude and latitude coordinates.

[0128] In an embodiment of the present application, after the geographic location is extracted from the traffic public opinion information as mentioned above, if the geographic location also includes the longitude and latitude coordinates corresponding to the geographic location, then the corresponding longitude and latitude coordinates can be extracted from the geographic location as the reported longitude and latitude coordinates.

[0129] S405. Correct the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates.

[0130] In an embodiment of the present application, after obtaining the reported longitude and latitude coordinates from the traffic public opinion information, and converting the geographical name information in the traffic public opinion information into longitude and latitude coordinates to obtain the target longitude and latitude coordinates corresponding to the geographical location, the target longitude and latitude coordinates can be corrected according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates.

[0131] Generally speaking, the geographic name information in traffic public opinion information is usually incomplete. For example, when citizens report traffic problems, the address will not be described as the standard "intersection of Xiaoying West Road and Shangdi East Road in Haidian District, Beijing", but directly as "Shangdi Qiaoxi Road Intersection" or "Shangdi Qiaoxi". After a long period of Internet application, open map services can intelligently identify "Shangdi Qiaoxi Road Intersection" as "intersection of Xiaoying West Road and Shangdi East Road". However, for some intersections or POIs, a city may have multiple places with the same name, such as "Gulou East Street". Both Dongcheng and Miyun districts in Beijing have "Gulou East Street". In this case, it is impossible to use the geographic name information in the traffic public opinion information, which is inaccurate. At the same time, the target longitude and latitude coordinates obtained by converting the longitude and latitude coordinates according to the geographic name information in the traffic public opinion information will also be inaccurate. At this time, it is necessary to correct the target longitude and latitude coordinates based on the reported longitude and latitude coordinates to obtain the corrected longitude and latitude coordinates.

[0132] Optionally, the correction method may be to directly use the reported longitude and latitude coordinates as the corrected longitude and latitude coordinates.

[0133] The above S403 "inputting the target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period" includes:

[0134] S403: Input the corrected target longitude and latitude coordinates and corresponding description information into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0135] In an embodiment of the present application, after the corrected target longitude and latitude coordinates and the corresponding description information are obtained as mentioned above, the corrected target longitude and latitude coordinates and the corresponding description information can be simultaneously input into a pre-trained preset traffic status prediction model for traffic status analysis to obtain the traffic status of the geographical location within a preset time period.

[0136] Optionally, the descriptive information in the traffic public opinion information can be first input into a pre-trained preset traffic status prediction model to perform traffic status analysis to obtain the traffic status corresponding to the descriptive information, and the descriptive information can be matched with the corrected target longitude and latitude coordinates to obtain the traffic status corresponding to the corrected target longitude and latitude coordinates, and after analyzing the traffic public opinion information within a preset time period, the traffic status of the geographical location within the preset time period can be obtained.

[0137] The method for correcting longitude and latitude coordinates provided in the embodiment of the present application corrects the target longitude and latitude coordinates obtained by converting the geographic name information based on the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates, thereby improving the accuracy of the determined longitude and latitude information, and providing a basis for subsequently accurately determining the target longitude and latitude of the geographic location.

[0138] In one embodiment, Figure 3-Figure 6 Based on the illustrated embodiment, the process of determining the traffic state of the target area can be described in detail. The above S302 "determining the traffic state of the target area according to the probability that all geographical locations are in abnormal traffic states" includes:

[0139] The abnormal traffic state with the largest probability value is determined as the traffic state of the target area.

[0140] Among them, abnormal traffic conditions include any one of congestion conditions, violation conditions, accident conditions, and fault conditions. The congestion condition may be road congestion, the violation condition may be zombie cars, nuisance to residents, illegal parking, etc., the accident condition may be a car accident, and the fault condition may be incorrect traffic light timing.

[0141] In the embodiment of the present application, after the probabilities of all geographical locations in the target area being in abnormal traffic conditions are determined, the abnormal traffic condition with the largest probability value may be determined as the traffic condition of the target area.

[0142] Optionally, assuming that the target area includes three geographical locations, namely geographical location 1, geographical location 2 and geographical location 3, the traffic status is estimated three times for each geographical location, the traffic status estimated for geographical location 1 includes: congestion status, violation status and congestion status, the traffic status estimated for geographical location 2 includes: congestion status, violation status and accident status, and the traffic status estimated for geographical location 3 includes: congestion status, fault status and accident status, then the congestion status in the target area appears 4 times, the violation status appears 2 times, the accident status appears twice, and the fault status appears once, then the abnormal traffic state with the highest probability is the congestion state, and the congestion state is determined as the traffic state of the target area.

[0143] The method for determining the traffic status of the target area provided in the embodiment of the present application determines the abnormal traffic status with the largest probability value as the traffic status of the target area, thereby providing a statistical method for the traffic status of the target area.

