Method and device for processing road condition exception in virtual driving scene, and storage medium

Abstract

The application relates to the technical field of virtual driving and provides a road condition exception processing method and device in a virtual driving scene and a storage medium, the method comprising the following steps: detecting whether a preset obstacle exists in the driving range of a target vehicle and visibility in real time; if the visibility is lower than a preset visibility, the target obstacle is detected to satisfy the target vehicle, a safe driving distance is calculated, and the road section distance of the target vehicle and a congestion road section is detected; temporary parking navigation guidance is generated according to the road section distance, which is used for controlling the target vehicle to safely drive to a temporary parking point, and the temporary parking navigation guidance comprises an avoidance route, and the avoidance route does not comprise the congestion road section and the obstacle within a first time length; and the target vehicle is controlled to drive to the temporary parking point according to the avoidance route according to the temporary parking navigation guidance. The scheme can effectively identify abnormal driving of the vehicle under specific weather and feedback, intelligently performs temporary parking navigation on the vehicle under specific weather, so that the vehicle can slow down and safely park in the temporary parking navigation.

Description

Technical Field

[0001] This application relates to the field of virtual driving technology, specifically to a method, device, and storage medium for handling abnormal road conditions in a virtual driving scenario. Background Technology

[0002] In virtual driving scenarios, although various control parameters are preset for different scenarios to control the speed and direction of the vehicle, the vehicle is also intelligently controlled to drive in the virtual scenario through preset scripts or other methods to complete the entire driving journey.

[0003] However, due to potential malfunctions in the vehicle's braking system, such as brake pedal failure, the vehicle's speed cannot be controlled regardless of operation. If the road surface includes a downhill section, this can further exacerbate the speed increase, or the vehicle may collide with another vehicle due to excessive speed and loss of control. In such situations, neither the vehicle nor the driver can quickly devise a route or driving plan to rapidly reduce speed, increasing the risk of an accident. Summary of the Invention

[0004] This application provides a method, device, and storage medium for handling abnormal road conditions in a virtual driving scenario. It can effectively identify abnormal situations in a virtual driving scenario, such as excessive vehicle speed or obstacles in front of the vehicle when visibility is low, and feed this information back to the physical engine to remind the user to slow down. It also automatically performs intelligent temporary parking navigation to achieve deceleration and safe parking during temporary parking navigation.

[0005] In a first aspect, embodiments of this application provide a method for handling abnormal road conditions in a virtual driving scenario. The method is used in a virtual driving control system, which includes a simulator, a vehicle perception model, and a driving scenario simulation platform. The driving scenario simulation platform includes a first area and a second area. The first area displays multiple abnormal training driving modes, each including at least two road segment materials. The second area currently displays dynamic footage under a specific weather driving mode. The dynamic footage includes a target vehicle in motion and at least two road segment materials corresponding to the specific weather driving mode. The dynamic footage and vehicle status of the target vehicle in the second area are transmitted to the vehicle perception model via a port. The method includes:

[0006] Real-time detection of whether there are preset obstacles within the driving range of the target vehicle in the driving direction of the target vehicle in the dynamic image of the second area, and the visibility of the dynamic image;

[0007] If it is determined that the visibility is lower than the preset visibility, and a target obstacle is detected and the target obstacle meets the preset conditions that hinder the normal driving of the target vehicle within a first time period, then the speed of the target vehicle in the second area and the first physical distance between the target vehicle and the target obstacle within the first time period are obtained.

[0008] Calculate the safe driving distance based on the first physical distance and the vehicle speed;

[0009] When the first physical distance is less than the safe driving distance, the distance between the target vehicle and the congested road section is detected;

[0010] A temporary parking navigation guide is generated and displayed based on the road segment distance. The temporary parking navigation guide is used to control the target vehicle to drive safely to the temporary parking point. The temporary parking navigation guide includes at least one avoidance route. The avoidance route does not include congested road segments with traffic congestion during the first time period, nor does it include any obstacles that hinder the normal driving of the target vehicle during the first time period.

[0011] Upon receiving confirmation from the user regarding the temporary parking navigation guidance, the system controls the speed and direction of the target vehicle according to the temporary parking navigation guidance, selects any avoidance route from the at least one avoidance route, and travels to the temporary parking point within a second time period.

