Vehicle direction prediction method and device, computer equipment and storage medium

Abstract

The invention relates to a vehicle direction prediction method and device, computer equipment and a storage medium. The method comprises the steps that if it is detected that vehicle static time reaches first preset time, a position point set of a vehicle in second preset time is obtained, the position point set comprises a plurality of position points, each position point is associated with a vehicle head angle, and a current vehicle head angle corresponding to the vehicle is calculated according to the vehicle head angle of each position point; and determining the current headstock direction of the vehicle in the static state according to the current headstock angle. By adopting the method, the vehicle head direction of the vehicle in a specific scene can be accurately predicted.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a vehicle direction prediction method, device, computer equipment and storage medium. Background Art

[0002] Existing navigation systems mainly rely on Global Positioning System (GPS) signals to determine the location of the vehicle. However, in certain specific situations, such as tunnels or underground parking lots where the GPS signal is weak or the vehicle is stationary for a long time, the vehicle will repeatedly report the same location point, and the navigation system may not be able to accurately determine the direction of the vehicle, which will cause deviations in the navigation guidance. Summary of the invention

[0003] Based on this, it is necessary to provide a vehicle direction prediction method, device, computer equipment and storage medium that can accurately predict the vehicle's front direction in a specific scenario in response to the above technical problems.

[0004] A vehicle direction prediction method, the method comprising:

[0005] If it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, the position point set including a plurality of position points, each position point being associated with a vehicle head angle;

[0006] Calculate the current head angle of the vehicle according to the head angle of each position point;

[0007] The current front direction of the vehicle in a stationary state is determined according to the current front angle.

[0008] In one embodiment, determining the current front direction of the vehicle in a stationary state according to the current front angle includes:

[0009] Get the starting position and ending position of the vehicle;

[0010] Generate a navigation route based on the starting location, current vehicle heading, and end location.

[0011] In one embodiment, if it is detected that the vehicle is stationary for a first preset time, obtaining a set of position points of the vehicle within a second preset time includes:

[0012] Get the vehicle stationary time corresponding to the vehicle;

[0013] Determining whether the vehicle stationary time reaches a first preset time;

[0014] If it is reached, the preset sampling interval, the second preset time and the vehicle stationary start time are obtained;

[0015] Within a second preset time before the vehicle stationary start time, a plurality of position points are collected according to a preset sampling interval to obtain a position point set.

[0016] In one embodiment, calculating the current head angle of the vehicle according to the head angle of each position point includes:

[0017] Get the weight corresponding to each location point;

[0018] The target vehicle head angle corresponding to each position point is calculated according to the weight of each position point and the vehicle head angle;

[0019] The current head angle of the vehicle is calculated based on each target head angle.

[0020] In one embodiment, the target vehicle head angle corresponding to each position point is calculated according to the weight of each position point and the vehicle head angle, including:

[0021] Calculate the product of the weight of each position point and the vehicle head angle to obtain the target vehicle head angle corresponding to each position point;

[0022] Among them, the current vehicle head angle corresponding to the vehicle is calculated according to each target vehicle head angle, including:

[0023] The mean of each target vehicle head angle is calculated to obtain the current vehicle head angle corresponding to the vehicle.

[0024] In one embodiment, before obtaining the weight corresponding to each position point, the process includes:

[0025] Get the current time corresponding to each location point;

[0026] Get the vehicle stationary start time corresponding to the vehicle;

[0027] The time interval corresponding to each position point is calculated based on each current moment and the vehicle stationary start time;

[0028] The weight corresponding to each location point is set according to each time interval.

[0029] In one embodiment, before calculating the current head angle of the vehicle according to the head angle of each position point, the method further includes:

[0030] Obtain the signal strength and position coordinates corresponding to each position point in the position point set;

[0031] Filtering each position point in the position point set according to signal strength, position coordinates and vehicle head angle to obtain a filtered position point set; and / or

[0032] Get the current road network information corresponding to the vehicle;

[0033] The location points in the location point set are screened according to the current road network information to obtain a screened location point set.

