Vehicle control method, vehicle and storage medium

Abstract

The invention provides a vehicle control method, a vehicle and a storage medium, the method is applied to the technical field of driving safety, and the method comprises the steps that under the condition that the vehicle is engaged into a driving gear, the movement direction corresponding to the driving gear is determined; identifying traffic participants outside the vehicle from the environment where the vehicle is located based on the motion direction; acquiring relative position information between the vehicle and the traffic participant; determining a volume parameter of a target audio component in the vehicle according to the relative position information; and controlling the target audio component to play a prompt tone corresponding to the traffic participant according to the volume parameter. Based on the scheme of the invention, the perception ability of a driver to surrounding traffic participants can be improved by utilizing the prompt sound with the dynamic volume.

Description

Technical Field

[0001] The present application relates to the field of driving safety technology, and more specifically, to a vehicle control method, a vehicle, and a storage medium in the field of driving safety technology. Background Art

[0002] While driving, drivers typically need to perceive pedestrians, e-bikes, other vehicles, and other traffic participants in their surroundings through direct observation or with the help of on-board display devices. However, this visually-based approach to environmental perception has significant limitations. Drivers must maintain constant focus on the road ahead in complex road conditions, making it difficult to divert attention and look elsewhere. Furthermore, due to limitations in human visual field and attention allocation, it is easy to miss traffic participants in certain areas. These factors can make it difficult for drivers to fully and timely grasp the surrounding environment, increasing driving risks. Therefore, improving drivers' ability to perceive surrounding traffic participants has become a technical issue that needs to be addressed. Summary of the Invention

[0003] The present application provides a vehicle control method, a vehicle, and a storage medium, which can utilize a dynamic volume prompt sound to enhance the driver's perception of surrounding traffic participants.

[0004] In a first aspect, a vehicle control method is provided, the method comprising:

[0005] When the vehicle is in a driving gear, determining the movement direction corresponding to the driving gear;

[0006] Identify traffic participants other than the vehicle from the vehicle's environment based on its direction of movement;

[0007] Obtaining the relative position information between the vehicle and traffic participants;

[0008] determining a volume parameter of a target audio component inside the vehicle based on the relative position information;

[0009] The target audio component is controlled according to the volume parameter to play the corresponding prompt sound of the traffic participants.

[0010] Through the above solution, by converting the relative position information between the vehicle and traffic participants into quantifiable auditory prompts, multi-dimensional perception of surrounding traffic participants is achieved without interfering with the driver's normal visual perception, thereby improving the driver's perception of surrounding traffic participants.

[0011] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the relative position information includes a target distance parameter of the traffic participant relative to the vehicle; obtaining the relative position information between the vehicle and the traffic participant includes: obtaining a first position of the vehicle; obtaining a second position of the traffic participant; and determining the target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position.

[0012] Through the above scheme, the first position and the second position are first determined, and then the first position and the second position are used to determine the target distance parameter of the traffic participant relative to the vehicle, thereby effectively improving the accuracy of the target distance parameter. The target distance parameter provides a reliable data basis for the subsequent determination of the volume parameter.

[0013] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the volume parameters of the target audio component inside the vehicle are determined based on the relative position information, including: determining the volume parameters of the target audio component inside the vehicle based on the target distance parameter, the volume parameters corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

[0014] Through the above solution, by establishing a distance measurement mechanism between vehicles and traffic participants and converting distance information into quantifiable volume parameters, dynamic matching of the prompt sound intensity and the actual distance of traffic participants is achieved, effectively improving the driver's perception of surrounding traffic participants.

[0015] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the relative position information also includes a first azimuth parameter of the traffic participant relative to the vehicle; after determining the target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position, it also includes: determining the first azimuth parameter of the traffic participant relative to the vehicle based on the first position and the second position.

[0016] Through the above scheme, the first position and the second position are used to determine the first azimuth parameter of the traffic participant relative to the vehicle, which effectively improves the accuracy of the first azimuth parameter, and the first azimuth parameter provides a reliable data basis for the subsequent determination of the target audio component.

[0017] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, multiple audio components are provided inside the vehicle; the volume parameters of the target audio component inside the vehicle are determined based on the relative position information, including: determining the target audio component among the multiple audio components based on the first azimuth parameter; determining the volume parameters of the target audio component inside the vehicle based on the target distance parameter, the volume parameter corresponding to the target audio component, and the first mapping relationship between the distance parameter and the volume parameter, the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

[0018] Through the above scheme, the target audio component that best matches the direction of the traffic participant is screened out from multiple audio components based on the first azimuth angle parameter. The target audio component and volume parameters can then be used to provide the driver with a prompt sound of a specific direction and intensity, thereby simultaneously improving the driver's perception of surrounding traffic participants in the spatial direction and distance dimensions.

[0019] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, a target audio component is determined among multiple audio components based on a first azimuth angle parameter, including: determining a third position of the driver in the vehicle, and a fourth position of each audio component among the multiple audio components; determining a second azimuth angle parameter of each audio component relative to the vehicle based on the third position and the fourth position of each audio component, the second azimuth angle parameter and the first azimuth angle parameter sharing the same reference system; calculating the angle between the second azimuth angle parameter and the first azimuth angle parameter of each audio component respectively to obtain the azimuth angle of each audio component; and determining, among the multiple audio components, an audio component whose azimuth angle is less than or equal to a preset angle threshold as a target audio component.

[0020] Through the above scheme, by performing angle calculation and threshold comparison based on the first azimuth parameter and the second azimuth parameter, accurate matching of the audio component with the orientation of the traffic participant can be achieved, and the appropriate target audio component can be determined from multiple audio components, thereby improving the driver's perception of the traffic participant's orientation.

[0021] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, determining the target audio component among multiple audio components based on the first azimuth parameter includes: determining the target audio component among multiple audio components based on the first azimuth parameter and the second mapping relationship between the azimuth parameter and the audio component.

[0022] This solution pre-establishes a second mapping relationship between azimuth parameters and audio components. Once the first azimuth parameter of a traffic participant is obtained, the target audio component can be quickly identified by querying the second mapping relationship based on that first azimuth parameter. Compared to real-time calculation of the audio component's azimuth angle, this solution significantly reduces computational complexity by pre-storing the mapping relationship.

[0023] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the method also includes: determining the prompt sound corresponding to the traffic participant based on the target object type of the traffic participant and the third mapping relationship between the object type and the prompt sound; wherein, the target object type is obtained by calling a preset recognition algorithm to identify the sensor data of the target sensor, and the detection direction of the target sensor corresponds to the movement direction.

[0024] Through the above solution, based on the typed prompt sound design, drivers can quickly distinguish different types of traffic participants through sound characteristics, and ultimately achieve accurate matching of traffic participant types with prompt sound characteristics. This allows drivers to not only perceive the location and distance of traffic participants, but also judge their type characteristics, providing more comprehensive environmental information support for driving decisions and further improving driving safety.

[0025] In a second aspect, a vehicle control device is provided, the device comprising:

[0026] a first determining unit, configured to determine a movement direction corresponding to a driving gear when the vehicle is in a driving gear;

[0027] an identification unit for identifying traffic participants other than the vehicle from the vehicle's environment based on the direction of movement;

[0028] an acquisition unit, for acquiring relative position information between the vehicle and traffic participants;

[0029] a second determining unit, configured to determine a volume parameter of a target audio component inside the vehicle according to the relative position information;

[0030] The playback unit is used to control the target audio component to play the corresponding prompt sound of the traffic participant according to the volume parameter.

