Vehicle whistling method and device and vehicle

Abstract

The invention discloses a vehicle whistling method and device and a vehicle, and relates to the technical field of vehicles. The method comprises the steps of obtaining road information of a current road section and vehicle speed information of a vehicle in response to a curve automatic whistling function starting instruction of the vehicle; determining whether the vehicle meets a preset whistling condition based on the road information of the current road section; matching at least one of target whistling frequency, target whistling volume and target whistling duration of the vehicle according to the road information of the current road section and the vehicle speed information under the condition of determining that the vehicle meets the preset whistling condition; and under the condition that the vehicle is located in the road section range between the starting point of the current road section and the maximum curvature point of the current road section, vehicle whistling is controlled according to the target whistling frequency, the target whistling volume and the target whistling duration. Therefore, the driving safety can be effectively improved, other traffic participants can be accurately warned, the system adapts to complex road conditions, accident risks caused by improper whistling are reduced, and meanwhile noise pollution can be reduced.

Description

Technical Field

[0001] The present application relates to the technical field of vehicles, and in particular, to a vehicle horn sounding method, a vehicle horn sounding device, and a vehicle. Background Art

[0002] The rapid development of new energy vehicles has put forward higher requirements for vehicle safety and road traffic accident prevention. Among various types of traffic accidents, the proportion of accidents occurring during curved road driving is particularly prominent, which has attracted extensive attention from all sectors of society. With the progress of technologies such as radar detection and intelligent driving, modern vehicles can already ensure safe lane-keeping driving in curves, yet they still cannot effectively prevent the possible lane-crossing behavior of oncoming vehicles. Therefore, sounding the horn to warn oncoming vehicles has become a necessary safety measure. For roads with fewer curves and gentler curvatures, manual horn sounding by the driver can still meet the requirements. However, in mountainous areas in the southwest of China, such as Yunnan, Guizhou, Sichuan, and Chongqing, where there are many hairpin curves and sharp curves, the traditional horn sounding method requires the driver to operate the steering wheel with one hand, which to a certain extent affects driving safety. Especially in continuous sharp curve sections, frequent horn sounding operations may cause the driver to be distracted, increasing the difficulty of control and potential safety hazards.

[0003] In related technologies, a patent document with the application number 201910062958.6 and the title of "A Control Method and Device for Automatic Horn Sounding of an Automobile" discloses that the vehicle automatically sounds the horn according to the radius of the curve and stops automatically sounding the horn according to the angle between the center line and the tangent of the curve side line, but does not consider the control of the horn sounding duration, horn sounding frequency, and horn sounding volume. Summary of the Invention

[0004] One of the objectives of the present invention is to provide a vehicle horn sounding method to solve the problem that frequent horn sounding operations in continuous sharp curve sections may cause the driver to be distracted, increasing the difficulty of control and potential safety hazards; the second objective is to provide a vehicle horn sounding device; the third objective is to provide a vehicle.

[0005] To achieve the above objectives, the technical solutions adopted by the present invention are as follows:

[0006] A vehicle horn sounding method, the method includes: in response to an instruction to turn on the automatic horn sounding function of the vehicle, obtaining road information of the current section and vehicle speed information of the vehicle; determining whether the vehicle meets a preset horn sounding condition based on the road information of the current section; in the case of determining that the vehicle meets the preset horn sounding condition, matching at least one of a target horn sounding frequency, a target horn sounding volume, and a target horn sounding duration of the vehicle according to the road information of the current section and the vehicle speed information; and when the vehicle is within the section range between the starting point of the current section and the point with the maximum curvature of the current section, controlling the vehicle to sound the horn according to the target horn sounding frequency, the target horn sounding volume, and the target horn sounding duration.

[0007] According to an embodiment of the present application, determining whether a vehicle meets a preset honking condition based on road information of a current road section includes: determining a radius of curvature of the current road section, a length of the current road section, and a honking restriction situation of the current road section according to the road information of the current road section; determining a curvature parameter of the current road section based on a ratio of the length of the current road section to the radius of curvature of the current road section; and determining that the vehicle meets the preset honking condition when the curvature parameter of the current road section is greater than a preset curvature parameter threshold and the current road section does not restrict honking.

[0008] According to an embodiment of the present application, matching a target honking frequency, a target honking volume, and a target honking duration of a vehicle according to road information of a current road section and vehicle speed information includes: determining a radius of curvature of the current road section and a length of the current road section according to the road information of the current road section; determining an average vehicle speed of the current road section according to the vehicle speed information; determining a curvature parameter of the current road section based on a ratio of the length of the current road section to the radius of curvature of the current road section; and determining the target honking frequency, the target honking volume, and the target honking duration according to the average vehicle speed of the current road section and the curvature parameter of the current road section.

[0009] According to an embodiment of the present application, determining the target honking frequency, the target honking volume, and the target honking duration according to the average vehicle speed of the current road section and the curvature parameter of the current road section includes: determining a first product based on a product of the average vehicle speed of the current road section and a first coefficient; determining a second product based on a product of the curvature parameter of the current road section and a second coefficient; determining the target honking frequency based on a sum value of the first product and the second product; determining a third product based on a product of the average vehicle speed of the current road section and a third coefficient; determining a fourth product based on a product of the curvature parameter of the current road section and a fourth coefficient; determining the target honking volume based on a sum value of the third product and the fourth product; determining a fifth product based on a product of the average vehicle speed of the current road section and a fifth coefficient; determining a sixth product based on a product of the curvature parameter of the current road section and a sixth coefficient; and determining the target honking duration based on a sum value of the fifth product and the sixth product.

[0010] According to an embodiment of the present application, the above method further includes: determining a width of the current road section according to the road information of the current road section; and when the width of the current road section is less than or equal to a preset road section width threshold, increasing the target honking frequency by a preset frequency, increasing the target honking volume by a preset volume, and increasing the target honking duration by a preset duration.

[0011] According to an embodiment of the present application, the above method further includes: determining the vehicle speed at the starting point of the current section and the vehicle speed at a preset point before entering the current section according to the vehicle speed information; when the vehicle speed at the preset point before entering the current section is greater than the preset speed threshold and meets the preset horn sounding condition, determining the horn volume and horn sounding duration at the starting point of the current section according to the vehicle speed at the starting point of the current section; when the vehicle is at the starting point of the current section, controlling the vehicle to sound the horn according to the horn volume and / or the horn sounding duration at the starting point of the current section.