[0034] A vehicle direction prediction device, the device comprising:

[0035] A detection module, configured to obtain a position point set of the vehicle within a second preset time if it is detected that the vehicle is stationary for a first preset time, wherein the position point set includes a plurality of position points, each position point being associated with a vehicle head angle;

[0036] A calculation module, used to calculate the current head angle of the vehicle according to the head angle of each position point;

[0037] The prediction module is used to determine the current head direction of the vehicle when it is stationary based on the current head angle.

[0038] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0039] If it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, the position point set including a plurality of position points, each position point being associated with a vehicle head angle;

[0040] Calculate the current head angle of the vehicle according to the head angle of each position point;

[0041] The current front direction of the vehicle in a stationary state is determined according to the current front angle.

[0042] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0043] If it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, the position point set including a plurality of position points, each position point being associated with a vehicle head angle;

[0044] Calculate the current head angle of the vehicle according to the head angle of each position point;

[0045] The current front direction of the vehicle in a stationary state is determined according to the current front angle.

[0046] The above-mentioned vehicle direction prediction method, device, computer equipment and storage medium, if it is detected that the vehicle is stationary for a first preset time, then obtain the vehicle's position point set within a second preset time, the position point set includes multiple position points, each position point is associated with a vehicle head angle, the current vehicle head angle corresponding to the vehicle is calculated based on the vehicle head angle of each position point, and the current vehicle head direction of the vehicle in a stationary state is determined based on the current vehicle head angle.

[0047] Among them, if the vehicle is stationary for a long time, it will repeatedly report the same position information, so it is impossible to determine the actual front direction of the vehicle when it is stationary. By detecting that the vehicle has been stationary for a long time, the actual front direction of the vehicle in the stationary state is predicted by the front angle of each position point in the position point concentration before the vehicle stops, and the front direction of the vehicle in a specific scenario can be accurately predicted. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A diagram showing an application environment of a vehicle direction prediction method in an embodiment;

[0049] Figure 2 A schematic diagram of a process flow of a vehicle direction prediction method in one embodiment;

[0050] Figure 3 It is a schematic diagram of a flow chart of a current vehicle head direction prediction step in one embodiment;

[0051] Figure 4 It is a flowchart of the step of obtaining a location point set in one embodiment;

[0052] Figure 5 It is a schematic diagram of a flow chart of a step of calculating the current vehicle head angle in one embodiment;

[0053] Figure 6 A schematic diagram of a flow chart of a step of setting a position point weight in one embodiment;

[0054] Figure 7 is a flow chart of a location point set screening step in one embodiment;

[0055] Figure 8 is a flow chart of a location point set screening step in one embodiment;

[0056] Fig. 9 is a structural block diagram of a vehicle direction prediction device in one embodiment;

[0057] Fig.10 is an internal structure diagram of a computer device in one embodiment;

[0058] Fig.11 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

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

[0060] The vehicle direction prediction method provided in this application can be applied to Figure 1 In the application environment shown, the vehicle terminal 102 communicates with the server 104 through a network. The vehicle terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices connected to the vehicle, and the server 104 can be implemented as an independent server or a server cluster composed of multiple servers.

[0061] Specifically, when the vehicle terminal 102 detects that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, the position point set includes multiple position points, each position point is associated with a vehicle head angle, and is sent to the server 104. The server 104 receives the position point set sent by the vehicle terminal 102, calculates the current vehicle head angle corresponding to the vehicle according to the vehicle head angle of each position point, and determines the current vehicle head direction of the vehicle in a stationary state according to the current vehicle head angle.

[0062] In another embodiment, if the vehicle terminal 102 detects that the vehicle is stationary for a first preset time, it obtains a set of position points of the vehicle within a second preset time, where the set of position points includes multiple position points, each position point is associated with a vehicle head angle, and the current vehicle head angle corresponding to the vehicle is calculated based on the vehicle head angle of each position point, and the current vehicle head direction of the vehicle in a stationary state is determined based on the current vehicle head angle.

[0063] In one embodiment, Figure 2 As shown, a vehicle direction prediction method is provided, and the method is applied to Figure 1 The vehicle terminal or server in the example is used to illustrate, including the following steps:

[0064] Step 202: If it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, where the position point set includes a plurality of position points, each of which is associated with a vehicle head angle.

