Method, device, equipment and storage medium for determining road traffic status

Abstract

The embodiments of the present application relate to a method, device, equipment and storage medium for determining the traffic status of a road, which are applicable to the fields of maps, navigation, automatic driving, vehicle networking, intelligent transportation, etc. The method includes: determining the travel information and navigation information of at least one user in a first time period; determining a target location point based on the travel information and navigation information of at least one user; determining at least one deviation information of the target location point, any deviation information of the target location point includes the actual exit road, navigation exit road and entry road of a first user corresponding to the target location point at the same time in the first time period when the actual exit road and navigation exit road of the first user are inconsistent; determining the traffic status of the road corresponding to the target location point after the first time period based on at least one deviation information. The use of the embodiments of the present application can improve the efficiency and accuracy of determining the traffic status of the road, and has high applicability.

Description

Technical Field

[0001] The present application relates to the field of transportation, and in particular to a method, device, equipment and storage medium for determining road traffic status. Background Art

[0002] With the continuous advancement of infrastructure construction, people have more and more roads to choose from, but the increase in the number of cars can easily lead to traffic jams, and road construction and changes in traffic rules can also lead to abnormal road traffic. In this case, people need to first determine the road traffic status before traveling and then choose the appropriate road to travel.

[0003] To this end, data analysis can be performed based on vehicle flow, vehicle speed, number and width of lanes, road topography, etc. to predict road traffic conditions, or by establishing statistical models to predict road traffic conditions. However, in certain situations, such as when the amount of data is large and data collection is difficult, the scope of data analysis is relatively limited, the accuracy is poor, and the applicability of statistical models is low. Therefore, how to accurately and efficiently determine the road traffic status has become an urgent problem to be solved. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment and storage medium for determining road traffic status, which can improve the efficiency and accuracy of determining road traffic status and have high applicability.

[0005] On the one hand, an embodiment of the present application provides a method for determining a road traffic status, the method comprising:

[0006] determining travel information and navigation information of at least one user during a first time period;

[0007] Determine a target location point based on the travel information and navigation information of the at least one user, the target location point being any location point at which, within the first time period, there is a discrepancy between an actual exit road indicated by the travel information of at least one first user and a navigation exit road indicated by the navigation information at the same time;

[0008] Determine at least one deviation information of the target location point, wherein any deviation information of the target location point includes an actual exit road, a navigation exit road, and an entry road of the first user corresponding to the target location point at the same time in the first time period when the actual exit road and the navigation exit road of the first user corresponding to the target location point at the same time in the first time period are inconsistent;

[0009] Based on the at least one deviation information, a traffic status of the road corresponding to the target location point after the first time period is determined.

[0010] On the other hand, an embodiment of the present application provides a device for determining a road traffic state, the device comprising:

[0011] an information determination module, configured to determine travel information and navigation information of at least one user in a first time period;

[0012] A location determination module, configured to determine a target location point based on the travel information and navigation information of the at least one user, wherein the target location point is any location point at which, within the first time period, there is a location point where an actual exit road indicated by the travel information of at least one first user is inconsistent with a navigation exit road indicated by the navigation information at the same time;

[0013] The information determination module is used to determine at least one deviation information of the target location point, wherein any deviation information of the target location point includes an actual exit road, a navigation exit road and an entry road of the first user corresponding to the target location point at the same time of the first time period when the actual exit road and the navigation exit road of the first user corresponding to the target location point are inconsistent;

[0014] A state determination module is used to determine the traffic state of the road corresponding to the target location point after the first time period based on the at least one deviation information.

[0015] On the other hand, an embodiment of the present application provides an electronic device, including a processor and a memory, wherein the processor and the memory are connected to each other;

[0016] The memory is used to store computer programs;

[0017] The above-mentioned processor is configured to execute the method for determining the road traffic status provided in the embodiment of the present application when calling the above-mentioned computer program.

[0018] On the other hand, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method for determining the road traffic status provided in the embodiment of the present application.

[0019] On the other hand, an embodiment of the present application provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method for determining the road traffic status provided in the embodiment of the present application.

[0020] In an embodiment of the present application, at least one yaw information of the target location point can be determined through the user's travel information and navigation information in the first time period, and then based on the at least one yaw information, the traffic status of the road at the target location point after the first time period can be determined, so that the traffic status of the road corresponding to the target location point can be determined in time according to the user's travel information and navigation information, thereby improving the efficiency and accuracy of determining the road traffic status. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments 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 drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 It is a schematic diagram of a scenario of a method for determining a road traffic status provided in an embodiment of the present application;

[0023] Figure 2 It is a flowchart of a method for determining a road traffic status provided in an embodiment of the present application;

[0024] Figure 3 is a schematic diagram comparing the travel trajectory and the travel road provided in the embodiment of the present application;

[0025] Figure 4 is a schematic diagram of a method for determining a road matching a trajectory point provided in an embodiment of the present application;

[0026] Figure 5 is a schematic diagram of a scene of a target location point provided in an embodiment of the present application;

[0027] Figure 6 is another schematic diagram of a target location provided in an embodiment of the present application;

[0028] Figure 7 is another flowchart of a method for determining a road traffic status provided in an embodiment of the present application;

[0029] Figure 8 is another scene schematic diagram of a target location point provided in an embodiment of the present application;

[0030] Fig. 9 is a schematic diagram of a process for determining a road traffic status based on a yaw rate provided in an embodiment of the present application;

[0031] Fig.10 It is a structural schematic diagram of a device for determining a road traffic status provided in an embodiment of the present application;

[0032] Fig.11It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0034] See also Figure 1 , Figure 1 Schematic diagram of a method for determining a road traffic status provided in an embodiment of the present application. Figure 1 As shown, the travel information and navigation information of at least one user in the first time period can be determined, such as determining Figure 1 The travel information and navigation information of the user 100 in the first time period.

[0035] For each user, the travel information of the user in the first time period is used to illustrate the roads that the user actually traveled in the first time period, such as the roads that the user drove in the first time period, the roads that the user rode in the first time period, etc. The navigation information of the user in the first time period is used to illustrate the corresponding navigation roads in the process of the user traveling on the roads indicated by the travel information.

[0036] Further, based on the travel information and navigation information of at least one user, a target location point may be determined. The target location point is any location point in the first time period where the actual exit road indicated by the travel information of at least one first user is inconsistent with the navigation exit road indicated by the navigation information at the same time. Figure 1 In the example, the user 100 indicated by the travel information of the user 100 leaves a certain location point at a certain time in the first time period ( Figure 1 If the time of exiting road 400 at the intersection in the figure is inconsistent with the navigation exit road 500 indicating that the navigation information of user 100 leaves the location point at the same time, the location point can be determined as the target location point 200.

[0037] Further, at least one deviation information of the target location point may be determined. For example, one deviation information of the target location point 200 includes the navigation exit road 500 corresponding to the target location point 200 of the user 100 at the same time in the first time period, the actual exit road 500, and the entry road 300 of the user 100 entering the target location point 200.

[0038] Further, for the target location point 200, the traffic status of the road corresponding to the target location point 200 after the first time period can be determined based on at least one deviation information of the target location point 200. For example, the traffic status of the actual exit road 400 or the navigation exit road 500 corresponding to the target location point 200 after the first time period can be determined.

[0039] The method for determining the road traffic status provided in the embodiment of the present application can be applied to fields such as mapping, transportation, and computer technology, such as intelligent transportation systems (ITS) and intelligent vehicle infrastructure cooperative systems (IVICS) in the transportation field.

[0040] Among them, the intelligent transportation system, also known as the intelligent transportation system (Intelligent Transportation System), is to effectively and comprehensively apply advanced science and technology (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operations research, artificial intelligence, etc.) to transportation, service control and vehicle manufacturing, strengthen the connection between vehicles, roads and users, and thus form a comprehensive transportation system that ensures safety, improves efficiency, improves the environment and saves energy. Based on the method for determining the road traffic status provided in the embodiment of the present application, the traffic status of each road at different times can be determined, thereby providing strong guarantees for transportation, service control and other aspects.

