Vehicle track dynamic display method and system, medium and electronic equipment

Abstract

The invention provides a vehicle track dynamic display method and system, a medium and electronic equipment, relates to the technical field of spatial data visualization, is applied to a back-end thread, and comprises the steps that an initial point location data set of a vehicle is periodically acquired, and elements in the initial point location data set comprise corresponding coordinate information of the vehicle in a browser front-end map; obtaining a target point location data set obtained by preprocessing the initial point location data set in the previous period; the target point location data set is sent to a browser main thread for rendering processing, and an initial track dynamic display animation is obtained; and based on the CPU remaining condition of the back-end thread, performing filtering processing on the initial track dynamic display animation to obtain a vehicle track dynamic display animation. The problem that in the prior art, when the vehicle track is dynamically displayed through a browser, a user needs to wait for a long time is solved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of spatial data visualization, and in particular to a method, system, medium, and electronic device for dynamically displaying vehicle trajectories. Background Art

[0002] Currently, autonomous driving requires large-scale vehicle trajectory data and real-time display of location changes. However, when autonomous driving services are connected to the internet and require browser-based visualization, and when the browser simultaneously monitors a large number of vehicles, the browser's limited computing resources and the enormous amount of computation required for visualization lead to very low browser computing efficiency. This results in very long wait times for users when visualizing data through the browser. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present disclosure provides a method, system, medium and electronic device for dynamically displaying vehicle trajectories, which solves the problem in the existing technology that users need to wait for a long time when dynamically displaying vehicle trajectories through a browser.

[0004] At least one embodiment of the present disclosure provides a method for dynamically displaying vehicle trajectories, which is applied to a backend thread and includes:

[0005] Periodically acquiring an initial point location dataset of a vehicle, wherein the elements in the initial point location dataset include coordinate information corresponding to the vehicle in a browser front-end map;

[0006] Acquire a target point data set obtained by preprocessing the initial point data set in the previous cycle, wherein the preprocessing includes removing abnormal data from the initial point data set and completing missing data;

[0007] Send the target point data set to the browser main thread for rendering processing to obtain the initial trajectory dynamic display animation;

[0008] Based on the remaining CPU of the backend thread, the initial trajectory dynamic display animation is filtered to obtain the vehicle trajectory dynamic display animation.

[0009] The technical solution provided by this disclosure has at least the following beneficial effects:

[0010] The present disclosure places the data rendering step of the previous cycle into the browser main thread, and places all other steps that require calculation and processing into the backend thread for operation. By separating the execution environments of the two, dual-thread parallel processing of data processing and rendering can be achieved, forming a double buffer structure. Moreover, since the browser renders the point data that has been processed in the previous cycle, on the one hand, it can also effectively avoid the backend thread and the browser main thread from operating the same memory area, reducing resource competition and screen tearing. On the other hand, this method can perform incremental processing on the point data of the newly added cycle instead of full calculation, thereby further reducing the rendering pressure of the main thread.

[0011] Through this processing method, data processing and rendering are decoupled on the browser side, balancing computing resource usage with real-time requirements. This effectively solves the performance bottleneck problem of dynamically displaying large-scale spatial data in vehicle trajectories and significantly reduces the waiting time required by users.

[0012] In a method for dynamically displaying a vehicle trajectory provided in one embodiment of the present disclosure, the preprocessing step includes:

[0013] Detecting abnormal point data in the initial point data set and removing the abnormal point data to obtain an intermediate point data set;

[0014] Determining the locations of missing points in the intermediate point data set where data is missing;

[0015] Obtain the missing point status of the missing point position, and complete the intermediate point data set based on the missing point status to obtain the target point data set; the missing point status includes the missing time period being greater than a preset threshold and the missing time period being less than or equal to the preset threshold.

[0016] The technical solution provided by this disclosure has at least the following beneficial effects:

[0017] By removing and completing abnormal point data, the accuracy of the vehicle trajectory displayed on the browser can be improved. At the same time, according to different missing point states, different methods are used to complete the intermediate point data, which can improve the accuracy of the completed data in a targeted manner.