[0031] According to a third aspect, a vehicle is provided, wherein the vehicle comprises:

[0032] a memory for storing executable program code;

[0033] A processor is used to call and run executable program code from the memory, so that the vehicle executes the method in the above-mentioned first aspect or any possible implementation of the first aspect.

[0034] In a fourth aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0035] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program code. When the computer program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a schematic diagram of a scene of a vehicle and surrounding traffic participants provided by an embodiment of the present application;

[0037] Figure 2 This is a flow chart of a vehicle control method provided in an embodiment of the present application;

[0038] Figure 3 This is an example schematic diagram of identifying traffic participants based on a target camera provided in an embodiment of the present application;

[0039] Figure 4 This is a flow chart of determining volume parameters provided by an embodiment of the present application;

[0040] Figure 5 This is a schematic diagram of an example of a reference position provided in an embodiment of the present application;

[0041] Figure 6 This is a flow chart of determining volume parameters provided by an embodiment of the present application;

[0042] Figure 7 This is an example schematic diagram of a multi-audio component provided in an embodiment of the present application;

[0043] Figure 8 This is a schematic structural diagram of a vehicle control device provided in an embodiment of the present application;

[0044] Figure 9 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] The following will clearly and thoroughly describe the technical solutions in this application in conjunction with the accompanying drawings. In the description of the embodiments of this application, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more than two.

[0046] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include one or more of such features.

[0047] See also Figure 1 , Figure 1 This is a schematic diagram of a scene of a vehicle and surrounding traffic participants provided in an embodiment of the present application. During vehicle driving, the driver usually needs to perceive traffic participants such as pedestrians, electric bicycles, and other vehicles in the surrounding environment through direct observation or with the help of on-board display equipment. However, this environmental perception method based on the driver's vision has obvious limitations: the driver needs to keep paying attention to the road ahead under complex road conditions and it is difficult to distract attention to observe other directions; at the same time, due to the limitations of human visual field and attention distribution, it is easy to miss traffic participants in some areas. It is understandable that the above factors may make it difficult for the driver to grasp the environmental conditions surrounding the vehicle in a timely and comprehensive manner, increasing driving risks.

[0048] In some possible scenarios, when a vehicle is driving at low speed on a congested urban road, pedestrians may frequently cross the road and electric bicycles may weave in and out of traffic. Because the driver needs to focus on the starting and stopping of the vehicle in front, it is difficult to continuously observe traffic participants on the side and behind. For example, when the vehicle is preparing to change lanes or turn right, if an electric bicycle or pedestrian in the right blind spot is not noticed, it may result in a scratch or even a collision. In addition, the rearview mirror has a limited field of view and cannot cover all potential danger areas, further increasing the driver's perceptual burden.

[0049] In some potential scenarios, drivers' visual observation abilities are reduced when driving at night or in adverse weather conditions such as rain, snow, fog, and smog. For example, on unlit roads at night, pedestrians or non-motorized vehicles may be difficult to spot due to their dark clothing. In rainy and foggy weather, water droplets or mist on the windshield further obscure vision, making it even more difficult for drivers to detect unexpected traffic participants. In these situations, relying solely on the driver's visual observation may result in insufficient reaction time, increasing the probability of accidents.

[0050] In summary, existing environmental perception methods based on driver vision have significant shortcomings in various driving scenarios, making it difficult for drivers to fully and timely grasp the dynamics of surrounding traffic participants. Therefore, improving drivers' ability to perceive surrounding traffic participants has become a technical problem that needs to be solved.

[0051] To address the above issues, the solution provided by the embodiments of this application mainly includes: first, identifying traffic participants outside the vehicle from the vehicle's environment; then, obtaining the relative position information between the vehicle and the traffic participants; then, determining the volume parameters of the target audio component inside the vehicle based on the relative position information; and finally, controlling the target audio component to play the corresponding prompt tone of the traffic participant based on the determined volume parameters. In this way, by converting the relative position information between the vehicle and the traffic participants into quantifiable auditory prompts, multi-dimensional perception of surrounding traffic participants is achieved without interfering with the driver's normal visual perception, thereby improving the driver's ability to perceive surrounding traffic participants.

[0052] based on Figure 1 The following scene is combined with Figure 2 - Figure 7 , the vehicle control method provided in the embodiment of the present application is introduced in detail.

[0053] See Figure 2 , Figure 2 This is a flow chart of a vehicle control method provided in an embodiment of the present application. Figure 2 As shown, the method of the embodiment of the present application may include the following steps S101-S105.

[0054] S101: When the vehicle is in a driving gear, determine a movement direction corresponding to the driving gear.

[0055] Specifically, the driving gears referred to in this embodiment refer to the working gears used to drive the vehicle, including forward and reverse gears. Driving gears are distinguished from non-driving gears such as parking and neutral. It is understood that when a vehicle is engaged in a driving gear, it indicates that the vehicle is in or about to enter a state of motion, in contrast to the stationary state of the vehicle in parking or neutral.

[0056] When a vehicle is in a driving gear, it is necessary to further determine the direction of movement corresponding to the driving gear. The direction of movement corresponding to the driving gear refers to the direction the vehicle actually travels after the gear is engaged. In some possible implementations, a preset correspondence exists between the driving gear and the direction of movement. This correspondence can be used to determine the corresponding direction of movement when determining the driving gear. For example, the direction of movement corresponding to the forward gear is directly forward of the vehicle, while the direction of movement corresponding to the reverse gear is directly backward of the vehicle.

[0057] S102 , based on the movement direction, identifying traffic participants other than the vehicle from the environment in which the vehicle is located.

[0058] Specifically, after determining the direction of motion, sensor data corresponding to that direction can be acquired for subsequent traffic participant identification. First, a target sensor in the vehicle is identified based on the direction of motion; the target sensor's detection direction corresponds to the direction of motion. Next, sensor data from the target sensor detecting the vehicle's environment is acquired. Finally, traffic participants outside the vehicle are identified based on the target sensor's sensor data.

[0059] The vehicle environment referred to in this embodiment refers to a three-dimensional spatial area centered on the vehicle and within a preset range. Traffic participants outside the vehicle refer to dynamic or static objects that potentially interact with the vehicle. For example, traffic participants may include pedestrians, electric bicycles, motorcycles, other vehicles, and other objects outside the vehicle.

[0060] Regarding the step of determining the target sensor in the vehicle based on the direction of movement, in some possible implementations, the vehicle is provided with at least one camera, and the target sensor is a target camera among the at least one camera. The target camera refers to a camera whose installation position and shooting angle can cover the main area of the vehicle's movement direction. Among them, the shooting direction of the target camera corresponds to the movement direction, which means that the angle between the main optical axis direction of the camera and the vehicle's movement direction is less than a preset threshold. In some possible implementations, the field of view angle coverage of each camera can be calculated based on the vehicle camera installation position parameters and the current movement direction, and then the camera with the smallest angle between the field of view centerline and the movement direction is selected as the target camera. In some possible implementations, the target sensor can also be the vehicle's target lidar or other types of sensors, which are not limited to this.

[0061] Regarding the step of acquiring sensor data obtained by the target sensor from detecting the vehicle's environment, in some possible implementations, images captured by the target camera of the vehicle's environment can be acquired. Specifically, the target camera can be controlled to capture the vehicle's environment at a preset sampling frequency and transmit the captured images to an image processing unit. In some possible implementations, key frames can be extracted from the video stream continuously captured by the target camera as the captured images.