[0041] Among them, the intelligent vehicle-road cooperative system, referred to as the vehicle-road cooperative system, is a development direction of the intelligent transportation system (ITS). The vehicle-road cooperative system adopts advanced wireless communication and new generation Internet technologies to implement all-round dynamic real-time information interaction between vehicles and roads, and carries out active vehicle safety control and road cooperative management based on the collection and integration of dynamic traffic information in all time and space, fully realizing the effective coordination of people, vehicles and roads, ensuring traffic safety, and improving traffic efficiency, thus forming a safe, efficient and environmentally friendly road traffic system. Based on the method for determining the road traffic status provided in the embodiment of the present application, technical support can be provided for traffic safety and vehicle-road collaboration based on the determined road traffic status.

[0042] See also Figure 2 , Figure 2 FIG. 1 is a flow chart of a method for determining a road traffic status provided in an embodiment of the present application. Figure 2 As shown, the method for determining the road traffic status provided in the embodiment of the present application may include the following steps:

[0043] Step S21: Determine travel information and navigation information of at least one user in a first time period.

[0044] In some feasible implementations, for each user, the user's travel information in the first time period is used to illustrate the road that the user actually traveled in the first time period, such as the road that the user drove in the first time period, the road that the user rode in the first time period, etc. The user's navigation information in the first time period is used to illustrate the corresponding navigation road in the process of the user traveling on the road indicated by the travel information, such as the road that the user is planned to travel next when the user reaches a certain road intersection.

[0045] Specifically, when determining the travel information of each user in the first time period, the travel trajectory of each user in the first time period can be obtained through the user terminal or navigation application, and then the travel information of each user is determined according to the travel trajectory of each user in the first time period.

[0046] For example, for the user "Xiao Wang", the travel trajectory of "Xiao Wang" in the first time period can be obtained through "Xiao Wang's" navigation application, and then the travel information of "Xiao Wang" in the first time period can be determined based on the travel trajectory of "Xiao Wang" in the first time period.

[0047] Among them, the above-mentioned user terminals include but are not limited to mobile phones, computers, intelligent voice interaction devices, smart home appliances, car terminals, etc., which can be determined based on the actual application scenario requirements and are not limited here.

[0048] Among them, the above-mentioned first time period represents a certain time interval, such as one day, 3 hours, etc. The specific time span can be determined based on the actual application scenario requirements and is not limited here.

[0049] In actual applications, due to weak GPS signals, poor communication conditions of user terminals, and positioning accuracy, the user's travel trajectory determined based on the above method often does not completely coincide with the user's actual route, and thus the user's travel trajectory cannot be directly used as the user's actual route. Figure 3 , Figure 3 It is a schematic diagram comparing the travel trajectory and the travel road provided in the embodiment of the present application. Figure 3 The road shown is the road that the user actually travels on at the intersection, and its corresponding travel trajectory is Figure 3 As shown by the arc in , the user's travel trajectory and the user's actual travel route are similar in terms of the travel route, but they do not overlap.

[0050] Therefore, when determining the travel information of each user in the first time period, for each user, the travel trajectory of the user in the first time period can be matched with each road in the road map, and then the road matching the travel trajectory of the user in the first time period can be determined as the travel information of the user in the first time period.

[0051] In some feasible implementations, when determining the roads matching the travel trajectories of each user, each trajectory point of each travel trajectory may be determined first. For each travel trajectory, a trajectory point of the travel trajectory is used to represent the travel position of the user corresponding to the travel trajectory at a certain time point, and each trajectory point of the travel trajectory may represent the travel position of the corresponding user at different time points, and thus each user's travel trajectory represents the travel position of the corresponding user at different time points.

[0052] Specifically, for each track point of each travel track, the angle between the track direction of the track point and each road in the road map can be determined. The track direction of the track point indicates the direction of travel of the user at the track point. The smaller the angle between the track direction of the track point and the road, the higher the overlap between the track direction of the track point and the corresponding road.

[0053] Based on this, for each trajectory point of each travel trajectory, the road with the smallest angle with the trajectory direction of the trajectory point can be determined as the road matching the trajectory point, and then based on the roads matching each trajectory point, the road matching the travel trajectory can be determined.

[0054] Optionally, for each track point, the distance between the track point and each road in the road map can also be determined. The smaller the distance between the track point and the road, the higher the overlap between the track point and the corresponding road.

[0055] Based on this, for each trajectory point of each travel trajectory, the road with the shortest distance to the trajectory point can be determined as the road matching the trajectory point, and then based on the roads matching each trajectory point, the road matching the travel trajectory can be determined.

[0056] Optionally, for each track point of each traveling track, a portion of roads with a smaller angle to the track direction of the track point may be determined, such as by arranging the roads in order of angles with the track direction of the track point from small to large, and selecting a portion of roads with an angle less than an angle threshold. Further, a road with the smallest distance to the track point is selected from the selected portions of roads, and is determined as a road matching the track point.

[0057] Alternatively, for each trajectory point, a portion of roads with a smaller distance from the trajectory point can be determined, such as arranging the roads in ascending order of distance from the trajectory point, selecting a portion of roads with a distance less than a distance threshold, and further selecting a road with the smallest angle with the trajectory direction of the trajectory point from the selected portions of roads, and determining it as the road matching the trajectory point.

[0058] Among them, the above-mentioned distance threshold and the above-mentioned angle threshold can be specifically determined based on the actual application scenario requirements and are not limited here.

[0059] Optionally, the roads matching each track point in the travel track can also be determined based on the Markov chain, so as to determine the roads matching the corresponding travel track based on the roads matching each track point. That is, based on the probability that each road matches the first track point, and then based on the probability that each road matches the first track point, the roads matching the first track point in each road are determined. Then, based on the first track point and the roads matching it, the probability that each road matches the second track point is determined, and then based on the probability that each continent matches the second track point, the roads matching the second track point in each road are determined. By analogy, the roads matching each track point can be obtained, and then based on the roads matching each track point, the roads matching the corresponding travel track are determined.

[0060] Optionally, when determining the roads that match the travel trajectory of each user, for each trajectory point of each travel trajectory, the angle between the trajectory direction of the trajectory point and each road, and the distance between the trajectory point and each road can be determined first, and then the angle weight corresponding to the angle between the trajectory direction and the road, and the distance weight corresponding to the distance between the trajectory point and the road can be determined. Further, for each road, the angle between the trajectory direction of the trajectory point and the road and the corresponding angle weight, and the distance between the trajectory point and the road and the corresponding distance weight can be determined to determine the matching degree between the trajectory point and the road.

[0061] Among them, the above-mentioned distance weight and the above-mentioned angle weight can be normalized weights, such as the angle weight is 0.5 and the distance weight is 0.5. The specific weight values ​​can be determined based on the actual application scenario and are not limited here.

[0062] Furthermore, for each trajectory point, after determining the matching degree between the trajectory point and each road, the road with the highest matching degree can be determined and determined as the road matching the trajectory point. Thus, the roads matching the trajectory points of the travel trajectory are sorted according to the travel order of the trajectory points in the travel trajectory, and the roads matching the travel trajectory are determined, so as to determine the corresponding user's travel information in the first time period based on the roads matching the travel trajectory.

[0063] See also Figure 4 , Figure 4 Schematic diagram of a method for determining a road matching a trajectory point provided in an embodiment of the present application. Figure 4 As shown, P is a trajectory point of a moving trajectory, the angles of its corresponding trajectory direction with road A and road B are α and β respectively, and the distances between trajectory point P and road A and road B are d1 and d2 respectively.

[0064] If the angle weight is W1 and the distance weight is W2, the matching degree between trajectory point P and road A is W1*cosα+W2d1, and the matching degree between trajectory point P and road B is W1*cosβ+W2d2. When the matching degree W1*cosβ+W2d2 between trajectory point P and road B is greater than the matching degree W1*cosα+W2d1 between trajectory point P and road A, road B can be determined to be the road that matches trajectory point P.

[0065] In some feasible implementations, when determining the probability that each road matches the first trajectory point based on the Markov chain, the probability that each road matches the first trajectory point can be determined based on the distance between each road and the first trajectory point, or the probability that each road matches the first trajectory point can be determined based on the angle between each road and the trajectory direction of the first trajectory point.