[0065] Among them, the vehicle stationary time is the length of time the vehicle is stationary, and the length of time the vehicle starts to stop traveling. The first preset time is the preset vehicle stationary time, which is used to determine whether the vehicle is stationary for a long time. It can be determined in advance based on actual business needs, actual product needs or actual application scenarios. For example, the first preset time is 10 minutes.

[0066] Among them, the second preset time is a preset time period for location point collection, which can be determined according to actual business needs, actual product needs or actual application scenarios. For example, the second preset time is 30 seconds.

[0067] Among them, the position point is the position coordinate point of the vehicle in the second time, such as longitude and latitude, and each position point is associated with a vehicle head angle. The vehicle head angle here is the angle of the vehicle head at the position point.

[0068] Specifically, when it is detected that the vehicle has stopped driving, the vehicle's stationary time is recorded. When the vehicle's stationary time reaches a first preset time, it means that the vehicle has been stationary for a long time. Then, the various position points of the vehicle within a second preset time can be collected to obtain a position point set, and each position point is associated with the angle of the vehicle's front at that position point, that is, each position point is associated with a vehicle front angle.

[0069] Step 204, calculating the current vehicle head angle corresponding to the vehicle according to the vehicle head angle at each position point.

[0070] The current front angle is the current front angle of the vehicle when it is stationary. After obtaining the position point set, the current front angle of the vehicle when it is stationary can be obtained based on the front angle of each position point. The calculation can be an average calculation, a weighted calculation, or a preset formula calculation, and the current front angle of the vehicle when it is stationary can be predicted by the front angle of each position point in the position point set.

[0071] Step 206, determining the current vehicle head direction of the vehicle in a stationary state according to the current vehicle head angle.

[0072] Specifically, after obtaining the current vehicle head angle, the current vehicle head direction of the vehicle in a stationary state can be determined according to the current vehicle head angle. For example, if the current vehicle head angle is 5.6 degrees, the current vehicle head direction is 5.6 degrees east of due north, and if the current vehicle head angle is -5.6 degrees, the current vehicle head direction is 5.6 degrees west of due north.

[0073] In the above vehicle direction prediction method, if it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, and the position point set includes multiple position points, each position point is associated with a vehicle head angle, and the current vehicle head angle corresponding to the vehicle is calculated based on the vehicle head angle of each position point, and the current vehicle head direction of the vehicle in a stationary state is determined based on the current vehicle head angle.

[0074] Among them, if the vehicle is stationary for a long time, it will repeatedly report the same position information, so it is impossible to determine the actual front direction of the vehicle when it is stationary. By detecting that the vehicle has been stationary for a long time, the actual front direction of the vehicle in the stationary state is predicted by the front angle of each position point in the position point concentration before the vehicle stops, and the front direction of the vehicle in a specific scenario can be accurately predicted.

[0075] In one embodiment, Figure 3 As shown, the current vehicle head direction of the vehicle in a stationary state is determined according to the current vehicle head angle, including:

[0076] Step 302, obtaining the starting position and ending position corresponding to the vehicle.

[0077] Step 304, generating a navigation route according to the starting position, the current vehicle head direction and the ending position.

[0078] Among them, the starting position is the current stationary position of the vehicle, and the ending position is the position of the destination that the vehicle needs to reach. The starting position, the ending position and the current vehicle head direction can be used to generate a navigation route suitable for the vehicle. When the vehicle starts again, the vehicle head direction when it is stationary is taken into consideration. The navigation route generated in this way is more accurate and reliable, avoiding misjudgment.

[0079] For example, if the current vehicle head direction is due east, and the route planned based on the starting and ending positions should be due east, then when the vehicle starts, the navigation will guide the vehicle to go straight. In the current navigation system, the default vehicle head direction is due north when the vehicle is stationary. If the route planned based on the starting and ending positions should be due east, the vehicle will be guided to turn left, but the actual vehicle head direction is already due east, so the vehicle can be directly guided to go straight.

[0080] In one embodiment, Figure 4 As shown, if it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, including:

[0081] Step 402, obtaining the vehicle stationary time corresponding to the vehicle.