[0012] According to an embodiment of the present application, the above method further includes: obtaining the road information of the current path; determining the road type of each section in the current path according to the road information of the current path; determining the bend factor of each section according to the road type of each section; determining the total bend factor based on the sum value of the bend factors of each section; when the total bend factor is greater than the preset bend factor threshold, controlling the vehicle to issue a reminder for turning on the automatic horn sounding function for bends.

[0013] According to an embodiment of the present application, the above method further includes: constructing a training set based on the road information of the section where the automatic horn sounding function for bends is turned on, as well as the vehicle speed information, horn sounding frequency, horn volume, and horn sounding duration when the vehicle is driving on this section; training a preset horn sounding model with the training set to obtain a training result; when the training result reaches the preset convergence condition, obtaining the preset horn sounding model; inputting the road information and vehicle speed information of the current section into the preset horn sounding model to determine at least one of the target horn sounding frequency, target horn volume, and target horn sounding duration.

[0014] A vehicle horn sounding device, the device includes: an acquisition module, configured to acquire the road information of the current section and the vehicle speed information of the vehicle in response to an instruction to turn on the automatic horn sounding function for bends of the vehicle; a first determination module, configured to determine whether the vehicle meets the preset horn sounding condition based on the road information of the current section; a second determination module, configured to match at least one of the target horn sounding frequency, target horn volume, and target horn sounding duration of the vehicle according to the road information of the current section and the vehicle speed information when it is determined that the vehicle meets the preset horn sounding condition; a control module, configured to control the vehicle to sound the horn according to the target horn sounding frequency, target horn volume, and target horn sounding duration when the vehicle is within the section range between the starting point of the current section and the point with the maximum curvature of the current section.

[0015] A vehicle, characterized in that it includes a memory, a processor, and a vehicle horn sounding program stored on the memory and executable on the processor. When the processor executes the vehicle horn sounding program, the foregoing vehicle horn sounding method is implemented.

[0016] Advantages of the present invention:

[0017] (1) For the horn sounding method of the present application, when the preset horn sounding conditions are met, at least one of the target horn frequency, target horn volume, and target horn duration is matched according to the road information and vehicle speed information of the current road section to control the horn sounding of the vehicle. In this way, it can effectively improve driving safety, accurately warn other traffic participants, adapt to complex road conditions, and reduce the accident risk caused by improper horn sounding; at the same time, it can reduce noise pollution, intelligently adjust the horn volume, frequency, and duration, avoid ineffective horn sounding, and reduce the noise interference to the surrounding environment; it can also improve traffic efficiency, optimize traffic order, and assist autonomous driving vehicles to better interact with other traffic participants;

[0018] (2) The two ways of actively turning on and prompting the vehicle owner to turn on through a pop-up window in complex road conditions are used to start the automatic horn sounding function for curves, providing a more convenient option compared to the traditional method and giving users a better experience;

[0019] (3) Utilize the learning ability of the current AI large model. Through the user's use of the automatic horn sounding function for curves, the AI large model performs self-learning. If the automatic horn sounding conditions for curves are met subsequently, it will automatically sound the horn without prompting the user to turn on this function through a pop-up window, enhancing the user experience. Description of the Drawings

[0020] Figure 1 is a flowchart of a vehicle horn sounding method according to some embodiments of the present application;

[0021] Figure 2 is a schematic diagram of gentle curve turning according to some embodiments of the present application;

[0022] Figure 3 is a schematic diagram of road types according to some embodiments of the present application;

[0023] Figure 4 is a schematic diagram of a vehicle horn sounding framework according to some embodiments of the present application;

[0024] Figure 5 is a flowchart of a vehicle horn sounding method according to some other embodiments of the present application;

[0025] Figure 6 is a block schematic diagram of a vehicle horn sounding device according to some embodiments of the present application;

[0026] Figure 7 is a block schematic diagram of a vehicle according to some embodiments of the present application. Detailed Embodiments

[0027] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0028] The vehicle horn sounding method, device, and vehicle according to the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0029] Figure 1 FIG. is a flowchart of a vehicle horn sounding method according to some embodiments of the present application. Referring to Figure 1 , the vehicle horn sounding method according to the embodiments of the present application may include the following steps:

[0030] S110, in response to an instruction to turn on the automatic horn sounding function for a vehicle on a curve, obtain road information of the current section and vehicle speed information of the vehicle.

[0031] Specifically, the user can issue an instruction to turn on the automatic horn sounding function for a vehicle on a curve by clicking a preset button. After the vehicle receives the instruction to turn on the automatic horn sounding function for a vehicle on a curve, the vehicle navigation system can be used to obtain road information of the current section. The road information of the current section includes, but is not limited to, the length of the current section, the starting point coordinates of the current section, the ending point coordinates of the current section, the coordinates of the point with the maximum curvature of the current section, and the horn sounding restriction situation of the current section. The vehicle speed information of the vehicle can be obtained through a vehicle speed sensor. The manner of obtaining the road information of the current section and the vehicle speed information is not specifically limited here.

[0032] S120, determine whether the vehicle meets a preset horn sounding condition based on the road information of the current section.

[0033] Specifically, based on the road information of the current section, the degree of curvature of the current section and whether the current section restricts horn sounding can be determined. For example, the degree of curvature of the current section can be determined according to the starting point coordinates, the ending point coordinates, and the coordinates of the point with the maximum curvature of the current section. Whether the preset horn sounding condition is met can be determined according to the degree of curvature of the current section and the horn sounding restriction situation, and then whether the vehicle horn can be controlled can be determined. For example, when the degree of curvature of the current section is relatively large and horn sounding is not restricted, it is determined that the preset horn sounding condition is met, that is, the vehicle horn can be controlled; when the degree of curvature of the current section is relatively small, or the current section restricts horn sounding, or the degree of curvature of the current section is relatively small and the current section restricts horn sounding, it is determined that the preset horn sounding condition is not met, that is, the vehicle horn cannot be controlled.