[0012] In some implementations, the dynamic footage includes multi-view footage from a third-person perspective; generating the temporary parking navigation guidance based on the road segment distance includes:

[0013] Acquire multi-view road condition images within a preset range of the target vehicle from a third-person perspective;

[0014] The temporary parking navigation guide is generated based on the target vehicle's current speed, the visibility of the multi-view road condition images, and the number of vehicles in the multi-view road condition images.

[0015] In some implementations, generating the temporary parking navigation guidance based on the target vehicle's current speed and the multi-view road condition images includes:

[0016] Based on the multi-view road condition images, determine the visibility of the environment around the target vehicle, the traffic congestion status, the number of vehicles in the multi-view road condition images, the number of vehicles interfering with the target vehicle's driving, the number of traffic lights, the characteristics of traffic signs, and the traffic light change status within the second time period.

[0017] The temporary parking navigation guide is generated based on the visibility, vehicle speed, traffic congestion status, number of vehicles in the multi-view road condition image, number of vehicles interfering with the target vehicle's movement, number of traffic lights, characteristics of traffic signs, and traffic light change status.

[0018] In some implementations, the vehicle status includes the real-time location of the target vehicle; the temporary parking navigation guidance includes at least one of the following:

[0019] At least one driving route from the current real-time location of the target vehicle to the temporary parking point;

[0020] Each driving route does not include any target object. The target object is a congested road section with traffic congestion during the first time period, or an obstacle that hinders the normal driving of the target vehicle during the first time period.

[0021] Vehicle speed and direction of travel for each segment of each route;

[0022] Each section of the driving route has a designated avoidance route for pre-set vehicles or rescue vehicles.

[0023] Secondly, embodiments of this application provide a road condition anomaly handling device, which has the functions described in the road condition anomaly handling method in the virtual driving scenario provided in the first aspect. The functions described in the road condition anomaly handling method in the virtual driving scenario can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, and the modules can be software and / or hardware. Embodiments of this application do not limit this.

[0024] In some embodiments, the road condition anomaly handling device is applied to a virtual driving control system. The driving scenario simulation platform includes a first area and a second area. The first area displays multiple abnormal training driving modes, each of which includes at least two road segment materials. The second area currently displays dynamic images under a specific weather driving mode. The dynamic images include a target vehicle in motion and at least two road segment materials corresponding to the specific weather driving mode. The dynamic images of the target vehicle in the second area and the vehicle status are transmitted to the vehicle perception model through a port.

[0025] The road condition anomaly handling device includes:

[0026] The detection module is used to detect in real time whether there are preset obstacles within the driving range of the target vehicle in the driving direction of the target vehicle in the dynamic image of the second area, as well as the visibility of the dynamic image;

[0027] The processing module is used to determine that the visibility is lower than a preset visibility, and if a target obstacle is detected and the target obstacle meets the preset conditions that hinder the normal driving of the target vehicle within a first time period, then the input / output module is used to obtain the speed of the target vehicle in the second area and the first physical distance between the target vehicle and the target obstacle within the first time period.

[0028] The processing module is also used to calculate a safe driving distance based on the first physical distance and the vehicle speed; when the first physical distance is less than the safe driving distance, it detects the distance between the target vehicle and the congested road section;

[0029] The processing module is also used to generate and display temporary parking navigation guidance based on the road segment distance. The temporary parking navigation guidance is used to control the target vehicle to drive safely to the temporary parking point. The temporary parking navigation guidance includes at least one avoidance route. The avoidance route does not include congested road segments with traffic congestion during the first time period, nor does it include any obstacles that hinder the normal driving of the target vehicle during the first time period.

[0030] The input / output module receives the user's confirmation operation for the temporary parking navigation guidance, controls the speed and direction of the target vehicle according to the temporary parking navigation guidance, selects any avoidance route from the at least one avoidance route, and travels to the temporary parking point within a second time period.

[0031] In some implementations, the dynamic footage includes multi-view footage from a third-person perspective; the processing module is specifically used for:

[0032] Acquire multi-view road condition images within a preset range of the target vehicle from a third-person perspective;

[0033] The temporary parking navigation guide is generated based on the target vehicle's current speed and the multi-view road condition images.