[0018] In a vehicle trajectory dynamic display method provided by one embodiment of the present disclosure, obtaining the missing point status of the missing point position, and completing the intermediate point data set based on the missing point status to obtain the target point data set includes:

[0019] Acquire a missing point status of the missing point position, and determine that the missing point status is characterized by a missing time period being less than or equal to a preset threshold;

[0020] The intermediate point data set is completed using a linear interpolation method to obtain the target point data set.

[0021] The technical solution provided by this disclosure has at least the following beneficial effects:

[0022] When the missing time period is less than or equal to the preset threshold, linear interpolation can be used to supplement the missing data, so as to minimize the demand for computing resources while ensuring the accuracy of the supplemented data.

[0023] In a vehicle trajectory dynamic display method provided by one embodiment of the present disclosure, obtaining the missing point status of the missing point position, and completing the intermediate point data set based on the missing point status to obtain the target point data set includes:

[0024] Acquire a missing point status of the missing point position, and determine that the missing point status is characterized by a missing time period being greater than a preset threshold;

[0025] Acquire multiple point data within a preset time period before and after the missing point location, and determine whether the changes between the point data show a preset motion pattern; if the changes between the point data show a preset motion pattern, establish a motion model according to the motion pattern;

[0026] The motion model is used to complete the intermediate point data set to obtain the target point data set.

[0027] The technical solution provided by this disclosure has at least the following beneficial effects:

[0028] When the missing time period is greater than the preset threshold, the motion model is used to complete the intermediate point data set to ensure the accuracy of the completed data.

[0029] In a method for dynamically displaying a vehicle trajectory provided in one embodiment of the present disclosure, the method further includes:

[0030] Detecting all discrete point data in the target point data set;

[0031] Using linear interpolation, the discrete path corresponding to the discrete point data is converted into a smooth path, where the smooth path is a cubic Bezier curve;

[0032] The target point data set is updated based on the smooth path to perform rendering processing on the updated target point data.

[0033] The technical solution provided by this disclosure has at least the following beneficial effects:

[0034] The present disclosure adopts a cubic Bezier curve with clear control points and low computational complexity to smooth discrete point data, rather than a conventional spline curve with continuous second-order derivatives, which can reduce the computational burden of real-time interpolation.

[0035] In a method for dynamically displaying a vehicle trajectory provided in one embodiment of the present disclosure, the method further includes:

[0036] Determining delayed point data in the target point data set and a delayed time corresponding to the delayed point data;

[0037] Acquire non-delayed point data and the motion state of the vehicle corresponding to the non-delayed point data, wherein the motion state includes coordinate information and speed of the vehicle, and the non-delayed point data is point data within a preset time period before the delay moment;

[0038] Based on the motion state of the vehicle and the non-delayed point data, obtaining the predicted point data at the delayed moment by linear extrapolation;

[0039] The delayed point data are replaced with the predicted point data to update the target point data set.

[0040] The technical solution provided by this disclosure has at least the following beneficial effects:

[0041] By replacing the delayed point data, low-latency processing of the images rendered by the browser main thread can be achieved, improving the smoothness of the final vehicle trajectory dynamic display animation.

[0042] In a vehicle trajectory dynamic display method provided by one embodiment of the present disclosure, filtering the initial trajectory dynamic display animation based on the remaining CPU status of the backend thread to obtain the vehicle trajectory dynamic display animation includes:

[0043] When the remaining CPU of the backend thread is lower than a threshold, high-frequency jitter of the initial trajectory dynamic display animation is filtered through low-frequency filtering to obtain a vehicle trajectory dynamic display animation;

[0044] When the remaining CPU of the backend thread is higher than or equal to a threshold, the initial trajectory dynamic display animation is filtered by using a Kalman filter to obtain a filtered initial trajectory dynamic display animation;

[0045] Based on the filtered initial trajectory dynamic display animation, combined with the vehicle motion model, the vehicle point image of the next frame is predicted;

[0046] The vehicle trajectory dynamic display animation is obtained by combining the filtered initial trajectory dynamic display animation and the vehicle point image of the next frame.