[0144] In one embodiment, Figure 2-Figure 6 Based on the embodiment shown, Figure 7 As shown, the above method also includes:

[0145] S203: Displaying the traffic status of the target area in each area of ​​the preset ground area distribution map on the current display interface, and / or displaying the traffic status of the geographical location in each area.

[0146] In an embodiment of the present application, after the traffic status of the target area and the traffic status at each geographical location are acquired as described above, the traffic status corresponding to each area can be displayed in each area in a preset ground area distribution map on the display interface of the computer device, and / or the traffic status at each geographical location can be displayed at each geographical location in a preset ground area distribution map on the display interface of the computer device.

[0147] Optionally, the traffic status of each geographical location may be displayed in a preset ground area distribution map on the display interface of the computer device using different colors according to the degree of abnormality of the traffic status.

[0148] The method for displaying traffic status provided in the embodiment of the present application enables users (for example, traffic management personnel) to accurately respond to traffic accidents based on the displayed traffic status, avoid traffic accidents, and reduce the loss of life and property by displaying the traffic status corresponding to each area and the traffic status of each geographical location in a preset ground area distribution map.

[0149] In one embodiment, Figure 8 As shown, a traffic status prediction method is also provided, including:

[0150] S10, obtaining traffic public opinion information collected within a preset time period;

[0151] S11, extracting geographic location and corresponding description information from traffic public opinion information;

[0152] S12, converting the coordinates of the geographical location to obtain the target longitude and latitude coordinates corresponding to the geographical location;

[0153] S13, extracting the reported longitude and latitude coordinates corresponding to the geographical location from the traffic public opinion information;

[0154] S14, correcting the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates;

[0155] S15, inputting the corrected target latitude and longitude coordinates and corresponding description information into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period;

[0156] S16, obtaining a preset ground area distribution map, and dividing the preset ground area distribution map into regions to obtain boundary information of each region;

[0157] S17, determining the target area where each geographical location is located according to the geographical location and the boundary information of each area;

[0158] S18, counting the probabilities of all geographical locations in the target area being in abnormal traffic conditions, and determining the traffic conditions of the target area according to the probabilities of all geographical locations being in abnormal traffic conditions;

[0159] S19: Displaying the traffic status of the target area in each area of ​​the preset ground area distribution map on the current display interface, and / or displaying the traffic status of the geographical location in each area.

[0160] The above method predicts the traffic status of each geographical location through the historical traffic public opinion information of each geographical location, and obtains the traffic status prediction results of each area, so as to provide clear traffic management guidance to the traffic management department before traffic problems occur, and avoid the occurrence of traffic accidents to a certain extent.

[0161] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0162] Based on the same inventive concept, the embodiment of the present application also provides a traffic state prediction device for implementing the traffic state prediction method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more traffic state prediction device embodiments provided below can refer to the limitations of the traffic state prediction method above, and will not be repeated here.

[0163] In an exemplary embodiment, as shown in FIG9 , a traffic status prediction device is provided, including: an acquisition module 10 and a prediction module 11, wherein:

[0164] The acquisition module 10 is used to obtain traffic public opinion information collected within a preset time period; the traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems.

[0165] The prediction module 11 is used to predict the traffic status of the target area where the geographical location is located according to the traffic public opinion information, so as to obtain the traffic status of the target area where the geographical location is located.

[0166] In an exemplary embodiment, the prediction module 11 includes: a prediction unit and a statistical unit, wherein:

[0167] The prediction unit is specifically used to input the traffic public opinion information into a preset traffic status prediction model for prediction, and obtain the traffic status of the geographical location within a preset time period;

[0168] The statistical unit is specifically used to count the probabilities that all geographical locations in the target area are in abnormal traffic conditions, and determine the traffic conditions of the target area according to the probabilities that all geographical locations are in abnormal traffic conditions.

[0169] In an exemplary embodiment, the prediction module 11 further includes: an acquisition unit and a determination unit, wherein:

[0170] The acquisition unit is specifically used to acquire a preset ground area distribution map, and divide the preset ground area distribution map into regions to obtain boundary information of each region;

[0171] The determination unit is specifically used to determine the target area where each geographical location is located according to the geographical location and the boundary information of each area.

[0172] In an exemplary embodiment, the above-mentioned prediction unit is specifically used to extract the geographic location and corresponding descriptive information from the traffic public opinion information; the descriptive information is used to describe the traffic problem and the traffic status under the traffic problem; the coordinates of the geographic location are converted to obtain the target longitude and latitude coordinates corresponding to the geographic location; the target longitude and latitude coordinates corresponding to the geographic location and the corresponding descriptive information are input into the preset traffic status prediction model for analysis to obtain the traffic status of the geographic location within a preset time period.