[0034] In some implementations, the processing module is specifically used for:

[0035] Based on the multi-view road condition images, determine the traffic congestion status, the number of vehicles interfering with the target vehicle's movement, the number of traffic lights, the characteristics of traffic signs, and the traffic light changes during the second time period.

[0036] The temporary parking navigation guide is generated based on the vehicle speed, the traffic congestion status, the number of vehicles interfering with the target vehicle's movement, the number of traffic lights, the characteristics of the traffic signs, and the traffic light change status.

[0037] In some implementations, the vehicle status includes the real-time location of the target vehicle; the temporary parking navigation guidance includes at least one of the following:

[0038] At least one driving route from the current real-time location of the target vehicle to the temporary parking point;

[0039] Each driving route does not include any target object. The target object is a congested road section with traffic congestion during the first time period, or an obstacle that hinders the normal driving of the target vehicle during the first time period.

[0040] Vehicle speed and direction of travel for each segment of each route;

[0041] Each section of the driving route has a designated avoidance route for pre-set vehicles or rescue vehicles.

[0042] Thirdly, embodiments of this application provide a computer device, the computer device comprising: at least one processor and a memory; wherein the memory is used to store a computer program, and the processor is used to invoke the computer program stored in the memory to execute the steps described in the first aspect and any of the embodiments of the first aspect.

[0043] Fourthly, embodiments of this application provide a computer-readable storage medium having the function of implementing the road condition anomaly handling method in a virtual driving scenario corresponding to the first aspect described above. The function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above function, and the modules can be software and / or hardware. Specifically, the computer-readable storage medium stores multiple instructions, which are adapted for loading by a processor to execute the steps of the first aspect and any implementation thereof in the embodiments of this application.

[0044] Compared to existing technologies, the solution provided in this application involves real-time detection of whether preset obstacles and visibility exist within the driving range of the target vehicle. If the visibility is lower than the preset visibility, and a target obstacle is detected that hinders the target vehicle, a safe driving distance is calculated, and the distance between the target vehicle and the congested road segment is detected. A temporary parking navigation guide is generated based on the road segment distance to control the target vehicle to safely drive to a temporary parking point. The temporary parking navigation guide includes an avoidance route, which does not include congested road segments or obstacles within the first time period. The target vehicle is controlled to drive to the temporary parking point according to the avoidance route based on the temporary parking navigation guide. Since the temporary parking navigation guide includes at least one avoidance route, which does not include congested road segments with traffic congestion within the first time period or any obstacles that hinder the normal driving of the target vehicle within the first time period, the target vehicle is controlled to drive to the temporary parking point within the second time period according to the avoidance route based on the temporary parking navigation guide. As can be seen, on the one hand, this solution can effectively identify abnormal situations in virtual driving scenarios, such as excessive speed or obstacles ahead, when visibility is low, and feed this information back to the physical engine, reminding the user to slow down and automatically providing intelligent temporary parking navigation to achieve deceleration and safe stopping. On the other hand, this solution can quickly design routes or driving plans that can rapidly reduce vehicle speed, i.e., the aforementioned temporary parking navigation guidance, regardless of whether the user is familiar with the current geographical area or the road conditions, without requiring human thought, and can quickly provide this temporary parking navigation guidance. Therefore, this method can assist intelligent driving vehicles in safely slowing down and stopping in specific weather conditions, thereby reducing the occurrence of traffic accidents. Attached Figure Description

[0045] Figure 1 This is a flowchart illustrating a method for handling abnormal road conditions in a virtual driving scenario, as described in this application.

[0046] Figure 2 This is a schematic diagram of a road condition anomaly handling device in an embodiment of this application;

[0047] Figure 3 This is a schematic diagram of the physical device that implements the method for handling abnormal road conditions in a virtual driving scenario in this application embodiment. Detailed Implementation

[0048] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects (e.g., the first region and the second region in the embodiments of this application represent different regions in the interface), and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. The division of modules in the embodiments of this application is merely a logical division; in actual applications, there may be other division methods. For example, multiple modules may be combined into or integrated into another system, or some features may be ignored or not performed. Additionally, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interface, and the indirect coupling or communication connection between modules may be electrical or other similar forms, none of which are limited in the embodiments of this application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separate, may or may not be physical modules, or may be distributed among multiple circuit modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of this application.

