Vehicle simulation trajectory noise adding method and device, electronic equipment and program product

Abstract

This application relates to the field of traffic simulation technology, and proposes a method, apparatus, electronic device, and computer program product for adding noise to vehicle simulation trajectories. The method includes: generating simulation trajectories of simulated vehicles from simulated road vehicle data; wherein the simulated road vehicle data is obtained by mapping from real road vehicle data; and adding noise to the simulation trajectory based on a first real trajectory of a first real vehicle corresponding to the simulated vehicle in the real road vehicle data. This method can improve the similarity between the generated simulation trajectory and the real trajectory, that is, it can improve the realism of the generated vehicle simulation trajectory.

Description

Technical Field

[0001] This application relates to the field of traffic simulation technology, and in particular to a method, apparatus, electronic device, and computer program product for adding noise to vehicle simulation trajectory. Background Technology

[0002] In the field of traffic simulation technology, real road vehicle data can be acquired through roadside sensing devices and mapped onto a simulated road network to obtain simulated road vehicle data. This simulated road vehicle data can then be used to simulate various vehicle events such as pulling over to the side of the road and collisions, generating corresponding simulated vehicle trajectories to mimic real traffic conditions. However, because real vehicle trajectories typically contain various types of noise, while the generated simulated trajectories usually lack noise or only contain fixed types of noise such as Gaussian noise, the resulting simulated trajectories differ significantly from the real trajectories, meaning the realism of the generated vehicle simulation trajectories is low. Summary of the Invention

[0003] In view of this, embodiments of this application provide a method, apparatus, electronic device, and computer program product for adding noise to vehicle simulation trajectories, which can improve the realism of the generated vehicle simulation trajectories.

[0004] The first aspect of this application provides a method for adding noise to a vehicle simulation trajectory, including:

[0005] The simulation trajectories of simulated vehicles in simulated road vehicle data are generated; wherein, the simulated road vehicle data is obtained by mapping real road vehicle data;

[0006] Noise is added to the simulation trajectory based on the first real trajectory of the first real vehicle corresponding to the simulation vehicle in the real road vehicle data.

[0007] In the technical solution of this application embodiment, simulated road vehicle data is obtained by mapping real road vehicle data. After generating the simulated trajectory of the simulated vehicle in the simulated road vehicle data, corresponding noise is added to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in the real road vehicle data. By setting it in this way, the generated simulated trajectory will have noise corresponding to the real trajectory, thereby improving the similarity between the simulated trajectory and the real trajectory, that is, improving the realism of the generated vehicle simulated trajectory.

[0008] In one implementation of this application, noise is added to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in real road vehicle data, including:

[0009] Noise feature analysis is performed on the first true trajectory, and the first noise type of the noise present in the first true trajectory is determined based on the results of the noise feature analysis.

[0010] Add noise of the first noise type to the simulated trajectory.

[0011] In one implementation of this application, adding noise of a first noise type to the simulated trajectory includes:

[0012] Retrieve the attribute parameters set for the first noise type;

[0013] Based on the attribute parameters, add noise of the first noise type to the simulation trajectory.

[0014] In one implementation of this application, after determining the first noise type of the noise present in the first true trajectory based on the result of noise feature analysis, the method further includes:

[0015] Determine the second noise type associated with the first noise type;

[0016] Add a second type of noise to the simulated trajectory.

[0017] In one implementation of this application, the method further includes:

[0018] If there is no first real vehicle corresponding to the simulated vehicle in the real road vehicle data, then search for a second real vehicle of the same type as the simulated vehicle in the real road vehicle data.

[0019] Noise is added to the simulated trajectory based on the second real trajectory of the second real vehicle.

[0020] In one implementation of this application, searching for a second real vehicle of the same type as the simulated vehicle from real road vehicle data includes:

[0021] If there are multiple candidate real vehicles of the same type as the simulated vehicle in the real road vehicle data, then the candidate real vehicle whose size is closest to the simulated vehicle is selected from the multiple candidate real vehicles as the second real vehicle.