[0066] Optionally, it can also be based on Figure 4 The implementation method shown in , determines the probability of each road matching the first trajectory point. That is, trajectory point P is the first trajectory point, and the angle between the trajectory direction corresponding to trajectory point P and road A is determined to be α, and the angle between the trajectory direction corresponding to road point P and road B is determined to be β, and the distance between trajectory point P and road A is determined to be d1, and the distance between trajectory point P and road B is determined to be d2. When the angle weight is W1 and the distance weight is W2, the matching degree between trajectory point P and road A is R1=W1*cosα+W2d1, and the matching degree between trajectory point P and road B is R2=W1*cosβ+W2d2. Then the probability of road A matching trajectory point P is The probability that road B matches trajectory point P is

[0067] When the matching degree R2 between trajectory point P and road B is greater than the matching degree R1 between trajectory point P and road A, the probability that road A matches trajectory point P is less than the probability that road B matches trajectory point P, then the probability that road B matches trajectory point P can be determined.

[0068] Furthermore, for each travel trajectory, after determining the roads that match each trajectory of each travel trajectory, the roads that match each trajectory point of the travel trajectory can be sorted according to the travel order of each trajectory point corresponding to the travel trajectory, and then the roads that match the travel trajectory are determined, and then the travel information of the corresponding user in the first time period is determined based on the roads that match the travel trajectory.

[0069] Optionally, after determining the roads matching each track point in the map road based on the Markov chain and arranging them according to the travel order of each track point corresponding to the travel track, if the arranged roads cannot completely connect the connecting roads with uninterrupted travel according to the travel order of the track line, then Figure 4 The method shown in FIG. 1 re-determines the road matching each trajectory point, and then Figure 4 The road matching each trajectory point determined in the manner shown is used to correct the road matching each trajectory point determined based on the Markov chain, so as to determine the road matching the corresponding travel trajectory based on the corrected road matching each trajectory point.

[0070] In some feasible implementations, when determining the roads that match the travel trajectory, for each travel trajectory, the travel trajectory can be divided into multiple trajectory intervals according to the trajectory inflection points, and then for each trajectory interval, the probability of each road matching the trajectory interval can be determined, and then based on the probability of each road matching the trajectory interval, the roads that match the trajectory interval are determined. Based on this, the roads that match each trajectory interval of the above travel trajectory can be determined, thereby obtaining the roads that match the travel trajectory.

[0071] For each trajectory interval, the probability of each road matching the trajectory interval can be determined by the angle, distance, length, etc. between the trajectory interval and each road. The specific determination method can be determined based on the actual application scenario requirements and is not limited here.

[0072] The travel information and navigation information of each user in the first time period can be obtained from the storage space corresponding to the user terminal or the navigation application. The storage space includes but is not limited to a database, a database management system or a blockchain, etc., which can be determined based on the actual application scenario requirements and is not limited here.

[0073] Among them, blockchain is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods, each of which is used to store the user's travel information and navigation information.

[0074] Step S22: Determine a target location point based on the travel information and navigation information of at least one user.

[0075] In some feasible implementations, the target location point is any location point in the first time period where the actual exit road indicated by the travel information of at least one first user is inconsistent with the navigation exit road indicated by the navigation information at the same time. For each first user, the actual exit road from the target location point indicated by the travel information of the first user is inconsistent with the navigation exit road from the target location point indicated by the navigation information of the first user at the same time in the first time period. In other words, when the actual exit road of at least one first user leaving a certain location point in the first time period is inconsistent with the navigation exit road indicating the exit from the location point, the location point can be determined as the target location point.

[0076] Among them, the above-mentioned location points can be road intersections, such as crossroads, and auxiliary road intersections, etc., which can be determined based on the actual application scenario requirements and are not limited here.

[0077] Step S23: Determine at least one yaw information of the target position point.

[0078] In some feasible embodiments, each deviation information of the target location point includes the actual exit road and the navigation exit road of the target location point corresponding to a first user at the same time in a first time period, when the actual exit road and the navigation exit road of the target location point are inconsistent, and the entry road of the first user into the target location point at that time.

[0079] For each deviation information, the deviation information can be represented by a triplet (entering the road, navigating to exit the road, and actually exiting the road).

[0080] See also Figure 5 , Figure 5 is a schematic diagram of a scene of a target location point provided by an embodiment of the present application. Figure 5 As shown, the user travels along road A to Figure 5 Based on the user's travel information, it can be known that the user actually travels to road C after exiting the location point (i.e. passing through the location point). The user's navigation information requires the user to travel to road B when exiting location point A. Figure 5 The road C in the figure is the actual exit road from the location point indicated by the user's travel information, and the road B is the navigation exit road from the location point indicated by the user's navigation information at the same time, then the location point can be determined as the target location point.

[0081] Based on this, a deviation information of the target location point may include the actual exit road (road C) and the navigation exit road (road B) of the user at the target location point, as well as the entry road (road A) passed by the user before entering the target location point.

[0082] The target location point may correspond to multiple yaw information. The navigation exit road, actual exit road and entry road included in each yaw information may be completely different, or partially or completely different. For example, for a road corresponding to the target location point, the road may be the entry road of a certain yaw information, and may also be the navigation exit road of another yaw information, and may also be the actual exit road of another yaw information.

[0083] See also Figure 6 , Figure 6 is a schematic diagram of a scene of a target location point provided by an embodiment of the present application. Figure 6 As shown, the user travels along road A to Figure 6 Based on the user's travel information, it can be known that the user actually drives to Road B after exiting the target location (i.e. passing the target location). The user's navigation information requires the user to drive to Road C when exiting the target location. Figure 6 The road B is the actual exit road from the target location point indicated by the user's travel information, and the road C is the navigation exit road from the target location point indicated by the user's navigation information at the same time.

[0084] Based on this, a deviation information of the target location point may include the actual exit road (road B) and the navigation exit road (road C) of the user at the target location point, as well as the entry road (road A) passed by the user before entering the target location point.

[0085] Step S24: determining the traffic status of the road corresponding to the target location point after the first time period based on at least one deviation information.

[0086] In some feasible implementations, when determining the traffic status of the target location point after a first time period based on at least one deviation information of the target location point, the deviation amount of the target location point corresponding to the same entry road and the same navigation exit road can be first determined based on the deviation information corresponding to the same entry road and the same navigation exit road in at least one deviation information of the target location point.

[0087] Specifically, the number of deviation information corresponding to the same entry road and the same navigation exit road in at least one deviation information of the target location point can be determined as the deviation amount of the target location point corresponding to the same entry road and the same navigation exit road. Wherein, one deviation amount of the target location point corresponds to a group of entry roads and navigation exit roads, that is, the number of deviation information including the same entry road and the same navigation exit road in at least one deviation information of the target location point is determined as one deviation amount of the target location point, thereby obtaining at least one deviation amount of the target location point.

[0088] Each deviation amount of the target location point is used to explain the number of deviations of each user from the target location point after entering the target location point through a fixed entry road and not exiting the target location point through a navigation exit road planned by the navigation within the first time period.

[0089] For example, the target location point has yaw information X, yaw information Y, and yaw information Z, wherein the entry road of yaw information X is road A, the navigation exit road is road B, and the actual exit road is road C; the entry road of yaw information Y is road A, the navigation exit road is road B, and the actual exit road is road D; the entry road of yaw information Z is road D, the navigation exit road is road E, and the actual exit road is road C. Since the yaw information X and the yaw information Y correspond to the same entry road and the navigation exit road, a yaw amount of the target location point corresponding to the same entry road (road A) and the same navigation exit road (road B) can be determined based on the yaw information X and the yaw information Y. Based on the yaw information Z, a yaw amount of the target location point corresponding to the same entry road (road D) and the same navigation exit road (road E) can be determined.

[0090] Furthermore, for each deviation amount of the target position point, if the number of deviations corresponding to the deviation amount is greater than the number threshold, it means that a certain number of users did not travel according to the navigation exit road of the navigation planning corresponding to the deviation amount in the first time period, and it means that the road traffic state of the navigation exit road corresponding to the deviation amount is abnormal in the first time period. For example, the navigation exit road corresponding to the deviation amount is congested or has road construction in the first time period, or the user chooses other roads to travel due to road closure and traffic rules.

[0091] Based on this, since the traffic status of the navigation exit road corresponding to the yaw amount in the first time period is abnormal, the traffic status of the navigation exit road corresponding to the yaw amount will most likely still be abnormal after the first time period. Therefore, in the case that the traffic status of the navigation exit road corresponding to the yaw amount in the first time period is abnormal, it can be determined that the traffic status of the navigation exit road corresponding to the yaw amount after the first time period is abnormal.