[0049] The following combination Figures 1-3 The technical solutions of the embodiments of this application will be described by way of example.

[0050] See Figure 1 A method for handling road condition anomalies in a virtual driving scenario is provided. This method can be applied to a virtual driving control system. The driving scenario simulation platform includes a first area and a second area. The first area displays multiple abnormal training driving modes, each including at least two road segment materials. The second area currently displays dynamic images under a specific weather driving mode. The dynamic images include a moving target vehicle and at least two road segment materials corresponding to the specific weather driving mode. The dynamic images and vehicle status of the target vehicle in the second area are transmitted to the vehicle perception model via a port. This method is executed by a simulator. Embodiments of this application include:

[0051] 101. Real-time detection of whether there are preset obstacles within the driving range of the target vehicle in the driving direction of the target vehicle in the dynamic image of the second area, and the visibility of the dynamic image.

[0052] 102. If a target obstacle is detected and the target obstacle meets the preset conditions that hinder the normal driving of the target vehicle within a first time period, then the vehicle speed of the target vehicle in the second area and the first physical distance between the target vehicle and the target obstacle within the first time period are obtained.

[0053] 103. Calculate the safe driving distance based on the first physical distance and the vehicle speed. When the first physical distance is less than the safe driving distance, detect the distance between the target vehicle and the congested road section.

[0054] 104. Generate and display temporary parking navigation guidance based on the distance of the road segment.

[0055] The temporary parking navigation guide is used to control the target vehicle to drive safely to the temporary parking point. The temporary parking navigation guide includes at least one avoidance route. The avoidance route does not include congested road sections with traffic congestion during the first time period, nor does it include any obstacles that hinder the normal driving of the target vehicle during the first time period.

[0056] 105. Receive the user's confirmation operation for the temporary parking navigation guide, control the speed and direction of the target vehicle according to the temporary parking navigation guide, select any avoidance route from the at least one avoidance route, and drive to the temporary parking point within the second time period.

[0057] The temporary parking navigation guide is used to control the target vehicle to safely drive to the temporary parking point.

[0058] In some implementations, the vehicle status also includes the real-time location of the target vehicle; the temporary parking navigation guidance includes at least one of the following:

[0059] At least one driving route from the current real-time location of the target vehicle to the temporary parking point;

[0060] Each driving route does not include any target object. The target object is a congested road section with traffic congestion during the first time period, or an obstacle that hinders the normal driving of the target vehicle during the first time period.

[0061] Vehicle speed and direction of travel for each segment of each route;

[0062] Each section of the driving route has a designated avoidance route for pre-set vehicles or rescue vehicles.

[0063] During this simulation, the user can continue driving according to a selected specific weather driving mode. Taking the fog driving mode as an example, the target vehicle will successively pass through light fog sections and dense fog sections. In the light fog section, if the visibility of the road ahead of the target vehicle is low and the physical distance to surrounding vehicles is less than the preset safe driving mode, the system can continuously send prompt messages to the user to remind them to slow down or pull over. For example, it can receive the user's confirmation operation for the first command and, in response to the first command, reduce the speed of the target vehicle.

[0064] 106. Receive the user's confirmation operation for the temporary parking navigation guide, and control the speed and direction of the target vehicle according to the temporary parking navigation guide until the vehicle reaches the temporary parking point.

[0065] In some implementations, the dynamic footage includes multi-view footage from a third-person perspective; generating the temporary parking navigation guidance includes:

[0066] (1) Obtain multi-view road condition images within a preset range of the target vehicle from a third-person perspective.

[0067] (2) Generate the temporary parking navigation guide based on the current speed of the target vehicle, the visibility of the multi-view road condition image, and the number of vehicles in the multi-view road condition image.

[0068] Specifically, based on the multi-view road condition images, the visibility of the environment around the target vehicle, the traffic congestion status, the number of vehicles in the multi-view road condition images, the number of vehicles interfering with the target vehicle's driving, the number of traffic lights, the characteristics of traffic signs, and the traffic light change status within the second time period are determined.