[0062] Finally, traffic participants other than vehicles are identified based on the sensor data from the target sensor. In some possible implementations, traffic participant identification can be achieved based on a deep learning semantic segmentation algorithm. For example, the captured image is input into a trained semantic segmentation neural network model, which classifies the input image pixel by pixel and outputs a segmentation result containing pixel-level semantic labels. Based on preset traffic participant categories, pixel regions belonging to traffic participant categories such as pedestrians and electric bicycles are extracted from the segmentation result. Morphological processing and region clustering are performed on the extracted pixel regions to obtain the precise boundary and position information of each traffic participant in the image, thus completing the identification of the traffic participant. In addition, traffic participant identification can also be achieved based on other algorithms. For example, object detection algorithms such as YOLO and Faster R-CNN can be used to directly locate the bounding boxes of traffic participants from the captured image to achieve traffic participant identification.

[0063] To understand this embodiment, please refer to Figure 3 , Figure 3 This is an example schematic diagram of an embodiment of the present application for identifying traffic participants based on a target camera. The target camera is a camera installed at the rear of the vehicle with a shooting direction facing directly behind the vehicle, and the traffic participant is a pedestrian moving from the right rear side of the vehicle to the directly behind the vehicle. Assuming that the vehicle is in reverse gear, the shooting direction of the target camera is consistent with the direction of movement of the vehicle. The target camera continuously captures images of the environment behind the vehicle, and the image processing unit analyzes and processes the captured images. The semantic segmentation neural network identifies the presence of pedestrian feature areas in the image, determines that the traffic participant is a pedestrian type, and thus completes the identification of the traffic participant.

[0064] In some possible implementations, the target sensor is a target lidar, and the point cloud data collected by the target lidar can be processed to identify traffic participants other than vehicles. Specifically, the point cloud data collected by the target lidar can be clustered based on a preset point cloud segmentation algorithm to obtain multiple point cloud clusters; the feature parameters of each point cloud cluster in the multiple point cloud clusters are calculated using a point cloud feature extraction algorithm, and the feature parameters include but are not limited to point cloud density distribution, geometric shape characteristics, and reflection intensity distribution; the feature parameters of each point cloud cluster are matched with a preset traffic participant feature database, which stores standard feature parameters of traffic participants such as pedestrians, electric bicycles, motorcycles, and other vehicles; when the similarity between the feature parameters of the point cloud cluster and a certain type of standard feature parameters in the traffic participant feature database exceeds a preset similarity threshold, the object corresponding to the point cloud cluster is determined to be a traffic participant other than a vehicle. In some cases, for the identified traffic participants, their three-dimensional coordinate information in the target lidar coordinate system can also be recorded for subsequent processing.

[0065] It should be noted that this embodiment does not limit the type and number of traffic participants.

[0066] S103, obtaining relative position information between the vehicle and traffic participants.

[0067] Specifically, the relative position information between a vehicle and a traffic participant refers to a set of parameters used to describe the spatial positional relationship between the traffic participant and the vehicle. For example, the relative position information may include one or more of a target distance parameter of the traffic participant relative to the vehicle and a first azimuth parameter of the traffic participant relative to the vehicle.

[0068] Regarding the process of obtaining the relative position information between the vehicle and the traffic participant, in some possible implementations, a certain position can be determined in the vehicle, and another position of the traffic participant can be determined. The position of the vehicle can be any preset fixed spatial point in the vehicle, the driver's position point, or the key component installation position point, representing the base reference point for calculating the relative position information; the position of the traffic participant can be the geometric center point or key feature position point of the traffic participant, representing the target reference point for calculating the relative position information. It should be noted that the position of the vehicle and the position of the traffic participant are both positions in the same coordinate system. Furthermore, based on the position of the vehicle and the position of the traffic participant, the distance parameters, azimuth parameters and other data of the traffic participant relative to the vehicle are determined, and the distance parameters, azimuth parameters and other data of the traffic participant relative to the vehicle are determined as the relative position information between the vehicle and the traffic participant.

[0069] S104: Determine a volume parameter of a target audio component inside the vehicle according to the relative position information.

[0070] Specifically, the audio component involved in this embodiment refers to a vehicle-mounted sound device that can receive electrical signals and convert them into sound waves for output. For example, the audio component can be a speaker, an audio unit, or an independent channel unit in a 3D surround sound system.

[0071] The vehicle involved in this embodiment is provided with at least one audio component inside, and the target audio component is selected from the at least one audio component. Therefore, the target audio component can be one or more, and there is no limitation on this.

[0072] The volume parameter of an audio component refers to the electrical or digital signal parameter that controls the intensity of the sound waves output by the audio component. It is understood that a higher volume parameter indicates a stronger tone output by the audio component, while a lower volume parameter indicates a weaker tone output by the audio component.

[0073] Regarding the process of determining the volume parameter of a target audio component within a vehicle based on relative position information, in some implementations, the relative position information only includes a distance parameter of the traffic participant relative to the vehicle. In this case, the volume parameter of the target audio component can be directly determined based on the distance parameter of the traffic participant relative to the vehicle and a preset mapping relationship. It should be noted that the closer the distance parameter indicates to the vehicle, the higher the volume parameter of the target audio component; and the farther the distance parameter indicates to the vehicle, the lower the volume parameter of the target audio component.

[0074] In some implementations, the relative position information includes both the distance parameter and the azimuth parameter of the traffic participant relative to the vehicle. In this case, the target audio component can be first screened out from multiple audio components based on the azimuth parameter, and then the volume parameter of the target audio component can be determined based on the distance parameter. Specifically, the azimuth parameter is used to determine the orientation of the traffic participant relative to the vehicle. When the orientation of each audio component relative to the vehicle is determined, some audio components that are closer to the orientation of the traffic participant can be selected as target audio components. After determining the target audio component, the volume parameter of the target audio component can be determined based on the distance parameter of the traffic participant relative to the vehicle and a preset mapping relationship.

[0075] It should be noted that the adjustment of the volume parameters can be performed in real time or updated periodically at preset time intervals to ensure that the intensity of the prompt sound is synchronized with the actual position changes of the traffic participants.

[0076] S105, controlling the target audio component to play the prompt sound corresponding to the traffic participant according to the volume parameter.

[0077] Specifically, the prompt sound corresponding to a traffic participant refers to a preset audio signal that matches the movement characteristics of the traffic participant. In some cases, the same prompt sound can be used for multiple types of traffic participants. For example, pedestrians, electric bicycles, and motorcycles can share an electronic buzzer as a prompt sound. In some cases, the prompt sound corresponding to each of the multiple types of traffic participants can be different. For example, the prompt sound corresponding to pedestrians can be footsteps; the prompt sound corresponding to electric bicycles can be a simulated motor running sound unique to electric bicycles in motion; and the prompt sound corresponding to other motor vehicles can be a recorded audio combination of the vehicle's engine running sound and tire friction sound.

[0078] Regarding the process of controlling the target audio component to play the corresponding prompt sound for traffic participants based on volume parameters, the specific implementation is as follows: presetting a standard prompt sound sample library for traffic participants; when a specific type of traffic participant is identified, retrieving the standard prompt sound sample corresponding to this type of traffic participant; loading the standard prompt sound sample corresponding to this type of traffic participant as an audio signal to be played through a digital signal processing module, and performing gain adjustment on the audio signal according to the current volume parameter; and transmitting the gain-adjusted audio signal to the selected target audio component for playback.