[0022] In one implementation of this application, generating the simulation trajectory of a simulated vehicle in simulated road vehicle data includes:

[0023] Generate simulated events for the simulated vehicle;

[0024] Based on simulated events, predict the movement state of the simulated vehicle to generate a simulated trajectory.

[0025] A second aspect of this application provides a vehicle simulation trajectory noise addition device, comprising:

[0026] The trajectory generation module is used to generate the simulation trajectory of the simulated vehicles in the simulated road vehicle data; wherein, the simulated road vehicle data is obtained by mapping the simulated road vehicle data;

[0027] The noise addition module is used to add noise to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in the real road vehicle data.

[0028] A third aspect of this application provides an electronic device, 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, it implements the vehicle simulation trajectory noise addition method provided in the first aspect of this application.

[0029] A fourth aspect of this application provides a computer program product that, when run on an electronic device, causes the electronic device to execute the vehicle simulation trajectory noise addition method provided in the first aspect of this application.

[0030] The fifth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle simulation trajectory noise addition method provided in the first aspect of this application.

[0031] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0032] Figure 1 This is a flowchart of a method for adding noise to a vehicle simulation trajectory provided in an embodiment of this application;

[0033] Figure 2 This is an operational diagram illustrating how to simulate and map real road vehicle data to obtain simulated road vehicle data, as provided in an embodiment of this application.

[0034] Figure 3 This is an operational schematic diagram of selecting a simulation vehicle and simulating events to generate a corresponding simulation trajectory, provided in an embodiment of this application.

[0035] Figure 4 This is a schematic diagram of various noise types that can be added to a simulated trajectory, provided in an embodiment of this application.

[0036] Figure 5 This is a schematic diagram of a noise parameter setting interface provided in an embodiment of this application;

[0037] Figure 6This is a comparative schematic diagram of the simulated trajectory before adding noise and the real trajectory provided in the embodiments of this application;

[0038] Figure 7 This is a comparative schematic diagram of the simulated trajectory with added noise and the real trajectory provided in the embodiments of this application;

[0039] Figure 8 This is a schematic diagram of the structure of a vehicle simulation trajectory noise addition device provided in an embodiment of this application;

[0040] Figure 9 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0041] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail. Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0042] Real-world vehicle data sensed by roadside equipment can be mapped to a simulated road network to generate corresponding simulated road vehicle data. This simulated data can then be used to simulate various vehicle events and generate simulated vehicle trajectories, allowing for analysis of potential traffic situations. However, currently generated simulated trajectories typically lack noise or only contain fixed types of noise such as Gaussian noise. These simulated trajectories differ significantly from the actual vehicle trajectories, resulting in low realism.

[0043] In view of this, embodiments of this application provide a method, apparatus, electronic device, and computer program product for adding noise to a vehicle simulation trajectory. By adding noise corresponding to the real trajectory to the simulation trajectory, the realism of the generated vehicle simulation trajectory can be improved. For more specific technical implementation details of the embodiments of this application, please refer to the method embodiments described below.

[0044] It should be understood that the implementing entity of the various method embodiments proposed in this application can be various types of electronic devices, such as mobile phones, tablets, wearable devices, vehicle terminals, augmented reality (AR) / virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), large-screen TVs, etc. The embodiments of this application do not impose any restrictions on the specific type of electronic device.

[0045] Please see Figure 1 This paper illustrates a method for adding noise to a vehicle simulation trajectory according to an embodiment of this application, including:

[0046] 101. Generate the simulation trajectories of the simulated vehicles in the simulated road vehicle data; wherein, the simulated road vehicle data is obtained by mapping real road vehicle data;