[0069] The temporary parking navigation guide is generated based on the visibility, vehicle speed, traffic congestion status, number of vehicles in the multi-view road condition image, number of vehicles interfering with the target vehicle's movement, number of traffic lights, characteristics of traffic signs, and traffic light change status.

[0070] In some embodiments, the method may further include:

[0071] Generate and output a target prompt message, which may include at least one of the following:

[0072] Generate a first prompt message of any type, including text, audio, or video, and output the first prompt message via at least one of the following methods: SMS, instant messaging, email, telephone, or pop-up window.

[0073] Understandably, after prompting the user, if the target vehicle's speed is subsequently detected to be below a first threshold, or the visibility of the target vehicle's surrounding environment is higher than a preset visibility level, then the driving on the normal road segment can be automatically canceled, the vehicle can exit the abnormal road segment, end the trip, and exit. After exiting, the vehicle perception model collects the target vehicle's driving data, including mileage, driving time, dangerous driving operation points, and driving scenes. The vehicle perception model can analyze the effectiveness of each virtual driving training session based on this driving data to continuously adjust and conduct more comprehensive driving simulation tests.

[0074] As can be seen, in this embodiment, the presence of preset obstacles and visibility within the driving range of the target vehicle are detected in real time. If the visibility is lower than the preset visibility, and a target obstacle is detected that hinders the target vehicle, a safe driving distance is calculated, and the distance between the target vehicle and the congested road segment is detected. A temporary parking navigation guide is generated based on the road segment distance to control the target vehicle to safely drive to a temporary parking point. The temporary parking navigation guide includes an avoidance route, which does not include congested road segments or obstacles within the first time period. The target vehicle is controlled to drive to the temporary parking point according to the avoidance route based on the temporary parking navigation guide. Since the temporary parking navigation guide includes at least one avoidance route, which does not include congested road segments with traffic congestion within the first time period or any obstacles that hinder the normal driving of the target vehicle within the first time period, the target vehicle is controlled to drive to the temporary parking point within the second time period according to the avoidance route based on the temporary parking navigation guide. As can be seen, on the one hand, this solution can effectively identify abnormal situations in virtual driving scenarios, such as excessive speed or obstacles ahead, when visibility is low, and feed this information back to the physical engine, reminding the user to slow down and automatically providing intelligent temporary parking navigation to achieve deceleration and safe stopping. On the other hand, this solution can quickly design routes or driving plans that can rapidly reduce vehicle speed, i.e., the aforementioned temporary parking navigation guidance, regardless of whether the user is familiar with the current geographical area or the road conditions, without requiring human thought, and can quickly provide this temporary parking navigation guidance. Therefore, this method can assist intelligent driving vehicles in safely slowing down and stopping in specific weather conditions, thereby reducing the occurrence of traffic accidents.

[0075] Figure 1 Any technical feature mentioned in the corresponding embodiments is also applicable to the embodiments of this application. Figure 2 , Figure 3 The corresponding implementation examples will not be repeated hereafter.

[0076] The above describes a method for handling abnormal road conditions in a virtual driving scenario according to an embodiment of this application. The following describes the road condition abnormality handling device that performs the above method for handling abnormal road conditions in a virtual driving scenario.

[0077] See Figure 2 ,like Figure 2 The diagram shows a road condition anomaly handling device 20, which can be applied to a virtual driving control system. The driving scenario simulation platform includes a first area and a second area. The first area displays multiple abnormal training driving modes, each including at least two road segment materials. The second area currently displays dynamic images under a specific weather driving mode. The dynamic images include a target vehicle in motion and at least two road segment materials corresponding to the specific weather driving mode. The dynamic images of the target vehicle in the second area and the vehicle status are transmitted to the vehicle perception model via a port. The road condition anomaly handling device 20 in this embodiment can achieve the above-mentioned... Figure 1 The corresponding embodiment describes the steps in the road condition anomaly handling method in a virtual driving scenario executed by the road condition anomaly handling device 20. The functions implemented by the road condition anomaly handling device 20 can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, and these modules can be software and / or hardware. The road condition anomaly handling device 20 may include an input / output module 201, a processing module 202, and a detection module 203. The functional implementation of the input / output module 201, processing module 202, and detection module 203 can be found in [reference needed]. Figure 1 The operations performed in the corresponding embodiments will not be described in detail here.