[0034] S130, when it is determined that the vehicle meets the preset honking conditions, matching at least one of the target honking frequency, target honking volume and target honking duration of the vehicle according to the road information of the current road section and the vehicle speed information.

[0035] Specifically, when it is determined that the vehicle can be controlled to honk, at least one of the target honk frequency, target honk volume, and target honk duration of the vehicle can be matched according to the road information of the current road section and the vehicle speed information. For example, when it is determined according to the road information of the current road section that the curvature of the current road section is large, or when it is determined according to the vehicle speed information that the average speed of the vehicle traveling on the current road section is large, the target honk frequency, target honk volume, and target honk duration of the larger vehicle are matched.

[0036] S140, when the vehicle is within the range of the road section between the starting point of the current road section and the point of maximum curvature of the current road section, controlling the vehicle to honk according to a target honking frequency, a target honking volume, and a target honking duration.

[0037] Specifically, when the vehicle is within the range of the road section between the starting point of the current road section and the point of maximum curvature of the current road section, the driver's vision is obstructed. Therefore, when the vehicle is within the range of the road section, the vehicle horn is controlled according to at least one of the target horn frequency, target horn volume and target horn duration.

[0038] The honking method of the present application, when the preset honking conditions are met, matches at least one of the target honking frequency, target honking volume and target honking duration according to the road information and vehicle speed information of the current road section, so as to control the honking of the vehicle. In this way, it can effectively improve driving safety, accurately warn other traffic participants, adapt to complex road conditions, and reduce the risk of accidents caused by improper honking; at the same time, it can reduce noise pollution, intelligently adjust the honking volume, frequency and duration, avoid invalid honking, and reduce noise interference to the surrounding environment; it can also improve traffic efficiency, optimize traffic order, and assist autonomous driving vehicles to better interact with other traffic participants.

[0039] In some embodiments, determining whether a vehicle meets a preset honking condition based on the road information of the current road section includes: determining the curvature radius of the current road section, the length of the current road section, and the honking restriction of the current road section based on the road information of the current road section; determining the curvature parameter of the current road section based on the ratio of the length of the current road section to the curvature radius of the current road section; and determining that the vehicle meets the preset honking condition when the curvature parameter of the current road section is greater than a preset curvature parameter threshold and the current road section does not restrict honking. The preset curvature parameter threshold can be determined according to actual conditions and is not specifically limited here.

[0040] Specifically, the road information of the current road segment includes the length of the current road segment, the starting point coordinates of the current road segment, the starting point coordinates of the current road segment, the coordinates of the point with the maximum curvature of the current road segment, and the whistle restriction situation of the current road segment. Among them, the curvature radius of the current road segment can be determined based on the starting point coordinates of the current road segment, the ending point coordinates of the current road segment, and the coordinates of the point with the maximum curvature of the current road segment. For example, referring to Figure 2 , B1 represents the starting point of the current road segment, C1 represents the point with the maximum curvature of the current road segment, D1 represents the ending point of the current road segment. Perpendicular lines are drawn from the starting point B1 and the ending point D1 of the current road segment respectively and intersect at point O1. Connect point O1 with the point C1 with the maximum curvature of the current road segment, and this line is used as the curvature radius of the current road segment.

[0041] Based on the ratio of the length of the current road segment to the curvature radius of the current road segment, the curvature parameter of the current road segment is determined. The curvature parameter is used to characterize the degree of bending of the road segment. When the curvature parameter of the current road segment is less than or equal to the preset curvature parameter threshold, it can be determined that the degree of bending of the current road segment is relatively small; when the curvature parameter of the current road segment is greater than the preset curvature parameter threshold, it can be determined that the degree of bending of the current road segment is relatively large.

[0042] Therefore, by comparing the curvature parameter of the current road segment with the preset curvature parameter threshold and determining whether the current road segment restricts whistling, it can be determined whether the vehicle meets the preset whistling condition.

[0043] Exemplarily, if the curvature parameter of the current road segment is greater than the preset curvature parameter threshold and it is determined that the current road segment does not restrict whistling, it is determined that the vehicle meets the preset whistling condition; otherwise, it is determined that the vehicle does not meet the preset whistling condition.

[0044] In some embodiments, matching the target whistling frequency, target whistling volume, and target whistling duration of the vehicle according to the road information of the current road segment and the vehicle speed information includes: determining the curvature radius and the length of the current road segment according to the road information of the current road segment; determining the average vehicle speed of the current road segment according to the vehicle speed information; determining the curvature parameter of the current road segment based on the ratio of the length of the current road segment to the curvature radius of the current road segment; and determining the target whistling frequency, target whistling volume, and target whistling duration according to the average vehicle speed of the current road segment and the curvature parameter of the current road segment.

[0045] Specifically, the process of determining the curvature parameter of the current road segment according to the road information of the current road segment has been described in detail in the above embodiments and will not be elaborated here. When the vehicle is driving on the road segment between the starting point of the current road segment and the point with the maximum curvature of the current road segment, the vehicle speed information can be obtained in real time through a speed sensor. For example, the vehicle speed sequence from the starting point of the current road segment to the current position of the vehicle can be collected by the speed sensor, and the average vehicle speed is calculated according to the vehicle speed sequence.

[0046] The average vehicle speed of the current road section and the curvature parameter of the current road section can be input into a preset formula to output a target honking frequency, a target honking volume, and a target honking duration. Exemplarily, the average vehicle speed of the current road section and the curvature parameter of the current road section are input into a preset target honking frequency calculation formula to output the target honking frequency of the vehicle; the average vehicle speed of the current road section and the curvature parameter of the current road section can be input into a preset target honking volume calculation formula to output the target honking volume of the vehicle; the average vehicle speed of the current road section and the curvature parameter of the current road section can be input into a preset target honking duration calculation formula to output the target honking duration of the vehicle.

