Vehicle whistling control method and vehicle

Abstract

The invention discloses a whistling control method of a vehicle and the vehicle. The method can comprise the steps that in the vehicle driving process, environment information corresponding to a vehicle and position information of the vehicle are obtained, the environment information is information related to vehicle driving in the environment where the vehicle is located, and the position information is used for representing the position where the vehicle is located in the environment in the vehicle driving process; based on the environment information and the position information, determining a risk coefficient of the vehicle, the risk coefficient being used for representing a risk degree of a risk of the vehicle at the position; a whistling strategy of the vehicle is determined at least based on the risk coefficient, the whistling strategy is used for representing a rule for controlling the vehicle to trigger whistling so as to reduce the risk degree, and the reduced risk degree is smaller than or equal to a risk degree threshold value; and according to the whistling strategy, the vehicle is controlled to execute whistling operation. The technical problem that the whistling control accuracy of the vehicle is low is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle horn control, in particular to a vehicle horn control method and vehicle. BACKGROUND

[0002] At present, the horn control of a vehicle depends on the subjective judgment and manual operation of a driver. However, in an emergency or complex driving situation, the driver may need some time to judge whether the horn is needed and determine the timing of the horn, and the subjective understanding of the driver to the road conditions may not effectively warn other road users. Therefore, there is still a technical problem of low accuracy of the horn control of the vehicle.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] The embodiments of the present application provide a vehicle horn control method and vehicle to at least solve the technical problem of low accuracy of the horn control of the vehicle.

[0005] According to an aspect of the embodiments of the present application, a vehicle horn control method is provided, which can include: obtaining environmental information corresponding to a vehicle and position information of the vehicle during driving of the vehicle, wherein the environmental information is information related to driving of the vehicle in an environment in which the vehicle is located, and the position information is used to indicate a position of the vehicle in the environment during driving of the vehicle; determining a risk coefficient of the vehicle based on the environmental information and the position information, wherein the risk coefficient is used to indicate a risk degree of a risk of the vehicle at the position; determining a horn strategy of the vehicle based at least on the risk coefficient, wherein the horn strategy is used to indicate a rule of controlling the vehicle to trigger the horn to reduce the risk degree, and the reduced risk degree is less than or equal to a risk degree threshold; and controlling the vehicle to perform a horn operation according to the horn strategy.

[0006] Optionally, the vehicle includes a horn system, and the determination of the risk coefficient of the vehicle based on the environmental information and the position information includes: determining the risk coefficient based on the environmental information and the position information by using the horn system.

[0007] Optionally, the horn system includes a domain controller, a perception system and a location service module, the domain controller, the perception system and the location service module are connected to each other through an Ethernet, and the determination of the risk coefficient based on the environmental information and the position information by using the horn system includes: in response to the domain controller receiving the environmental information from the perception system and the position information from the location service module, fusing the environmental information and the position information by using the domain controller to obtain a fusion result; and determining the risk coefficient based on the fusion result by using the domain controller.

[0008] Optionally, the horn strategy of the vehicle is determined based on at least the risk coefficient, including: determining the horn strategy based on the horn rule of the environment and the risk coefficient, wherein the horn rule is used to indicate whether the environment allows the vehicle to perform the horn operation.

[0009] Optionally, the horn strategy includes volume information, and the horn strategy is determined based on the horn rule of the environment and the risk coefficient, including at least one of: in response to the horn rule being allowed to trigger the horn operation, the environment belonging to a first environment type, and the risk degree being greater than a risk degree threshold, determining volume information less than a volume information threshold, wherein the first environment type is used to indicate that the volume information greater than or equal to the volume information threshold is not allowed; in response to the horn rule being allowed to trigger the horn operation, the environment belonging to a second environment type, and the risk degree being greater than the risk degree threshold, determining volume information greater than or equal to the volume information threshold, wherein the second environment type is used to indicate that the volume information greater than or equal to the volume information threshold is allowed.

[0010] Optionally, the horn strategy includes loudness information, and the horn strategy is determined based on the horn rule of the environment and the risk coefficient, including at least one of: in response to the horn rule being allowed to trigger the horn operation, the risk degree being greater than a risk degree threshold, and the distance between the vehicle and at least one target object in the driving direction being less than a distance threshold, determining loudness information less than a loudness information threshold; in response to the horn rule being allowed to trigger the horn operation, the risk degree being greater than the risk degree threshold, and the distance being greater than or equal to the distance threshold, determining loudness information greater than or equal to the loudness information threshold.

[0011] Optionally, the horn strategy includes frequency information, and the horn strategy is determined based on the horn rule of the environment and the risk coefficient, including: in response to the horn rule being allowed to trigger the horn operation, the risk degree being greater than a risk degree threshold, determining frequency information, wherein the frequency information is used to indicate the frequency of triggering the horn operation, which is positively correlated with the time length of triggering the horn operation.

[0012] Optionally, during driving of the vehicle, the environment information corresponding to the vehicle is obtained, including: in the environment, detecting target objects in the driving direction of the vehicle through a perception system to obtain the environment information; during driving of the vehicle, the position information of the vehicle is obtained, including: in the environment, obtaining the position information based on map data and a positioning system through a position service module.

[0013] Optionally, the vehicle includes a horn system, and the horn system includes an acoustic broadcasting unit, and the vehicle performs the horn operation according to the horn strategy, including: controlling the vehicle to perform the horn operation according to the horn strategy by using the acoustic broadcasting unit; the method further includes: adjusting the horn strategy by using feedback sound waves corresponding to the horn operation to obtain an adjusted horn strategy.

[0014] According to another aspect of the embodiments of the present application, a horn control device of a vehicle is provided. The device can include: an obtaining unit configured to obtain environment information corresponding to the vehicle and position information of the vehicle during driving of the vehicle, the environment information being information related to driving of the vehicle in an environment in which the vehicle is located, and the position information being indicative of a position of the vehicle in the environment during driving of the vehicle; a first determining unit configured to determine a risk coefficient of the vehicle based on the environment information and the position information, the risk coefficient being indicative of a risk degree of the vehicle in the position; a second determining unit configured to determine a horn strategy of the vehicle based on at least the risk coefficient, the horn strategy being indicative of a rule of controlling the vehicle to trigger a horn to reduce the risk degree, the reduced risk degree being less than or equal to a risk degree threshold; and a control unit configured to control the vehicle to perform a horn operation according to the horn strategy.

[0015] According to another aspect of the embodiments of the present application, a computer readable storage medium is provided. The computer readable storage medium includes a stored program, wherein the program, when executed by a device in which the computer readable storage medium is located, causes the device to perform the above method according to the embodiments of the present application.

[0016] According to another aspect of the embodiments of the present application, a processor is provided. The processor is configured to execute a program, wherein the program, when executed, causes the processor to perform the above method according to the embodiments of the present application.

[0017] According to another aspect of the embodiments of the present application, an electronic device is provided. The electronic device includes a memory and a processor, the memory storing a computer program, and the processor being configured to execute the computer program to perform the above method according to the embodiments of the present application.

[0018] According to another aspect of the embodiments of the present application, a computer program product is provided. The computer program product includes a computer program, the computer program, when executed by a processor, implementing the above method according to the embodiments of the present application.

[0019] According to another aspect of the embodiments of the present application, a vehicle is provided. The vehicle includes a memory and a processor, the memory storing a computer program, and the processor being configured to execute the computer program to perform the above method according to the embodiments of the present application.