[0082] Step 404, determining whether the vehicle stationary time reaches a first preset time.

[0083] Step 406: If reached, obtain the preset sampling interval, the second preset time and the vehicle stationary start time.

[0084] Step 408 : within a second preset time before the vehicle stationary start time, a plurality of position points are collected at a preset sampling interval to obtain a position point set.

[0085] Among them, the vehicle stationary time is the length of time the vehicle is stationary. The vehicle stationary time can be used to determine whether the vehicle is stationary for a long time. Therefore, when it is detected that the vehicle begins to stationary, the vehicle stationary time is recorded. When the vehicle stationary time reaches the first preset time, it means that the vehicle has been stationary for a long time. Therefore, when starting again, it is necessary to determine the current front direction of the vehicle.

[0086] Among them, the preset sampling interval is the interval between the collection of each location point within the second preset time, which can be determined according to actual business needs, actual product needs or actual application scenarios. For example, the preset sampling interval is 5 seconds.

[0087] Among them, the second preset time is a preset time period for location point collection, which can be determined according to actual business needs, actual product needs or actual application scenarios. For example, the second preset time is 30 seconds.

[0088] The vehicle stationary start time is the time point when the vehicle starts to stop. Specifically, when the vehicle stationary time reaches the first preset time, the preset sampling interval, the second preset time and the vehicle stationary start time are obtained, and the vehicle stationary start time is taken as the starting time point. Within the second preset time, multiple position points are collected according to the preset sampling interval to obtain a position point set.

[0089] For example, the position points 30 seconds forward from the vehicle's stationary start time are obtained, and a total of 60 position points are extracted, with one position point collected every 5 seconds. Among them, the second preset time is 30 seconds, the preset sampling interval is 5 seconds, and the 60 position points constitute a position point set.

[0090] In one embodiment, Figure 5 As shown, the current head angle of the vehicle corresponding to each position point is calculated according to the head angle of each position point, including:

[0091] Step 502: Obtain the weight corresponding to each position point.

[0092] Step 504, calculating the target vehicle head angle corresponding to each position point according to the weight of each position point and the vehicle head angle.

[0093] Step 506, calculating the current vehicle head angle corresponding to the vehicle according to each target vehicle head angle.

[0094] Among them, the weight here refers to the importance of the location point in the location point set. Different location points may correspond to different weights. The weight of the location point can be determined according to the time interval between the time point where the location point is located and the start time of the vehicle's stationary state. The larger the weight corresponding to the location point that is closer to the start time of the vehicle's stationary state, the smaller the weight corresponding to the location point that is farther from the start time point of the vehicle's stationary state.

[0095] Of course, the weight of each location point can also be determined based on the signal strength of the location point, or based on the location point and road network information. The weight of each location point can also be determined based on actual business needs, actual product needs or actual application scenarios.

[0096] Specifically, the weight corresponding to each position point in the position point set is obtained, and the target vehicle head angle corresponding to each position point is calculated by the weight of each position point and the vehicle head angle, and then the current vehicle head angle corresponding to the vehicle is calculated by the target vehicle head angle corresponding to each position point. The target vehicle head angle here is the value calculated by the weight of the position point and the vehicle head angle, which can be a product or a weighted sum value.

[0097] In one embodiment, the target vehicle head angle corresponding to each position point is calculated based on the weight of each position point and the vehicle head angle, including: calculating the product between the weight of each position point and the vehicle head angle to obtain the target vehicle head angle corresponding to each position point.

[0098] Among them, the current vehicle head angle corresponding to the vehicle is calculated according to each target vehicle head angle, including:

[0099] The mean of each target vehicle head angle is calculated to obtain the current vehicle head angle corresponding to the vehicle.

[0100] The target vehicle head angle may be the product of the weight of the position point and the vehicle head angle. Specifically, the target vehicle head angle corresponding to each position point may be obtained by performing a product calculation between the weight of each position point and the vehicle head angle.

[0101] Furthermore, the target vehicle head angles at each position point are averaged to obtain the average value, which is determined as the current vehicle head angle corresponding to the vehicle. That is, each position point is calculated according to the weight and the vehicle head angle, and then the average value is taken to obtain the current vehicle head angle.