[0047] By utilizing roadside equipment, real-world road vehicle data, such as position, speed, type, size, heading angle, and trajectory, can be obtained. This real-world road vehicle data is then mapped to a simulated road network to generate corresponding simulated road vehicle data. This simulated road vehicle data contains a one-to-one correspondence between simulated vehicles and real-world vehicles in the actual road vehicle data. These simulated vehicles can be used to simulate various traffic events and generate simulated trajectories for analysis of potential traffic situations. Furthermore, users can delete or add simulated vehicles to the simulated road vehicle data based on their actual simulation needs. For example, if it's necessary to simulate the traffic situation that might occur if a real vehicle A is missing, the corresponding simulated vehicle A can be deleted; if it's necessary to simulate the traffic situation that might occur if a vehicle B is added, an additional simulated vehicle B can be added, even if the added simulated vehicle B does not have a corresponding real vehicle in the actual road vehicle data.

[0048] As an example, Figure 2 This is a schematic diagram illustrating an operation of simulating and mapping real road vehicle data to obtain simulated road vehicle data, as provided in an embodiment of this application. Figure 2 Above is real road vehicle data, which includes real vehicles traveling in real lanes: real vehicle A, real vehicle B, and real vehicle C. Figure 2Below is the simulated road vehicle data, which includes simulated vehicle A, simulated vehicle B, and simulated vehicle C, each corresponding to a real vehicle. Users can perform various edits on the simulated road vehicle data, such as deleting mapped simulated vehicles, adding additional simulated vehicles, or modifying the position parameters of each simulated vehicle, etc.

[0049] Users can operate the road simulation system to generate simulation trajectories for any simulated vehicle in the simulated road vehicle data. The initially generated simulation trajectory is an idealized trajectory without noise. In subsequent step 102, noise corresponding to the real trajectory needs to be added to the simulation trajectory to improve its realism.

[0050] In one implementation of this application, generating the simulation trajectory of a simulated vehicle in simulated road vehicle data includes:

[0051] (1) Generate simulated events for the simulated vehicle;

[0052] (2) Based on the simulated events, predict the movement state of the simulated vehicle to generate the simulated trajectory.

[0053] Users can select one or more simulated vehicles in the road simulation system and set simulated events for the selected vehicles, such as parking, emergency braking, lane changing, and collisions. Based on the set simulated events, the system can deduce the simulated vehicle's operational response to various simulated events, predict its movement state, and generate corresponding simulated trajectories.

[0054] As an example, Figure 3 This is an operational diagram illustrating the selection of a simulated vehicle and the simulation of events to generate a corresponding simulated trajectory, provided in an embodiment of this application. Figure 3 In this study, a simulated vehicle B is selected to simulate a parking event at the side of the road. By simulating the operational response of the simulated vehicle B during parking, the movement state of the simulated vehicle B can be predicted, thereby generating data such as... Figure 3 The simulated trajectory is shown.

[0055] 102. Based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in the real road vehicle data, add noise to the simulated trajectory.

[0056] After generating the simulation trajectory of the simulated vehicle, the corresponding real vehicle is found from the real road vehicle data and designated as the first real vehicle. The real trajectory of the first real vehicle is then obtained and designated as the first real trajectory. Next, appropriate noise is added to the simulation trajectory based on the first real trajectory. This process adds noise to the simulation trajectory, improving its realism. Specifically, noise feature analysis can be performed on the first real trajectory to identify the noise present, and then the corresponding noise is added to the simulation trajectory. For example, for the simulation trajectory of vehicle A, the real trajectory of vehicle A is first found from the real road vehicle data, the noise present in this trajectory is analyzed, and the corresponding noise is added to the simulation trajectory of vehicle A. Similarly, for the simulation trajectory of vehicle B, the real trajectory of vehicle B is first found from the real road vehicle data, the noise present in this trajectory is analyzed, and the corresponding noise is added to the simulation trajectory of vehicle B, and so on.

[0057] In one implementation of this application, noise is added to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in real road vehicle data, including:

[0058] (1) Perform noise feature analysis on the first real trajectory, and determine the first noise type of the noise present in the first real trajectory based on the results of the noise feature analysis;

[0059] (2) Add noise of the first noise type to the simulation trajectory.