[0173] In an exemplary embodiment, the above-mentioned prediction unit is specifically used to extract the reported longitude and latitude coordinates corresponding to the geographic location from the traffic public opinion information; correct the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates; input the corrected target longitude and latitude coordinates and the corresponding description information into a preset traffic status prediction model for analysis to obtain the traffic status of the geographic location within a preset time period.

[0174] In an exemplary embodiment, the above-mentioned determination unit is specifically used to determine the abnormal traffic state with the largest probability value as the traffic state of the target area; the abnormal traffic state includes any one of a congestion state, a violation state, an accident state, and a fault state.

[0175] In an exemplary embodiment, the above-mentioned device also includes: a display module, which is used to display the traffic status of the target area in each area in the preset ground area distribution map on the current display interface, and / or display the traffic status at the geographical location in each area.

[0176] Each module in the above traffic status prediction device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0177] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG10. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. 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 and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for predicting traffic conditions is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0178] Those skilled in the art will understand that the structure shown in FIG. 10 is merely a block diagram of a partial 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 arrangement of components.

[0179] In an exemplary 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:

[0180] Obtain traffic public opinion information collected within a preset time period; traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0181] The traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0182] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0183] Input traffic public opinion information into a preset traffic status prediction model for prediction, and obtain the traffic status of the geographical location within a preset time period;

[0184] The probability that all geographical locations in the target area are in abnormal traffic conditions is counted, and the traffic conditions of the target area are determined based on the probability that all geographical locations are in abnormal traffic conditions.

[0185] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0186] Obtaining a preset ground area distribution map, and dividing the preset ground area distribution map into regions to obtain boundary information of each region;

[0187] According to the geographical location and the boundary information of each area, the target area where each geographical location is located is determined.

[0188] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0189] Extracting geographic location and corresponding description information from traffic public opinion information; the description information is used to describe traffic problems and traffic status under traffic problems;

[0190] Convert the coordinates of the geographical location to obtain the target longitude and latitude coordinates corresponding to the geographical location;

[0191] The target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0192] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0193] Extract the reported longitude and latitude coordinates corresponding to the geographical location from the traffic public opinion information;

[0194] Correct the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates;

[0195] The target latitude and longitude coordinates and corresponding description information corresponding to the geographical location are input into the preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within the preset time period, including:

[0196] The corrected target latitude and longitude coordinates and corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0197] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0198] The abnormal traffic state with the largest probability value is determined as the traffic state of the target area; the abnormal traffic state includes any one of a congestion state, a violation state, an accident state, and a fault state.

[0199] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0200] The traffic status of the target area is displayed in each area of ​​the preset ground area distribution map on the current display interface, and / or the traffic status of the geographical location is displayed in each area.

[0201] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0202] Obtain traffic public opinion information collected within a preset time period; traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0203] The traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0204] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0205] Input traffic public opinion information into a preset traffic status prediction model for prediction, and obtain the traffic status of the geographical location within a preset time period;

[0206] The probability that all geographical locations in the target area are in abnormal traffic conditions is counted, and the traffic conditions of the target area are determined based on the probability that all geographical locations are in abnormal traffic conditions.

[0207] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0208] Obtaining a preset ground area distribution map, and dividing the preset ground area distribution map into regions to obtain boundary information of each region;

[0209] According to the geographical location and the boundary information of each area, the target area where each geographical location is located is determined.

[0210] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0211] Extracting geographic location and corresponding description information from traffic public opinion information; the description information is used to describe traffic problems and traffic status under traffic problems;

[0212] Convert the coordinates of the geographical location to obtain the target longitude and latitude coordinates corresponding to the geographical location;

[0213] The target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0214] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0215] Extract the reported longitude and latitude coordinates corresponding to the geographical location from the traffic public opinion information;

[0216] Correct the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates;

[0217] The target latitude and longitude coordinates and corresponding description information corresponding to the geographical location are input into the preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within the preset time period, including:

[0218] The corrected target latitude and longitude coordinates and corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0219] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0220] The abnormal traffic state with the largest probability value is determined as the traffic state of the target area; the abnormal traffic state includes any one of a congestion state, a violation state, an accident state, and a fault state.

[0221] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0222] The traffic status of the target area is displayed in each area of ​​the preset ground area distribution map on the current display interface, and / or the traffic status of the geographical location is displayed in each area.

[0223] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0224] Obtain traffic public opinion information collected within a preset time period; traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems;

[0225] The traffic status of the target area where the geographical location is located is predicted based on the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

[0226] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0227] Input traffic public opinion information into a preset traffic status prediction model for prediction, and obtain the traffic status of the geographical location within a preset time period;

[0228] The probability that all geographical locations in the target area are in abnormal traffic conditions is counted, and the traffic conditions of the target area are determined based on the probability that all geographical locations are in abnormal traffic conditions.