[0020] In this embodiment of the invention, during vehicle operation, environmental information and location information of the vehicle are acquired. The environmental information refers to information related to vehicle operation within the environment in which the vehicle is located, and the location information indicates the vehicle's position within the environment during operation. Based on the environmental and location information, a risk coefficient for the vehicle is determined, representing the degree of risk present at the vehicle's current location. At least based on the risk coefficient, a horn-honking strategy is determined, whereby the horn-honking strategy represents a rule for controlling the vehicle to trigger a horn to reduce the risk level, where the reduced risk level is less than or equal to a risk level threshold. The vehicle is then controlled to perform a horn-honking operation according to the horn-honking strategy. In other words, in this embodiment of the invention, considering that different driving scenarios have different levels of risk, different horn-honking strategies are required for different levels of risk. The risk level of the driving scenario corresponding to the actual environment in which the vehicle is located can be accurately measured based on the environmental and location information. Based on the risk coefficients corresponding to the aforementioned risk levels, corresponding horn-honking strategies are formulated and implemented. By intelligently adjusting the horn-honking strategy based on environmental and location information, driving safety is ensured while reducing unnecessary horn noise interference. This achieves the technical effect of improving the accuracy of vehicle horn-honking control and solves the technical problem of low accuracy in vehicle horn-honking control. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0022] Figure 1 This is a flowchart of a vehicle horn control method according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of a vehicle horn system according to an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of a vehicle horn control device according to an embodiment of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] According to an embodiment of the present invention, an embodiment of a vehicle horn control method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0028] Figure 1 This is a flowchart of a vehicle horn control method according to an embodiment of the present invention, such as... Figure 1 As shown, the method may include the following steps:

[0029] Step S102: During the vehicle's operation, acquire the vehicle's environmental information and its location information.

[0030] In the technical solution provided by step S102 of the present invention, the environmental information can be used to represent information related to vehicle driving in the environment in which the vehicle is located. The environmental information can be information acquired by sensors in the vehicle that can influence the vehicle's horn-honking strategy. For example, the environmental information can be the activity status of pedestrians and other vehicles in the vehicle's environment, as well as obstacles and road signs in the vehicle's environment. Optionally, the location information can be used to represent the vehicle's position in the environment during driving. For example, the location information can include the coordinates corresponding to the vehicle's real-time position in the environment, or it can include the area attribute corresponding to the environment in which the vehicle is located. The area attribute can be a rule set for the vehicle's horn-honking strategy based on the type of area in the environment. For example, if the type is a school zone, the horn-honking strategy for the vehicle driving in the school zone is that honking is prohibited in this area.

[0031] In this embodiment, during the vehicle's operation, environmental information about the environment in which the vehicle is located can be obtained, as well as the vehicle's location information in the environment during its operation.

[0032] Optionally, environmental information corresponding to the vehicle can be acquired during vehicle operation. For example, if the aforementioned sensor is a vision sensor in the vehicle, the environmental information collected by the vision sensor can be visual perception information.

[0033] For example, if the aforementioned vehicle-mounted sensor is a vehicle-mounted vision sensor, the front-view camera can acquire the image of the vehicle in front. Surround-view cameras can acquire side and rear images. From these front, side, and rear images, the activity status of pedestrians and other vehicles in the vehicle's environment, as well as obstacles and road signs, can be detected to obtain the vehicle's environmental information.

[0034] It should be noted that the aforementioned front-view camera and surround-view camera, as well as the front image acquired by the front-view camera and the side and rear images acquired by the surround-view camera, are merely examples. No specific limitations are made on the types of vehicle vision sensors or the information content acquired by different types of vehicle vision sensors.

[0035] Optionally, the vehicle's location information can be obtained through location-based services (LBS) corresponding to the vehicle.

[0036] For example, if the LBS mentioned above is a Global Navigation Satellite System (GNSS) and / or base station positioning technology, the real-time latitude and longitude coordinates of the vehicle during its journey can be obtained through this technology. If the LBS mentioned above is high-precision map data, the specific regional attributes of the vehicle's environment (e.g., school zone, hospital zone, residential zone, commercial street, industrial zone, etc.) can be identified through the map data and the vehicle's real-time latitude and longitude coordinates.

[0037] It should be noted that this is only an example and no specific restrictions are placed on the methods for obtaining vehicle location information or the specific content of the location information.

[0038] Through step S102 of the present invention, the vehicle's surrounding environment can be continuously acquired and analyzed using onboard visual sensors (e.g., forward-facing cameras, surround-view cameras, and millimeter-wave radar). This allows for the identification of the movement of pedestrians, vehicles, and obstacles, as well as the detection of road signs and traffic light status in the vehicle's environment. Based on LBS, the vehicle's real-time latitude and longitude coordinates can be determined through global navigation satellite systems and / or base station positioning. Simultaneously, high-precision map data can be used to determine the specific area attributes of the vehicle's location (e.g., school district, hospital district, residential area, etc.).

[0039] Step S104: Determine the risk coefficient of the vehicle based on environmental and location information.

[0040] In the technical solution provided by step S104 of the present invention, the risk coefficient can be used to represent the degree of risk of the vehicle in its location, such as the proximity of pedestrians and vehicles, the degree of influence of obstacles and road signs in the vehicle's environment on the vehicle's current driving process, and the degree of influence of the regional attributes of the area where the vehicle is located on the vehicle's response strategy when encountering an emergency during the current driving process.

[0041] In this embodiment, during the vehicle's operation, after acquiring the vehicle's environmental information and location information, the vehicle's risk coefficient can be determined based on the environmental and location information.

[0042] Optionally, after obtaining environmental and location information, this information can be analyzed to extract at least one risk factor that can affect the level of risk affecting vehicle operation. For example, the obtained pedestrian location information, obstacle location information, road rules, and area attributes can be converted into pedestrian approach risk, obstacle impact risk, road rule matching risk, and area sensitivity risk. The risk level of at least one of these risk factors can then be assessed to obtain the vehicle's risk coefficient.

[0043] Optionally, based on the obtained environmental and location information, at least one risk factor that can affect the risk level of vehicle driving can be obtained, including but not limited to the proximity of pedestrians and vehicles, the type and location of obstacles, the indication of road signs, and the regional attributes of the vehicle, whether it is a no-honking zone, and real-time latitude and longitude coordinates.

[0044] Optionally, at least one risk factor that can affect the degree of risk of vehicle driving is integrated to determine the risk factor with the highest impact on vehicle driving among the aforementioned risk factors, and then the degree of risk of the vehicle being in its location is determined based on the aforementioned risk factors.

[0045] Through step S104 of the present invention, pedestrian and vehicle proximity data collected from the vehicle's visual sensors can be integrated with vehicle location information and area attribute data provided by LBS. By analyzing the risks represented by the above data, each potential risk (i.e., risk factor) in the vehicle's environment can be identified, such as pedestrian approach, road sign restrictions, and special area rules, thereby determining the risk level of the vehicle's current driving process.

[0046] Step S106: Determine the vehicle's horn-honking strategy based at least on the risk level, wherein the horn-honking strategy is used to represent the rules for controlling the vehicle to trigger horn-honking to reduce the risk level, and the reduced risk level is less than or equal to the risk level threshold.

[0047] In the technical solution provided in step S106 of the present invention, the aforementioned horn-honking strategy can be represented by rules that control the vehicle to trigger horn-honking to reduce the level of risk, such as dynamic volume adjustment, directional sound propagation, and adjustment of frequency and loudness. The aforementioned risk level threshold can be used to represent a preset series of limit values ​​to distinguish driving environments with different risk levels.

[0048] In this embodiment, after determining the risk level of the vehicle based on environmental and location information, the vehicle's horn-honking strategy can be determined based on the risk level.