[0047] The technical solution provided by this disclosure has at least the following beneficial effects:

[0048] When the remaining CPU of the backend thread is lower than the threshold, the initial trajectory dynamic display animation is filtered through a low-pass filter with low computational requirements, which can comprehensively consider computing resource usage and real-time requirements.

[0049] When the remaining CPU of the backend thread is higher than or equal to the threshold, the initial trajectory dynamic display animation is filtered using a more effective Kalman filter, and the vehicle point image of the next frame is predicted. This can provide a better vehicle trajectory dynamic display effect when there are fewer monitored vehicles and the backend thread has sufficient remaining computing resources.

[0050] At least one embodiment of the present disclosure further provides a vehicle trajectory dynamic display system, comprising: a backend thread module and a browser main thread module, wherein:

[0051] The backend thread module includes: a data acquisition unit, a data preprocessing unit and a filtering unit, wherein,

[0052] The data acquisition unit is used to periodically acquire an initial point data set of the vehicle, wherein the elements in the initial point data set are the coordinate information of the vehicle on the browser front-end map;

[0053] The data preprocessing unit is used to obtain the target point data set obtained by preprocessing the initial point data set in the previous cycle;

[0054] The main thread module is used to obtain the target point data set of the previous cycle and perform rendering processing to obtain the initial trajectory dynamic display animation;

[0055] The filtering unit is used to perform filtering processing on the initial trajectory dynamic display animation to obtain the vehicle trajectory dynamic display animation.

[0056] The present disclosure also provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes the above-mentioned method for dynamically displaying vehicle trajectories.

[0057] The present disclosure also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, a vehicle trajectory dynamic display method as described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a flow chart of a method for dynamically displaying vehicle trajectories disclosed herein;

[0059] Figure 2 A schematic diagram of the connection relationship of a vehicle trajectory dynamic display system disclosed in the present invention;

[0060] Figure 3 A schematic diagram of the structure of an electronic device provided by the present disclosure.

[0061] In the accompanying drawings, the components represented by the reference numerals are as follows:

[0062] 100. Vehicle trajectory dynamic display system, 101. Backend thread module, 102. Main thread module, 1011. Data acquisition unit, 1012. Data preprocessing unit, 1013. Filtering unit;

[0063] 10. Electronic device, 11. Processor, 12. Read-only memory (ROM), 13. Random access memory (RAM), 14. Bus, 15. Input / output (I / O) interface, 16. Input unit, 17. Output unit, 18. Storage unit, 19. Communication unit. DETAILED DESCRIPTION

[0064] The principles and features of the embodiments of the present disclosure are described below. The examples given are only used to explain the embodiments of the present disclosure and are not used to limit the scope of the embodiments of the present disclosure.

[0065] The present disclosure provides a method for dynamically displaying vehicle trajectories. Figure 1 As shown, it is applied to the backend thread, including:

[0066] S1. Periodically obtain an initial point data set of the vehicle, where the elements in the initial point data set include the coordinate information corresponding to the vehicle in the browser front-end map;

[0067] S2. Obtaining a target point data set obtained by preprocessing the initial point data set in the previous cycle, where the preprocessing includes removing abnormal data from the initial point data set and completing missing data;

[0068] S3. Send the target point data set to the browser main thread for rendering processing to obtain the initial trajectory dynamic display animation;

[0069] S4. Based on the remaining CPU of the backend thread, the initial trajectory dynamic display animation is filtered to obtain the vehicle trajectory dynamic display animation.

[0070] The disclosed embodiment places the data rendering step of the previous cycle into the browser main thread, and places all other steps that require computational processing into the backend thread for computation. By separating the execution environments of the two, dual-thread parallel processing of data processing and rendering can be achieved, forming a double buffer structure. Moreover, since the browser renders the point data that has been processed in the previous cycle, on the one hand, it can also effectively avoid the backend thread and the browser main thread from operating on the same memory area, reducing resource competition and screen tearing. On the other hand, this method can perform incremental processing on the point data of the newly added cycle instead of full computation, which can further reduce the rendering pressure of the main thread.