[0078] In some embodiments, the detection module 203 can be used to detect in real time whether there are preset obstacles within the driving range of the target vehicle in the driving direction of the target vehicle in the dynamic image of the second area, as well as the visibility of the dynamic image;

[0079] The processing module 202 is used to obtain, through the input / output module 201, the speed of the target vehicle in the second area and the first physical distance between the target vehicle and the target obstacle within the first time period if it is determined that the visibility is lower than the preset visibility, and a target obstacle is detected and the target obstacle meets the preset conditions that hinder the normal driving of the target vehicle within the first time period.

[0080] The processing module 202 is used to calculate a safe driving distance based on the first physical distance and the vehicle speed; when the first physical distance is less than the safe driving distance, it detects the distance between the target vehicle and the congested road section.

[0081] The processing module 202 is also used to generate and display temporary parking navigation guidance based on the road segment distance. The temporary parking navigation guidance is used to control the target vehicle to drive safely to the temporary parking point. The temporary parking navigation guidance includes at least one avoidance route. The avoidance route does not include congested road segments with traffic congestion during the first time period, nor does it include any obstacles that hinder the normal driving of the target vehicle during the first time period.

[0082] The input / output module 201 receives the user's confirmation operation for the temporary parking navigation guide, controls the speed and direction of the target vehicle according to the temporary parking navigation guide, selects any avoidance route from the at least one avoidance route, and drives to the temporary parking point within a second time period.

[0083] In some embodiments, the dynamic scene includes multi-view scenes from a third-person perspective; the processing module 202 is specifically used for:

[0084] Acquire multi-view road condition images within a preset range of the target vehicle from a third-person perspective;

[0085] The temporary parking navigation guide is generated based on the target vehicle's current speed, the visibility of the multi-view road condition images, and the number of vehicles in the multi-view road condition images.

[0086] In some embodiments, the processing module 202 is specifically used for:

[0087] Based on the multi-view road condition images, determine the visibility of the environment around the target vehicle, the traffic congestion status, the number of vehicles in the multi-view road condition images, the number of vehicles interfering with the target vehicle's driving, the number of traffic lights, the characteristics of traffic signs, and the traffic light change status within the second time period.

[0088] The temporary parking navigation guide is generated based on the visibility, vehicle speed, traffic congestion status, number of vehicles in the multi-view road condition image, number of vehicles interfering with the target vehicle's movement, number of traffic lights, characteristics of traffic signs, and traffic light change status.

[0089] In some implementations, the vehicle status includes the real-time location of the target vehicle; the temporary parking navigation guidance includes at least one of the following:

[0090] At least one driving route from the current real-time location of the target vehicle to the temporary parking point;

[0091] Each driving route does not include any target object. The target object is a congested road section with traffic congestion during the first time period, or an obstacle that hinders the normal driving of the target vehicle during the first time period.

[0092] Vehicle speed and direction of travel for each segment of each route;

[0093] Each section of the driving route has a designated avoidance route for pre-set vehicles or rescue vehicles.

[0094] This solution can effectively identify abnormal situations in virtual driving scenarios, such as excessive speed or obstacles in front of the vehicle when visibility is low, and feed this information back to the physical engine to remind the user to slow down. It also automatically performs intelligent temporary parking navigation to enable the user to slow down and stop safely during temporary parking navigation.

[0095] The road condition anomaly handling device 20 for executing the road condition anomaly handling method in a virtual driving scenario in this application embodiment has been described above from the perspective of modular functional entities. The road condition anomaly handling device 20 for executing the road condition anomaly handling method in a virtual driving scenario in this application embodiment will be described below from the perspective of hardware processing. It should be noted that in this application embodiment... Figure 2 In the embodiments shown, the physical device corresponding to the input / output module 201 can be a processor, input / output unit, transceiver, radio frequency circuit, communication module, and output interface, etc., and the physical device corresponding to the detection module 203 and processing module 202 can be a processor. Figure 2 The road condition abnormality handling device 20 shown can have the following functions: Figure 3 The structure shown, when Figure 2 The road condition abnormality handling device 20 shown has the following features: Figure 3 When the structure shown is used, Figure 3 The processor and transceiver in the device can perform the same or similar functions as the input / output module 201, processing module 202, and detection module 203 provided in the aforementioned embodiment of the road condition anomaly handling device 20. Figure 3 The memory stores the computer programs that the processor needs to call when executing the road condition anomaly handling method in the above virtual driving scenario.