[0092] For example, still taking the target location point with the above-mentioned deviation information X, deviation information Y and deviation information Z as an example, based on the deviation information X and deviation information Y, it can be determined that the deviation amount of the target location point corresponding to the same entry road (road A) and the same navigation exit road (road B) is 2, and based on the deviation information z, it can be determined that the deviation amount of the target location point corresponding to the same entry road (road D) and the same navigation exit road (road E) is 1. If the deviation number threshold is 1, it can be determined that after entering the target location point through road A in the first time period, each user did not choose to pass through the navigation-planned road B, but chose to pass through other roads, which further indicates that the traffic of road B in the first time period is abnormal. Based on this, it can be determined that the traffic status of road B after the first time period is also abnormal.

[0093] Furthermore, for each deviation amount of the target position point, if the number of deviations corresponding to the deviation amount is less than or equal to the number threshold, it means that within the first time period, some individual users did not travel along the navigation exit road of the navigation plan corresponding to the deviation amount, which means that the road traffic status of the navigation exit road corresponding to the deviation amount was normal within the first time period.

[0094] Furthermore, since each deviation information of the target location point indicates that a user did not follow the navigation exit road of the corresponding navigation plan at a certain time, and instead traveled through other actual exit roads, therefore, if the navigation exit road corresponding to the deviation amount has abnormal road traffic in the first time period, the number of occurrences of each actual exit road in each deviation information corresponding to the deviation amount can be determined. For the actual exit road with the most occurrences (such as road 1), when the navigation exit road corresponding to the deviation amount has abnormal road traffic in the first time period, most users choose road 1 to travel, and it can be determined that road 1 has normal road traffic in the first time period. In this case, it can be determined that the actual exit road with the most occurrences has normal traffic after the first time period.

[0095] See also Figure 7 , Figure 7 FIG. 2 is another flow chart of the method for determining the road traffic status provided in the embodiment of the present application. Figure 7 As shown, the method for determining the road traffic status provided in the embodiment of the present application may include the following steps:

[0096] Step S71: Determine travel information and navigation information of at least one user in a first time period.

[0097] Step S72: Determine a target location point based on the travel information and navigation information of at least one user.

[0098] Step S73: Determine at least one yaw information of the target position point.

[0099] In some possible implementations, Figure 7 The specific implementation of steps S71 to S73 can be found in Figure 2 The implementation method shown in steps S21 to S23 will not be repeated here.

[0100] Step S74: if within the first time period, at least one actual exit road indicated by the travel information of the second user at the target location point is consistent with the navigation exit road indicated by the navigation information at the same time, then determine at least one along-course information of the target location point.

[0101] In some feasible implementations, after determining at least one deviation information of each location point, if within the first time period, the actual exit road indicated by the travel information of at least one second user is consistent with the navigation exit road indicated by the navigation information at the same time, then at least one along-course information of the target location point can be determined. Wherein, for each second user, the actual exit road from the target location point indicated by the travel information of the second user is the same as the navigation exit road from the target location point indicated by the navigation information of the second user at the same time in the first time period.

[0102] Among them, each along-route information of the target location point includes a navigation exit road of a second user corresponding to the target location point at the same time when the actual exit road and the navigation exit road of the second user are consistent, and an entry road of the user to enter the target location point.

[0103] For each piece of directional navigation information, the directional navigation information can be represented by a tuple (entering road, navigating exiting road).

[0104] See also Figure 8 , Figure 8 is another scene schematic diagram of the target location point provided in the embodiment of the present application. Figure 8 As shown, the user travels along road A to Figure 8 The target location point in the figure, based on the user's travel information, it can be known that the user actually travels to road B after exiting the target location point (i.e. passing the target location point), and the user's navigation information also plans that the user needs to travel to road B when the user exits the target location point. The road that the user travels after exiting the target location point is consistent with the road that the navigation information plans when the user exits the target location point. Figure 8 The road B in FIG. 1 is the actual exit road from the target location point indicated by the user's travel information, and is also the navigation exit road from the target location point indicated by the user's navigation information at the same time.

[0105] Based on this, the navigation information of the target location point may include the navigation exit road (road B) of the user at the target location point, and the entry road (road A) that the user passes before entering the target location point.

[0106] The target location point may not correspond to any lateral navigation information, or may correspond to at least one lateral navigation information. And the navigation exit roads and entry roads included in each lateral navigation information corresponding to the target location point may be completely the same or completely different. For example, a road at the target location point may be the entry road of a certain lateral navigation information, and may also be the navigation exit road of another lateral navigation information.

[0107] Step S75: Based on at least one deviation information and at least one forward information, determine the traffic status of the road corresponding to the target location point after the first time period.

[0108] In some feasible implementations, after determining at least one deviation information and at least one directional information corresponding to the target location point, the traffic status of the road corresponding to the target location point after the first time period can be determined based on the at least one deviation information and at least one directional information of the target location point. Figure 8 The traffic conditions of Road B, Road C, etc. shown after the first time period.

[0109] Specifically, the deviation amount of the target location point corresponding to the same entry road and the same exit road can be determined based on the deviation information corresponding to the same entry road and the same navigation exit road in at least one deviation information of the target location point. Specifically, the number of deviation information corresponding to the same entry road and the same navigation exit road in at least one deviation information of the target location point can be determined as a deviation amount of the target location point. For example, among the 8 deviation information of the target location point, 5 deviation information include entry roads H, and the corresponding navigation exit roads J, and the deviation amount of the target location point corresponding to the entry road H and the navigation exit road J can be determined to be 5. That is, in the first time period, after each user enters the target location point from road H, the number of times that the user does not exit the target location point through navigation exit road J is 5.

[0110] Similarly, the amount of the target location point corresponding to the same entry road and the same exit road can be determined based on the navigation information corresponding to the same entry road and the same navigation exit road in at least one navigation information of the target location point. Specifically, the number of navigation information corresponding to the same entry road and the same navigation exit road in each navigation information of the target location point can be determined as a navigation amount of the target location point. For example, among the 10 navigation information of the target location point, 8 navigation information include entry roads K, and the corresponding navigation exit roads L, and the navigation amount of the target location point corresponding to the entry road K and the navigation exit road L can be determined as 8. That is, in the first time period, after each user enters the target location point from road H, the number of times the user exits the target location point through navigation exit road L is 8.

[0111] Based on this, since the target location point may correspond to multiple yaw information, and the actual entry road and the actual exit road corresponding to different yaw information may be partially or completely different, at least one yaw amount of the target location point can be determined based on the above implementation method, that is, each group of entry roads and navigation exit roads of the target location point corresponds to a yaw amount. Similarly, since the target location point may correspond to multiple lateral navigation information, and the actual entry road and the actual exit road corresponding to different lateral navigation information may be partially or completely different, at least one lateral navigation amount of the target location point can be determined based on the above implementation method, that is, each group of entry roads and navigation exit roads of the target location point corresponds to a lateral navigation amount.

[0112] Further, after determining at least one downcourse amount and at least one yaw amount corresponding to the target location point, at least one yaw rate of the target location point may be determined based on the at least one yaw amount and at least one downcourse amount of the target location point. That is, based on the yaw amount and downcourse amount corresponding to the same entry road and the same navigation exit road of the target location point, a yaw rate of the target location point is determined, and a yaw rate of the target location point corresponds to a set of entry roads and navigation exit roads, and different yaw rates correspond to different road combinations (entry roads and navigation exit roads).

[0113] For example, the yaw amount of the target position point corresponding to entering road M and navigating exit road N is a, and the forward heading amount corresponding to entering road M and navigating exit road N is b. Then the yaw rate of the target position point corresponding to entering road M and navigating exit road N is a / (a+b).

[0114] Furthermore, the traffic status of the road corresponding to the target location point after the first time period may be determined based on at least one yaw rate of the target location point.

[0115] Specifically, if the yaw rate of the target location point corresponding to the same entry road and the same navigation exit road is greater than or equal to the yaw rate threshold, it means that after each user enters the target location point from the corresponding entry road in the first time period, they do not choose the corresponding navigation exit road to leave the target location point, but have a high probability of leaving the target location point through other actual exit roads, and then it can be determined that the navigation exit road corresponding to the yaw rate has a traffic abnormality in the first time period, such as traffic congestion or road construction in the first time period, or the user chooses other roads to pass due to road closure and traffic rules. Since the traffic state of the navigation exit road corresponding to the yaw rate in the first time period is a traffic abnormality, the navigation exit road corresponding to the yaw rate is likely to still have a traffic abnormality after the first time period. Therefore, if the navigation exit road corresponding to the yaw rate has a traffic abnormality in the first time period, it can be determined that the traffic state of the navigation exit road corresponding to the yaw rate after the first time period is a traffic abnormality.