[0071] Through this processing method, data processing and rendering are decoupled on the browser side, balancing computing resource usage with real-time requirements. This effectively solves the performance bottleneck problem of dynamically displaying large-scale spatial data in vehicle trajectories and significantly reduces the waiting time required by users.

[0072] In an exemplary embodiment of the present application, the step of preprocessing the currently collected initial point data set in each cycle includes removing abnormal data and completing data, which may specifically include:

[0073] Detect abnormal point data in the initial point data set and remove the abnormal point data to obtain the intermediate point data set;

[0074] In this embodiment, the above-mentioned method for detecting abnormal point data can be based on statistical methods, such as the 3σ principle. During the detection process, the format of the point data, duplicate points, or obviously invalid coordinates (such as longitude and latitude outside the reasonable range) are specifically checked. If the amount of data is large, the distribution of abnormal points can be preliminarily observed through visualization (scatter plot):

[0075] The specific steps are:

[0076] A. First calculate the mean (μ) and standard deviation (σ) of the coordinate axis (such as x and y) of each point data.

[0077] B. Then set the threshold based on the mean (μ) and standard deviation (σ): normal range: [μ-3σ, μ+3σ];

[0078] C. Filter out the point data that exceeds the threshold in any dimension.

[0079] Determine the locations of missing points in the intermediate point dataset where data is missing, such as discontinuous timestamps or empty coordinate values;

[0080] Obtain the missing point status of the missing point location, and complete the intermediate point dataset based on the missing point status to obtain the target point dataset; the missing point status includes whether the missing time period is greater than the preset threshold and whether the missing time period is less than or equal to the preset threshold.

[0081] When it is determined that the missing point state is characterized by a missing time period that is less than or equal to a preset threshold, and the coordinate changes of the point data near the missing point position are relatively slow;

[0082] The linear interpolation method is used to complete the intermediate point data set to obtain the target point data set, so as to minimize the demand for computing resources while ensuring the accuracy of the completed data.

[0083] When it is determined that the missing point state is characterized by a missing time period greater than a preset threshold;

[0084] Acquire multiple point data within a preset time period before and after the missing point location, and determine whether the changes between the point data show a preset motion pattern; if the changes between the point data show a preset motion pattern, establish a motion model based on the motion pattern;

[0085] The motion model is used to complete the intermediate point data set to obtain the target point data set.

[0086] In another exemplary embodiment, after removing and completing the abnormal point data, the present disclosure further includes:

[0087] Use linear interpolation to insert intermediate points between low-frequency point data in the target point data set to avoid jumps;

[0088] Then all discrete point data in the target point data set are detected;

[0089] Using linear interpolation, the discrete path corresponding to the discrete point data is converted into a smooth path, which is a cubic Bezier curve.

[0090] The target point data set is updated based on the smooth path, so as to render the updated target point data.

[0091] In this embodiment, the specific steps of converting the discrete path corresponding to the discrete point data into a smooth path based on the characteristics of the cubic Bezier curve may include:

[0092] A. Input: discrete point data sequence P0, P1, ..., P n (such as vehicle trajectory points). And they are arranged in order according to the path points, without duplication or outliers.

[0093] B. Construct Bezier curves in segments: Each segment of the curve is defined by 4 control points (starting point P i , end point P i+1 , and two intermediate control points C1, C2), the positions of the intermediate control points need to be determined.

[0094] Take three adjacent points P i-1,P i ,P i+1 For example:

[0095] Calculate P i Tangent direction at: T i =k(P i+1 -P i-1 )(k∈[0.2,0.5], controls the smoothness of the curve)

[0096] Define the intermediate control point: C1 = P i +T i / 3,C2=P i +T i+1 / 3;

[0097] C. Generate Bezier curve points: interpolate each curve segment and calculate the coordinates of the middle point:

[0098] B(t)=(1-t) 3 P0+3(1-t) 2 tC1+3(1-t)t 2 C2+t 3 P1(t∈[0,1])

[0099] D. Connect each segment of the Bezier curve to form a complete, natural and smooth path.