[0060] By performing noise feature analysis on the first real trajectory, we can identify the types of noise present in the first real trajectory and determine their primary noise types. For example, if the first real trajectory detects missing points, we can determine that the first real trajectory contains target loss noise; if the positions of some trajectory points in the first real trajectory abruptly change in the vertical direction perpendicular to the driving direction, we can determine that the first real trajectory contains vertical jitter noise, and so on. It can be understood that if the first real trajectory contains only one type of noise, then the primary noise type is one type; if the first real trajectory contains multiple types of noise simultaneously, then the primary noise type includes multiple types. After determining the primary noise types present in the first real trajectory, noise of the same primary noise type is added to the simulated trajectory. This way, the simulated trajectory will have one or more types of noise identical to the corresponding real trajectory, significantly improving realism.

[0061] like Figure 4 The diagram shown is a schematic representation of various noise types that can be added to a simulated trajectory according to an embodiment of this application. Figure 4The noise types shown include the following nine: stationary vehicle jitter noise, vertical abrupt change noise, vertical jitter noise, forward leap noise, category jump noise, bounding box size jump noise, target loss noise, heading angle jump noise, and backtracking noise. Specifically, stationary vehicle jitter noise is: for a vehicle target near a base station ID with a configured vehicle category and a speed of 0, a certain change is added to the center point position of the vehicle target, causing it to jitter forward and backward; vertical jitter noise is: for a vehicle target near a base station ID with a configured vehicle category, a certain positional change is added in the vertical direction with a certain probability, changing its center point position; vertical abrupt change noise is similar to vertical jitter noise, but the change added in the vertical direction is larger, and the lane will also change accordingly; forward leap noise is: for a vehicle target near a base station ID with a configured vehicle category, the speed and position of the vehicle target are changed with a certain probability; category jump noise is: for a vehicle target near a base station ID with a certain probability, the vehicle category of some frames is modified, for example, jumping from vehicle category A to [other category]. Vehicle category B; Bbox size jump noise: For vehicle targets near the configured vehicle category and base station ID, the size of their Bbox is modified with a certain probability, resulting in random finite abrupt changes in length, width, and height; Target loss noise: For vehicle targets near the configured vehicle category and base station ID, the vehicle target is lost in some frames with a certain probability; Heading angle jump noise: For vehicle targets near the configured vehicle category and base station ID, the heading angle is modified in some frames with a certain probability, which can be divided into small-range changes and reverse abrupt changes; Backoff noise: For vehicle targets near the configured vehicle category and base station ID, the vehicle is backoffed in some frames with a certain probability. Backoff can be divided into multiple backoffs at the same lane position, a single backoff at the same lane position, backoffs at other lanes, and backoffs accompanied by lane changes. Any one or more of these nine noise types can be added to the simulated trajectory based on the noise situation present in the actual trajectory. It should be noted that... Figure 4 This is merely a schematic diagram of various noise types that can be added, and is not intended to limit the types of noise that can be added in the embodiments of this application.

[0062] In one implementation of this application, adding noise of a first noise type to the simulated trajectory includes:

[0063] (1) Obtain the attribute parameters set for the first noise type;

[0064] (2) Add noise of the first noise type to the simulation trajectory according to the attribute parameters.

[0065] When adding noise of the first noise type to the simulated trajectory, the attribute parameters set for the first noise type are first obtained. These attribute parameters may include noise level, probability of occurrence, type of vehicle involved, location of the base station involved, amplitude and range of jitter, etc. On one hand, the road simulation system can provide a corresponding noise parameter setting interface, through which users can input the attribute parameters corresponding to each noise type. On the other hand, the road simulation system can also automatically set the attribute parameters of the first noise type based on the relevant characteristics of the first noise type existing in the real trajectory. For example, based on the jitter amplitude M of the first noise type existing in the real trajectory, the jitter amplitude of the first noise type can be automatically set to M or 1.2*M, etc. Then, according to the set attribute parameters, the first noise type noise is added to the simulated trajectory. For example, if the noise level is set to medium, the probability of occurrence is 10%, and the jitter amplitude is M, then medium-level first noise type noise with a 10% probability of occurrence and a jitter amplitude of M is added to the simulated trajectory.