[0116] If the yaw rate of the target location point corresponding to the same entry road and the same navigation exit road is less than the yaw rate threshold, it means that after each user enters the target location point from the corresponding entry road in the first time period, the probability of choosing the corresponding navigation exit road to leave the target location point is high, and then it can be determined that the navigation exit road corresponding to the yaw rate is normal in the first time period. Since the navigation exit road corresponding to the yaw rate is normal in the first time period, the navigation exit road corresponding to the yaw rate is likely to still be normal after the first time period. Therefore, if the navigation exit road corresponding to the yaw rate is normal in the first time period, it can be determined that the navigation exit road corresponding to the yaw rate is normal after the first time period.

[0117] Since any road corresponding to the target location point can be a navigation exit road in any deviation information and any along-course information of the target location point, the traffic status of each road corresponding to the target location point after the first time period can be determined based on the above method.

[0118] In some feasible implementations, in order to reduce the deviation information and / or the less along-course information, the deviation amount of the determined target location point cannot effectively represent the inaccurate probability of each user leaving the target location point through other roads other than the corresponding navigation exit road after entering the target location point from the corresponding entry road in the first time period. For example, the amount of deviation information corresponding to the same entry road and the same navigation exit road is 1, and the along-course information corresponding to the same entry road and the same navigation exit road is 0. Then, a yaw rate of the target location point determined based on this is 100%. However, it is obvious that the determined deviation amount cannot represent the road selection situation of each user after entering the target location point based on the corresponding entry road in the first time period.

[0119] Therefore, after determining at least one yaw rate of the target position point, at least one target yaw rate among the at least one yaw rate of the target position point may also be determined. Each target yaw rate is a yaw rate greater than or equal to a first threshold value, and a corresponding yaw amount greater than or equal to a second threshold value. That is, at least one target yaw rate is determined from the at least one yaw rate of the target position point, and a yaw rate greater than or equal to the first threshold value, and a corresponding yaw amount greater than or equal to the second threshold value.

[0120] Among them, for any target yaw rate, if the target yaw rate is greater than or equal to the first threshold, and the corresponding yaw amount is greater than or equal to the second threshold, it means that after each user enters the target location point from the entry road corresponding to the target yaw rate in the first time period, a considerable number of users leave the target location point through other roads other than the navigation exit road corresponding to the target yaw rate. Then, based on the traffic state of the actual exit road corresponding to each target yaw rate in the first time period, the traffic state of the road corresponding to the target location point after the first time period can be determined.

[0121] Furthermore, for each target yaw rate of the target position point, since the target yaw rate is determined based on a certain amount of yaw information (yaw amount), the target yaw rate corresponds to at least one actual exit road and a corresponding navigation exit road. Based on this, at least one first target yaw rate of at least one target yaw rate of the target position point can be determined, wherein, for each first target yaw rate, among the actual exit roads corresponding to the yaw information corresponding to the first target yaw rate, there is an actual exit road that is normally accessible in the first time period. For example, the number of yaw information used to determine the target yaw rate is 9 and the actual exit roads corresponding to the 9 yaw information are all different. If, among the 9 actual exit roads corresponding to the 9 yaw information, there is at least one actual exit road that is normally accessible in the first time period, then the target yaw rate can be determined as a first target yaw rate.

[0122] For each first target yaw rate, if there is an actual exit road that has normal traffic in the first time period among the actual exit roads corresponding to the first target yaw rate, it means that after the users enter the target location point from the entry road corresponding to the target yaw rate in the first time period, a considerable number of users leave the target location point through the actual exit road that has normal traffic in the first time period.

[0123] In some feasible implementations, at least one first probability of a target navigation exit road may be determined based on the travel information of at least one user, and the target navigation exit road is any navigation exit road among the navigation exit roads corresponding to the above-mentioned first target yaw rates. That is, for the navigation exit roads corresponding to the above-mentioned first target yaw rates, at least one first probability of any navigation exit road. Any first probability of a target navigation exit road is used to indicate the probability of abnormal traffic on the target navigation exit road after a first time period when corresponding to a first target yaw rate. That is, the probability of abnormal traffic on the target navigation exit road after a first time period when corresponding to different first target yaw rates may be determined, such as the probability of not choosing to leave the target location point through the corresponding navigation exit road after entering the target location point from the entry road corresponding to the corresponding first target yaw rate at each first target yaw rate.

[0124] For the target navigation exit road, the target first probability with the highest probability among the first probabilities corresponding to the first target yaw rates of the target navigation exit road can be determined. If the target first probability is not less than the first probability threshold, it can be determined that the probability that each user does not choose to leave the target location point through the target navigation exit road after entering the target location point in the first time period is high, that is, the probability that the target navigation exit road has abnormal traffic in the first time period is high. Therefore, in the case where the target navigation exit road has a high probability of abnormal traffic in the first time period, it can be determined that the target navigation exit road has abnormal traffic after the first time period, that is, the probability that the target navigation exit road has a high probability of changing its traffic state from normal to abnormal after the first time period.

[0125] Optionally, the average probability of the first probability of each first target yaw rate corresponding to the target navigation exit road can be determined. If the average probability is not less than the second probability threshold, it can be determined that the probability that each user did not choose to leave the target location point through the target navigation exit road after entering the target location point in the first time period is high, that is, the probability that the target navigation exit road has abnormal traffic in the first time period is high. Therefore, in the case where the probability of abnormal traffic on the target navigation exit road in the first time period is high, it can be determined that the target navigation exit road has abnormal traffic after the first time period, that is, the probability that the traffic state of the target navigation exit road changes from normal to abnormal after the first time period is high.

[0126] When at least one first probability of a target navigation exit road is determined based on the travel information of at least one user, a first road penetration amount of at least one target entry road corresponding to the target navigation exit road and a second road penetration amount of the target navigation exit road can be determined. Any target entry road corresponding to the target navigation exit road is an entry road corresponding to a first target yaw rate corresponding to the target navigation exit road. That is, the target navigation exit road can correspond to at least one first target yaw rate, each target yaw rate corresponds to an entry road, and then each entry road corresponding to each first target yaw rate corresponding to the target navigation exit road is the target entry road corresponding to the target navigation exit road.

[0127] Based on a first road penetration amount of a target entry road corresponding to the target navigation exit road and a second road penetration amount of the target navigation exit road, a first probability of the target navigation exit road can be determined.

[0128] As an example, a first probability of the target navigation exiting the road may be Wherein, S is a probability parameter, such as S=50, which can be specifically determined based on the actual application scenario requirements and is not limited here.

[0129] Among them, the above-mentioned first road penetration volume is used to represent the total number of times at least one user enters the road through the corresponding target in the first time period, and the above-mentioned second road penetration volume is used to represent the total number of times at least one user exits the road through target navigation in the first time period.

[0130] In some feasible implementations, when determining at least one first probability of a target navigation exit road based on the travel information of at least one user, a second probability that the target actual exit road has normal traffic after the first time period can also be determined. The above-mentioned target actual exit road is any actual exit road with abnormal traffic in the first time period among the actual exit roads corresponding to at least one target yaw rate. That is, each target yaw rate corresponds to multiple yaw information and multiple lateral information, so each target yaw rate corresponds to multiple actual exit roads. Therefore, any actual exit road with abnormal traffic in the first time period among all the actual exit roads corresponding to each target yaw rate can be determined as the target actual exit road.

[0131] For any target yaw rate of the target location point, if there is a target actual exit road with abnormal traffic in the first time period among the actual exit roads corresponding to the target yaw rate, after each user enters the target location point from the entry road corresponding to the target yaw rate in the first time period, a considerable number of users still leave the target location point through the target actual exit road, indicating that the target actual exit road is gradually recovering from the abnormal traffic state to the normal traffic state. Therefore, based on the travel information of at least one user in the first time period, the second probability of the target actual exit road being normal after the first time period can be determined, and then the traffic state of the target actual exit road after the first time period can be determined based on the second probability.