[0096] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0097] 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 modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0098] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules 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 indirect coupling or communication connection through some interfaces, apparatuses, or modules, and may be electrical, mechanical, or other forms.

[0099] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0100] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0101] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0102] The computer program product includes one or more computer instructions. When the computer program is loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0103] The technical solutions provided in the embodiments of this application have been described in detail above. Specific examples have been used in the embodiments of this application to illustrate the principles and implementation methods of the embodiments of this application. The description of the above embodiments is only for the purpose of helping to understand the methods and core ideas of the embodiments of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the embodiments of this application. Therefore, the content of this specification should not be construed as a limitation on the embodiments of this application.

Claims

1. A method for handling abnormal road conditions in a virtual driving scenario, the method being used in a virtual driving control system, the virtual driving control system comprising a simulator, a vehicle perception model, and a driving scenario simulation platform; characterized in that, The driving scenario simulation platform includes a first area and a second area. The first area displays multiple abnormal training driving modes, each of which includes at least two road segment materials under a specific weather condition. The second area currently displays dynamic images under a specific weather driving mode. The dynamic images include a target vehicle in motion and at least two road segment materials corresponding to the specific weather driving mode. The dynamic images of the target vehicle in the second area and the vehicle status are transmitted to the vehicle perception model through a port. The method includes: Real-time detection of whether there are preset obstacles within the driving range of the target vehicle in the driving direction of the target vehicle in the dynamic image of the second area, and the visibility of the dynamic image; If it is determined that the visibility is lower than the preset visibility, and a target obstacle is detected and the target obstacle meets the preset conditions that hinder the normal driving of the target vehicle within a first time period, then the speed of the target vehicle in the second area and the first physical distance between the target vehicle and the target obstacle within the first time period are obtained. Calculate the safe driving distance based on the first physical distance and the vehicle speed; When the first physical distance is less than the safe driving distance, the distance between the target vehicle and the congested road section is detected; A temporary parking navigation guide is generated and displayed based on the road segment distance. The temporary parking navigation guide is used to control the target vehicle to drive safely to the temporary parking point. The temporary parking navigation guide includes at least one avoidance route. The avoidance route does not include congested road segments with traffic congestion during the first time period, nor does it include any obstacles that hinder the normal driving of the target vehicle during the first time period. The system receives confirmation from the user regarding the temporary parking navigation guidance, controls the speed and direction of the target vehicle according to the temporary parking navigation guidance, selects any avoidance route from the at least one avoidance route, and travels to the temporary parking point within a second time period.

2. The method for handling abnormal road conditions in a virtual driving scenario according to claim 1, characterized in that, The dynamic visuals include multi-view visuals from a third-person perspective; generating the temporary parking navigation guidance based on the road segment distance includes: Acquire multi-view road condition images within a preset range of the target vehicle from a third-person perspective; The temporary parking navigation guide is generated based on the target vehicle's current speed, the visibility of the multi-view road condition images, and the number of vehicles in the multi-view road condition images.

3. The method for handling abnormal road conditions in a virtual driving scenario according to claim 2, characterized in that, The step of generating the temporary parking navigation guidance based on the target vehicle's current speed and the multi-view road condition images includes: Based on the multi-view road condition images, determine the visibility of the environment around the target vehicle, the traffic congestion status, the number of vehicles in the multi-view road condition images, the number of vehicles interfering with the target vehicle's driving, the number of traffic lights, the characteristics of traffic signs, and the traffic light change status within the second time period. The temporary parking navigation guide is generated based on the visibility, vehicle speed, traffic congestion status, number of vehicles in the multi-view road condition image, number of vehicles interfering with the target vehicle's movement, number of traffic lights, characteristics of traffic signs, and traffic light change status.