[0100] The disclosed embodiment uses a cubic Bezier curve with clear control points and low computational complexity to smooth discrete point data, rather than a conventional spline curve with continuous second-order derivatives, which can reduce the computational burden of real-time interpolation.

[0101] More preferably, to improve the smoothness of the final vehicle trajectory dynamic display animation, after converting the discrete paths corresponding to the discrete point data into smooth paths to update the target point data set, this embodiment further includes:

[0102] Determine the delayed point data in the target point data set and the delayed time corresponding to the delayed point data;

[0103] Obtaining non-delayed point data and the motion state of the vehicle corresponding to the non-delayed point data, the motion state including the coordinate information and speed of the vehicle, and the non-delayed point data being point data within a preset time period before the delay moment;

[0104] Based on the vehicle's motion state and non-delayed point data, that is, the most recently known motion state, it is assumed that the target maintains uniform linear motion in a short period of time, and then the predicted point data at the delayed time is obtained through linear extrapolation;

[0105] The delayed point data is replaced with the predicted point data to update the target point data set.

[0106] This embodiment replaces the delayed point data to achieve low-latency processing of the images rendered by the browser main thread, thereby improving the smoothness of the final vehicle trajectory dynamic display animation.

[0107] In an exemplary embodiment provided herein, the target point dataset is sent to the browser main thread for rendering processing to obtain the initial trajectory dynamic display animation. Preferably, when the browser main thread performs rendering processing, an easing function is used to adjust the rate of attribute change during the animation process to achieve a natural acceleration or deceleration effect. For example, the movement of a vehicle on a map may require simulating the following physical behaviors:

[0108] Starting phase: gradually accelerate from a standstill to a constant speed.

[0109] Stopping phase: gradually decelerating from a constant speed to a standstill.

[0110] Steering phase: Smoothly adjust the direction to avoid sudden changes in the path.

[0111] In this embodiment, the easing function is an ease-in-out function, and the specific mathematical formula is as follows:

[0112]

[0113] Where t∈[0,1] represents the animation progress (0 = start, 1 = end). This function accelerates (ease-in) in the first half of the animation and decelerates (ease-out) in the second half.

[0114] In an exemplary embodiment provided by this application, in order to comprehensively improve the filtering effect of this process, the filtering process of this embodiment includes:

[0115] When the remaining CPU usage of the backend thread is lower than the threshold, the high-frequency jitter of the initial trajectory dynamic display animation is filtered out through low-frequency filtering, retaining the low-frequency motion trend and obtaining the vehicle trajectory dynamic display animation, so as to comprehensively consider computing resource usage and real-time requirements.

[0116] Among them, the steps of low-pass filtering are:

[0117] 1. Initialize the filtered target point data set as the initial data set.

[0118] 2. For each point data in the initial data set:

[0119] Calculate the current filter value: alpha*current filter value+(1-alpha)*last filter value.

[0120] 3. Output the current filter value.

[0121] Optionally, the filtering process in the above embodiment may further include: when the remaining CPU of the backend thread is greater than or equal to a threshold, based on business needs, filtering the initial trajectory dynamic display animation using a Kalman filter to obtain a filtered initial trajectory dynamic display animation;

[0122] Based on the filtered initial trajectory, the dynamic display animation is combined with the vehicle motion model to predict the vehicle point image of the next frame;

[0123] The vehicle trajectory dynamic display animation is obtained by combining the filtered initial trajectory dynamic display animation and the vehicle point image of the next frame. This can provide better vehicle trajectory dynamic display effects when there are fewer monitored vehicles and the backend thread has sufficient remaining computing resources.

[0124] In summary:

[0125] This disclosure uses Bezier curves instead of spline curves to reduce the computational burden of real-time interpolation, and combines low-complexity interpolation (such as linear interpolation) with motion model prediction to reduce the demand for computing resources. Computationally intensive tasks such as filtering and interpolation are moved to background threads to avoid blocking the main thread and improve the smoothness of page rendering. Use the 3σ principle to quickly detect and filter outliers to avoid the additional overhead brought by complex algorithms. By separating data processing and rendering threads, double buffering is used to reduce screen tearing and freezes, and improve real-time performance. Realize the parallel operation of "data processing-rendering" dual threads to form a double buffer structure:

[0126] The background thread is responsible for preprocessing the data of the next frame (writing it into buffer A);

[0127] The main thread performs real-time rendering based on the processed data of the current frame (reading buffer B);

[0128] Processing and rendering alternately switch buffers to avoid directly operating the same memory area, reducing resource competition and screen tearing.