[0049] Optionally, the real-time determined risk level can be compared with a preset risk level threshold to determine the risk level of the current driving environment. Based on the comparison result between the risk level and the threshold, the most suitable horn-honking strategy can be selected from a preset strategy library.

[0050] Optionally, the aforementioned risk level thresholds are set based on a combination of factors, including various road conditions, time factors, geographical location characteristics (e.g., school zones, hospital zones, residential areas), and vehicle speed. For example, a low-risk threshold can be set for driving scenarios in open areas where no pedestrians or other vehicles are approaching within the vehicle's perception range. A medium-risk threshold can be set for driving scenarios on city streets where pedestrians and non-motorized vehicles appear frequently, or in normal traffic flow on highways. A high-risk threshold can be set for driving scenarios where a pedestrian suddenly crosses the road ahead, or other vehicles suddenly slow down or change lanes, posing a collision risk.

[0051] It should be noted that the above classification of risk level thresholds and the driving scenarios corresponding to different risk level thresholds are only examples, and no specific limitations are made on different driving scenarios and the risk level thresholds corresponding to different driving scenarios.

[0052] Optionally, based on the different levels of risk mentioned above, the vehicle's horn-honking strategy may include, but is not limited to: in environments with dense pedestrian traffic or many obstacles, if the risk level is high, the vehicle can increase the volume of its horn. When the vehicle is in areas such as school zones, hospital zones, or residential areas, even if the risk level is high, the vehicle can choose to use a low-frequency, gentle horn-honking method to reduce disturbance to local residents.

[0053] For example, a suitable strategy mode can be selected from preset horn-honking strategy rules based on the current risk level. For instance, a gentle alert mode can be selected for low risk, an alert mode for medium risk, and an emergency alarm mode for high risk. It should be noted that this is merely an example, and no specific restrictions are placed on the classification of different risk levels and their corresponding modes.

[0054] Through step S106 of this invention, the risk level can be determined based on real-time acquired environmental and location information. Then, based on this risk level and a pre-set risk level threshold, the vehicle's horn-honking strategy can be flexibly adjusted. For example, based on the attributes (environmental information) of the area where the vehicle is located, such as school zones, hospital zones, and residential areas, the horn-honking strategy can be adjusted by setting area-specific optimization rules. In these sensitive areas, even if the risk level is high, a low-frequency, gentle horn-honking method is chosen to ensure driving safety while also considering the environment and order.

[0055] Step S108: In accordance with the horn-honking strategy, control the vehicle to perform the horn-honking operation.

[0056] In the technical solution provided by step S108 of the present invention, the above-mentioned horn operation can be used to indicate that the vehicle's loudspeaker is controlled to sound the horn according to a preset horn strategy in order to warn of potential dangers in the surrounding environment.

[0057] In this embodiment, after determining the vehicle's horn-honking strategy based on the level of risk, the vehicle can be controlled to perform the horn-honking operation according to the horn-honking strategy.

[0058] Optionally, the volume, frequency, and loudness of the speakers can be adjusted according to the horn-honking strategy to ensure that the horn sound effectively conveys warning information without causing excessive noise. For example, the direction of sound wave emission from the speaker array can be controlled to precisely direct the horn sound towards potential risk sources, improving warning efficiency. The horn-honking strategy determines whether to use short warning horns, continuous emergency horns, or a special horn-honking mode tailored to the current environment, such as using a soft warning sound in a specific area. Simultaneously with horn-honking, it can work in conjunction with other vehicle safety warning systems, such as flashing lights and intelligent driving assistance systems, to provide more comprehensive warnings.

[0059] In steps S102 to S108 of this invention, during vehicle operation, environmental information and location information of the vehicle are acquired. The environmental information refers to information related to vehicle operation within the vehicle's environment, and the location information indicates the vehicle's position within the environment during operation. Based on the environmental and location information, a risk coefficient for the vehicle is determined, representing the degree of risk present at the vehicle's current location. At least based on the risk coefficient, a horn-honking strategy is determined, representing a rule for controlling the vehicle to trigger a horn to reduce the risk level, where the reduced risk level is less than or equal to a risk level threshold. The vehicle is then controlled to perform a horn-honking operation according to the horn-honking strategy. In other words, in this embodiment of the invention, considering that different driving scenarios have different levels of risk, different horn-honking strategies are required for different levels of risk. The risk level of the driving scenario corresponding to the actual environment in which the vehicle is located can be accurately measured based on the environmental and location information. Based on the risk coefficients corresponding to the aforementioned risk levels, corresponding horn-honking strategies are formulated and implemented. By intelligently adjusting the horn-honking strategy based on environmental and location information, driving safety is ensured while reducing unnecessary horn noise interference. This achieves the technical effect of improving the accuracy of vehicle horn-honking control and solves the technical problem of low accuracy in vehicle horn-honking control.

[0060] The method described in this embodiment will be further described below.

[0061] As an alternative embodiment, the vehicle includes a horn system to determine the risk factor of the vehicle based on environmental information and location information, including: using the horn system to determine the risk factor based on environmental information and location information.

[0062] In this embodiment, the aforementioned horn system can be used to refer to an integrated system in a vehicle capable of horn control, including but not limited to: a visual perception system, LBS, etc.

[0063] Optionally, a forward-facing camera and millimeter-wave radar can be used to capture and analyze environmental information such as pedestrians, obstacles, and traffic signs around the vehicle in real time. Location-based services (LBS) provide accurate vehicle location and area attribute data.

[0064] Optionally, potential risks can be extracted from the collected environmental information, such as the distance of pedestrians from the roadway, the size and location of obstacles, and the safety level of traffic signs; at the same time, regional rule factors can be obtained from the location information, such as whether the above-mentioned area is a no-honking zone and noise restrictions for the current time period.

[0065] Optionally, all the risks obtained above can be comprehensively calculated using a multimodal fusion algorithm or other methods to obtain a quantitative value representing the degree of risk faced by the vehicle under the current driving environment, i.e., the risk coefficient.

[0066] For example, the environmental and location information collected above, such as pedestrian approach speed, obstacle size and location, traffic sign safety level, environmental noise level, and regional rule factors, are transformed into a series of risk factors. Each risk factor is assigned a different weight according to its potential threat level. A multimodal fusion algorithm is used for comprehensive analysis to consider the interaction and influence between the risk factors, and finally the risk coefficient is calculated.

[0067] In this embodiment of the invention, the above method can detect pedestrians, obstacles, and traffic signs in real time, as well as locate vehicle positions. It can also identify specific rules governing the area where the vehicle is located, such as whether it is in a no-honking zone or the noise control requirements for the current time period. Key risks obtained from environmental information, such as the relative distance between pedestrians and the roadway, the size and location of obstacles, and the indication level of traffic signs, along with regional rules obtained from location information, are used to quantify and comprehensively calculate the aforementioned driving risks, resulting in a risk coefficient that reflects the degree of risk in the current driving environment.

[0068] As an optional embodiment, the horn system includes a domain controller, a sensing system, and a location service module. The domain controller, sensing system, and location service module are interconnected via Ethernet. Using the horn system, a risk coefficient is determined based on environmental information and location information, including: in response to the domain controller receiving environmental information from the sensing system and location information from the location service module, the domain controller fuses the environmental information and location information to obtain a fusion result; and the domain controller determines the risk coefficient based on the fusion result.