[0079] In this embodiment, the direction of motion corresponding to the driving gear is first determined when the vehicle is in driving gear, ensuring that the recognition function is only activated when the vehicle is in driving mode, avoiding invalid recognition when not in driving mode. Based on the direction of motion, traffic participants outside the vehicle are identified from the vehicle's environment. By aligning the recognition direction with the vehicle's direction of motion, effective monitoring of traffic participants in the vehicle's direction of motion is ensured. The relative position information between the vehicle and the traffic participants is obtained, providing accurate spatial relationship data for subsequent volume control. The volume parameters of the target audio component inside the vehicle are determined based on the relative position information, and finally, the target audio component is controlled based on the volume parameters to play the prompt tone corresponding to the traffic participant. In this way, by converting the relative position information between the vehicle and the traffic participant into a quantifiable auditory prompt, multi-dimensional perception of surrounding traffic participants is achieved without interfering with the driver's normal visual perception, thereby improving the driver's perception of surrounding traffic participants.

[0080] See Figure 4 , provides a flow chart of determining volume parameters for an embodiment of the present application, such as Figure 4 As shown, the method of the embodiment of the present application may include the following steps S201-S204, wherein steps S201-S203 may be used as Figure 2 The detailed step of step S103 in the embodiment shown in the figure, step S204 can be used as Figure 2 The detailed steps of step S104 in the embodiment are shown.

[0081] S201, obtaining a first position of the vehicle;

[0082] S202, obtaining a second position of a traffic participant;

[0083] S203, determining a target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position;

[0084] S204: Determine the volume parameter of the target audio component inside the vehicle based on the target distance parameter, the volume parameter corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, wherein the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

[0085] Specifically, the "first position" refers to any preset fixed spatial point in the vehicle, the driver's location, or a key component installation location, representing a reference point for calculating relative position information. In specific implementations, the "first position" can be the vehicle's geometric center, the driver's location, or other locations. The process of obtaining the vehicle's "first position" can be performed by obtaining the three-dimensional coordinates of a preset fixed point as the first position, or by using an in-vehicle camera to determine the driver's location in real time and determine that location as the first position.

[0086] The second position refers to the geometric center point or key feature position point of the traffic participant, representing the target reference point used to calculate relative position information. In a specific implementation, for pedestrians, the second position can be the center point of the human torso or the position point of the head; for two-wheeled vehicles, it can be the center point of the wheel axis or the center point of the handlebar; for four-wheeled vehicles, it can be the center point of the vehicle's front face or the center point of the rear axle. The process of obtaining the second position of a traffic participant can be manifested as: detecting the reflection center point of the object through millimeter-wave radar and determining it as the first position; capturing an image through a camera and then identifying feature points through a target detection algorithm, and determining it as the first position; or calculating the geometric center point of the object through lidar point cloud data and determining it as the first position.

[0087] It should be noted that the first position and the second position mentioned above can be expressed as coordinates in a coordinate system.

[0088] The process of determining the target distance parameter based on the first position and the second position includes: first converting the first position and the second position to the same coordinate system (if they are in the same coordinate system beforehand, no conversion is required); then calculating the Euclidean distance between the two points as the target distance parameter.

[0089] For example, the calculation formula of the target distance parameter may be:

[0090] d=√[(x2-x1)2+(y2-y1)2+(z2-z1)2]

[0091] Among them, (x1, y1, z1) are the coordinates corresponding to the first position, (x2, y2, z2) are the coordinates corresponding to the second position, and d is the target distance parameter.

[0092] The first mapping relationship between the distance parameter and the volume parameter refers to a preset mapping relationship between the distance parameter and the volume parameter. Under the guidance of this first mapping relationship, a specific volume parameter can be determined based on a specific distance parameter. This first mapping relationship can be implemented using a linear function, a piecewise function, or a lookup table, without limitation.

[0093] Regarding the process of calculating the first mapping relationship between the target distance parameter, the volume parameter corresponding to the target audio component, and the distance parameter and the volume parameter, in some possible implementations, the first mapping relationship is implemented using a linear function. Then, based on the ratio of the target distance parameter to the preset maximum distance parameter and minimum distance parameter, the volume parameter corresponding to the target audio component is obtained by linear interpolation calculation; wherein, when the target distance parameter is equal to the minimum distance parameter, the volume parameter takes the maximum value; when the target distance parameter is equal to the maximum distance parameter, the volume parameter takes the minimum value.

[0094] In some possible implementations, the first mapping relationship is implemented using a piecewise function, and then the corresponding function relationship is selected to calculate the volume parameter corresponding to the target audio component based on the distance interval in which the target distance parameter is located; wherein the distance interval includes a short distance interval, a medium distance interval, and a long distance interval, and the volume parameter change gradient corresponding to the short distance interval is greater than that of the medium distance interval, and the volume parameter change gradient corresponding to the medium distance interval is greater than that of the long distance interval.

[0095] In some possible implementations, the first mapping relationship is implemented using a table lookup method, where a preset distance-volume comparison table is queried based on the target distance parameter to obtain the corresponding volume parameter; wherein the distance-volume comparison table stores multiple discrete distance parameters and their corresponding volume parameter values. When the target distance parameter is between two discrete distance parameters, the corresponding volume parameter is obtained by linear interpolation.

[0096] It should be noted that the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component. This means that when the target distance parameter indicates that the traffic participant is closer to the vehicle, the volume parameter corresponding to the target audio component is larger; when the target distance parameter indicates that the traffic participant is farther away from the vehicle, the volume parameter corresponding to the target audio component is smaller. For example, when the target distance parameter is 5 meters, the volume parameter corresponding to the target audio component is 80 decibels; when the target distance parameter is 8 meters, the volume parameter corresponding to the target audio component is 60 decibels; and when the target distance parameter is 10 meters, the volume parameter corresponding to the target audio component is 40 decibels.

[0097] To understand this embodiment, please refer to Figure 5 , Figure 5This is an example schematic diagram of a reference position provided in an embodiment of the present application. For example, the center point of the vehicle's cabin is taken as the first position, and its coordinates are (x1, y1, z1); the traffic participant is identified as a pedestrian, and the pedestrian is located to the right rear of the vehicle, and the center point of the pedestrian's torso is obtained as the second position, and its coordinates are (x2, y2, z2). After unifying the first position and the second position to the vehicle coordinate system, the Euclidean distance d = √[(x2-x1)2+(y2-y1)2+(z2-z1)2] is calculated, and it is assumed that the target distance parameter d = 5 meters is obtained. According to the first mapping relationship between the preset distance parameter and the volume parameter, substituting the target distance parameter d = 5 meters can determine that the volume parameter is 72 decibels, that is, the target audio component can be controlled to play the footstep prompt sound corresponding to the pedestrian at a volume parameter of 72 decibels.

[0098] In this embodiment, the first position of the vehicle is first obtained as a reference point, and the second position of the traffic participant is simultaneously obtained as a target point. By calculating the spatial distance between the first position and the second position, the target distance parameter of the traffic participant relative to the vehicle is determined. Then, based on the target distance parameter, combined with a pre-established first mapping relationship between the distance parameter and the volume parameter, the volume parameter corresponding to the target audio component inside the vehicle is determined, wherein the target distance parameter and the volume parameter corresponding to the target audio component maintain a positive correlation. In this way, by establishing a distance measurement mechanism between the vehicle and the traffic participant and converting the distance information into a quantifiable volume parameter, a dynamic matching of the prompt sound intensity and the actual distance of the traffic participant is achieved: when the traffic participant is closer to the vehicle, the prompt volume is automatically increased to improve the warning effect; when the traffic participant is farther away from the vehicle, the prompt volume is correspondingly reduced to avoid interference. This allows the driver to intuitively judge the proximity of the traffic participant by the intensity of the prompt sound, effectively improving the driver's perception of surrounding traffic participants.