[0047] The target honking frequency can also be determined by querying a multi-dimensional relationship mapping table between the average vehicle speed and the curvature parameter and the target honking frequency, where the multi-dimensional relationship mapping table includes multiple combinations of the average vehicle speed and the curvature parameter and the corresponding target honking frequencies; the target honking volume can be determined by querying a multi-dimensional relationship mapping table between the average vehicle speed and the curvature parameter and the target honking volume, where the multi-dimensional relationship mapping table includes multiple combinations of the average vehicle speed and the curvature parameter and the corresponding target honking volumes; the target honking duration can be determined by querying a multi-dimensional relationship mapping table between the average vehicle speed and the curvature parameter and the target honking duration, where the multi-dimensional relationship mapping table includes multiple combinations of the average vehicle speed and the curvature parameter and the corresponding target honking durations.

[0048] In some embodiments, determining the target honking frequency, the target honking volume, and the target honking duration according to the average vehicle speed of the current road section and the curvature parameter of the current road section includes: determining a first product based on the product of the average vehicle speed of the current road section and a first coefficient; determining a second product based on the product of the curvature parameter of the current road section and a second coefficient; determining the target honking frequency based on the sum value of the first product and the second product; determining a third product based on the product of the average vehicle speed of the current road section and a third coefficient; determining a fourth product based on the product of the curvature parameter of the current road section and a fourth coefficient; determining the target honking volume based on the sum value of the third product and the fourth product; determining a fifth product based on the product of the average vehicle speed of the current road section and a fifth coefficient; determining a sixth product based on the product of the curvature parameter of the current road section and a sixth coefficient; determining the target honking duration based on the sum value of the fifth product and the sixth product.

[0049] Exemplarily, the target honking frequency can be calculated by the following formula:

[0050] F = k1×v + k2×γ

[0051] Wherein, F represents the target horn frequency; k1 represents the first coefficient; v represents the average vehicle speed on the current road section; k2 represents the second coefficient; γ represents the curvature parameter of the current road section. The first coefficient and the second coefficient can be calibrated according to the actual situation, and no specific limitation is made here.

[0052] The target horn volume can be calculated by the following formula:

[0053] dB = k3×v + k4×γ

[0054] Wherein, dB represents the target horn volume; k3 represents the third coefficient; v represents the average vehicle speed on the current road section; k4 represents the fourth coefficient; γ represents the curvature parameter of the current road section. The third coefficient and the fourth coefficient can be calibrated according to the actual situation, and no specific limitation is made here.

[0055] The target horn duration can be calculated by the following formula:

[0056] T = k5×v + k6×γ

[0057] Wherein, T represents the target horn duration; k5 represents the fifth coefficient; v represents the average vehicle speed on the current road section; k6 represents the sixth coefficient; γ represents the curvature parameter of the current road section. The fifth coefficient and the sixth coefficient can be calibrated according to the actual situation, and no specific limitation is made here.

[0058] In some embodiments, the above method further includes: determining the width of the current road section according to the road information of the current road section; when the width of the current road section is less than or equal to a preset road section width threshold, increasing the target horn frequency by a preset frequency, increasing the target horn volume by a preset volume, and increasing the target horn duration by a preset duration. The preset road section width threshold can be calibrated according to the actual situation, and no specific limitation is made here.

[0059] Specifically, when the vehicle is driving on a narrow curve, the probability of an accident will further increase. Therefore, the width of the current road section can be compared with the preset road section width threshold to determine whether the current road section is a narrow road, and when it is determined that the current road section is a narrow road, the target horn frequency, the target horn volume, and the target horn duration can be further increased to improve the driving safety of the vehicle.

[0060] Exemplarily, if the width of the current road segment is less than or equal to the preset road segment width threshold, it is determined that the current road segment is a narrow road, and the target honking frequency is increased by a preset frequency, the target honking volume is increased by a preset volume, and the target honking duration is increased by a preset duration; otherwise, there is no need to increase the target honking frequency, the target honking volume, and the target honking duration. Among them, the preset frequency can be determined by looking up a two-dimensional relationship mapping table between the road segment width and the preset frequency, and this two-dimensional relationship mapping table includes multiple road segment widths and the preset frequencies corresponding to each road segment width; the preset volume can be determined by looking up a two-dimensional relationship mapping table between the road segment width and the preset volume, and this two-dimensional relationship mapping table includes multiple road segment widths and the preset volumes corresponding to each road segment width; the preset duration can be determined by looking up a two-dimensional relationship mapping table between the road segment width and the preset duration, and this two-dimensional relationship mapping table includes multiple road segment widths and the preset durations corresponding to each road segment width.

[0061] In some embodiments, the above method further includes: determining the vehicle speed at the starting point of the current road segment and the vehicle speed at a preset point before entering the current road segment according to the vehicle speed information; in the case where the vehicle speed at the preset point before entering the current road segment is greater than the preset speed threshold and the preset honking condition is satisfied, determining the honking volume and the honking duration at the starting point of the current road segment according to the vehicle speed at the starting point of the current road segment; when the vehicle is at the starting point of the current road segment, controlling the vehicle to honk according to the honking volume at the starting point of the current road segment, and / or the honking duration at the starting point of the current road segment. Among them, the preset speed threshold can be determined according to the actual situation and is not specifically limited here.

[0062] Specifically, in the case where it is determined that the vehicle meets the preset honking condition according to the road information of the current road segment, when the vehicle reaches the preset point before entering the current road segment, the vehicle speed information collected by the speed sensor is used to determine the vehicle speed at the preset point before entering the current road segment, and the vehicle speed at the preset point before entering the current road segment is compared with the preset speed threshold to judge the magnitude of the vehicle speed at the preset point before entering the current road segment. For example, if the vehicle speed at the preset point before entering the current road segment is greater than the preset speed threshold, it is determined that the vehicle speed at the preset point before entering the current road segment is relatively large. At this time, the vehicle can be controlled to honk at the starting point of the current road segment based on the honking volume at the starting point of the current road segment, or the honking duration at the starting point of the current road segment, or the honking volume and the honking duration at the starting point of the current road segment to prompt the driver to slow down. In this way, the driving safety can be further improved.