[0102] For example, the weight of point A is x1, the front angle is a, the weight of point B is x2, the front angle is b, the weight of point C is x3, the front angle is c, and the current front angle is: (x1*a+x2*b+x3*c) / 3.

[0103] In one embodiment, Figure 6 As shown, before obtaining the weights corresponding to each location point, it includes:

[0104] Step 602, obtaining the current time corresponding to each location point.

[0105] Step 604, obtaining the vehicle stationary start time corresponding to the vehicle.

[0106] Step 606: calculate the time interval corresponding to each position point based on each current moment and the vehicle stationary start time.

[0107] Step 608: setting the weight corresponding to each location point according to each time interval.

[0108] Among them, before obtaining the weight corresponding to each position point, the weight corresponding to each position point can be set, which can be determined according to the time interval between the time point where the position point is located and the start time of the vehicle stationary. The weight corresponding to the position point that is closer to the start time of the vehicle stationary is larger, and the weight corresponding to the position point that is farther away from the start time of the vehicle stationary is smaller.

[0109] The current time is the time point at which the location point is located. Each location point has a corresponding event point, and the current time corresponding to each location point is obtained.

[0110] The vehicle stationary start time is the time point when the vehicle starts to stationary. Specifically, the interval between the current time of each position point and the vehicle stationary start time is calculated to obtain the time interval corresponding to each position point. Furthermore, the weight corresponding to each position point is set according to each time interval, and the weight corresponding to the position point close to the vehicle stationary start time is larger, and the weight corresponding to the position point far from the vehicle stationary start time is smaller.

[0111] For example, the position signal closest to the vehicle's stationary start time has a higher weight, and the specific weights are as follows:

[0112] 1.51% (farthest point), 1.53%, 1.55%, 1.57%, 1.59%, 1.61%, 1.63%, 1.65%, 1.67%, 1.69%, 1.71%, 1.73%, 1.75%, 1.77%, 1.79%, 1.81%, 1.83%, 1.85%, 1.87%, 1.89%, 1.91%, 1.93%, 1.95%, 1.97%, 1.99% ,2.01%,2.03%,2.05%,2.07%,2.09%,2.11%,2.13%,2.15%,2.17%,2.19%,2.21%,2.23%,2.25%,2.27%,2.29%,2.31%,2.33%,2.35%,2.37%,2.39%,2.41%,2.43%,2.45%,2.47%,2.49% (recent points)

[0113] In one embodiment, Figure 7 As shown, before calculating the current head angle of the vehicle according to the head angle of each position point, the following steps are also included:

[0114] Step 702: Obtain the signal strength and position coordinates corresponding to each position point in the position point set.

[0115] Step 704, filtering each position point in the position point set according to the signal strength, position coordinates and vehicle head angle to obtain a filtered position point set.

[0116] After obtaining the location point set, each location point in the location point set may be subjected to abnormal point removal and outlier filtering processing to obtain a filtered location point set.

[0117] Among them, the screening can be performed based on the signal strength, location coordinates and front angle of the location point. Specifically, the signal strength and location coordinates corresponding to each location point in the location point set are obtained. The signal strength is the signal strength of the location point, and the location coordinates are the longitude and latitude of the location point.

[0118] Furthermore, the position points whose signal strength is less than or equal to the signal strength threshold may be filtered, or the position points whose distance between the position coordinates and other position coordinates exceeds the distance threshold may be filtered, or the position points whose vehicle head angle exceeds the angle threshold may be filtered, and the position point set is filtered and screened by the signal strength, position coordinates and vehicle head angle to obtain the filtered position point set. In one embodiment, Figure 8 As shown, before calculating the current head angle of the vehicle according to the head angle of each position point, the following steps are also included:

[0119] Step 802, obtaining the current road network information corresponding to the vehicle.

[0120] Step 802: Filter each location point in the location point set according to the current road network information to obtain a filtered location point set.

[0121] Among them, the current road network information is a road system composed of various roads that are interconnected and interwoven into a network distribution within a certain area. The current road network information where the vehicle is currently located is obtained, and the location points in the location point set are screened through the current road network information to obtain a screened location point set.