[0099] See Figure 6 , provides a flow chart of determining volume parameters for an embodiment of the present application. In which, there are multiple audio components inside the vehicle. Figure 6 As shown, the method of the embodiment of the present application may include the following steps S301-S306, wherein steps S301-S304 may be used as Figure 2 The detailed steps of step S103 in the embodiment shown, steps S305-S306 can be used as Figure 2 The detailed steps of step S104 in the embodiment are shown.

[0100] S301, obtaining a first position of the vehicle;

[0101] S302, obtaining a second position of a traffic participant;

[0102] S303, determining a target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position;

[0103] S304, determining a first azimuth angle parameter of the traffic participant relative to the vehicle based on the first position and the second position;

[0104] S305, determining a target audio component from a plurality of audio components according to the first azimuth parameter;

[0105] S306: Determine the volume parameter of the target audio component inside the vehicle based on the target distance parameter, the volume parameter corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, wherein the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

[0106] Specifically, a vehicle is equipped with multiple audio components, and the multiple audio components may be located in different locations within the vehicle. Considering the driver's need to perceive the direction of sound sources in different directions, this embodiment proposes determining a target audio component from the multiple audio components, and the number of target audio components may be one or more.

[0107] The implementation of steps S301-S303 can be found in Figure 4 For the explanation of steps S201 to S203 in the embodiment shown, please refer to the implementation of step S306. Figure 4 The explanation related to step S204 in the illustrated embodiment will not be repeated here.

[0108] After determining the target distance parameter, it is also necessary to determine the first azimuth parameter of the traffic participant relative to the vehicle based on the first and second positions. Regarding this process, in some possible implementations, a three-dimensional coordinate system can be established with the first position as the origin. The coordinates of the second position in this coordinate system can be converted into polar coordinates, and the azimuth component can be extracted as the first azimuth parameter of the traffic participant relative to the vehicle. In other possible implementations, the horizontal angle between the line connecting the first and second positions and a reference line in the vehicle's forward direction can be calculated, and this horizontal angle can be determined as the first azimuth parameter of the traffic participant relative to the vehicle.

[0109] Furthermore, a target audio component is determined from among the multiple audio components based on the first azimuth parameter. Specifically, the target audio component that matches the first azimuth parameter can be determined from among the multiple audio components by comparing the correspondence between the first azimuth parameter and the azimuth parameters of each audio component, or according to a preset azimuth matching rule.

[0110] In this embodiment, a first position of the vehicle and a second position of a traffic participant are first obtained. A spatial relationship between the first and second positions is calculated to determine a target distance parameter and a first azimuth parameter of the traffic participant relative to the vehicle. A target audio component that best matches the traffic participant's position is then selected from multiple audio components based on the first azimuth parameter. Finally, a volume parameter of the target audio component is determined based on a first mapping relationship between the target distance parameter and a preset distance parameter and volume parameter, wherein the target distance parameter and the volume parameter maintain a positive correlation. Thus, by establishing a spatial position measurement mechanism, the position and distance information of the traffic participant relative to the vehicle are converted into quantifiable audio control parameters, achieving a spatial correspondence between the direction of the warning sound and the actual position of the traffic participant. Furthermore, the intensity of the warning sound is dynamically adjusted with distance. When a traffic participant is at a specific position of the vehicle, the target audio component at the corresponding position is selected to play the warning sound, allowing the driver to intuitively determine the traffic participant's position based on the direction of the sound source. As the traffic participant gets closer to the vehicle, the volume parameter of the target audio component increases to enhance the warning effect, while as the distance increases, the volume decreases to avoid interference, thereby simultaneously improving the driver's perception of surrounding traffic participants in both spatial position and distance dimensions.

[0111] In one embodiment, Figure 6 Step S305 of the embodiment may be further refined to include the following steps:

[0112] determining a third location of the driver in the vehicle and a fourth location of each of the plurality of audio components;

[0113] determining a second azimuth parameter of each audio component relative to the vehicle based on the third position and a fourth position of each audio component, wherein the second azimuth parameter and the first azimuth parameter share a same reference system;

[0114] Calculating the angle between the second azimuth parameter and the first azimuth parameter of each audio component to obtain the azimuth angle of each audio component;

[0115] Among multiple audio components, an audio component whose azimuth angle is less than or equal to a preset angle threshold is determined as a target audio component.

[0116] Specifically, the third position refers to the spatial location of the driver's head or ears, representing the primary location where the driver receives sound signals. In specific implementations, the third position can be the center of the driver's seat headrest, the center of the steering wheel, or the driver's facial features detected in real time by an in-vehicle camera. For example, the third position is determined by obtaining the driver's seat adjustment parameters using a seat position sensor, calculating the head position based on a preset human body model, or capturing the three-dimensional coordinates of the driver's head in real time using an in-vehicle stereo vision system. Alternatively, the third position can be determined directly using the driver's preset standard sitting position.

[0117] The fourth position refers to the location point corresponding to each audio component, characterizing the spatial distribution characteristics of each audio component. In a specific implementation, the fourth position can be the center point of the speaker diaphragm, the geometric center point of the speaker housing, or the fixing point of the mounting bracket. For example, the preset installation coordinates of each audio component are obtained and determined as the corresponding fourth position; or the geometric center coordinates of each audio component are extracted based on a three-dimensional model of the vehicle interior and determined as the corresponding fourth position.

[0118] It should be noted that the third position and the fourth position mentioned above can be expressed as coordinates in a coordinate system.

[0119] The second azimuth parameter refers to the azimuth angle value of each audio component relative to the driver's position based on the vehicle's reference system. The process of determining the second azimuth parameter of each audio component relative to the vehicle based on the third position and the fourth position of each audio component is as follows: establishing a polar coordinate system with the third position as the origin; converting the fourth position coordinates of each audio component to the polar coordinate system; and calculating the azimuth component corresponding to each audio component as the second azimuth parameter. It should be noted that the second azimuth parameter and the first azimuth parameter use the same reference reference plane and zero-degree reference line to ensure the consistency of the angle calculation.

[0120] The azimuth angle refers to the minimum angular difference between the first azimuth parameter of the traffic participant and the second azimuth parameter of each audio component. For example, if the first azimuth parameter is a specific angle value and the second azimuth parameter of a certain audio component is another specific angle value, the azimuth angle is the minimum angular difference between the two. Regarding the process of calculating the angle between the second azimuth parameter and the first azimuth parameter of each audio component to obtain the azimuth angle of each audio component, specifically: for each audio component among the multiple audio components, calculate the absolute difference between the second azimuth parameter and the first azimuth parameter of the audio component; when the absolute difference does not exceed half a circle angle, determine the absolute difference as the azimuth angle of the audio component; when the absolute difference exceeds half a circle angle, subtract the absolute difference from the full circle angle to determine the result as the azimuth angle of the audio component.

[0121] The preset angle threshold refers to the maximum allowable azimuth angle deviation used to screen the target audio component. In a specific implementation, the preset angle threshold can be dynamically adjusted according to the vehicle's interior space size, the number of audio components, and the distribution density. When the number of audio components is large and densely distributed, the preset angle threshold can be appropriately reduced to improve the azimuth resolution accuracy; when the number of audio components is small and sparsely distributed, the preset angle threshold can be appropriately increased to ensure coverage. Regarding the process of determining an audio component whose azimuth angle is less than or equal to the preset angle threshold as a target audio component among multiple audio components, specifically: compare the relationship between the azimuth angle of each audio component in the multiple audio components and the preset angle threshold in turn; add the audio component whose azimuth angle does not exceed the preset angle threshold to the target audio component set; and exclude the audio component whose azimuth angle exceeds the preset angle threshold from the target audio component set.