[0063] Among them, the honking volume and honking duration at the starting point of the current road section can be determined according to the vehicle speed at the starting point of the current road section. For example, the honking volume at the starting point of the current road section can be determined by querying the two-dimensional relationship mapping table between the vehicle speed at the starting point of the road section and the honking volume at the starting point of the road section, where the two-dimensional relationship mapping table includes the vehicle speeds of multiple starting points of the road section and the honking volumes at the starting points of the road sections corresponding to the vehicle speeds of each starting point of the road section; the honking duration at the starting point of the current road section can be determined by querying the two-dimensional relationship mapping table between the vehicle speed at the starting point of the road section and the honking duration at the starting point of the road section, where the two-dimensional relationship mapping table includes the vehicle speeds of multiple starting points of the road section and the honking durations at the starting points of the road sections corresponding to the vehicle speeds of each starting point of the road section.

[0064] In some embodiments, the above method further includes: obtaining road information of the current path; determining the road type of each road section in the current path according to the road information of the current path; determining the bend factor of each road section according to the road type of each road section; determining the total bend factor based on the sum value of the bend factors of each road section; and controlling the vehicle to issue a reminder for turning on the automatic honking function when the total bend factor is greater than a preset bend factor threshold. Among them, the preset bend factor threshold can be calibrated according to the actual situation and is not specifically limited here.

[0065] Specifically, the vehicle can use the navigation system to plan the current path of the vehicle, and at the same time, the navigation system can also obtain the road information of the current path, such as obtaining the coordinates of each path point in the current path. The road type of each road section in the current path can be determined according to the coordinates of each path point in the current path. Among them, referring to Figure 3 , the road types include straight road sections, curved road sections, right-angle curved road sections, and circular road sections. For a curved road section, it can be further determined whether the curved road section is a gentle curve section or a sharp curve section according to the curvature parameter of the road section. For example, if the curvature parameter of the road section is greater than or equal to the first preset curvature parameter threshold and less than the second preset curvature parameter threshold, it is determined that the road section is a gentle curve section; if the curvature parameter of the road section is greater than or equal to the second preset curvature parameter threshold, it is determined that the road section is a sharp curve section. Among them, the first preset curvature parameter threshold and the second preset curvature parameter threshold can be calibrated according to the actual situation and are not specifically limited here. The determination process of the curvature parameter of the road section has been described in detail in the above embodiments and will not be elaborated here.

[0066] The bend factor of each road segment can be determined by looking up a two-dimensional relationship mapping table between road types and bend factors, where the two-dimensional relationship mapping table includes multiple road types and the corresponding bend factors for each road type. For example, the bend factor corresponding to a gentle bend road segment is 1, the bend factor corresponding to a sharp bend road segment is 2, the bend factor corresponding to a right-angle bend road segment is 2, and the bend factor corresponding to a circular road segment is 3. It should be noted that the bend factor of each road segment is used to characterize the complexity of the road segment. The higher the bend factor, the higher the complexity of the road segment, that is, the bendier the road.

[0067] In the case where the bend road segment is a narrow road, the probability of an accident will further increase, so the bend factor will also increase accordingly. For example, the bend factor increases by 1 for every consecutive 100 meters of narrow road. That is to say, the bend factor corresponding to a 100-meter narrow gentle bend road segment is 2, the bend factor corresponding to a 200-meter narrow gentle bend road segment is 3, the bend factor corresponding to a 100-meter narrow sharp bend road segment is 3, the bend factor corresponding to a 100-meter narrow right-angle bend road segment is 3, and the bend factor corresponding to a 100-meter narrow circular road segment is 4.

[0068] Due to the problem of slope during driving, the view downhill is often better than that uphill. The problem of accidents often lies in the fact that vehicles going uphill drive on the wrong side when passing through a bend. Therefore, for uphill road segments, the bend factor is further increased, for example, doubling the original bend factor. That is to say, the bend factor corresponding to a gentle bend uphill road segment is 2, the bend factor corresponding to a 100-meter narrow gentle bend uphill road segment is 4, the bend factor corresponding to a 200-meter narrow gentle bend uphill road segment is 6, and so on, which will not be elaborated here.

[0069] The current path includes multiple road segments. Add up the bend factors of each road segment to determine the total bend factor. Exemplarily, assume the current path is a 300-meter uphill narrow road, and there are 4 gentle bend road segments and 2 sharp bend road segments. Then its bend factor is as follows: the bend factor for a 300-meter narrow road is 3, the bend factor for a gentle bend is 4, the bend factor for a sharp bend is 4. Since it is uphill, the corresponding bend factor is multiplied by 2. The total bend factor for this road segment is 22.

[0070] The total bend factor is used to characterize the complexity of the current path. The larger the total bend factor, the higher the complexity of the current path. Therefore, when the total bend factor is relatively high, for example, when the total bend factor is greater than the preset bend factor threshold, the vehicle will issue a reminder to turn on the automatic bend whistle function, such as prompting on the vehicle terminal device screen "There are many bends in the previous path. It is recommended to turn on the automatic bend whistle function" to remind the user to turn on the automatic bend whistle function.

[0071] In some embodiments, the above method further includes: constructing a training set based on the road information of the section where the automatic horn function is turned on, as well as the vehicle speed information, horn frequency, horn volume, and horn duration when the vehicle is driving on this section; training a preset horn model using the training set to obtain a training result; obtaining the preset horn model when the training result reaches a preset convergence condition; and inputting the road information and vehicle speed information of the current section into the preset horn model to determine at least one of the target horn frequency, target horn volume, and target horn duration.

[0072] Specifically, receive the path where the user turns on the automatic horn, the vehicle speed information when driving on this path, as well as the corresponding horn frequency, horn volume, and horn duration, and construct a data set. After cleaning the data set to remove outliers and noise data, divide the data into a training set and a test set. Usually, the ratio of the training set to the test set is 8:2 or 7:3.

[0073] Select a suitable machine learning model or deep learning model as the preset horn model. For example, a model based on the Transformer architecture can be used. This model can process sequence data and is suitable for processing data with time series characteristics such as road information and vehicle driving information.

[0074] During the process of training the preset horn model using the training set, the model will learn the relationship between the road information, vehicle speed information, and horn frequency, horn volume, and horn duration. Define a loss function, such as the mean squared error loss function, to measure the difference between the model's predicted value and the actual value. Use an optimization algorithm (such as the Adam optimizer) to update the model parameters to minimize the loss function.