[0129] Only the point data within the newly added period is processed, rather than the entire data set, to reduce duplicate calculations. This, combined with a double-buffering mechanism, further reduces the rendering pressure on the main thread. Once the background thread completes the calculation of the new data, it passes the result to the main thread via asynchronous communication, ensuring that the rendering thread always updates the screen based on the latest buffered data, thereby improving smoothness (FPS) and reducing lag.

[0130] These designs jointly reduce the computational complexity and resource usage of the algorithm, enabling efficient and low-latency processing of large-scale spatial data on the browser side, reflecting the core goal of lightweightness.

[0131] The present disclosure also provides a vehicle trajectory dynamic display system 100, which is referred to herein. Figure 2As shown, it includes: a backend thread module 101 and a browser main thread module 102, wherein,

[0132] The backend thread module 101 includes: a data acquisition unit 1011, a data pre-processing unit 1012 and a filtering unit 1013, wherein:

[0133] The data acquisition unit 1011 is used to periodically acquire the initial point location data set of the vehicle. The elements in the initial point location data set include the coordinate information corresponding to the vehicle in the browser front-end map;

[0134] The data preprocessing unit 1012 is used to obtain the target point data set obtained by preprocessing the initial point data set in the previous cycle. The preprocessing includes removing abnormal data in the initial point data set and filling in missing data.

[0135] The main thread module 102 is used to obtain the target point data set of the previous cycle and perform rendering processing to obtain the initial trajectory dynamic display animation;

[0136] The filtering unit 1013 is used to filter the initial trajectory dynamic display animation based on the remaining CPU status of the backend thread to obtain the vehicle trajectory dynamic display animation.

[0137] Furthermore, the data preprocessing unit 1012 specifically includes:

[0138] Detect abnormal point data in the initial point data set and remove the abnormal point data to obtain the intermediate point data set;

[0139] Determine the location of missing points in the intermediate point data set where data is missing;

[0140] Obtain the missing point status of the missing point location, and complete the intermediate point dataset based on the missing point status to obtain the target point dataset; the missing point status includes whether the missing time period is greater than the preset threshold and whether the missing time period is less than or equal to the preset threshold.

[0141] Furthermore, the data preprocessing unit 1012 specifically includes:

[0142] Obtaining a missing point status of the missing point location, and determining that the missing point status is characterized by a missing time period being less than or equal to a preset threshold;

[0143] The linear interpolation method is used to complete the intermediate point data set to obtain the target point data set.

[0144] Furthermore, the data preprocessing unit 1012 specifically includes:

[0145] Obtaining a missing point status of the missing point location, and determining that the missing point status is characterized by a missing time period greater than a preset threshold;

[0146] Acquire multiple point data within a preset time period before and after the missing point location, and determine whether the changes between the point data show a preset motion pattern; if the changes between the point data show a preset motion pattern, establish a motion model based on the motion pattern;

[0147] The motion model is used to complete the intermediate point data set to obtain the target point data set.

[0148] Furthermore, the backend thread module 101 further includes a path smoothing unit:

[0149] Detect all discrete point data in the target point data set;

[0150] Using linear interpolation, the discrete path corresponding to the discrete point data is converted into a smooth path, which is a cubic Bezier curve.

[0151] The target point data set is updated based on the smooth path, so as to render the updated target point data.

[0152] Furthermore, the backend thread module 101 also includes a low-latency processing unit:

[0153] Determine the delayed point data in the target point data set and the delayed time corresponding to the delayed point data;

[0154] Obtaining non-delayed point data and the motion state of the vehicle corresponding to the non-delayed point data, the motion state including the coordinate information and speed of the vehicle, and the non-delayed point data being point data within a preset time period before the delay moment;

[0155] Based on the vehicle's motion state and non-delayed point data, the predicted point data at the delayed time is obtained through linear extrapolation;

[0156] The delayed point data is replaced with the predicted point data to update the target point data set.