[0122] In this embodiment, the third position of the driver and the fourth position of each audio component in the vehicle are first determined to establish a reference system centered on the driver. Then, the second azimuth angle parameter of each audio component relative to the vehicle is calculated based on the third position and the fourth position of each audio component, ensuring that the second azimuth angle parameter and the first azimuth angle parameter of the traffic participant use the same reference system. Then, by calculating the angle between the second azimuth angle parameter and the first azimuth angle parameter of each audio component, the azimuth deviation between each audio component and the traffic participant is quantified. Finally, by comparing the azimuth angle with a preset angle threshold, the audio component with an azimuth angle less than or equal to the preset angle threshold is selected as the target audio component. In this way, by establishing a driver-centered azimuth angle calculation system, the consistency between the sound source positioning and the driver's actual perception is ensured. The first azimuth angle parameter and the second azimuth angle parameter are calculated using the same reference system to eliminate coordinate system conversion errors. By calculating the angle and comparing the threshold, the audio component and the traffic participant's position are accurately matched. Finally, the selection of the target audio component is consistent with the acoustic positioning principle and adapted to the vehicle's internal spatial structure, thereby improving the driver's perception of the traffic participant's position.

[0123] For easier understanding Figure 6 For solutions of related embodiments, please see Figure 5 and Figure 7 , Figure 5 is an example schematic diagram of a reference position provided in an embodiment of the present application. Figure 7 This is an example schematic diagram of a multi-audio component provided in an embodiment of the present application.

[0124] like Figure 5As shown, the center of the vehicle's cabin is used as the first position. A pedestrian is detected as a traffic participant, and the center of the pedestrian's torso is obtained as the second position. Based on the first and second positions, the target distance parameter d = 5 meters from the traffic participant to the vehicle is calculated, and the first azimuth parameter α = 135° (0° is directly in front of the vehicle, and increases clockwise).

[0125] like Figure 7 As shown, after determining the driver's third position, the second azimuth parameters of the four audio components are obtained: the second azimuth parameter of audio component 1 is β1 = 310°, the second azimuth parameter of audio component 2 is β2 = 66°, the second azimuth parameter of audio component 3 is β3 = 138°, and the second azimuth parameter of audio component 4 is β4 = 208°. The azimuth angle of each audio component is calculated separately: for audio component 1, |α - β1| is calculated to be 175° > 180°, and 360° - 175° = 185°; for audio component 2, |α - β2| is calculated to be 69°; for audio component 3, |α - β3| is calculated to be 3°; and for audio component 4, |α - β4| is calculated to be 73°. Assuming the preset angle threshold is θ = 90°, after comparison, the azimuth angle of audio component 3 is 3° ≤ θ, the azimuth angles of audio components 2 and 4 are both greater than θ, and the azimuth angle of audio component 1 is 185° > θ. Therefore, the target audio component is determined to be audio component 3. Finally, based on the target distance parameter d = 5 meters and the first mapping relationship f(d), the volume parameter of audio component 3 is determined to be V = f(5).

[0126] In one embodiment, Figure 6 Step S305 of the embodiment may be further refined to include the following steps:

[0127] A target audio component is determined from the plurality of audio components according to the first azimuth parameter and a second mapping relationship between the azimuth parameter and the audio component.

[0128] Specifically, the second mapping relationship refers to a pre-established correspondence table or functional relationship between the azimuth parameters and the audio components, which is used to match the corresponding audio components according to the azimuth parameters. The second mapping relationship can be established through calibration or theoretical calculation, specifically by dividing the interior space of the vehicle into several areas according to the azimuth angle, and each area is associated with one or more audio components; or establishing a direct index relationship between the azimuth parameters and the audio component numbers. In a specific implementation, the second mapping relationship can be stored in the form of a lookup table, in which each azimuth angle interval corresponds to a specific audio component combination; or it can be implemented in the form of a mathematical function, and the target audio component is determined by calculating the function value of the azimuth angle parameter.

[0129] Regarding the process of determining the target audio component among multiple audio components based on the first azimuth parameter and the second mapping relationship between the azimuth parameter and the audio component, the following steps are specifically included: first, the first azimuth parameter is normalized and converted to a preset standard angle range; then the second mapping relationship is queried to obtain the audio component identification information that matches the normalized first azimuth parameter; finally, the target audio component is determined from the multiple audio components based on the audio component identification information. In a specific implementation, when the second mapping relationship is in the form of a lookup table, the azimuth interval where the first azimuth parameter is located can be quickly located through a binary search algorithm, and the audio component number corresponding to the interval can be returned; when the second mapping relationship is in the form of a function, the first azimuth parameter can be input into a preset matching function, and the number or selection weight of the target audio component can be determined by calculating the function output value.

[0130] In this embodiment, by pre-establishing a second mapping relationship between the azimuth parameter and the audio component, after obtaining the first azimuth parameter of the traffic participant, the target audio component can be quickly determined by directly querying the second mapping relationship based on the first azimuth parameter. Compared with the solution of calculating the azimuth angle of the audio component in real time, this embodiment significantly reduces the computational complexity by pre-storing the mapping relationship. At the same time, the second mapping relationship established based on the measured data can accurately reflect the characteristics of the acoustic environment inside the vehicle, ensuring that the selection of the target audio component is in line with the theoretical acoustic positioning principle, and ultimately achieving an accurate match between the traffic participant's position and the prompt sound playback position, so that the driver can intuitively judge the actual position of the traffic participant by the direction of the sound source, thereby improving driving safety.

[0131] Based on the above Figure 2 - Figure 7 In one embodiment, the vehicle control method further comprises the following steps:

[0132] determining a prompt sound corresponding to the traffic participant according to the target object type of the traffic participant and a third mapping relationship between the object type and the prompt sound;

[0133] The target object type is obtained by calling a preset recognition algorithm to identify the sensing data of the target sensor, and the detection direction of the target sensor corresponds to the movement direction.

[0134] Specifically, the target object type refers to the classification of traffic participants according to preset classification standards, including but not limited to pedestrians, electric bicycles, motorcycles, other vehicles, etc. In a specific implementation, the target object type can be represented as an enumeration value, with each type corresponding to a unique type identifier.

[0135] The third mapping relationship refers to a pre-established set of correspondences between object types and prompt sounds, used to match prompt sound samples to the type of traffic participant. This third mapping relationship can be expressed as a library of standard prompt sound samples for various types of traffic participants, or as an index relationship between type identifiers and audio file paths. In a specific implementation, the third mapping relationship can be configured as an editable database to support subsequent updating and maintenance of prompt sound samples.

[0136] The process of determining the corresponding prompt sound for a traffic participant based on the traffic participant's target object type and the third mapping relationship between the object type and the prompt sound specifically includes the following steps: first, obtaining the traffic participant's target object type identifier; then, querying the third mapping relationship to obtain the prompt sound data associated with the target object type identifier; and finally, loading the obtained prompt sound data into a playable audio signal format. For example, when the third mapping relationship is in the form of a database, the prompt sound data associated with the target object type identifier can be retrieved by searching for a match using an SQL query statement; when the third mapping relationship is in the form of a file index, the path to the prompt sound data associated with the target object type identifier can be directly located using a type identifier, and the prompt sound data associated with the target object type identifier can be obtained based on the path.