[0075] After each training cycle, calculate the loss value on the training set and record it to observe the training process and convergence of the model. Evaluate the trained model on the test set and use evaluation metrics (such as accuracy, recall, etc.) to check the performance of the model. Optimize the model according to the evaluation results, such as adjusting the model structure, parameters of the optimization algorithm, etc., to improve the performance of the model. If the performance of the model on the test set is not satisfactory, it can return to the data collection stage, collect more data or perform further processing and analysis on the data, and then retrain the model.

[0076] When the training result reaches the preset convergence condition, that is, the loss values of the model on the training set and the test set tend to be stable and meet certain performance index requirements, the preset horn model is obtained.

[0077] In the application stage of the preset horn model, the road information and vehicle speed information of the current road section are input into the preset horn model. The model will output at least one of the target horn frequency, target horn volume, and target horn duration according to the previously learned knowledge, so as to realize the intelligent control of the automatic horn function of the vehicle in curves, improve driving safety and comfort, and enhance the user experience.

[0078] As a specific example, referring to Figure 4 , the vehicle horn framework 300 includes: EDC (Electronic Control Unit) 310, VIU (Vehicle Interface Unit) 320, AI (Artificial Intelligence) large model 330, and vehicle horn 340.

[0079] Among them, the electronic control unit (EDC) 310 is used to receive the road information of the current path output by the navigation system, determine the road type of each road section in the current path according to the road information of the current path, calculate the total curve factor according to the road type, remind the user to turn on the curve horn function according to the total curve factor, and send the horn frequency, horn volume, and horn duration to the vehicle interface unit (VIU) 320 at the place where horn is needed, and request the vehicle interface unit (VIU) 320 to perform the horn operation.

[0080] The vehicle interface unit (VIU) 320 is used to receive the horn request from the electronic control unit (EDC) 310 and issue the horn request command to the vehicle horn.

[0081] The AI large model 330 is used to receive the road information of the road section where the automatic curve horn function is turned on from the electronic control unit (EDC) 310, as well as the vehicle speed information, horn frequency, horn volume, and horn duration when the vehicle is driving on this road section, train the above data, and when the received data and the training results reach a certain level, the training results will be pushed to the user. The user can decide whether to turn on the AI automatic horn operation by himself. If the user turns on the AI automatic horn function and subsequently meets the automatic curve horn condition, it will automatically sound the horn without popping up a window to remind the user to turn on this function, enhancing the user experience.

[0082] The vehicle horn 340 is used to sound the horn based on the horn frequency, horn volume, and horn duration.

[0083] As a specific example, referring to Figure 5 , the vehicle horn method may include the following steps:

[0084] S201, the vehicle starts navigation and drives.

[0085] S202, the electronic control unit obtains the road information of the current navigation path.

[0086] S203, calculate the total bend factor of the current path.

[0087] S204, determine whether the total bend factor is greater than the preset bend factor threshold. If so, execute S205.

[0088] S205, prompt on the vehicle terminal device screen "There are many bends in the previous path. It is recommended to turn on the automatic horn function for bends" to remind the user to turn on the automatic horn function for bends.

[0089] S206, determine whether the user has turned on the automatic horn function for bends. If so, execute S208; otherwise, execute S207.

[0090] S207, no reminder to turn on the automatic horn function for bends will be issued for this navigation path.

[0091] S208, calculate the curvature parameter of the current road section.

[0092] S209, determine whether the curvature parameter of the current road section is greater than the preset curvature parameter threshold and determine whether the current road section is a honkable road section. If so, execute S211; otherwise, execute S210.

[0093] S210, do not send a honk request to the vehicle interface unit.

[0094] S211, send a honk request to the VIU according to the curvature parameter of the current road section and the average vehicle speed.

[0095] S212, the vehicle interface unit controls the horn to honk, and the control includes at least one of the honk frequency, honk volume, and honk duration.

[0096] It should be noted that if the user navigates to a destination during driving, there is a soft switch on the EDC screen to turn on the automatic horn function for curves. If the user actively turns on this button, the EDC will identify the curvature of the road on the navigation path and the section where the road is located. If it is in an urban section or a no-honking section at this time, the EDC will not issue a horn request. If it is not in an urban section or a non-no-honking section at this time, the EDC will request the VIU to honk according to the curvature of the road curve. If the user does not turn on the soft switch of the EDC, the EDC will then obtain the navigation path from the current location to the destination in real time. If there are multiple curves or narrow roads in the path from the current location and a certain distance behind, and the factor calculated in the next few kilometers is greater than the preset curve factor threshold, the EDC will pop up a window to prompt the user that "there are many curves in the previous section of the journey, it is recommended to turn on the automatic horn function for curves". If the user selects "Yes", then in the next driving path, the automatic horn for curves will be sounded at curves or narrow roads, and the number of honks and the sound of the horn need to be controlled according to the curvature of the curve. If there is a no-honking section in the driving section, the automatic horn will not be sounded; if the user selects "No", then there will be no pop-up prompt and automatic horn for curves in this section of the navigation path. In this way, the automatic horn function for curves is started in two ways: actively turning on and prompting the owner to turn on through pop-up windows in complex road conditions, providing a more convenient choice compared to the traditional method and giving users a better experience.

[0097] In addition, during the use of the automatic horn for curves by the user, the AI large model will learn the user's usage behavior. When a certain training level is reached, it will perform the function of automatically honking the horn for curves according to the user's daily behavior, so that there is no need to remind the user to select the automatic horn function for curves every time. This function will predict the travel destination according to the user's historical travel pattern and actively turn on the automatic horn function for curves (note: this function will take effect after driving for a period of time).

[0098] In summary, for the horn sounding method of the present application, when the preset horn sounding condition is satisfied, at least one of the target horn frequency, target horn volume, and target horn duration is matched according to the road information and vehicle speed information of the current road section to control the horn sounding of the vehicle. In this way, the driving safety can be effectively improved, other traffic participants can be accurately warned, complex road conditions can be adapted, and the accident risk caused by improper horn sounding can be reduced; at the same time, noise pollution can be reduced, the horn volume, frequency, and duration can be intelligently adjusted, ineffective horn sounding can be avoided, and the noise interference to the surrounding environment can be reduced; the traffic efficiency can also be improved, the traffic order can be optimized, and the interaction between autonomous driving vehicles and other traffic participants can be assisted better; the curve automatic horn sounding function is started in two ways, namely, actively opening and reminding the vehicle owner to open through a pop-up window in complex road conditions, which provides a more convenient option compared with the traditional method and the user has a better experience; by utilizing the learning ability of the current AI large model, the AI large model performs self-learning through the user's use of the curve automatic horn sounding function. If the curve automatic horn sounding condition is met subsequently, the horn will sound automatically without reminding the user to open this function through a pop-up window, enhancing the user experience.