[0122] For example, if a vehicle goes straight on a certain road, then turns right, and then stops, all the position points collected by the vehicle when going straight can be filtered out according to the current road network information, leaving only the position points on the right-turn road to obtain a position point set.

[0123] For another example, the location points are offset to points outside the H3 grid in the current road network information, the points with abnormal speed are removed, and the remaining points form a location point set.

[0124] In a specific application scenario, a vehicle direction prediction method is provided, which can be described in detail through the following steps:

[0125] 1. Case scenario: A vehicle has been stationary for 10 minutes at a certain location. When it starts again, it is impossible to determine the direction of the vehicle for route planning. It is necessary to use a prediction method to predict the direction and provide reliable user guidance and route planning. 2. Specific embodiments:

[0127] (1) Obtaining point information: The system obtains the point information 30 seconds before the most recent point, and extracts a total of 60 points (reporting a point every 5 seconds);

[0128] (2) Noise reduction: remove the points outside the H3 grid and the points with abnormal speed, leaving 50 points and extracting the direction angle (based on true north);

[0129] (3) Algorithm prediction: weight calculation based on the reporting time of 50 points;

[0130] a. The position signal of the closest point in time has a higher weight, and the specific weights are as follows:

[0131] 1.51% (farthest point), 1.53%, 1.55%, 1.57%, 1.59%, 1.61%, 1.63%, 1.65%, 1.67%, 1.69%, 1.71%, 1.73%, 1.75%, 1.77%, 1.79%, 1.81%, 1.83%, 1.85%, 1.87%, 1.89%, 1.91%, 1.93%, 1.95%, 1.97%, 1.99% ,2.01%,2.03%,2.05%,2.07%,2.09%,2.11%,2.13%,2.15%,2.17%,2.19%,2.21%,2.23%,2.25%,2.27%,2.29%,2.31%,2.33%,2.35%,2.37%,2.39%,2.41%,2.43%,2.45%,2.47%,2.49% (recent points)

[0132] b. Calculate the angle of each point according to the weight (the point angles are no longer enumerated one by one), and then take the average value, the angle is 5.6 degrees (5.6 degrees east of due north)

[0133] (4) Route planning is performed according to the direction, and the system prompts the vehicle in the direction it needs to travel next. It should be understood that although the various steps in the above flowchart are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least part of the steps in the above flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0134] In one embodiment, Fig. 9As shown, a vehicle direction prediction device 900 is provided, comprising: a detection module 902, a calculation module 904 and a prediction module 906, wherein:

[0135] The detection module 902 is used to obtain a position point set of the vehicle within a second preset time if it is detected that the vehicle is stationary for a first preset time. The position point set includes multiple position points, and each position point is associated with a vehicle head angle.

[0136] The calculation module 904 is used to calculate the current head angle of the vehicle according to the head angle of each position point.

[0137] The prediction module 906 is used to determine the current vehicle head direction of the vehicle in a stationary state according to the current vehicle head angle.

[0138] In one embodiment, the calculation module 904 obtains the starting position and the ending position corresponding to the vehicle, and generates a navigation route according to the starting position, the current vehicle head direction and the ending position.

[0139] In one embodiment, the detection module 902 obtains the vehicle stationary time corresponding to the vehicle, determines whether the vehicle stationary time reaches a first preset time, and if so, obtains a preset sampling interval, a second preset time, and a vehicle stationary start time, and collects multiple position points according to a preset sampling interval within the second preset time before the vehicle stationary start time to obtain a position point set.

[0140] In one embodiment, the calculation module 904 obtains the weight corresponding to each position point, calculates the target vehicle head angle corresponding to each position point based on the weight of each position point and the vehicle head angle, and calculates the current vehicle head angle corresponding to the vehicle based on each target vehicle head angle.

[0141] In one embodiment, the calculation module 904 calculates the product of the weight of each position point and the vehicle head angle to obtain the target vehicle head angle corresponding to each position point, and performs mean calculation on each target vehicle head angle to obtain the current vehicle head angle corresponding to the vehicle.