[0137] It should be noted that the target object type involved in this embodiment is obtained by calling a preset recognition algorithm to identify the sensor data of the target sensor, and the detection direction of the target sensor corresponds to the movement direction. Specifically, the target sensor refers to a sensor installed on the vehicle and whose detection direction matches the movement direction corresponding to the vehicle's current driving gear. The target sensor can sense the environment in which the vehicle is located; the detection direction of the target sensor corresponds to the movement direction, which means that the angle between the main detection axis of the target sensor and the vehicle's movement direction is less than a preset angle threshold (for example, 15 degrees), ensuring that the effective detection range of the target sensor covers the main area of the vehicle's movement direction; the sensor data of the target sensor refers to the original environmental perception data collected by the target sensor during the detection process, and its data format is directly related to the type of target sensor; the preset recognition algorithm refers to the algorithm stored in the vehicle control system for identifying the type of traffic participants from the sensor data.

[0138] For example, if the target sensor is a target camera, the sensor data of the target sensor is a captured image. The image captured by the target camera is identified by calling a preset recognition algorithm. This can be performed as follows: first, the captured image is preprocessed, including denoising, color correction, and image enhancement; the preprocessed image is input into a trained convolutional neural network model, which includes multiple convolutional layers, pooling layers, and fully connected layers; the convolutional neural network model extracts and classifies the multi-level features of the image, outputting a probability distribution of traffic participant types; the target object type is determined from the type probability distribution based on a preset probability threshold; when the probability of a certain type exceeds the threshold, the type is determined as the target object type; and traffic participants that cannot be clearly classified are classified as a preset unknown type.

[0139] For example, if the target sensor is a target lidar, then the sensor data of the target sensor is point cloud data. The target lidar's point cloud data is identified by calling a preset recognition algorithm. This can be performed as follows: first, the original point cloud data is filtered to remove noise points and invalid data; a clustering algorithm based on Euclidean distance is used to segment the point cloud data into multiple point cloud clusters; the geometric feature parameters of each point cloud cluster are extracted, including point cloud density, height distribution, reflection intensity distribution, and three-dimensional shape features; the geometric feature parameters are input into a pre-trained support vector machine classifier, which contains discriminant models for traffic participant types such as pedestrians, two-wheeled vehicles, and four-wheeled vehicles; the support vector machine classifier calculates the probability score of each point cloud cluster belonging to each category, and the category corresponding to the highest score is determined as the target object type; for point cloud clusters with scores below the confidence threshold, they are marked as objects to be confirmed and continuously tracked.

[0140] It's understood that the sensor data from the target sensor (such as captured images or point cloud data) directly reflects the physical attributes and motion state of traffic participants in their detection direction, providing the raw data foundation for object type recognition. By combining this with a pre-defined recognition algorithm to identify the sensor data, the target object type of a traffic participant can be accurately determined.

[0141] In this embodiment, by pre-establishing a third mapping relationship between object type and prompt tone, after identifying the target object type of a traffic participant, the corresponding prompt tone can be directly matched based on that type. Compared to solutions that use a single prompt tone, this embodiment uses a categorized prompt tone design, allowing drivers to quickly distinguish different types of traffic participants based on their sound characteristics. Ultimately, accurate matching of traffic participant types with prompt tone characteristics is achieved, allowing drivers to not only perceive the location and distance of traffic participants but also determine their type characteristics. This provides more comprehensive environmental information support for driving decisions and further improves driving safety.

[0142] Based on the above Figure 1 The following is a scene diagram of Figure 8 The vehicle control device provided in the embodiment of the present application is introduced in detail. It should be noted that, Figure 8 The vehicle control device is used to execute the present application Figure 2 - Figure 7 For the convenience of explanation, only the part related to the embodiment of the present application is shown. For the specific technical details not disclosed, please refer to the present application. Figure 2 - Figure 7 Specifically, the vehicle control device 800 may include a first determination unit 801, an identification unit 802, an acquisition unit 803, a second determination unit 804, and a playback unit 805, as follows:

[0143] The first determining unit 801 is configured to determine the movement direction corresponding to the driving gear when the vehicle is in the driving gear;

[0144] an identification unit 802 for identifying traffic participants other than the vehicle from the vehicle's environment based on the direction of movement;

[0145] An acquisition unit 803 is used to acquire relative position information between the vehicle and traffic participants;

[0146] A second determining unit 804 is configured to determine a volume parameter of a target audio component inside the vehicle according to the relative position information;

[0147] The playing unit 805 is used to control the target audio component to play the prompt sound corresponding to the traffic participant according to the volume parameter.

[0148] Optionally, the relative position information includes a target distance parameter of the traffic participant relative to the vehicle; in some embodiments, the acquisition unit 803 can be used to: obtain a first position of the vehicle; obtain a second position of the traffic participant; and determine the target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position.

[0149] Optionally, in some embodiments, the second determination unit 804 can be used to determine the volume parameter of the target audio component inside the vehicle based on the target distance parameter, the volume parameter corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, and the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

[0150] Optionally, in some embodiments, the relative position information also includes a first azimuth parameter of the traffic participant relative to the vehicle; the acquisition unit 803 can be used to determine the first azimuth parameter of the traffic participant relative to the vehicle based on the first position and the second position.

[0151] Optionally, in some embodiments, multiple audio components are provided inside the vehicle; the second determination unit 804 can be used to: determine a target audio component among the multiple audio components based on the first azimuth parameter; determine the volume parameter of the target audio component inside the vehicle based on the target distance parameter, the volume parameter corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

[0152] Optionally, in some embodiments, the second determination unit 804 can be used to: determine a third position of the driver in the vehicle, and a fourth position of each audio component among multiple audio components; determine a second azimuth parameter of each audio component relative to the vehicle based on the third position and the fourth position of each audio component, the second azimuth parameter and the first azimuth parameter sharing the same reference system; calculate the angle between the second azimuth parameter and the first azimuth parameter of each audio component respectively to obtain the azimuth angle of each audio component; and among multiple audio components, determine an audio component whose azimuth angle is less than or equal to a preset angle threshold as a target audio component.

[0153] Optionally, in some embodiments, the second determining unit 804 may be configured to determine a target audio component from a plurality of audio components according to the first azimuth parameter and a second mapping relationship between the azimuth parameter and the audio component.

[0154] Optionally, in some embodiments, the vehicle control device 800 may be configured to determine a prompt sound corresponding to the traffic participant based on the target object type of the traffic participant and a third mapping relationship between the object type and the prompt sound.

[0155] The effects that can be achieved by this embodiment can be found in the relevant embodiments of the above-mentioned vehicle control method, which will not be repeated here.

[0156] See Figure 9 , provides a structural diagram of a vehicle according to an embodiment of the present application. Figure 9 As shown, the vehicle 900 includes a processor 901 and a memory 902. The processor 901 is electrically connected to the memory 902.

[0157] Processor 901 is the control center of vehicle 900 and may include one or more processing cores. Processor 901 utilizes various interfaces and circuits to connect various components of vehicle 900. By running or invoking computer programs stored in memory 902 and accessing data stored in memory 902, it executes various functions of vehicle 900 and processes data, thereby providing overall control over vehicle 900. Optionally, processor 901 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field programmable gate array (FPGA), or a programmable logic array (PLA). Processor 901 may integrate one or a combination of a CPU, a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interfaces, and applications; the GPU is responsible for rendering and drawing display content; and the modem handles wireless communications. It is understood that the modem may not be integrated into processor 901 and may instead be implemented via a separate communications chip.

[0158] Memory 902 can be used to store software programs and modules. Processor 901 executes various functional applications and data processing by running the computer programs and modules stored in memory 902. Memory 902 may primarily include a program storage area and a data storage area. The program storage area may store an operating system, computer programs required for at least one function, and the like; the data storage area may store data generated based on the use of vehicle 900.

[0159] In addition, the memory 902 may include a high-speed random access memory and a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory 902 may also include a memory controller to provide the processor 901 with access to the memory 902.