[0066] As an example, Figure 5 This is a schematic diagram of a noise parameter setting interface provided in an embodiment of this application. Figure 5 This shows the parameter setting interface for Bbox size jump noise. Users can input attributes such as noise level, occurrence probability, length variation range, width variation range, height variation range, and the location of the base station where the Bbox size jump noise occurs. The parameter setting interfaces for other noise types are similar. Figure 5 Similar, but the specific attribute parameters that can be set are different.

[0067] In one implementation of this application, after determining the first noise type of the noise present in the first true trajectory based on the result of noise feature analysis, the method further includes:

[0068] (1) Determine the second noise type associated with the first noise type;

[0069] (2) Add a second type of noise to the simulation trajectory.

[0070] Certain types of noise exhibit correlations, and these different types of noise may occur simultaneously in real-world situations. To address this, the correlations between various noise types can be pre-stored. After determining the first noise type present in the first real trajectory, a second noise type associated with the first noise type can be found, and noise of the second noise type can be added to the simulated trajectory. Similarly, the second noise type can be one or more types. For example, regarding the trajectory of a vehicle parking at the side of the road, vertical jitter noise, vertical abrupt change noise, and jitter noise before and after stopping the vehicle may occur simultaneously. Assuming vertical jitter noise is detected in the real trajectory of a real vehicle A, after simulating a parking event and generating its corresponding simulated trajectory, in addition to adding vertical jitter noise to the simulated trajectory, vertical abrupt change noise and jitter noise before and after stopping the vehicle can also be added. This better simulates the vehicle trajectory of a parking event and further improves the realism of the simulated trajectory.

[0071] In one implementation of this application, the method further includes:

[0072] (1) If there is no first real vehicle corresponding to the simulated vehicle in the real road vehicle data, then search for a second real vehicle of the same type as the simulated vehicle in the real road vehicle data.

[0073] (2) Add noise to the simulated trajectory based on the second real trajectory of the second real vehicle.

[0074] Referring to the previous description, a simulated vehicle can be added to the simulated road vehicle data. This simulated vehicle may not have a corresponding real vehicle in the actual road vehicle data. In this case, no first real vehicle corresponding to the simulated vehicle will be found in the actual road vehicle data. To address this, considering the similarity in the movement trajectories of vehicles of the same type, they may contain similar trajectory noise. Therefore, another real vehicle of the same type as the simulated vehicle can be found in the actual road vehicle data, designated as the second real vehicle. Based on the second real vehicle's second real trajectory, corresponding noise is added to the simulated trajectory. The specific method for adding noise to the simulated trajectory based on the second real trajectory is similar to adding noise based on the first real trajectory and will not be elaborated here. For example, assuming a simulated trajectory for a car-type vehicle B has been generated, but no corresponding real vehicle B exists in the actual road vehicle data, a real vehicle C of the same type can be found in the actual road vehicle data. Based on the real trajectory of vehicle C, corresponding noise is added to the simulated trajectory of vehicle B. This setup improves the comprehensiveness and success rate of adding noise to the simulated trajectory.

[0075] In one implementation of this application, searching for a second real vehicle of the same type as the simulated vehicle from real road vehicle data includes:

[0076] If there are multiple candidate real vehicles of the same type as the simulated vehicle in the real road vehicle data, then the candidate real vehicle whose size is closest to the simulated vehicle is selected from the multiple candidate real vehicles as the second real vehicle.

[0077] If multiple real-world vehicles of the same type as the simulated vehicle exist in the real-world vehicle data, these vehicles are first considered as candidate vehicles. Then, the size of each candidate vehicle is compared with the size of the simulated vehicle. The candidate vehicle whose size is closest to the simulated vehicle is selected as the second real vehicle. For example, regarding the simulated vehicle B mentioned above, if the real-world vehicle data includes vehicles C, D, and E that are all cars, and vehicle D's size is closest to that of simulated vehicle B, then vehicles C, D, and E are first considered as candidate vehicles. Then, by comparing their sizes, vehicle D is selected as the second real vehicle. The rationale for this approach is that, under the condition of the same vehicle type, vehicles with closer sizes have a higher similarity in their movement trajectories.