[0142] In one embodiment, the calculation module 904 obtains the current time corresponding to each position point, obtains the vehicle stationary start time corresponding to the vehicle, calculates the time interval corresponding to each position point according to each current time and the vehicle stationary start time, and sets the weight corresponding to each position point according to each time interval.

[0143] In one embodiment, the vehicle direction prediction device 900 obtains the signal strength and position coordinates corresponding to each position point in the position point set, and filters each position point in the position point set according to the signal strength, position coordinates and vehicle head angle to obtain a filtered position point set.

[0144] In one embodiment, the vehicle direction prediction device 900 obtains the current road network information corresponding to the vehicle, and filters each position point in the position point set according to the current road network information to obtain a filtered position point set.

[0145] For the specific definition of the vehicle direction prediction device, please refer to the definition of the vehicle direction prediction method above, which will not be repeated here. Each module in the above-mentioned vehicle direction prediction device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0146] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store a set of location points. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle direction prediction method is implemented.

[0147] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.11 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle direction prediction method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0148] Those skilled in the art will understand that Fig.10 or Fig.11The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0149] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented: if it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, the position point set includes a plurality of position points, each position point is associated with a vehicle head angle, a current vehicle head angle corresponding to the vehicle is calculated based on the vehicle head angle of each position point, and a current vehicle head direction of the vehicle in a stationary state is determined based on the current vehicle head angle.

[0150] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the starting position and the ending position corresponding to the vehicle, and generating a navigation route according to the starting position, the current vehicle head direction and the ending position.

[0151] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the vehicle stationary time corresponding to the vehicle, determining whether the vehicle stationary time reaches a first preset time, and if so, obtaining a preset sampling interval, a second preset time, and a vehicle stationary start time, and collecting multiple position points according to a preset sampling interval within a second preset time before the vehicle stationary start time to obtain a position point set.

[0152] In one embodiment, when the processor executes the computer program, it also implements the following steps: obtaining the weight corresponding to each position point, calculating the target vehicle head angle corresponding to each position point based on the weight of each position point and the vehicle head angle, and calculating the current vehicle head angle corresponding to the vehicle based on each target vehicle head angle.

[0153] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the product between the weight of each position point and the vehicle head angle is calculated to obtain the target vehicle head angle corresponding to each position point.

[0154] In one embodiment, when the processor executes the computer program, the following steps are also implemented: average calculation is performed on each target vehicle head angle to obtain the current vehicle head angle corresponding to the vehicle.

[0155] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the current time corresponding to each position point, obtaining the vehicle stationary start time corresponding to the vehicle, calculating the time interval corresponding to each position point based on each current time and the vehicle stationary start time, and setting the weight corresponding to each position point according to each time interval.

[0156] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the signal strength and position coordinates corresponding to each position point in the position point set, filtering each position point in the position point set according to the signal strength, position coordinates and vehicle head angle, and obtaining a filtered position point set.

[0157] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining current road network information corresponding to the vehicle, filtering each position point in the position point set according to the current road network information, and obtaining a filtered position point set.

[0158] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: if it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, the position point set includes multiple position points, each position point is associated with a vehicle head angle, the current vehicle head angle corresponding to the vehicle is calculated based on the vehicle head angle of each position point, and the current vehicle head direction of the vehicle in a stationary state is determined based on the current vehicle head angle.

[0159] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the starting position and the ending position corresponding to the vehicle, and generating a navigation route according to the starting position, the current vehicle head direction and the ending position.

[0160] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the vehicle stationary time corresponding to the vehicle, determining whether the vehicle stationary time reaches a first preset time, and if so, obtaining a preset sampling interval, a second preset time and a vehicle stationary start time, and collecting multiple position points according to a preset sampling interval within a second preset time before the vehicle stationary start time to obtain a position point set.

[0161] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the weight corresponding to each position point, calculating the target vehicle head angle corresponding to each position point based on the weight of each position point and the vehicle head angle, and calculating the current vehicle head angle corresponding to the vehicle based on each target vehicle head angle.

[0162] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the product between the weight of each position point and the vehicle head angle is calculated to obtain the target vehicle head angle corresponding to each position point.