[0157] Furthermore, the filtering unit 1013 specifically includes:

[0158] When the remaining CPU of the backend thread is lower than the threshold, the high-frequency jitter of the initial trajectory dynamic display animation is filtered through low-frequency filtering to obtain the vehicle trajectory dynamic display animation;

[0159] When the remaining CPU of the backend thread is higher than or equal to the threshold, the initial trajectory dynamic display animation is filtered using Kalman filtering to obtain a filtered initial trajectory dynamic display animation;

[0160] Based on the filtered initial trajectory, the dynamic display animation is combined with the vehicle motion model to predict the vehicle point image of the next frame;

[0161] The vehicle trajectory dynamic display animation is obtained by combining the filtered initial trajectory dynamic display animation and the vehicle point image of the next frame.

[0162] An embodiment of the present disclosure further provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes a vehicle trajectory dynamic display method as described above.

[0163] An embodiment of the present disclosure also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, a method for dynamically displaying a vehicle trajectory as described above is implemented.

[0164] It should be noted that in this disclosure, all actions related to the acquisition of signals, information or data are carried out in strict compliance with the relevant data protection laws and policies of the country where they are located and with the authorization of the corresponding device owner. The owner mainly includes:

[0165] (1) Automobile manufacturers: As vehicle hardware and system developers, they control the underlying hardware and software platforms of the vehicle and have the right to manage and control the data generated by vehicle operation, such as driving and fault data.

[0166] (2) Parts suppliers: They provide key components for automobiles and have certain ownership of the data collected and processed by the components, which is used for product optimization and after-sales service, such as data generated by sensors and chips.

[0167] (3) Vehicle owner or user: The actual user of the vehicle, who has the right to decide how and to what extent vehicle data is used, such as whether to share data such as driving trajectory and driving habits, and has the need and right to protect the privacy of his or her own relevant data.

[0168] (4) Service providers: provide software, data analysis and other services, and have the right to use and manage the acquired and processed data within the framework of the agreement, but the ownership usually belongs to other entities.

[0169] An embodiment of the present disclosure further provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes a vehicle trajectory dynamic display method as described above.

[0170] An embodiment of the present disclosure also provides an electronic device, including a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, a method for dynamically displaying a vehicle trajectory as described above is implemented.

[0171] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present disclosure described and / or required herein.

[0172] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0173] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0174] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a method for dynamically displaying vehicle trajectories.

[0175] In some embodiments, a method for dynamically displaying a vehicle trajectory can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for dynamically displaying a vehicle trajectory described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform a method for dynamically displaying a vehicle trajectory by any other appropriate means (e.g., by means of firmware).

[0176] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0177] The computer programs for implementing the methods of the embodiments of the present disclosure may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0178] In the context of the embodiments of the present disclosure, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0179] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or an LCD (liquid crystal display)) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0180] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0181] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0182] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and features of different embodiments or examples, unless they are mutually inconsistent.

[0183] Although the embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are illustrative and are not to be construed as limitations on the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A vehicle trajectory dynamic display method, characterized in that: Applicable to backend threads, including: Periodically acquiring an initial point location dataset of a vehicle, wherein the elements in the initial point location dataset include coordinate information corresponding to the vehicle in a browser front-end map; Acquire a target point data set obtained by preprocessing the initial point data set in the previous cycle, wherein the preprocessing includes removing abnormal data from the initial point data set and completing missing data; Send the target point data set to the browser main thread for rendering processing to obtain the initial trajectory dynamic display animation; Based on the remaining CPU of the backend thread, the initial trajectory dynamic display animation is filtered to obtain the vehicle trajectory dynamic display animation.