[0132] Specifically, if the second probability of the target actual exit road is not less than the third probability threshold, it can be determined that the target actual exit road has normal traffic after the first time period, that is, the probability that the traffic state of the target actual exit road changes from abnormal to normal after the first time period. Otherwise, it can be determined that the target actual exit road has abnormal traffic after the first time period.

[0133] Among them, when determining the second probability of the target actually exiting the road, the third road penetration amount of the target's actual exit road can be determined based on the travel information of each user in the first time period, and then based on the third road penetration amount of the target's actual exit road, the second probability of the target actually exiting the road can be determined.

[0134] As an example, the third probability corresponding to the target actually exiting the road can be Wherein, T is a probability parameter, such as T=50, which can be determined based on the actual application scenario requirements and is not limited here.

[0135] The third road penetration amount of the target actual exit road is used to represent the total number of times each user passes through the target actual exit road in the first time period.

[0136] In the embodiment of the present application, the yaw amount, the amount of following the course, and the yaw rate of the target position point can be calculated based on computer technology and cloud computing. Among them, cloud computing is the product of the development and integration of traditional computer and network technologies such as grid computing, distributed computing, parallel computing, utility computing, network storage technologies, virtualization, and load balancing. Based on cloud computing, the calculation efficiency of the yaw amount, the amount of following the course, and the yaw rate in the embodiment of the present application can be improved.

[0137] Combine the following Fig. 9 The method for determining the road traffic status based on the yaw rate provided in an embodiment of the present application is further explained. Fig. 9 is a flow chart of determining the road traffic status based on the yaw rate provided in an embodiment of the present application. Fig. 9 As shown, a target yaw rate with a yaw rate greater than or equal to 0.5 and a corresponding yaw amount greater than or equal to 3 is determined from at least one yaw rate of the target position point. If for each target yaw rate, if there is an actual exit road corresponding to the target yaw rate that has normal traffic in the first time period, then based on each travel information, at least one first probability of the target navigation exit road is determined, and then based on the at least one first probability, the traffic status of the target navigation exit road after the first time period is determined.

[0138] For each target yaw rate, if there is a target actual exit road with abnormal traffic in the first time period among the actual exit roads corresponding to the target yaw rate, a second probability that the target actual exit road has normal traffic after the first time period is determined based on the travel information of at least one user, and the traffic status of the target actual exit road after the first time period is determined based on the second probability that the target actual exit road has normal traffic after the first time period.

[0139] In an embodiment of the present application, at least one yaw information of the target location point can be determined through the user's travel information and navigation information in the first time period, and then based on the at least one yaw information, the traffic status of the road at the target location point after the first time period can be determined, so that the traffic status of the road can be determined in time according to the user's travel information and navigation information, thereby improving the efficiency and accuracy of determining the road traffic status.

[0140] Among them, the user's travel information and navigation information are easy to obtain, and the amount of data is small, which can reduce the data acquisition time and thus improve the efficiency of determining the road traffic status. And the road traffic status is determined based on the yaw information determined by the travel information and navigation information, and the data processing complexity is low, thereby improving the accuracy of determining the road traffic status and high applicability. In addition, by determining the amount of down-course and yaw at the target location point, and then determining the yaw rate of the target location point, the traffic status of the road at the target location point in the next time period can be determined based on the yaw rate of the target location point and the corresponding actual exit road traffic status in the first time period, without introducing additional features such as weather, terrain, road saturation, etc., thereby ensuring the accuracy of determining the road traffic status.

[0141] See also Fig.10 , Fig.10 : is a schematic diagram of the structure of a device for determining a road traffic status provided in an embodiment of the present application. The device for determining a road traffic status provided in an embodiment of the present application includes:

[0142] An information determination module 11, configured to determine travel information and navigation information of at least one user in a first time period;

[0143] The location determination module 12 is used to determine a target location point based on the travel information and navigation information of the at least one user, wherein the target location point is any location point at which, within the first time period, there is a location point where the actual exit road indicated by the travel information of at least one first user is inconsistent with the navigation exit road indicated by the navigation information at the same time;

[0144] The information determination module 11 is used to determine at least one deviation information of the target location point, wherein any deviation information of the target location point includes an actual exit road, a navigation exit road and an entry road of the first user corresponding to the target location point at the same time of the first time period when the actual exit road and the navigation exit road of the first user corresponding to the target location point are inconsistent;

[0145] The state determination module 13 is used to determine the traffic state of the road corresponding to the target location point after the first time period based on the at least one deviation information.

[0146] In some feasible implementation manners, the information determination module 11 is further used to:

[0147] If the target location point has an actual exit road indicated by the travel information of at least one second user that is consistent with the navigation exit road indicated by the navigation information at the same time within the first time period, then at least one along-route information of the target location point is determined, and any along-route information of the target location point includes an entry road and a navigation exit road of the second user corresponding to the target location point at the same time in the first time period when the actual exit road and the navigation exit road of the second user are consistent;

[0148] The state determination module 13 is used to:

[0149] Based on the at least one deviation information and the at least one directional information, a traffic status of the road corresponding to the target location point after the first time period is determined.

[0150] In some feasible implementations, the state determination module 13 is used to:

[0151] Determine a deviation amount of the target position point based on the deviation information corresponding to the same entry road and the same navigation exit road in the at least one deviation information;

[0152] Determine a downflight amount of the target location point based on downflight information corresponding to the same entry road and the same navigation exit road in the at least one downflight information;

[0153] Based on at least one deviation amount and at least one lateral amount of the target location point, a traffic state of the road corresponding to the target location point after the first time period is determined.

[0154] In some feasible implementations, the state determination module 13 is used to:

[0155] Determine a yaw rate of the target location point based on the yaw amount and the down-course amount of the target location point corresponding to the same entry road and the same navigation exit road;

[0156] Based on at least one yaw rate of the target location point, a traffic state of the road corresponding to the target location point after the first time period is determined.

[0157] In some feasible implementations, the state determination module 13 is used to:

[0158] Determine at least one target yaw rate of the target position point, which is greater than or equal to the first threshold and has a corresponding yaw amount greater than or equal to the second threshold;

[0159] Based on the traffic status of the actual exit road corresponding to the at least one target yaw rate in the first time period, the traffic status of the road corresponding to the target position point after the first time period is determined.

[0160] In some feasible implementations, the state determination module 13 is used to:

[0161] Determine at least one first target yaw rate among the at least one target yaw rate, wherein among the actual exit roads corresponding to the first target yaw rate, there is an actual exit road with normal traffic in the first time period;

[0162] Based on the travel information of the at least one user, at least one first probability of a target navigation exit road is determined, the target navigation exit road being any navigation exit road among the navigation exit roads corresponding to the at least one first target yaw rate, and the any first probability of the target navigation exit road is used to represent the probability of abnormal traffic on the target navigation exit road after the first time period when the target navigation exit road corresponds to the corresponding first target yaw rate;

[0163] Based on the at least one first probability, a traffic status of the target navigation exit road after the first time period is determined.

[0164] In some feasible implementations, the state determination module 13 is used to:

[0165] Based on the travel information of the at least one user, determining a second probability that the target actual exit road has normal traffic after the first time period, the target actual exit road being any actual exit road with abnormal traffic in the first time period among the actual exit roads corresponding to the at least one first target yaw rate;

[0166] Based on the second probability that the target actual exit road is normally accessible after the first time period, the traffic status of the target actual exit road after the first time period is determined.

[0167] In some feasible implementations, the state determination module 13 is used to:

[0168] Based on the travel information of the at least one user, determine a first road penetration amount of at least one target entry road corresponding to the target navigation exit road and a second road penetration amount of the target navigation exit road, wherein any target entry road corresponding to the target navigation exit road is an entry road corresponding to the first target yaw rate corresponding to the target navigation exit road, the first road penetration amount is used to indicate the total number of times the at least one user passes through the corresponding target entry road in the first time period, and the second road penetration amount is used to indicate the total number of times the at least one user passes through the target navigation exit road in the first time period;

[0169] Based on the first road penetration amount and the second road penetration amount of the at least one target entering the road, at least one first probability that the target navigates out of the road is determined.

[0170] In some feasible implementations, the state determination module 13 is used to:

[0171] Determine, based on the travel information of the at least one user, a third road penetration amount of the target actual exit road, wherein the third road penetration amount is used to represent a total number of times that the at least one user passes through the target actual exit road in the first time period;

[0172] Based on the third road penetration amount, a second probability that the target actual exit road will be normally accessible after the first time period is determined.