[0163] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: average calculation is performed on each target vehicle head angle to obtain the current vehicle head angle corresponding to the vehicle.

[0164] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the current time corresponding to each position point, obtaining the vehicle stationary start time corresponding to the vehicle, calculating the time interval corresponding to each position point based on each current time and the vehicle stationary start time, and setting the weight corresponding to each position point according to each time interval.

[0165] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the signal strength and position coordinates corresponding to each position point in the position point set, filtering each position point in the position point set according to the signal strength, position coordinates and vehicle head angle, and obtaining a filtered position point set.

[0166] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining current road network information corresponding to the vehicle, filtering each position point in the position point set according to the current road network information, and obtaining a filtered position point set.

[0167] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0168] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0169] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A vehicle direction prediction method, the method comprising: If it is detected that the vehicle is stationary for a first preset time, a position point set of the vehicle within a second preset time is obtained, wherein the position point set includes a plurality of position points, each of which is associated with a vehicle head angle; Calculating the current head angle of the vehicle according to the head angle of each position point; The current vehicle head direction of the vehicle in a stationary state is determined according to the current vehicle head angle.

2. The method according to claim 1, characterized in that The determining the current vehicle head direction of the vehicle in a stationary state according to the current vehicle head angle includes: Obtaining the starting position and ending position corresponding to the vehicle; A navigation route is generated according to the starting position, the current vehicle head direction and the ending position.

3. The method according to claim 1, characterized in that: If it is detected that the vehicle is stationary for a first preset time, obtaining a position point set of the vehicle within a second preset time includes: Obtaining a vehicle stationary time corresponding to the vehicle; Determining whether the vehicle stationary time reaches a first preset time; If it is reached, the preset sampling interval, the second preset time and the vehicle stationary start time are obtained; Within the second preset time before the vehicle stationary start time, a plurality of position points are collected according to the preset sampling interval to obtain the position point set.

4. The method according to claim 1, characterized in that: The calculating the current head angle of the vehicle according to the head angle of each position point includes: Obtaining the weight corresponding to each of the position points; Calculate the target vehicle head angle corresponding to each position point according to the weight of each position point and the vehicle head angle; The current vehicle head angle corresponding to the vehicle is calculated according to each of the target vehicle head angles.

5. The method according to claim 4, characterized in that The step of calculating the target vehicle head angle corresponding to each position point according to the weight of each position point and the vehicle head angle includes: Calculate the product of the weight of each position point and the vehicle head angle to obtain the target vehicle head angle corresponding to each position point; Wherein, the calculating according to each of the target vehicle head angles to obtain the current vehicle head angle corresponding to the vehicle includes: The mean of each target vehicle head angle is calculated to obtain the current vehicle head angle corresponding to the vehicle.

6. The method according to claim 4, characterized in that Before obtaining the weights corresponding to the position points, the method includes: Obtaining the current time corresponding to each of the position points; Obtaining a vehicle stationary start time corresponding to the vehicle; The time interval corresponding to each of the position points is calculated based on each of the current moments and the vehicle stationary start time; The weight corresponding to each of the position points is set according to each of the time intervals.

7. The method according to claim 1, characterized in that Before calculating the current vehicle head angle corresponding to the vehicle according to the vehicle head angles at each of the position points, the method further includes: Obtaining the signal strength and position coordinates corresponding to each of the position points in the position point set; Filtering each of the position points in the position point set according to the signal strength, the position coordinates and the vehicle head angle to obtain a filtered position point set; and / or Obtaining current road network information corresponding to the vehicle; The location points in the location point set are screened according to the current road network information to obtain a screened location point set.

8. A vehicle direction prediction device, characterized in that: The device comprises: A detection module, configured to obtain a position point set of the vehicle within a second preset time if it is detected that the vehicle is stationary for a first preset time, wherein the position point set includes a plurality of position points, each of which is associated with a vehicle head angle; A calculation module, used for calculating the current head angle of the vehicle according to the head angle of each position point; The prediction module is used to determine the current vehicle head direction of the vehicle in a stationary state according to the current vehicle head angle.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images