2. A vehicle trajectory dynamic display method according to claim 1, characterized in that: The pre-processing step comprises: Detecting abnormal point data in the initial point data set and removing the abnormal point data to obtain an intermediate point data set; Determining the locations of missing points in the intermediate point data set where data is missing; Obtain the missing point status of the missing point position, and complete the intermediate point data set based on the missing point status to obtain the target point data set; the missing point status includes the missing time period being greater than a preset threshold and the missing time period being less than or equal to the preset threshold.

3. A vehicle trajectory dynamic display method according to claim 2, characterized in that: The acquiring of the missing point status of the missing point position, and completing the intermediate point data set based on the missing point status to obtain the target point data set, includes: Acquire a missing point status of the missing point position, and determine that the missing point status is characterized by a missing time period being less than or equal to a preset threshold; The intermediate point data set is completed using a linear interpolation method to obtain the target point data set.

4. A vehicle trajectory dynamic display method according to claim 3, characterized in that: The acquiring of the missing point status of the missing point position, and completing the intermediate point data set based on the missing point status to obtain the target point data set, includes: Acquire a missing point status of the missing point position, and determine that the missing point status is characterized by a missing time period being greater than a preset threshold; Acquire multiple point data within a preset time period before and after the missing point location, and determine whether the changes between the point data show a preset motion pattern; if the changes between the point data show a preset motion pattern, establish a motion model according to the motion pattern; The motion model is used to complete the intermediate point data set to obtain the target point data set.

5. A vehicle trajectory dynamic display method according to claim 1, characterized in that: The method further comprises: Detecting all discrete point data in the target point data set; Using linear interpolation, the discrete path corresponding to the discrete point data is converted into a smooth path, where the smooth path is a cubic Bezier curve; The target point data set is updated based on the smooth path to perform rendering processing on the updated target point data.

6. A vehicle trajectory dynamic display method according to claim 1, characterized in that: The method further comprises: Determining delayed point data in the target point data set and a delayed time corresponding to the delayed point data; Acquire non-delayed point data and the motion state of the vehicle corresponding to the non-delayed point data, wherein the motion state includes coordinate information and speed of the vehicle, and the non-delayed point data is point data within a preset time period before the delay moment; Based on the motion state of the vehicle and the non-delayed point data, obtaining the predicted point data at the delayed moment by linear extrapolation; The delayed point data is replaced by the predicted point data to update the target point data set.

7. A vehicle trajectory dynamic display method according to claim 1, characterized in that: The filtering process of the initial trajectory dynamic display animation based on the remaining CPU of the backend thread to obtain the vehicle trajectory dynamic display animation includes: When the remaining CPU of the backend thread is lower than a threshold, high-frequency jitter of the initial trajectory dynamic display animation is filtered through low-frequency filtering to obtain a vehicle trajectory dynamic display animation; When the remaining CPU of the backend thread is higher than or equal to a threshold, the initial trajectory dynamic display animation is filtered by using a Kalman filter to obtain a filtered initial trajectory dynamic display animation; Based on the filtered initial trajectory dynamic display animation, combined with the vehicle motion model, the vehicle point image of the next frame is predicted; The vehicle trajectory dynamic display animation is obtained by combining the filtered initial trajectory dynamic display animation and the vehicle point image of the next frame.

8. A vehicle trajectory dynamic display system, characterized in that: include: Backend thread module and browser main thread module, among which, The backend thread module includes: a data acquisition unit, a data preprocessing unit and a filtering unit, wherein, The data acquisition unit is configured to periodically acquire an initial point data set of the vehicle, wherein the elements in the initial point data set include coordinate information corresponding to the vehicle in the browser front-end map; The data preprocessing unit is configured to obtain a target point data set obtained by preprocessing the initial point data set in a previous cycle, wherein the preprocessing includes removing abnormal data from the initial point data set and completing missing data; The main thread module is configured to obtain the target point data set of the previous cycle and perform rendering processing to obtain an initial trajectory dynamic display animation; The filtering unit is configured to perform filtering processing on the initial trajectory dynamic display animation based on the remaining CPU status of the backend thread to obtain the vehicle trajectory dynamic display animation.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes a vehicle trajectory dynamic display method according to any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that: When the processor executes the program, a vehicle trajectory dynamic display method according to any one of claims 1 to 7 is implemented.

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