[0078] To illustrate the technical effects of the vehicle simulation trajectory noise addition method provided in this application's embodiments, please refer to... Figure 6 and Figure 7 .in, Figure 6 This is a schematic diagram comparing the simulated trajectory before noise was added with the actual trajectory. Figure 7 This is a comparative diagram showing the simulated trajectory with added noise and the actual trajectory. Figure 6 and Figure 7 It can be seen that the simulated trajectory before adding noise differs significantly from the real trajectory because it lacks noise. However, the simulated trajectory after adding appropriate noise to the real trajectory shows very little difference from the real trajectory, exhibiting extremely high realism.

[0079] In the technical solution of this application embodiment, simulated road vehicle data is obtained by mapping real road vehicle data. After generating the simulated trajectory of the simulated vehicle in the simulated road vehicle data, corresponding noise is added to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in the real road vehicle data. By setting it in this way, the generated simulated trajectory will have noise corresponding to the real trajectory, thereby improving the similarity between the simulated trajectory and the real trajectory, that is, improving the realism of the generated vehicle simulated trajectory.

[0080] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0081] The above mainly describes a method for adding noise to a vehicle simulation trajectory. The following will describe a device for adding noise to a vehicle simulation trajectory.

[0082] Please see Figure 8 One embodiment of a vehicle simulation trajectory noise addition device in this application includes:

[0083] The trajectory generation module 801 is used to generate the simulation trajectory of the simulated vehicle in the simulated road vehicle data; wherein, the simulated road vehicle data is obtained by mapping the real road vehicle data;

[0084] The noise addition module 802 is used to add noise to the simulation trajectory based on the first real trajectory of the first real vehicle corresponding to the simulation vehicle in the real road vehicle data.

[0085] In one implementation of this application, the noise addition module includes:

[0086] The noise type determination unit is used to perform noise feature analysis on the first real trajectory and determine the first noise type of the noise present in the first real trajectory based on the results of the noise feature analysis.

[0087] The first noise addition unit is used to add noise of the first noise type to the simulated trajectory.

[0088] In one implementation of this application, the first noise adding unit includes:

[0089] The attribute parameter acquisition subunit is used to retrieve the attribute parameters set for the first noise type.

[0090] The noise addition sub-unit is used to add noise of the first noise type to the simulation trajectory according to the attribute parameters.

[0091] In one implementation of this application, the noise addition module further includes:

[0092] An associated noise determination unit is used to determine a second noise type associated with a first noise type;

[0093] The second noise addition unit is used to add a second type of noise to the simulated trajectory.

[0094] In one implementation of this application, the vehicle simulation trajectory noise addition device further includes:

[0095] The vehicle search module is used to search for a second real vehicle of the same type as the simulated vehicle from the real road vehicle data if there is no first real vehicle corresponding to the simulated vehicle in the real road vehicle data.

[0096] A backup noise addition module is used to add noise to the simulated trajectory based on the second real trajectory of the second real vehicle.

[0097] In one implementation of this application, the vehicle search module includes:

[0098] The vehicle selection unit is used to select the candidate real vehicle whose size is closest to that of the simulation vehicle from the multiple candidate real vehicles in the real road vehicle data if there are multiple candidate real vehicles of the same type as the simulation vehicle, and use it as the second real vehicle.

[0099] In one implementation of this application, the trajectory generation module includes:

[0100] The simulation event generation unit is used to generate simulated events for the simulated vehicle.

[0101] The simulation trajectory generation unit is used to predict the movement state of the simulated vehicle based on simulated events in order to generate a simulation trajectory.

[0102] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a vehicle simulation trajectory noise addition method as described in any of the above embodiments.