[0173] In some feasible implementations, the information determination module 11 is used to:

[0174] Obtaining a travel trajectory of at least one user in a first time period;

[0175] A road matching the travel trajectory is determined, and the road matching the travel trajectory is determined as the travel information of the corresponding user in the first time period.

[0176] In some feasible implementations, the information determination module 11 is used to:

[0177] Determine each track point of the above-mentioned travel track;

[0178] For each of the above trajectory points, determine the angle between the trajectory direction of the trajectory point and each road, and the distance between the trajectory point and each road, and determine the matching degree between the trajectory point and each road based on the angle between the trajectory direction of the trajectory point and the road, and the distance between the trajectory point and the road;

[0179] For each of the above trajectory points, based on the matching degree between the trajectory point and each of the above roads, determining a road matching the trajectory point;

[0180] Based on the roads matching each of the trajectory points, a road matching the travel trajectory is determined.

[0181] In a specific implementation, the above-mentioned device 1 can execute the above-mentioned functions through its built-in functional modules. Figure 2 and / or Figure 7 For the implementation methods provided in each step, please refer to the implementation methods provided in the above steps for details, which will not be repeated here.

[0182] See also Fig.11 , Fig.11 Schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Fig.11 As shown, the electronic device 1000 in this embodiment may include: a processor 1001, a network interface 1004 and a memory 1005. In addition, the above-mentioned electronic device 1000 may also include: a user interface 1003, and at least one communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. Among them, the user interface 1003 may include a display screen (Display), a keyboard (Keyboard), and the user interface 1003 may optionally include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1004 may be a high-speed RAM memory, or it may be a non-volatile memory (non-volatile memory), such as at least one disk storage. The memory 1005 may optionally also be at least one storage device located away from the aforementioned processor 1001. As Fig.11 As shown, the memory 1005 as a computer-readable storage medium may include an operating system, a network communication module, a user interface module, and a device control application program.

[0183] exist Fig.11In the electronic device 1000 shown, the network interface 1004 can provide a network communication function; the user interface 1003 is mainly used to provide an input interface for the user; and the processor 1001 can be used to call the device control application stored in the memory 1005 to achieve:

[0184] determining travel information and navigation information of at least one user during a first time period;

[0185] Determine a target location point based on the travel information and navigation information of the at least one user, the target location point being any location point at which, within the first time period, there is a discrepancy between an actual exit road indicated by the travel information of at least one first user and a navigation exit road indicated by the navigation information at the same time;

[0186] Determine at least one deviation information of the target location point, wherein any deviation information of the target location point includes an actual exit road, a navigation exit road, and an entry road of the first user corresponding to the target location point at the same time in the first time period when the actual exit road and the navigation exit road of the first user corresponding to the target location point at the same time in the first time period are inconsistent;

[0187] Based on the at least one deviation information, a traffic status of the road corresponding to the target location point after the first time period is determined.

[0188] In some feasible implementation manners, for each of the above-mentioned location points, the above-mentioned processor 1001 is used to:

[0189] If the target location point has an actual exit road indicated by the travel information of at least one second user that is consistent with the navigation exit road indicated by the navigation information at the same time within the first time period, then at least one along-route information of the target location point is determined, and any along-route information of the target location point includes an entry road and a navigation exit road of the second user corresponding to the target location point at the same time in the first time period when the actual exit road and the navigation exit road of the second user are consistent;

[0190] Based on the at least one deviation information and the at least one directional information, a traffic status of the road corresponding to the target location point after the first time period is determined.

[0191] In some feasible implementations, the processor 1001 is configured to:

[0192] Determine a deviation amount of the target position point based on the deviation information corresponding to the same entry road and the same navigation exit road in the at least one deviation information;

[0193] Determine a downflight amount of the target location point based on downflight information corresponding to the same entry road and the same navigation exit road in the at least one downflight information;

[0194] Based on at least one deviation amount and at least one lateral amount of the target location point, a traffic state of the road corresponding to the target location point after the first time period is determined.

[0195] In some feasible implementations, the processor 1001 is configured to:

[0196] Determine a yaw rate of the target location point based on the yaw amount and the down-course amount of the target location point corresponding to the same entry road and the same navigation exit road;

[0197] Based on at least one yaw rate of the target location point, a traffic state of the road corresponding to the target location point after the first time period is determined.

[0198] In some feasible implementations, the processor 1001 is configured to:

[0199] Determine at least one target yaw rate of the target position point, which is greater than or equal to the first threshold and has a corresponding yaw amount greater than or equal to the second threshold;

[0200] Based on the traffic status of the actual exit road corresponding to the at least one target yaw rate in the first time period, the traffic status of the road corresponding to the target position point after the first time period is determined.

[0201] In some feasible implementations, the processor 1001 is configured to:

[0202] Determine at least one first target yaw rate among the at least one target yaw rate, wherein among the actual exit roads corresponding to the first target yaw rate, there is an actual exit road with normal traffic in the first time period;

[0203] Based on the travel information of the at least one user, at least one first probability of a target navigation exit road is determined, the target navigation exit road being any navigation exit road among the navigation exit roads corresponding to the at least one first target yaw rate, and the any first probability of the target navigation exit road is used to represent the probability of abnormal traffic on the target navigation exit road after the first time period when the target navigation exit road corresponds to the corresponding first target yaw rate;

[0204] Based on the at least one first probability, a traffic status of the target navigation exit road after the first time period is determined.

[0205] In some feasible implementations, the processor 1001 is configured to:

[0206] Based on the travel information of the at least one user, determining a second probability that the target actual exit road has normal traffic after the first time period, the target actual exit road being any actual exit road with abnormal traffic in the first time period among the actual exit roads corresponding to the at least one first target yaw rate;

[0207] Based on the second probability that the target actual exit road is normally accessible after the first time period, the traffic status of the target actual exit road after the first time period is determined.

[0208] In some feasible implementations, the processor 1001 is configured to:

[0209] Based on the travel information of the at least one user, determine a first road penetration amount of at least one target entry road corresponding to the target navigation exit road and a second road penetration amount of the target navigation exit road, wherein any target entry road corresponding to the target navigation exit road is an entry road corresponding to the first target yaw rate corresponding to the target navigation exit road, the first road penetration amount is used to indicate the total number of times the at least one user passes through the corresponding target entry road in the first time period, and the second road penetration amount is used to indicate the total number of times the at least one user passes through the target navigation exit road in the first time period;

[0210] Based on the first road penetration amount and the second road penetration amount of the at least one target entering the road, at least one first probability that the target navigates out of the road is determined.

[0211] In some feasible implementations, the processor 1001 is configured to:

[0212] Determine, based on the travel information of the at least one user, a third road penetration amount of the target actual exit road, wherein the third road penetration amount is used to represent a total number of times that the at least one user passes through the target actual exit road in the first time period;

[0213] Based on the third road penetration amount, a second probability that the target actual exit road will be normally accessible after the first time period is determined.

[0214] In some feasible implementations, the processor 1001 is configured to:

[0215] Obtaining a travel trajectory of at least one user in a first time period;

[0216] A road matching the travel trajectory is determined, and the road matching the travel trajectory is determined as the travel information of the corresponding user in the first time period.

[0217] In some feasible implementations, the processor 1001 is configured to:

[0218] Determine each track point of the above-mentioned travel track;

[0219] For each of the above trajectory points, determine the angle between the trajectory direction of the trajectory point and each road, and the distance between the trajectory point and each road, and determine the matching degree between the trajectory point and each road based on the angle between the trajectory direction of the trajectory point and the road, and the distance between the trajectory point and the road;

[0220] For each of the above trajectory points, based on the matching degree between the trajectory point and each of the above roads, determining a road matching the trajectory point;

[0221] Based on the roads matching each of the trajectory points, a road matching the travel trajectory is determined.

[0222] It should be understood that in some feasible implementations, the processor 1001 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0223] In a specific implementation, the electronic device 1000 can execute the above-mentioned functions through its built-in functional modules. Figure 2 and / or Figure 7 For the implementation methods provided in each step, please refer to the implementation methods provided in the above steps for details, which will not be repeated here.

[0224] The present application also provides a computer-readable storage medium, which stores a computer program and is executed by a processor to implement Figure 2 and / or Figure 7 For the methods provided in each step, please refer to the implementation methods provided in the above steps for details, which will not be repeated here.