[0069] In this embodiment, the domain controller can represent a high-performance, integrated central processing unit responsible for receiving, processing, and fusing data from various sensors. These sensors may include, but are not limited to, a system-on-a-chip domain controller (SoC) integrating a vision processing unit, LBS, and a multimodal fusion algorithm engine to execute decision-making algorithms and control actuators, such as the response of an Acoustic Vehicle Alerting System (AVAS). The perception system can represent a visual perception module composed of a forward-facing camera and millimeter-wave radar, used to acquire real-time information about changes in the vehicle's surrounding environment, such as the presence or movement of pedestrians, vehicles, and obstacles. The location service module can represent a positioning and area identification system based on high-precision maps, GNSS, and base station positioning technologies. It can provide precise vehicle location information and identify the type of area where the vehicle is located (e.g., school zone, hospital zone, residential zone) and specific rules of the area (e.g., no-honking rules, noise restrictions). The fusion result can represent a comprehensive data packet containing current environmental visualization features, obstacle status, vehicle location, and area attributes.

[0070] Optionally, Ethernet is used to ensure that the domain controller can receive environmental information from the sensing system and location and area attribute data from the location service module in a high-bandwidth, low-latency manner.

[0071] Optionally, the domain controller preprocesses the environmental and location information to ensure data consistency and accuracy. Key features are extracted from the preprocessed data, such as the relative positions of pedestrians and vehicles, the type and size of obstacles, the type of area, and time period. Based on these features, the domain controller combines the environmental and location information to generate a fused result containing comprehensive information about the vehicle's current driving environment.

[0072] Optionally, the domain controller can use a multimodal fusion algorithm to calculate the above fusion results to obtain a quantitative value that can comprehensively reflect the degree of risk faced by the vehicle in the current driving environment, namely the risk coefficient.

[0073] In this embodiment of the invention, the above method can be used to integrate a high-performance domain controller, combined with a visual perception system and a location service module, to acquire and analyze environmental changes and geographic information around the vehicle in real time and comprehensively. After processing and fusing the environmental and location information, a comprehensive data packet (i.e., fusion result) is generated. Based on the fusion result, the domain controller uses a multimodal fusion algorithm to calculate the comprehensive risk coefficient in real time, such as pedestrian distance, regional noise sensitivity, time period, etc.

[0074] As an optional implementation method, the vehicle's horn-honking strategy is determined at least based on a risk factor, including: determining the horn-honking strategy based on environmental horn-honking rules and risk factors.

[0075] In this embodiment, the aforementioned horn rules can be used to indicate whether the environment permits a vehicle to honk its horn. For example, based on the vehicle's geographical location, if it is located in a noise-sensitive area such as near a school, hospital, or library, a silent or low-frequency horn rule should be followed. Horn restrictions should be set according to the current time, such as during nighttime rest periods. Even in non-sensitive areas, a low-volume horn or no-honking rule should be enforced to reduce disturbance to surrounding residents.

[0076] Optionally, the domain controller can look up matching horn rules based on the vehicle's current location and time of day. For example, in a school zone, horn rules might require limiting the volume to a low level during the day and further reducing it to a very low level or complete silence at night.

[0077] Optionally, the vehicle compares a real-time calculated risk coefficient with a threshold set in the rules. For example, even in school zones where quiet is required, if the risk coefficient exceeds a preset "emergency" threshold (detecting a pedestrian suddenly crossing the road), the horn system should exceed the current rule restrictions and execute an emergency horn strategy to ensure driving safety.

[0078] Optionally, based on the rule matching results and risk coefficient assessment, a specific horn-honking strategy is generated, including whether to honk the horn, the volume, frequency, loudness and mode of the horn (e.g., short warning, continuous alert).

[0079] In this embodiment of the invention, the above method can flexibly adjust the horn-honking rules according to the vehicle's geographical location and current time, thereby automatically switching to the most suitable horn-honking behavior in different environments. By calculating the risk coefficient in real time and comparing it with the threshold of the preset rules, the safety of vehicles and personnel can be ensured while complying with laws and regulations. Even in areas where horn-honking is normally prohibited, in case of an emergency (such as a pedestrian suddenly entering the lane), a high-risk response strategy can be activated immediately, issuing a warning horn to effectively avoid accidents.

[0080] As an optional embodiment, the horn-honking strategy includes volume information, horn-honking rules based on the environment, and a risk coefficient. Determining the horn-honking strategy includes at least one of the following: in response to the horn-honking rule allowing the triggering of the horn-honking operation, the environment belonging to a first environment type and the risk level being greater than a risk level threshold, determining volume information less than a volume information threshold; in response to the horn-honking rule allowing the triggering of the horn-honking operation, the environment belonging to a second environment type and the risk level being greater than a risk level threshold, determining volume information greater than or equal to a volume information threshold.

[0081] In this embodiment, the volume information can be used to represent the volume level of a vehicle horn. The first environmental information can be used to indicate that the volume information is not allowed to be greater than or equal to a volume information threshold. For example, in a residential area or at night. The volume information threshold can be used to represent the maximum horn volume allowed in a specific environment to ensure driving safety. The second environmental type can be used to indicate that the volume information is allowed to be greater than or equal to the volume information threshold. For example, on a general road or highway.

[0082] Optionally, the domain controller identifies the vehicle's current environment type (e.g., residential area, near a school, or at night) based on information provided by LBS. These environments have strict noise control and typically do not use high-volume horns. Based on the fusion of environmental and location information, the system calculates the potential risk level faced by the vehicle in real time. In the first environment type, if the risk level exceeds a pre-set threshold, the vehicle needs to react to ensure driving safety. However, given the specific nature of the first environment type, even when facing a higher risk, the vehicle will adjust its volume to be below the threshold, i.e., below the maximum allowed volume for this environment, to issue a sufficient warning signal without violating local noise control regulations. For example, in a school zone, even if a pedestrian is detected suddenly crossing the road, the system will sound its horn moderately, keeping the volume within a non-disturbing range, while ensuring that the pedestrian hears the horn and takes evasive action.

[0083] Optionally, the domain controller analyzes LBS data to confirm that the vehicle is in a second environment type (e.g., general roads, highways, or other areas without strict noise restrictions), where a louder horn can be used to enhance warning effectiveness. The surrounding environment can be continuously monitored via a visual perception system and other auxiliary sensors. If a high-risk situation is detected, including but not limited to: a vehicle suddenly stopping ahead or a pedestrian entering the lane, the risk level is immediately assessed to determine if it exceeds a threshold. When the risk level is confirmed to exceed a preset threshold, the vehicle can increase the horn volume to equal or exceed the threshold (i.e., the allowed maximum volume range) to ensure that even at high speeds or in extreme situations, the horn can quickly and effectively notify all surrounding road users, avoiding potential collision hazards.

[0084] In this embodiment of the invention, the above method can automatically adjust the horn-honking strategy according to different environments in which the vehicle is located. In the first environment type, even if a certain risk is detected, the vehicle will control the horn volume at a low level to reduce interference with residents' lives. In the second environment type, when the risk level exceeds the risk level threshold, the vehicle will activate a high-volume horn-honking strategy to ensure that the horn sound can still serve as a warning in noisy traffic, thereby effectively preventing traffic accidents.

[0085] As an optional embodiment, the horn-honking strategy includes loudness information, environmental horn-honking rules, and a risk coefficient. Determining the horn-honking strategy includes at least one of the following: in response to the horn-honking rule allowing the triggering of a horn-honking operation, the risk level is greater than a risk level threshold, and the distance between the vehicle and at least one target object in the driving direction is less than a distance threshold, determining loudness information less than a loudness information threshold; in response to the horn-honking rule allowing the triggering of a horn-honking operation, the risk level is greater than a risk level threshold, and the distance is greater than or equal to a distance threshold, determining loudness information greater than or equal to a loudness information threshold.