[0099] Corresponding to the above embodiments, the present application also proposes a vehicle horn sounding device.

[0100] Referring to Figure 6 , the vehicle horn sounding device 400 includes: an acquisition module 410, a first determination module 420, a second determination module 430, and a control module 440.

[0101] Among them, the acquisition module 410 is configured to acquire the road information of the current road section and the vehicle speed information of the vehicle in response to the curve automatic horn sounding function activation instruction of the vehicle. The first determination module 420 is configured to determine whether the vehicle meets the preset horn sounding condition based on the road information of the current road section. The second determination module 430 is configured to match at least one of the target horn frequency, target horn volume, and target horn duration of the vehicle according to the road information of the current road section and the vehicle speed information when it is determined that the vehicle meets the preset horn sounding condition. The control module 440 is configured to control the vehicle to sound the horn according to the target horn frequency, target horn volume, and target horn duration when the vehicle is within the road section range between the starting point of the current road section and the point with the maximum curvature of the current road section.

[0102] According to an embodiment of the present application, the first determination module 420 is specifically configured to determine the radius of curvature of the current road section, the length of the current road section, and the horn sounding restriction situation of the current road section according to the road information of the current road section; determine the curvature parameter of the current road section based on the ratio of the length of the current road section to the radius of curvature of the current road section; and determine that the vehicle meets the preset horn sounding condition when the curvature parameter of the current road section is greater than the preset curvature parameter threshold and the current road section does not restrict horn sounding.

[0103] According to an embodiment of the present application, the second determination module 430 is specifically configured to determine the radius of curvature and the length of the current road section based on the road information of the current road section; determine the average vehicle speed of the current road section according to the vehicle speed information; determine the curvature parameter of the current road section based on the ratio of the length of the current road section to the radius of curvature of the current road section; determine the target honking frequency, the target honking volume, and the target honking duration according to the average vehicle speed of the current road section and the curvature parameter of the current road section.

[0104] According to an embodiment of the present application, the second determination module 430 is specifically configured to determine a first product based on the product of the average vehicle speed of the current road section and a first coefficient; determine a second product based on the product of the curvature parameter of the current road section and a second coefficient; determine the target honking frequency based on the sum value of the first product and the second product; determine a third product based on the product of the average vehicle speed of the current road section and a third coefficient; determine a fourth product based on the product of the curvature parameter of the current road section and a fourth coefficient; determine the target honking volume based on the sum value of the third product and the fourth product; determine a fifth product based on the product of the average vehicle speed of the current road section and a fifth coefficient; determine a sixth product based on the product of the curvature parameter of the current road section and a sixth coefficient; determine the target honking duration based on the sum value of the fifth product and the sixth product.

[0105] According to an embodiment of the present application, determine the width of the current road section according to the road information of the current road section; in the case where the width of the current road section is less than or equal to a preset road section width threshold, increase the target honking frequency by a preset frequency, increase the target honking volume by a preset volume, and increase the target honking duration by a preset duration.

[0106] According to an embodiment of the present application, determine the vehicle speed at the starting point of the current road section and the vehicle speed at a preset point before entering the current road section according to the vehicle speed information; in the case where the vehicle speed at the preset point before entering the current road section is greater than a preset speed threshold and satisfies a preset honking condition, determine the honking volume and the honking duration at the starting point of the current road section according to the vehicle speed at the starting point of the current road section; when the vehicle is at the starting point of the current road section, control the vehicle to honk according to the honking volume at the starting point of the current road section, and / or the honking duration at the starting point of the current road section.

[0107] According to an embodiment of the present application, obtain the road information of the current path; determine the road type of each road section in the current path according to the road information of the current path; determine the bend factor of each road section according to the road type of each road section; determine the total bend factor based on the sum value of the bend factors of each road section; in the case where the total bend factor is greater than a preset bend factor threshold, control the vehicle to issue a reminder for turning on the automatic honking function for bends.

[0108] According to an embodiment of the present application, a training set is constructed based on the road information of the section where the automatic horn sounding function for curves is enabled, as well as the vehicle speed information, horn sounding frequency, horn sounding volume, and horn sounding duration when the vehicle is traveling on this section; the preset horn model is trained using the training set to obtain a training result; when the training result reaches the preset convergence condition, the preset horn model is obtained; the road information and vehicle speed information of the current section are input into the preset horn model to determine at least one of the target horn sounding frequency, target horn sounding volume, and target horn sounding duration.

[0109] It should be noted that the above explanations of the embodiments and beneficial effects of the vehicle horn sounding method are also applicable to the vehicle horn sounding device of the embodiments of the present application. To avoid redundancy, no detailed elaboration will be made here.

[0110] Corresponding to the above embodiments, the present application also proposes a computer-readable storage medium.

[0111] The computer-readable storage medium of the present application stores a vehicle horn sounding program, and when the vehicle horn sounding program is executed by a processor, the foregoing vehicle horn sounding method is implemented.

[0112] It should be noted that the above explanations of the embodiments and beneficial effects of the vehicle horn sounding method are also applicable to the computer-readable storage medium of the embodiments of the present application. To avoid redundancy, no detailed elaboration will be made here.

[0113] Corresponding to the above embodiments, the present application also proposes a vehicle.

[0114] See Figure 7 As shown, the vehicle 500 of the present application includes a memory 510, a processor 520, and a vehicle horn sounding program stored on the memory 510 and executable on the processor 520. When the processor executes the vehicle horn sounding program, the foregoing vehicle horn sounding method is implemented.

[0115] It should be noted that the above explanations of the embodiments and beneficial effects of the vehicle horn sounding method are also applicable to the vehicle of the embodiments of the present application. To avoid redundancy, no detailed elaboration will be made here.