[0229] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0230] Obtaining a preset ground area distribution map, and dividing the preset ground area distribution map into regions to obtain boundary information of each region;

[0231] According to the geographical location and the boundary information of each area, the target area where each geographical location is located is determined.

[0232] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0233] Extracting geographic location and corresponding description information from traffic public opinion information; the description information is used to describe traffic problems and traffic status under traffic problems;

[0234] Convert the coordinates of the geographical location to obtain the target longitude and latitude coordinates corresponding to the geographical location;

[0235] The target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0236] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0237] Extract the reported longitude and latitude coordinates corresponding to the geographical location from the traffic public opinion information;

[0238] Correct the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates;

[0239] The target latitude and longitude coordinates and corresponding description information corresponding to the geographical location are input into the preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within the preset time period, including:

[0240] The corrected target latitude and longitude coordinates and corresponding description information are input into a preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within a preset time period.

[0241] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0242] The abnormal traffic state with the largest probability value is determined as the traffic state of the target area; the abnormal traffic state includes any one of a congestion state, a violation state, an accident state, and a fault state.

[0243] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0244] The traffic status of the target area is displayed in each area of ​​the preset ground area distribution map on the current display interface, and / or the traffic status of the geographical location is displayed in each area.

[0245] 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, and the collection, use and processing of relevant data must comply with relevant regulations.

[0246] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed 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 the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can 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 can include random access memory (RAM) or external cache memory, etc. As an 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 each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0247] The technical features of the above embodiments may 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 application.

[0248] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for predicting traffic conditions, characterized in that: The method comprises: Obtaining traffic public opinion information collected within a preset time period; the traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems; The traffic status of the target area where the geographical location is located is predicted according to the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located.

2. The method according to claim 1, characterized in that The step of predicting the traffic status of the target area where the geographical location is located according to the traffic public opinion information to obtain the traffic status of the target area where the geographical location is located includes: Inputting the traffic public opinion information into a preset traffic status prediction model for prediction to obtain the traffic status of the geographical location within the preset time period; The probabilities of all geographical locations in the target area being in abnormal traffic conditions are counted, and the traffic conditions of the target area are determined according to the probabilities of all geographical locations being in abnormal traffic conditions.

3. The method according to claim 2, characterized in that The method further comprises: Obtaining a preset ground area distribution map, and dividing the preset ground area distribution map into regions to obtain boundary information of each region; According to the geographical locations and the boundary information of each of the areas, a target area where each of the geographical locations is located is determined.

4. The method according to claim 2, characterized in that: The step of inputting the traffic public opinion information into a preset traffic status prediction model for prediction to obtain the traffic status of the geographical location within the preset time period includes: Extracting the geographical location and corresponding description information from the traffic public opinion information; the description information is used to describe the traffic problem and the traffic status under the traffic problem; Convert the coordinates of the geographical location to obtain the target longitude and latitude coordinates corresponding to the geographical location; The target longitude and latitude coordinates corresponding to the geographic location and the corresponding description information are input into the preset traffic status prediction model for analysis to obtain the traffic status of the geographic location within the preset time period.

5. The method according to claim 4, characterized in that The method further comprises: Extracting the reported longitude and latitude coordinates corresponding to the geographic location from the traffic public opinion information; Correcting the target longitude and latitude coordinates according to the reported longitude and latitude coordinates to obtain corrected longitude and latitude coordinates; The inputting the target latitude and longitude coordinates corresponding to the geographical location and the corresponding description information into the preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within the preset time period includes: The corrected target longitude and latitude coordinates and corresponding description information are input into the preset traffic status prediction model for analysis to obtain the traffic status of the geographical location within the preset time period.

6. The method according to any one of claims 2 to 5, characterized in that: The determining the traffic status of the target area according to the probability that all geographical locations are in abnormal traffic status includes: The abnormal traffic state with the largest probability value is determined as the traffic state of the target area; the abnormal traffic state includes any one of a congestion state, a violation state, an accident state, and a fault state.

7. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: The traffic status of the target area is displayed in each area of ​​the preset ground area distribution map on the current display interface, and / or the traffic status at the geographical location is displayed in each area.

8. A traffic status prediction device, characterized in that: The device comprises: An acquisition module is used to acquire traffic public opinion information collected within a preset time period; the traffic public opinion information includes the geographical location and description information corresponding to historical traffic problems; The prediction module is used to predict the traffic status of the target area where the geographical location is located according to the traffic public opinion information, so as to obtain the traffic status of the target area where the geographical location is located.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. 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 7 are implemented.

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