[0086] In this embodiment, the loudness information can be used to represent the intensity and clarity of the sound when a vehicle horn sounds. The distance threshold can be used to represent the safe distance limit between a vehicle and a target object (e.g., a pedestrian, other vehicles) in a specific environmental type. When the distance between the vehicle and the target object is less than the threshold, it indicates that the target object has entered the vehicle's direct warning range, requiring a gentler horn-sounding strategy to avoid excessive fright or interference to the target object. The loudness information threshold can be used to represent the minimum horn loudness allowed to ensure driving safety under specific environmental conditions and risk assessments. When the risk level exceeds a preset risk level threshold, and the distance between the vehicle and the target object is greater than or equal to the distance threshold, the vehicle will use a horn-sounding strategy higher than the loudness information threshold to clearly convey the warning signal at a greater distance, increasing the alertness of road users.

[0087] Optionally, a visual perception system and LBS (Location Based Services) can be used to identify target objects in the driving direction in real time and measure the precise distance between the vehicle and the target object. The domain controller comprehensively analyzes the environmental type and risk level of the vehicle to determine whether the horn-honking condition is met, i.e., whether the risk level is greater than a preset risk level threshold. When the distance between the vehicle and the target object is less than the distance threshold, even if the risk level meets the horn-honking condition, the vehicle will determine a loudness information below the loudness information threshold to avoid startling the target object at close range, especially in noise-sensitive areas such as residential areas and near schools. Based on the determined loudness information, the AVAS (Audio-Assisted Sound System) speaker will generate a directional and gentle horn sound, ensuring that the target object can clearly but not frightenedly perceive the warning, while reducing the noise impact on the surrounding environment.

[0088] Optionally, the domain controller uses LBS data to confirm the vehicle's location in a second environment type, such as a highway or urban expressway. If vehicle analysis shows a risk level significantly exceeding a risk threshold, it indicates a serious threat in the surrounding environment, such as sudden braking by a vehicle ahead or road construction obstacles, requiring immediate action. The vehicle adjusts the determined loudness information to be greater than or equal to a preset loudness threshold, ensuring that the horn sound can still penetrate background noise at long distances. The vehicle can also amplify the low-frequency components of the horn sound to allow it to travel further, thus promptly conveying the warning to all relevant road users and preventing potential collisions. The directional sound wave technology of the vehicle's AVAS speakers can precisely project the high-loudness horn sound onto the target location, reducing noise diffusion in irrelevant directions while ensuring the target effectively receives the warning signal.

[0089] In this embodiment of the invention, the above method can be used to accurately identify the environmental type and target objects in the direction of travel around the vehicle in real time by integrating a visual perception system and LBS positioning technology. Based on the actual distance to the target object, the loudness of the horn can be flexibly adjusted to ensure that the warning signal is both effective and appropriate. The domain controller dynamically determines whether to initiate the horn operation and the specific parameters of the horn-honking strategy based on real-time risk level analysis and comparison with a preset risk level threshold. In the first environmental type, even with certain risks, priority is given to minimizing the startling of the target object and the impact on the environment, keeping the loudness information at a low but still effective level. In the second environmental type, facing high-risk situations, a horn-honking strategy higher than the loudness information threshold can be activated, while increasing the low-frequency components of the horn sound to ensure that the horn sound can travel a longer distance, penetrate background noise, and effectively improve the alertness of distant road users.

[0090] As an optional embodiment, the horn-honking strategy includes frequency information, environment-based horn-honking rules, and a risk coefficient. Determining the horn-honking strategy includes: in response to the horn-honking rule allowing the triggering of a horn-honking operation, and the risk level being greater than a risk level threshold, determining the frequency information, wherein the frequency information is used to represent the frequency of triggering the horn-honking operation and is positively correlated with the duration of triggering the horn-honking operation.

[0091] In this embodiment, the frequency information described above can be used to represent the frequency at which the horn-honking operation is triggered. The duration of the horn-honking operation described above can be used to represent the specific duration of the horn-honking, that is, the time interval from the start to the end of the horn-honking.

[0092] Optionally, the LBS positioning module determines the current environment type of the vehicle, such as city streets, residential areas, near schools, or highways. Combining the forward targets (pedestrians, vehicles, obstacles, etc.) detected by a visual perception system (e.g., cameras, radar) and their motion states, with real-time traffic information provided by LBS, the domain controller calculates the risk level of the current driving environment. Based on the risk level and environment type, the domain controller generates frequency information. In high-risk situations, the system may select a higher baseband frequency and a complex frequency modulation mode, such as frequency sweep or pulse frequency modulation.

[0093] Optionally, since the frequency information is positively correlated with the duration of the horn trigger, the domain controller will adjust the horn duration based on the risk level and environmental characteristics while determining the frequency information. In cases of particularly high risk or high ambient noise, the horn can be gradually accelerated to ensure that the warning signal is effectively conveyed.

[0094] Optionally, the domain controller sends frequency information and duration parameters to the AVAS speaker. The speaker generates a horn sound of a specific frequency according to the received instructions and continues for a specified duration to achieve directional and dynamic horn warning.

[0095] In this embodiment of the invention, the above method can be used to adjust the frequency and duration of the horn according to the type of environment in which the vehicle is located. In noise-sensitive areas such as residential areas, a low-frequency and short-duration horn-honking strategy is adopted to reduce noise pollution. On highways, in the face of high risk and background noise, a high-frequency and long-duration horn-honking strategy is adopted to ensure that distant road users can receive the warning in time.

[0096] As an optional embodiment, during vehicle operation, acquiring environmental information corresponding to the vehicle includes: in the environment, detecting target objects in the vehicle's driving direction through a perception system to obtain environmental information; and during vehicle operation, acquiring the vehicle's location information includes: in the environment, acquiring location information based on map data and a positioning system through a location service module.

[0097] In this embodiment, the target object can be used to represent any entity or factor on the road or vehicle travel path that affects driving safety, including but not limited to pedestrians, cyclists, other motor vehicles, animals, stationary obstacles, dynamic obstacles, and road signs.

[0098] Optionally, visual perception devices such as front-facing cameras and radar can be used to scan the environment in front of the vehicle in real time, identify and classify various target objects, and determine whether they pose a potential threat to the vehicle. The relative distance and speed between the vehicle and the target objects can also be measured.

[0099] Optionally, high-precision vehicle positioning can be achieved using various positioning technologies such as high-precision maps, GNSS / base station positioning, etc. By accessing a high-precision map database, attribute information about the vehicle's location can be obtained, such as whether it is a school area, near a hospital, a residential area, a commercial street, or a specially controlled area.

[0100] In this embodiment, the above method can continuously and rapidly acquire and analyze the vehicle's surrounding environment, identifying the movement of pedestrians, vehicles, and obstacles, as well as detecting the status of road signs and traffic lights in the vehicle's environment. Based on LBS, the vehicle, combined with the Global Navigation Satellite System and base station positioning, quickly locks its real-time latitude and longitude coordinates, ensuring the accuracy and immediacy of positioning. Simultaneously, high-precision map data is used to determine the specific area attributes of the vehicle's location (e.g., school zone, hospital zone, residential area, etc.).

[0101] As an optional embodiment, the vehicle includes a horn system, which includes an acoustic broadcasting unit. The method controls the vehicle to perform a horn-sounding operation according to a horn-sounding strategy, including: using the acoustic broadcasting unit to control the vehicle to perform a horn-sounding operation according to the horn-sounding strategy; the method further includes: using the feedback sound wave corresponding to the horn-sounding operation to adjust the horn-sounding strategy to obtain an adjusted horn-sounding strategy.