[0116] It should be noted that the logic and / or steps represented in the flowchart or described otherwise herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection part with one or more wirings (electronic device), a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0117] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0118] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0119] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of this application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0120] In this application, unless otherwise clearly defined and limited, terms such as "installed", "connected", "coupled", "fixed", etc. shall be construed in a broad sense. For example, it may be a fixed connection, a detachable connection, or integrated; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements or the interaction relationship between two elements, unless otherwise clearly limited. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0121] Although the embodiments of this application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting this application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

[0122] The above embodiments are only preferred embodiments given to fully illustrate the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or transformations made by those skilled in the art on the basis of the present invention are all within the protection scope of the present invention.

Claims

1. A vehicle horn method, characterized in that: The method comprises: In response to a command to start an automatic horn function on a curve of the vehicle, obtaining road information of a current road section and vehicle speed information of the vehicle; Determining whether the vehicle meets a preset horn condition based on the road information of the current road section; When it is determined that the vehicle satisfies the preset honking condition, matching at least one of a target honking frequency, a target honking volume, and a target honking duration of the vehicle according to the road information of the current road section and the vehicle speed information; When the vehicle is within the range of a road section between a starting point of the current road section and a point with a maximum curvature of the current road section, the vehicle is controlled to honk according to the target honking frequency, the target honking volume and the target honking duration.

2. The vehicle horn method according to claim 1, characterized in that: Determining whether the vehicle meets a preset horn condition based on the road information of the current road section includes: Determining the curvature radius of the current road section, the length of the current road section, and the horn-honking restriction of the current road section according to the road information of the current road section; Determining a curvature parameter of the current road section based on a ratio of the length of the current road section to the curvature radius of the current road section; When the curvature parameter of the current road section is greater than a preset curvature parameter threshold and honking is not restricted on the current road section, it is determined that the vehicle meets the preset honking condition.

3. The vehicle horn method according to claim 1, characterized in that: Matching a target honking frequency, a target honking volume, and a target honking duration of the vehicle according to the road information of the current road section and the vehicle speed information includes: Determine the curvature radius of the current road section and the length of the current road section according to the road information of the current road section; Determine the average speed of vehicles on the current road section according to the vehicle speed information; Determining a curvature parameter of the current road section based on a ratio of the length of the current road section to the curvature radius of the current road section; The target honking frequency, the target honking volume and the target honking duration are determined according to the average vehicle speed of the current road section and the curvature parameter of the current road section.

4. The vehicle horn honking method according to claim 3, characterized in that: Determining the target honking frequency, the target honking volume, and the target honking duration according to the average speed of vehicles on the current road section and the curvature parameter of the current road section includes: Determining a first product based on the product of the average speed of the vehicles on the current road section and the first coefficient; Determining a second product based on the product of the curvature parameter of the current road section and the second coefficient; determining the target whistle frequency based on the sum of the first product and the second product; Determining a third product based on the product of the average vehicle speed of the current road section and a third coefficient; Determining a fourth product based on the product of the curvature parameter of the current road section and a fourth coefficient; determining the target whistle volume based on the sum of the third product and the fourth product; Determining a fifth product based on the product of the average speed of the vehicles on the current road section and a fifth coefficient; Determining a sixth product based on the product of the curvature parameter of the current road section and the sixth coefficient; The target whistle duration is determined based on the sum of the fifth product and the sixth product.

5. The vehicle horn method according to claim 3 or 4, characterized in that: The method further comprises: Determining the width of the current road section according to the road information of the current road section; When the width of the current road section is less than or equal to a preset road section width threshold, the target whistle frequency is increased by a preset frequency, the target whistle volume is increased by a preset volume, and the target whistle duration is increased by a preset duration.

6. The vehicle horn honking method according to claim 1, characterized in that: The method further comprises: Determine the vehicle speed at the starting point of the current road section and the vehicle speed at a preset point before entering the current road section according to the vehicle speed information; When the vehicle speed at the preset point before entering the current road section is greater than the preset speed threshold and meets the preset honking condition, determine the honking volume and honking duration at the starting point of the current road section according to the vehicle speed at the starting point of the current road section; When the vehicle is at the starting point of the current road section, the vehicle is controlled to honk according to the horn volume at the starting point of the current road section and / or the horn duration at the starting point of the current road section.

7. The vehicle horn honking method according to claim 1, characterized in that: The method further comprises: Get the road information of the current path; Determine the road type of each road section in the current path according to the road information of the current path; Determining a curve factor of each of the road sections according to the road type of each of the road sections; Determining a total curve factor based on the sum of the curve factors of each of the road sections; When the total curve factor is greater than a preset curve factor threshold, the vehicle is controlled to issue a reminder to turn on the automatic horn function on the curve.

8. The vehicle horn honking method according to claim 1, characterized in that: The method further comprises: A training set is constructed based on the road information of the road section where the automatic horn function is enabled, as well as the vehicle speed information, horn frequency, horn volume, and horn duration of the vehicle when driving on the road section; Using the training set to train a preset whistle model to obtain a training result; When the training result reaches a preset convergence condition, obtaining the preset whistle model; The road information of the current road section and the vehicle speed information are input into the preset honking model to determine at least one of the target honking frequency, the target honking volume and the target honking duration.

9. A vehicle horn device, characterized in that: The device comprises: an acquisition module, for acquiring road information of a current road section and vehicle speed information of the vehicle in response to an instruction to start the automatic horn function on a curve of the vehicle; A first determination module, configured to determine whether the vehicle meets a preset horn condition based on the road information of the current road section; A second determination module is used to match at least one of a target honking frequency, a target honking volume, and a target honking duration of the vehicle according to the road information of the current road section and the vehicle speed information when it is determined that the vehicle meets the preset honking condition; The control module is used to control the vehicle to honk according to the target honking frequency, the target honking volume and the target honking duration when the vehicle is within the section range between the starting point of the current section and the point with the maximum curvature of the current section.

10. A vehicle, characterized in that: The invention comprises a memory, a processor and a vehicle horn program stored in the memory and executable on the processor. When the processor executes the vehicle horn program, the vehicle horn method according to any one of claims 1 to 7 is implemented.

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