[0225] The computer-readable storage medium may be an internal storage unit of the device and / or electronic device provided in any of the aforementioned embodiments, such as a hard disk or memory of an electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (smart media card, SMC), a secure digital (secure digital, SD) card, a flash card (flash card), etc. equipped on the electronic device. The computer-readable storage medium may also include a disk, an optical disk, a read-only memory (read-only memory, ROM) or a random access memory (random access memory, RAM), etc. Further, the computer-readable storage medium may also include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by the electronic device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0226] The embodiment of the present application provides a computer program product or a computer program, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes Figure 2 and / or Figure 7 The methods provided in each step.

[0227] The terms "first", "second", etc. in the claims, specification and drawings of the present application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or electronic device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or electronic devices. Mentioning "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. Displaying the phrase at various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments. The term "and / or" used in the present application specification and the attached claims refers to any combination of one or more of the items listed in association and all possible combinations, and includes these combinations.

[0228] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Professional and technical personnel may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0229] The above disclosure is only the preferred embodiment of the present application, which cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A method for determining a road traffic status, characterized in that: The method comprises: determining travel information and navigation information of at least one user during a first time period; Determine a target location point based on the travel information and navigation information of the at least one user, the target location point being any location point at which an actual exit road indicated by the travel information of at least one first user is inconsistent with a navigation exit road indicated by the navigation information at the same time within the first time period; Determine at least one deviation information of the target location point, wherein any deviation information of the target location point includes an actual exit road, a navigation exit road, and an entry road of the first user corresponding to the target location point at the same time of the first time period when the actual exit road and the navigation exit road of the first user corresponding to the target location point at the same time of the first time period are inconsistent; Based on the at least one deviation information, a traffic status of the road corresponding to the target location point after the first time period is determined.

2. The method according to claim 1, characterized in that The determining, based on the at least one deviation information, before the traffic state of the road corresponding to the target location point after the first time period further includes: If the target location point is within the first time period, there is at least one second user's actual exit road indicated by the travel information that is consistent with the navigation exit road indicated by the navigation information at the same time, then at least one piece of co-navigation information of the target location point is determined, and any co-navigation information of the target location point includes an entry road and a navigation exit road of the second user corresponding to the target location point at the same time in the first time period when the actual exit road and the navigation exit road of the second user are consistent; The determining, based on the at least one deviation information, a traffic state of the road corresponding to the target location point after the first time period includes: Based on the at least one deviation information and the at least one forward heading information, a traffic status of the road corresponding to the target location point after the first time period is determined.

3. The method according to claim 2, characterized in that The determining, based on the at least one deviation information and the at least one directional information, a traffic state of the road corresponding to the target location point after the first time period includes: Determine a deviation amount of the target position point based on the deviation information corresponding to the same entry road and the same navigation exit road in the at least one deviation information; Determine a downflight amount of the target location point based on downflight information corresponding to the same entry road and the same navigation exit road in the at least one downflight information; Based on at least one deviation amount and at least one lateral heading amount of the target location point, a traffic state of the road corresponding to the target location point after the first time period is determined.

4. The method according to claim 3, characterized in that The determining, based on at least one deviation amount and at least one lateral amount of the target location point, a traffic state of the road corresponding to the target location point after the first time period includes: Determine a yaw rate of the target location point based on the yaw amount and the down-travel amount of the target location point corresponding to the same entry road and the same navigation exit road; Based on at least one yaw rate of the target location point, a traffic state of the road corresponding to the target location point after the first time period is determined.

5. The method according to claim 4, characterized in that The determining, based on at least one yaw rate of the target location point, a traffic state of the road corresponding to the target location point after the first time period includes: Determine at least one target yaw rate of the target position point, which is greater than or equal to a first threshold and whose corresponding yaw amount is greater than or equal to a second threshold; Based on the traffic status of the actual exit road corresponding to the at least one target yaw rate in the first time period, the traffic status of the road corresponding to the target position point after the first time period is determined.

6. The method according to claim 5, characterized in that The determining the traffic state of the road corresponding to the target location point after the first time period based on the traffic state of the actual exit road corresponding to the at least one target yaw rate in the first time period includes: Determining at least one first target yaw rate among the at least one target yaw rate, wherein among the actual exit roads corresponding to the first target yaw rate, there is an actual exit road with normal traffic in the first time period; Based on the travel information of the at least one user, determining at least one first probability of a target navigation exit road, the target navigation exit road being any navigation exit road among the navigation exit roads corresponding to the at least one first target yaw rate, the any first probability of the target navigation exit road being used to represent a probability of abnormal traffic on the target navigation exit road after the first time period when corresponding to the corresponding first target yaw rate; Based on the at least one first probability, a traffic status of the target navigation exit road after the first time period is determined.

7. The method according to claim 5, characterized in that The determining the traffic state of the road corresponding to the target location point after the first time period based on the traffic state of the actual exit road corresponding to the at least one target yaw rate in the first time period includes: Determine, based on the travel information of the at least one user, a second probability that a target actual exit road has normal traffic after the first time period, wherein the target actual exit road is any actual exit road that has abnormal traffic in the first time period among the actual exit roads corresponding to the at least one first target yaw rate; Based on the second probability that the target actual exit road is normally accessible after the first time period, the traffic status of the target actual exit road after the first time period is determined.

8. The method according to claim 6, characterized in that The determining, based on the travel information of the at least one user, at least one first probability that the target navigation exits the road comprises: Based on the travel information of the at least one user, determining a first road penetration amount of at least one target entry road corresponding to the target navigation exit road and a second road penetration amount of the target navigation exit road, wherein any target entry road corresponding to the target navigation exit road is an entry road corresponding to the first target yaw rate corresponding to the target navigation exit road, the first road penetration amount is used to represent the total number of times the at least one user passes through the corresponding target entry road in the first time period, and the second road penetration amount is used to represent the total number of times the at least one user passes through the target navigation exit road in the first time period; At least one first probability that the object navigates off a road is determined based on the first road penetration amount and the second road penetration amount of the at least one object entering the road.

9. The method according to claim 7, characterized in that: The determining, based on the travel information of the at least one user, a second probability that the target actual exit road is passable normally after the first time period includes: Determine, based on the travel information of the at least one user, a third road penetration amount of the target actual exit road, wherein the third road penetration amount is used to represent a total number of times that the at least one user passes through the target actual exit road in the first time period; Based on the third road penetration amount, a second probability that the target actual exit road will be normally accessible after the first time period is determined.

10. The method according to claim 1, characterized in that Determining travel information of at least one user in a first time period includes: Obtaining a travel trajectory of at least one user in a first time period; A road matching the travel trajectory is determined, and the road matching the travel trajectory is determined as the corresponding user's travel information in the first time period.

11. The method according to claim 10, characterized in that The determining of a road matching the travel trajectory comprises: Determining each track point of the travel track; For each of the trajectory points, determining an angle between the trajectory direction of the trajectory point and each road, and a distance between the trajectory point and each road, and determining a matching degree between the trajectory point and each road based on the angle between the trajectory direction of the trajectory point and the road, and the distance between the trajectory point and the road; For each of the trajectory points, based on the matching degree between the trajectory point and each of the roads, determining a road matching the trajectory point; Based on the roads matching the trajectory points, a road matching the travel trajectory is determined.

12. A device for determining a road traffic status, characterized in that: The device comprises: an information determination module, configured to determine travel information and navigation information of at least one user in a first time period; a location determination module, configured to determine a target location point based on the travel information and navigation information of the at least one user, the target location point being any location point at which, within the first time period, there is a location point where an actual exit road indicated by the travel information of at least one first user is inconsistent with a navigation exit road indicated by the navigation information at the same time; The information determination module is used to determine at least one deviation information of the target location point, wherein any deviation information of the target location point includes an actual exit road, a navigation exit road, and an entry road of the first user corresponding to the target location point at the same time of the first time period when the actual exit road and the navigation exit road of the first user corresponding to the target location point at the same time of the first time period are inconsistent; A state determination module is used to determine the traffic state of the road corresponding to the target location point after the first time period based on the at least one deviation information.

13. An electronic device, characterized in that: comprising a processor and a memory, wherein the processor and the memory are connected to each other; The memory is used to store computer programs; The processor is configured to execute the method according to any one of claims 1 to 11 when calling the computer program.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 11.

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