[0102] In this embodiment, the acoustic broadcasting unit can be used to represent a speaker system integrated into the vehicle, particularly advanced speakers capable of generating specific spectral and directional sounds, such as AVAS speakers. Feedback sound waves can be used to represent sound signals reflected from the vehicle's external environment, captured by a microphone array or other acoustic sensors mounted on the vehicle to evaluate the actual effect of horn operation.

[0103] Optionally, based on the horn-sounding strategy generated by the domain controller, the acoustic broadcasting unit (e.g., an AVAS loudspeaker) adjusts the base frequency and volume of the emitted sound waves. For example, in low-risk environments, a lower frequency and volume can be set to reduce unnecessary noise; while in high-risk areas, such as traffic congestion or densely populated pedestrian areas, the frequency and volume can be increased to ensure that the warning sound can penetrate background noise and be effectively perceived by potential road users. The multi-array structure of the AVAS loudspeaker can be utilized to achieve directional sound beam emission (e.g., focusing towards pedestrians) using a two-in-one loudspeaker array, reducing environmental diffusion so that the horn sound can be focused on a specific target, such as pedestrians or vehicles ahead, reducing sound wave diffusion in other directions and avoiding noise interference to unrelated areas.

[0104] Optionally, sound wave signals reflected from the external environment can be collected by a microphone array or other acoustic sensors. The domain controller analyzes the characteristics of the feedback sound waves and determines whether they are effectively received by the target object in order to evaluate the actual effect of the horn strategy.

[0105] Optionally, if the above feedback sound waves show that the attenuation of the horn sound in a specific environment is greater than expected, or the contrast with the background noise is insufficient, the domain controller will adjust the horn strategy, such as increasing the volume or using a more penetrating frequency, to compensate for the impact of environmental noise and ensure that the horn achieves the expected warning effect.

[0106] Optionally, based on the above analysis, the domain controller can adjust the horn-honking strategy in real time, including but not limited to parameters such as frequency, volume, loudness, and duration, to ensure that the horn-honking adapts to environmental changes while minimizing unnecessary interference with the surrounding environment. The adjusted horn-honking strategy will more accurately match the current driving conditions. For example, in low-risk and quiet residential areas, a softer and shorter horn-honking method may be selected to avoid disturbing residents; while on high-risk highway sections, the system will activate a stronger and longer horn-honking strategy to ensure that safety warnings are conveyed.

[0107] In this embodiment of the invention, the vehicle dynamically adjusts its horn-honking strategy based on real-time environmental information and the status of the target object using the above method. In low-risk, quiet environments, the system selects a gentle, short horn-honking mode to avoid unnecessary noise pollution. In high-risk situations, such as a suddenly appearing pedestrian or traffic congestion ahead, the system can increase the horn volume and frequency, and employ a special frequency modulation mode to ensure that the horn warning is effectively heard even in noisy environments. Through an integrated perception system and LBS location service module, target object information and vehicle location attributes are acquired in real time. Combining environmental noise collected by internal and external microphones with horn feedback sound waves, the domain controller can accurately evaluate the horn-honking effect and identify whether horn parameters, such as frequency, volume, loudness, or duration, need to be adjusted to adapt to the constantly changing external environment. If the horn-honking effect is found to be poor or there is excessive noise, the domain controller will immediately adjust the strategy to find the optimal combination of horn parameters.

[0108] In this embodiment of the invention, during vehicle operation, environmental information and location information of the vehicle are acquired. The environmental information refers to information related to vehicle operation within the environment in which the vehicle is located, and the location information indicates the vehicle's position within the environment during operation. Based on the environmental and location information, a risk coefficient for the vehicle is determined, representing the degree of risk present at the vehicle's current location. At least based on the risk coefficient, a horn-honking strategy is determined, whereby the horn-honking strategy represents a rule for controlling the vehicle to trigger a horn to reduce the risk level, where the reduced risk level is less than or equal to a risk level threshold. The vehicle is then controlled to perform a horn-honking operation according to the horn-honking strategy. In other words, in this embodiment of the invention, considering that different driving scenarios have different levels of risk, different horn-honking strategies are required for different levels of risk. The risk level of the driving scenario corresponding to the actual environment in which the vehicle is located can be accurately measured based on the environmental and location information. Based on the risk coefficients corresponding to the aforementioned risk levels, corresponding horn-honking strategies are formulated and implemented. These strategies are intelligently adjusted based on environmental and location information, ensuring driving safety while reducing unnecessary horn noise interference. This achieves the technical effect of improving the accuracy of vehicle horn control and solves the technical problem of low horn control accuracy. The technical solution of this invention will be illustrated below with examples of preferred embodiments.

[0109] Currently, traditional horn systems cannot dynamically adjust parameters according to the environment, easily causing noise pollution or insufficient warning; human subjective decision-making makes it difficult to fully perceive complex scenarios, leading to unreasonable timing and methods of horn use; traditional horn-speaker distributed control architectures are complex, costly, and lack real-time performance. Therefore, there is an urgent need for an adaptive horn system that integrates multi-sensor technology and efficient collaborative control.

[0110] This invention improves scene recognition accuracy and avoids false horn use by combining multimodal perception fusion, including but not limited to vision and LBS; adjusts horn characteristics in real time according to the environment to balance safety and noise reduction requirements, i.e., dynamic parameter adjustment; reduces system complexity and cost with a three-in-one AVAS speaker, i.e., hardware integration optimization; and achieves multi-task processing on a single chip to ensure millisecond-level response, i.e., efficient collaboration of SoC domain control.

[0111] In this embodiment, the device structure may include: a three-in-one AVAS speaker, a SoC domain controller, a visual perception system, an LBS location service module, a communication interface, and an acoustic broadcasting unit. The three-in-one AVAS speaker may include a speaker integrating an acoustic alarm system (AVAS) function, a horn function (for generating and directional propagating horn signals), and a microphone array (for collecting feedback sound waves). The SoC domain controller may include a built-in visual processing unit, an LBS positioning module, and a multimodal fusion algorithm engine, responsible for real-time perception data processing and horn-sounding strategy decisions. The visual perception system may include a forward-facing camera and millimeter-wave radar for detecting pedestrians, obstacles, and road signs. The LBS location service module may include a module that acquires the vehicle's real-time location and surrounding environmental attributes (e.g., schools, hospitals, residential areas) based on high-precision maps and GNSS / base station positioning. The communication interface may include a connection to an in-vehicle Ethernet network for data interaction and functional collaboration. The acoustic broadcasting unit may include a two-in-one speaker, a broadcasting unit with dual functions of AVAS and horn (Honking Of Road Notification, or HORN) and corresponding hardware performance.

[0112] In this embodiment, the adaptive horn-honking process includes: environmental perception and positioning: the vision system identifies targets ahead (pedestrians, vehicles, traffic signs, etc.) and their distances in real time; the LBS module determines the type of area where the vehicle is located (e.g., no-honking zone, speed-limited zone, residential area) and the current time period. Data fusion and risk assessment: the SoC domain controller fuses the visual perception data with LBS location information to calculate a comprehensive risk coefficient (e.g., pedestrian approach speed, area noise sensitivity, etc.).

[0113] In this embodiment, the horn-honking strategy generation may include dynamically adjusting horn parameters based on risk factors and area rules: volume adaptation, such as lowering the base volume in residential areas or at night, and increasing the volume on highways or in emergency scenarios; loudness adjustment: dynamically changing according to the target distance (e.g., softer at close range, stronger at long range, such as increasing the low-frequency components on highways to spread further and increase loudness); frequency modulation, such as generating warning sound effects through AVAS speakers (e.g., gradually changing frequency to remind of danger).