4. The method for handling abnormal road conditions in a virtual driving scenario according to any one of claims 1-3, characterized in that, The vehicle status also includes the real-time location of the target vehicle; the temporary parking navigation guidance includes at least one of the following: At least one driving route from the current real-time location of the target vehicle to the temporary parking point; Each driving route does not include any target object. The target object is a congested road section with traffic congestion during the first time period, or an obstacle that hinders the normal driving of the target vehicle during the first time period. Vehicle speed and direction of travel for each segment of each route; Each section of the driving route has a designated avoidance route for pre-set vehicles or rescue vehicles.

5. A road condition anomaly handling device, wherein the road condition anomaly handling device is applied to a virtual driving control system, the virtual driving control system comprising a simulator, a vehicle perception model, and a driving scenario simulation platform; characterized in that, The driving scenario simulation platform includes a first area and a second area. The first area displays multiple abnormal training driving modes, each of which includes at least two road segment materials. The second area currently displays dynamic images under a specific weather driving mode. The dynamic images include a target vehicle in motion and at least two road segment materials corresponding to the specific weather driving mode. The dynamic images of the target vehicle in the second area and the vehicle status are transmitted to the vehicle perception model through a port. The road condition anomaly handling device includes: The detection module is used to detect in real time whether there are preset obstacles within the driving range of the target vehicle in the driving direction of the target vehicle in the dynamic image of the second area, as well as the visibility of the dynamic image; The processing module is used to obtain the vehicle speed of the target vehicle in the second area and the first physical distance between the target vehicle and the target obstacle within the first time period if it is determined that the visibility is lower than the preset visibility, and a target obstacle is detected and the target obstacle meets the preset conditions that hinder the normal driving of the target vehicle within the first time period. The processing module is also used to calculate a safe driving distance based on the first physical distance and the vehicle speed; when the first physical distance is less than the safe driving distance, it detects the distance between the target vehicle and the congested road section; The processing module is also used to generate and display temporary parking navigation guidance based on the road segment distance. The temporary parking navigation guidance is used to control the target vehicle to drive safely to the temporary parking point. The temporary parking navigation guidance includes at least one avoidance route. The avoidance route does not include congested road segments with traffic congestion during the first time period, nor does it include any obstacles that hinder the normal driving of the target vehicle during the first time period. The input / output module receives confirmation from the user regarding the temporary parking navigation guidance, controls the speed and direction of the target vehicle according to the temporary parking navigation guidance, selects any avoidance route from the at least one avoidance route, and travels to the temporary parking point within a second time period.

6. The road condition anomaly handling device according to claim 5, characterized in that, The dynamic visuals include multi-view visuals from a third-person perspective; the processing module is specifically used for: Acquire multi-view road condition images within a preset range of the target vehicle from a third-person perspective; The temporary parking navigation guide is generated based on the target vehicle's current speed, the visibility of the multi-view road condition images, and the number of vehicles in the multi-view road condition images.

7. The road condition anomaly handling device according to claim 6, characterized in that, The processing module is specifically used for: Based on the multi-view road condition images, determine the visibility of the environment around the target vehicle, the traffic congestion status, the number of vehicles in the multi-view road condition images, the number of vehicles interfering with the target vehicle's driving, the number of traffic lights, the characteristics of traffic signs, and the traffic light change status within the second time period. The temporary parking navigation guide is generated based on the visibility, vehicle speed, traffic congestion status, number of vehicles in the multi-view road condition image, number of vehicles interfering with the target vehicle's movement, number of traffic lights, characteristics of traffic signs, and traffic light change status.

8. The road condition anomaly handling device according to any one of claims 5-7, characterized in that, The vehicle status includes the real-time location of the target vehicle; the temporary parking navigation guidance includes at least one of the following: At least one driving route from the current real-time location of the target vehicle to the temporary parking point; Each driving route does not include any target object. The target object is a congested road section with traffic congestion during the first time period, or an obstacle that hinders the normal driving of the target vehicle during the first time period. Vehicle speed and direction of travel for each segment of each route; Each section of the driving route has a designated avoidance route for pre-set vehicles or rescue vehicles.

9. A computer device, characterized in that, The computer device includes: At least one processor and memory; The memory is used to store computer programs, and the processor is used to invoke the computer programs stored in the memory to execute the method as described in any one of claims 1-4.

10. A computer-readable storage medium, characterized in that, It includes instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1-4.

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