[0160] In this embodiment, the processor 901 in the vehicle 900 loads instructions corresponding to one or more computer program processes into the memory 902 according to the following steps, and the processor 901 runs the computer program stored in the memory 902 to implement various functions as follows:

[0161] When the vehicle is in a driving gear, determining the movement direction corresponding to the driving gear;

[0162] Identify traffic participants other than the vehicle from the vehicle's environment based on its direction of movement;

[0163] Obtaining the relative position information between the vehicle and traffic participants;

[0164] determining a volume parameter of a target audio component inside the vehicle based on the relative position information;

[0165] The target audio component is controlled according to the volume parameter to play the corresponding prompt sound of the traffic participants.

[0166] Optionally, the relative position information includes a target distance parameter of the traffic participant relative to the vehicle; when the processor 901 executes the acquisition of the relative position information between the vehicle and the traffic participant, it specifically performs: acquiring the first position of the vehicle; acquiring the second position of the traffic participant; and determining the target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position.

[0167] Optionally, when the processor 901 determines the volume parameters of the target audio component inside the vehicle based on the relative position information, it specifically performs: determining the volume parameters of the target audio component inside the vehicle based on the target distance parameter, the volume parameters corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, and the target distance parameter is positively correlated with the volume parameters corresponding to the target audio component.

[0168] Optionally, the relative position information also includes a first azimuth parameter of the traffic participant relative to the vehicle; after the processor 901 determines the target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position, it also executes: determining the first azimuth parameter of the traffic participant relative to the vehicle based on the first position and the second position.

[0169] Optionally, multiple audio components are provided inside the vehicle; when the processor 901 determines the volume parameter of the target audio component inside the vehicle based on the relative position information, it specifically performs: determining the target audio component among the multiple audio components based on the first azimuth parameter; determining the volume parameter of the target audio component inside the vehicle based on the target distance parameter, the volume parameter corresponding to the target audio component, and the first mapping relationship between the distance parameter and the volume parameter, the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

[0170] Optionally, when the processor 901 determines the target audio component among multiple audio components based on the first azimuth parameter, it specifically performs the following: determining the third position of the driver in the vehicle and the fourth position of each audio component among the multiple audio components; determining the second azimuth parameter of each audio component relative to the vehicle based on the third position and the fourth position of each audio component, the second azimuth parameter and the first azimuth parameter sharing the same reference system; calculating the angle between the second azimuth parameter and the first azimuth parameter of each audio component respectively to obtain the azimuth angle of each audio component; and determining, among the multiple audio components, the audio component whose azimuth angle is less than or equal to a preset angle threshold as the target audio component.

[0171] Optionally, when the processor 901 determines the target audio component among multiple audio components based on the first azimuth parameter, it specifically performs: determining the target audio component among multiple audio components based on the first azimuth parameter and the second mapping relationship between the azimuth parameter and the audio component.

[0172] Optionally, the processor 901 may further execute: determining the prompt sound corresponding to the traffic participant according to the target object type of the traffic participant and a third mapping relationship between the object type and the prompt sound.

[0173] The effects that can be achieved by this embodiment can be found in the relevant embodiments of the above-mentioned vehicle control method, which will not be repeated here.

[0174] It should be understood that the device provided in the embodiment of the present application is used to execute the above-mentioned vehicle control method, and therefore can achieve the same effect as the above-mentioned implementation method.

[0175] In the case of an integrated unit, the device may include a processing module and a storage module. When the device is used in a vehicle, the processing module may be used to control and manage the vehicle's movements, while the storage module may be used to support the vehicle's execution of relevant program codes.

[0176] The processing module may be a processor or controller that implements or executes the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processing system (DSP) and a microprocessor, and the storage module may be a memory.

[0177] In addition, the device provided in the embodiment of the present application can specifically be a chip, component or module, and the chip may include a connected processor and memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a vehicle control method provided in the above embodiment.

[0178] An embodiment of the present application also provides a computer-readable storage medium, which stores computer program code. When the computer program code runs on a computer, the computer executes the above-mentioned related method steps to implement a vehicle control method provided by the above-mentioned embodiment.

[0179] This embodiment also provides a computer program product. When the computer program product is run on a computer, it enables the computer to execute the above-mentioned related steps to implement a vehicle control method provided by the above embodiment.

[0180] Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0181] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0182] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0183] The above content is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A vehicle control method, characterized in that: The method comprises: When the vehicle is in a driving gear, determining a movement direction corresponding to the driving gear; Based on the movement direction, identifying traffic participants other than the vehicle from the environment of the vehicle; Obtaining relative position information between the vehicle and the traffic participant; determining a volume parameter of a target audio component inside the vehicle according to the relative position information; The target audio component is controlled according to the volume parameter to play the prompt sound corresponding to the traffic participant.

2. The method according to claim 1, characterized in that The relative position information includes a target distance parameter of the traffic participant relative to the vehicle; and obtaining the relative position information between the vehicle and the traffic participant includes: obtaining a first position of the vehicle; Acquiring a second position of the traffic participant; A target distance parameter of the road participant relative to the vehicle is determined based on the first position and the second position.

3. The method according to claim 2, characterized in that Determining the volume parameter of the target audio component inside the vehicle according to the relative position information includes: The volume parameter of the target audio component inside the vehicle is determined based on the target distance parameter, the volume parameter corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, wherein the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

4. The method according to claim 2, characterized in that The relative position information also includes a first azimuth parameter of the traffic participant relative to the vehicle; after determining a target distance parameter of the traffic participant relative to the vehicle based on the first position and the second position, the method further includes: A first azimuth parameter of the road participant relative to the vehicle is determined based on the first position and the second position.

5. The method according to claim 4, characterized in that The vehicle interior is provided with a plurality of audio components; and determining the volume parameter of the target audio component in the vehicle interior according to the relative position information includes: determining a target audio component among the plurality of audio components according to the first azimuth parameter; The volume parameter of the target audio component inside the vehicle is determined based on the target distance parameter, the volume parameter corresponding to the target audio component, and a first mapping relationship between the distance parameter and the volume parameter, wherein the target distance parameter is positively correlated with the volume parameter corresponding to the target audio component.

6. The method according to claim 5, characterized in that The step of determining a target audio component from among the plurality of audio components according to the first azimuth parameter comprises: determining a third location of a driver in the vehicle and a fourth location of each of the plurality of audio components; determining a second azimuth parameter of each audio component relative to the vehicle based on the third position and the fourth position of each audio component, wherein the second azimuth parameter and the first azimuth parameter share a same reference system; Calculating the angle between the second azimuth angle parameter and the first azimuth angle parameter of each audio component to obtain the azimuth angle of each audio component; Among the multiple audio components, an audio component whose azimuth angle is less than or equal to a preset angle threshold is determined as a target audio component.

7. The method according to claim 5, characterized in that The step of determining a target audio component from among the plurality of audio components according to the first azimuth parameter comprises: A target audio component is determined from the plurality of audio components according to the first azimuth parameter and a second mapping relationship between the azimuth parameter and the audio component.

8. The method according to claim 1, characterized in that The method further comprises: Determining a prompt sound corresponding to the traffic participant according to the target object type of the traffic participant and a third mapping relationship between the object type and the prompt sound; The target object type is obtained by calling a preset recognition algorithm to identify the sensing data of the target sensor, and the detection direction of the target sensor corresponds to the movement direction.

9. A vehicle, characterized in that: include: a memory for storing executable program code; A processor is configured to call and run the executable program code from the memory, so that the vehicle executes the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program code, and when the computer program code is executed, the method according to any one of claims 1 to 8 is implemented.

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