[0114] In this embodiment, directional sound propagation and feedback may include using a two-in-one speaker array to achieve directional sound beam emission (e.g., focusing towards pedestrians); reducing environmental diffusion, for example, using a microphone array to collect feedback sound waves and optimize subsequent horn parameters (e.g., echo suppression, direction calibration).

[0115] For example, when a vehicle enters a school zone (LBS positioning), the SoC reduces the basic horn volume to 60 decibels (dB); the vision system detects a pedestrian crossing the road 5 meters ahead, increasing the risk factor; the system triggers an emergency horn: the volume is increased to 75dB, the frequency gradually changes from 500 Hz to 1000 Hz, and the sound beam is directed towards the pedestrian; if the pedestrian does not respond, the vehicle lights flash as a warning.

[0116] This invention integrates visual perception with LBS location services to drive a three-in-one AVAS speaker under SoC domain control, enabling adaptive horn activation. This effectively balances driving safety and noise control, providing an efficient and environmentally friendly warning interaction solution for smart cars.

[0117] Optionally, the three-in-one AVAS speaker integrated design includes, but is not limited to: integrating an acoustic alarm system (AVAS), a sound directional emission module, and an environmental sensing microphone array into a single speaker to achieve horn signal generation, precise sound beam control, and environmental sound feedback acquisition, thereby reducing system complexity and cost while improving acoustic performance.

[0118] Optionally, the multimodal perception fusion algorithm includes, but is not limited to: fusing visual perception (camera + millimeter-wave radar) with LBS location services (high-precision map + GNSS / base station positioning), and calculating the comprehensive risk coefficient (e.g., pedestrian distance, regional noise sensitivity, time period, etc.) in real time through SoC domain control, breaking through the limitations of single sensor perception and improving scene recognition accuracy.

[0119] Optionally, the adaptive horn parameter dynamic adjustment includes, but is not limited to, dynamically adjusting the horn volume, loudness, and frequency based on risk factors and area rules.

[0120] Optionally, real-time collaborative processing under SoC domain control includes, but is not limited to, integrating vision processing, LBS positioning, and multimodal fusion algorithms into a single-chip SoC domain controller to achieve millisecond-level data processing and decision-making, avoid distributed architecture latency, and improve system response efficiency.

[0121] Optionally, directional sound propagation and feedback optimization includes, but is not limited to, using speaker arrays to achieve precise directional sound beam emission (e.g., focusing on the direction of pedestrians) to reduce the spread of environmental noise; and using microphone arrays to collect feedback sound waves to dynamically optimize horn parameters (e.g., echo suppression, direction calibration) to ensure the effectiveness of warnings.

[0122] Optionally, embodiments of this application propose an adaptive horn-honking device that integrates vision and LBS perception, including a three-in-one AVAS speaker, a SoC domain controller, a vision perception system (e.g., a camera + millimeter-wave radar) and an LBS module, wherein: the AVAS speaker integrates acoustic signal generation, directional transmission and ambient sound acquisition functions; the SoC domain controller generates a dynamic horn-honking strategy through multimodal data fusion and controls the AVAS speaker to execute it.

[0123] Optionally, embodiments of this application propose an adaptive horn-honking process, including but not limited to real-time environmental perception and localization (visual target detection + LBS area recognition); multimodal data fusion to calculate risk coefficients; dynamic adjustment of horn-honking parameters (volume, loudness, frequency) based on risk coefficients and area rules; directional sound beam emission and feedback optimization.

[0124] Optionally, the method for automatically adjusting the horn volume and enabling rules based on LBS positioning area attributes (e.g., no-honking zones, school zones) and time period information may include algorithm logic that uses visual perception of target distance and movement trajectory to dynamically optimize horn loudness and frequency; structural design and control method of sound beam directional emission module in three-in-one AVAS loudspeaker; and implementation architecture and real-time decision-making process of multimodal data fusion engine in SoC domain control.

[0125] Optionally, this application proposes an intelligent vehicle system in which the adaptive horn device collaborates with other vehicle control systems (such as intelligent cockpit and autonomous driving domain control) via in-vehicle Ethernet to achieve warning function linkage (such as horn honking + headlight flashing).

[0126] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments; the numbers in these embodiments are merely illustrative and are not intended to impose specific limitations. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention, and are not specifically limited here.

[0127] According to an embodiment of the present invention, a vehicle horn system is also provided. It should be noted that the vehicle horn system of this embodiment can be used to execute the vehicle horn control method of the present invention.

[0128] Figure 2 This is a schematic diagram of a vehicle horn system according to an embodiment of the present invention. Figure 2 As shown, the vehicle's horn system 200 may include: a domain controller 202, a sensing system 204, a location service module 206, and an acoustic broadcasting unit 208.

[0129] Domain controller 202 calculates the risk level in real time and formulates and adjusts the horn-honking strategy based on the target object information received from the perception system and the vehicle location and environmental attributes obtained from the location service module.

[0130] The perception system 204 monitors the vehicle's surrounding environment in real time, including target objects in the vehicle's direction of travel, such as pedestrians, other vehicles, and obstacles, and provides their location, motion status, and other relevant information. The perception system may include various sensors, such as cameras, radar (millimeter-wave radar, lidar), and infrared sensors.

[0131] The location service module 206 provides detailed location information, including but not limited to vehicle coordinates, direction of travel, and area attributes (such as whether it is a school area or a no-honking area), based on the vehicle's current location and through satellite positioning systems such as the Global Navigation Satellite System and BeiDou, as well as ground base station information.

[0132] The acoustic broadcasting unit 208, based on the horn-honking strategy generated or adjusted by the domain controller 202, actually executes the horn-honking operation, converting electronic signals into sound wave signals and sending specific horn sounds to the surrounding environment. According to the instructions of the domain controller, the acoustic broadcasting unit can adjust the volume, frequency, loudness, and duration of the horn sound in real time to adapt to different environmental conditions and target object states. Utilizing multi-array loudspeaker technology, the acoustic broadcasting unit can achieve directional sound wave emission, focusing the horn sound on a specific target.

[0133] The vehicle horn system in this embodiment, through domain controller 202, calculates the risk level in real time and formulates and adjusts the horn-honking strategy based on target object information received from the perception system and vehicle location and environmental attributes obtained from the location service module. The perception system 204 monitors the vehicle's surrounding environment in real time, including target objects in the vehicle's direction of travel, such as pedestrians, other vehicles, and obstacles, and provides the location, movement status, and other relevant information of these targets. The location service module 206, based on the vehicle's current location, provides detailed location information, including but not limited to vehicle coordinates, direction of travel, and area attributes (e.g., whether it is a school zone or a no-honking zone), through satellite positioning systems such as the Global Navigation Satellite System and BeiDou, as well as ground base station information. The acoustic broadcasting unit 208, according to the horn-honking strategy generated or adjusted by domain controller 202, actually executes the horn-honking operation, converting electronic signals into sound wave signals and sending a specific horn sound to the surrounding environment. According to the instructions of the domain controller, the acoustic broadcasting unit can adjust the volume, frequency, loudness, and duration of the horn sound in real time to adapt to different environmental conditions and target object states. By utilizing multi-array loudspeaker technology, the acoustic broadcasting unit can achieve directional sound wave emission, such as focusing the sound towards the direction of pedestrians, thereby improving the accuracy of vehicle horn control and solving the technical problem of low accuracy in vehicle horn control.