[0103] This application also provides a computer program product that, when run on an electronic device, causes the electronic device to execute a vehicle simulation trajectory noise addition method as described in any of the above embodiments.

[0104] Figure 9 This is a schematic diagram of an electronic device provided in an embodiment of this application. Figure 9 As shown, the electronic device 9 of this embodiment includes: a processor 90, a memory 91, and a computer program 92 stored in the memory 91 and executable on the processor 90. When the processor 90 executes the computer program 92, it implements the steps in the embodiments of the various vehicle simulation trajectory noise addition methods described above, for example... Figure 1 Steps 101 to 102 are shown. Alternatively, when the processor 90 executes the computer program 92, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 8 The functions of modules 801 to 802 are shown.

[0105] The computer program 92 can be divided into one or more modules / units, which are stored in the memory 91 and executed by the processor 90 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 92 in the electronic device 9.

[0106] The processor 90 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0107] The memory 91 can be an internal storage unit of the electronic device 9, such as a hard disk or memory. The memory 91 can also be an external storage device of the electronic device 9, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 91 can include both internal and external storage units of the electronic device 9. The memory 91 is used to store the computer program and other programs and data required by the electronic device. The memory 91 can also be used to temporarily store data that has been output or will be output.

[0108] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0109] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0110] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0111] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0112] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0113] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0114] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0115] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0116] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for adding noise to a vehicle simulation trajectory, characterized in that, include: The simulation trajectory of the simulated vehicle in the simulated road vehicle data is generated; wherein the simulated road vehicle data is obtained by mapping real road vehicle data; Noise is added to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in the real road vehicle data.

2. The method as described in claim 1, characterized in that, The step of adding noise to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in the real road vehicle data includes: Noise feature analysis is performed on the first real trajectory, and the first noise type of the noise present in the first real trajectory is determined based on the results of the noise feature analysis. Add noise of the first noise type to the simulated trajectory.

3. The method as described in claim 2, characterized in that, Adding noise of the first noise type to the simulated trajectory includes: Retrieve the attribute parameters set for the first noise type; According to the attribute parameters, noise of the first noise type is added to the simulation trajectory.

4. The method as described in claim 2, characterized in that, After determining the first noise type of the noise present in the first real trajectory based on the results of the noise feature analysis, the method further includes: Determine the second noise type associated with the first noise type; Add noise of the second noise type to the simulated trajectory.

5. The method as described in claim 1, characterized in that, Also includes: If there is no first real vehicle corresponding to the simulated vehicle in the real road vehicle data, then search for a second real vehicle of the same type as the simulated vehicle in the real road vehicle data. Noise is added to the simulated trajectory based on the second real trajectory of the second real vehicle.

6. The method as described in claim 5, characterized in that, The step of finding a second real vehicle of the same type as the simulated vehicle from the real road vehicle data includes: If there are multiple candidate real vehicles of the same type as the simulated vehicle in the real road vehicle data, then the candidate real vehicle whose size is closest to the simulated vehicle is selected from the multiple candidate real vehicles as the second real vehicle.

7. The method according to any one of claims 1 to 6, characterized in that, The simulated vehicle trajectories in the generated simulated road vehicle data include: Generate simulated events for the simulated vehicle; Based on the simulated events, the movement state of the simulated vehicle is predicted to generate the simulated trajectory.

8. A vehicle simulation trajectory noise addition device, characterized in that, include: The trajectory generation module is used to generate the simulated trajectory of the simulated vehicle in the simulated road vehicle data; wherein, the simulated road vehicle data is obtained by mapping real road vehicle data; The noise addition module is used to add noise to the simulated trajectory based on the first real trajectory of the first real vehicle corresponding to the simulated vehicle in the real road vehicle data.

9. An electronic 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, it implements the vehicle simulation trajectory noise addition method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, When the computer program product is run on an electronic device, the electronic device performs the vehicle simulation trajectory noise addition method as described in any one of claims 1 to 7.

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