[0134] According to an embodiment of the present invention, a vehicle horn control device is also provided. It should be noted that the vehicle horn control device of this embodiment can be used to execute the vehicle horn control method of the present invention.

[0135] Figure 3 This is a schematic diagram of a vehicle horn control device according to an embodiment of the present invention. Figure 3 As shown, the vehicle's horn control device 300 may include: an acquisition unit 302, a first determination unit 304, a second determination unit 306, and a control unit 308.

[0136] The acquisition unit 302 acquires environmental information and location information of the vehicle during the vehicle's operation. The environmental information is information related to the vehicle's operation in the environment in which the vehicle is located, and the location information is used to indicate the vehicle's location in the environment during the operation.

[0137] The first determining unit 304 determines the risk coefficient of the vehicle based on environmental information and location information, wherein the risk coefficient is used to represent the degree of risk that exists in the vehicle's location.

[0138] The second determining unit 306 determines the vehicle's horn-honking strategy based at least on the risk coefficient, wherein the horn-honking strategy is used to represent the rule for controlling the vehicle to trigger horn-honking to reduce the risk level, and the reduced risk level is less than or equal to the risk level threshold.

[0139] Control unit 308 controls the vehicle to perform horn-sounding operations according to the horn-sounding strategy.

[0140] The vehicle horn control device of this embodiment acquires environmental information and vehicle location information corresponding to the vehicle during vehicle operation via the acquisition unit 302. The first determining unit 304 determines the vehicle's risk coefficient based on the environmental and location information. The second determining unit 306 determines the vehicle's horn-honking strategy, at least based on the risk coefficient. The horn-honking strategy represents a rule for controlling the vehicle to trigger the horn to reduce the risk level, where the reduced risk level is less than or equal to a risk level threshold. The control unit 308 controls the vehicle to perform the horn-honking operation according to the horn-honking strategy, thereby improving the accuracy of vehicle horn-honking control and solving the technical problem of low accuracy in vehicle horn-honking control.

[0141] According to embodiments of the present invention, a computer-readable storage medium is also provided, the storage medium including a stored program, wherein the program executes the methods described in the embodiments of the present invention.

[0142] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program executes the methods described above in the embodiments of the present invention during runtime.

[0143] According to another aspect of the present invention, an electronic device is also provided. The electronic device includes a memory and a processor, the memory storing a computer program, and the processor being configured to run the computer program to perform the methods described in the embodiments of the present invention.

[0144] According to another aspect of the present invention, a computer program product is also provided. This computer program product includes a computer program that, when executed by a processor, implements the methods described above in the embodiments of the present invention.

[0145] According to another aspect of the present invention, a computer program product is also provided. This computer program product includes a computer program that, when executed by a processor, implements the methods described above in the embodiments of the present invention.

[0146] According to another aspect of the present invention, a vehicle is also provided. The vehicle includes a memory and a processor, the memory storing a computer program, and the processor being configured to run the computer program to perform the methods described in the embodiments of the present invention.

[0147] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0148] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed can be through some interfaces; the indirect coupling or communication connection of units or modules can be electrical or other forms.

[0149] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0150] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as an application function unit.

[0151] If the integrated unit is implemented as an application function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of an application product. This computer application product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0152] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for controlling the horn of a vehicle, characterized in that, include: During the vehicle's operation, environmental information corresponding to the vehicle and location information of the vehicle are acquired. The environmental information is information related to the vehicle's operation in the environment where the vehicle is located, and the location information is used to indicate the vehicle's location in the environment during its operation. Based on the environmental information and the location information, a risk coefficient for the vehicle is determined, wherein the risk coefficient is used to represent the degree of risk that the vehicle faces at its location; Based at least on the risk coefficient, a horn-honking strategy for the vehicle is determined, wherein the horn-honking strategy represents a rule for controlling the vehicle to trigger the horn to reduce the risk level, and the reduced risk level is less than or equal to a risk level threshold. According to the horn-honking strategy, the vehicle is controlled to honk its horn.

2. The method according to claim 1, characterized in that, The vehicle includes a horn system. Based on the environmental information and the location information, the risk factor of the vehicle is determined, including: Using the horn system, the risk coefficient is determined based on the environmental information and the location information.

3. The method according to claim 2, characterized in that, The horn system includes a domain controller, a sensing system, and a location service module. The domain controller, the sensing system, and the location service module are interconnected via Ethernet. Using the horn system, based on the environmental information and the location information, the risk coefficient is determined, including: In response to the domain controller receiving the environmental information from the sensing system and the location information from the location service module, the domain controller fuses the environmental information and the location information to obtain a fusion result. The risk coefficient is determined using the domain controller based on the fusion results.

4. The method according to claim 3, characterized in that, Based at least on the aforementioned risk coefficient, determine the vehicle's horn-honking strategy, including: Based on the horn-honking rules of the environment and the risk coefficient, the horn-honking strategy is determined, wherein the horn-honking rules are used to indicate whether the environment allows the vehicle to perform the horn-honking operation.

5. The method according to claim 4, characterized in that, The horn-honking strategy includes volume information. Based on the horn-honking rules of the environment and the risk coefficient, the horn-honking strategy is determined, including at least one of the following: In response to the horn-honking rule allowing the horn-honking operation, the environment belongs to a first environment type, and the risk level is greater than the risk level threshold, the volume information is determined to be less than the volume information threshold, wherein the first environment type is used to indicate that the volume information is not allowed to be greater than or equal to the volume information threshold; In response to the horn rule allowing the horn operation to be triggered, the environment belongs to a second environment type, and the risk level is greater than the risk level threshold, the volume information is determined to be greater than or equal to the volume information threshold, wherein the second environment type is used to indicate that the volume information is allowed to be greater than or equal to the volume information threshold.

6. The method according to claim 4, characterized in that, The horn-honking strategy includes loudness information. Based on the horn-honking rules of the environment and the risk coefficient, the horn-honking strategy is determined, including at least one of the following: In response to the horn-honking rule allowing the horn-honking operation to be triggered, the risk level is greater than the risk level threshold, and the distance between the vehicle and at least one target object in the driving direction is less than the distance threshold, the loudness information is determined to be less than the loudness information threshold; In response to the horn rule allowing the horn operation to be triggered, if the risk level is greater than the risk level threshold and the distance is greater than or equal to the distance threshold, the loudness information is determined to be greater than or equal to the loudness information threshold.

7. The method according to claim 4, characterized in that, The horn-honking strategy includes frequency information. Based on the horn-honking rules of the environment and the risk coefficient, the horn-honking strategy is determined, including: In response to the horn-honking rule allowing the horn-honking operation to be triggered, and the risk level being greater than the risk level threshold, the frequency information is determined, wherein the frequency information is used to represent the frequency of triggering the horn-honking operation and is positively correlated with the duration of triggering the horn-honking operation.

8. The method according to claim 3, characterized in that, During vehicle operation, environmental information corresponding to the vehicle is acquired, including: In the environment, the perception system detects target objects in the direction of travel of the vehicle to obtain environmental information. During vehicle operation, the vehicle's location information is acquired, including: In the environment, the location information is obtained through the location service module based on map data and the positioning system.

9. The method according to any one of claims 1 to 8, characterized in that, The vehicle includes a horn system, which includes an acoustic broadcasting unit. According to the horn-honking strategy, the system controls the vehicle to perform the horn-honking operation, including: Using the acoustic broadcasting unit, the vehicle is controlled to perform the horn-honking operation according to the horn-honking strategy; The method further includes: The horn-honking strategy is adjusted using the feedback sound wave corresponding to the horn-honking operation, resulting in the adjusted horn-honking strategy.

10. A vehicle, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 9.

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