An automobile automatic horn control method and device and a storage medium

Abstract

The application discloses a kind of automobile automatic horn control method, computer device and storage medium, the application can realize the automatic perception driving behavior information and road condition information of car, wherein driving behavior information indicates the state of car itself, road condition information indicates the traffic state of the environment where car is located, and according to the state of car itself and the traffic state of the environment where car is located Demand, horn demand can be accurately identified, horn is executed at the appropriate time to automatically control siren, so as to assist the horn operation of driver, improve the problem that the artificial horn operation of driver exists, because it depends on personal skill level and experience and physical health state, it is difficult to standardize operation to horn, so that the horn function of car can fully play the role of reminding traffic participants, it is beneficial to reduce traffic safety risk.The application is widely applied in the field of automobile technology.

Description

Technical Field

[0001] The present invention relates to the field of automobile technology, and in particular to a method for controlling an automatic automobile horn, a computer device, and a storage medium. Background Art

[0002] A horn is installed on the car so that the car can be controlled to sound the horn to alert other vehicles or pedestrians on the road, so that other vehicles or pedestrians can pay attention to the car and take appropriate actions such as avoiding the car in time.

[0003] Currently, car horns are manually controlled by the driver, so their use depends on their individual driving skills and experience. Drivers with low driving skills or limited driving experience may fail to fully consider current traffic conditions and underestimate the risks. This can lead to improper horn use in high-risk scenarios such as nighttime driving, crossing intersections, or when traffic facilities malfunction and lack of traffic guidance are present, rendering the car's horn function ineffective. Furthermore, some drivers inevitably disobey traffic rules or have poor safety awareness, engaging in behaviors such as running red lights, driving against traffic, and "crawling." If drivers can observe or foresee such behavior, they can effectively mitigate the likelihood of accidents by honking their horn to alert them. However, such behavior is often difficult to foresee even for highly skilled and experienced drivers, making it difficult for drivers to honk their horns in a timely manner, posing a significant traffic safety risk. The driver may be careless or physically unwell, resulting in decreased observation or attention, and thus no awareness of operating the horn, or even being unable to operate the horn even if he is aware of operating the horn. Summary of the Invention

[0004] In view of the technical problems existing in current automobile horn honking technology, such as low degree of automation and high traffic safety risks, the purpose of the present invention is to provide a method for controlling automatic automobile horn honking, a computer device and a storage medium.

[0005] In one aspect, an embodiment of the present invention includes a method for controlling an automatic horn of a vehicle, the method comprising:

[0006] Detecting the driving behavior information of the vehicle;

[0007] Detecting road condition information of the vehicle's environment;

[0008] The vehicle is controlled to honk the horn according to the driving behavior information and the road condition information.

[0009] Furthermore, the detecting of the road condition information of the vehicle's environment includes:

[0010] Capture images of the vehicle's environment to obtain exterior images;

[0011] Performing target search on the image outside the vehicle to determine traffic notice information in the image outside the vehicle;

[0012] Performing semantic recognition on the traffic notice information to obtain semantic information;

[0013] The semantic information is used as the road condition information.

[0014] Furthermore, the detecting of the road condition information of the vehicle's environment includes:

[0015] Perceive the vehicle's environment and obtain the location information of non-visual targets; the non-visual targets are targets outside the vehicle's visual range;

[0016] The location information of the non-visual target is used as the road condition information.

[0017] Furthermore, the sensing of the vehicle's environment to obtain location information of non-visual targets includes:

[0018] Call the sound sensor to detect the environment where the vehicle is located and obtain sound information;

[0019] Performing sound source analysis on the sound information to determine the location information of the sound source;

[0020] Calling the line-of-sight sensor to detect the environment in which the vehicle is located to obtain the position information of the visible target; the visible target is the target within the visual range of the vehicle;

[0021] The position information of the non-visual target is determined according to the position information of the sound source and the position information of the visible target.

[0022] Furthermore, determining the position information of the non-visual target based on the position information of the sound source and the position information of the visible target includes:

[0023] Matching the positions of the sound source and the visual target according to the position information of the sound source and the position information of the visual target;

[0024] The position information of the sound source that is not matched to the visual target is determined as the position information of the non-visual target.

[0025] Furthermore, controlling the vehicle to honk according to the driving behavior information and the road condition information includes:

[0026] During a driving process, the road condition information is continuously collected to obtain a road condition information time series;

[0027] Accumulating information on the road condition information time series to obtain an information accumulation value;

[0028] determining a driving concentration level based on the driving behavior information;

[0029] When the information accumulation value is greater than a first threshold and the driving concentration is less than a second threshold, the vehicle is controlled to automatically honk the horn.

[0030] Furthermore, controlling the vehicle to honk according to the driving behavior information and the road condition information includes:

[0031] During a driving process, the road condition information is continuously collected to obtain a road condition information time series;

[0032] Accumulating information on the road condition information time series to obtain an information accumulation value;

[0033] determining a driving concentration level based on the driving behavior information;

[0034] When the information accumulation value is greater than a first threshold, determining the intensity of the horn sound according to the driving concentration; the horn sound intensity is negatively correlated with the driving concentration;

[0035] The vehicle is controlled to automatically honk the horn at the horn sound intensity.

[0036] Furthermore, the accumulating information of the road condition information time series to obtain an information accumulation value includes:

[0037] quantizing each piece of traffic condition information in the traffic condition information time series;

[0038] For any piece of traffic condition information in the traffic condition information time series, a weight is determined based on the time interval between the time corresponding to the traffic condition information and the current time; wherein the weight is positively correlated with the time interval;

[0039] A weighted sum is performed based on each of the quantized road condition information and their corresponding weights to obtain the information accumulation value.

[0040] On the other hand, an embodiment of the present invention also includes a computer device, including a memory and a processor, the memory is used to store at least one program, and the processor is used to load at least one program to execute the automatic car horn control method in the embodiment.

[0041] On the other hand, an embodiment of the present invention further includes a computer-readable storage medium storing a program executable by a processor. When the program is executed by the processor, it is used to execute the method for controlling the automatic horn of a car in the embodiment.

[0042] The beneficial effects of the present invention are as follows: the automatic horn control method for a car in the embodiment can realize automatic perception of driving behavior information and road condition information by the car, wherein the driving behavior information represents the state of the car itself, and the road condition information represents the traffic state of the environment in which the car is located. According to the state of the car itself and the traffic state requirements of the environment in which the car is located, the horn can be accurately identified and the horn can be automatically controlled to perform the horn at the appropriate time, thereby assisting the driver in performing the horn operation, improving the problem of the driver's manual horn operation being difficult to perform in a standardized manner due to reliance on personal skill level, experience and physical health status, so that the car's horn function can fully play the role of reminding traffic participants, which is conducive to reducing traffic safety risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Schematic diagram of an automobile system to which the automobile automatic horn control method can be applied in the embodiments;

[0044] Figure 2 Schematic diagram of the steps of the method for controlling the automatic horn of a car in an embodiment;

[0045] Figure 3 Schematic diagram of the principles of steps S20101B-S20104B in the embodiment. DETAILED DESCRIPTION

[0046] In this embodiment, the method for controlling the automatic horn of a car can be applied to Figure 1 In the car system shown. Figure 1The automobile system includes components such as a control module, a horn, a behavior sensor, a sound sensor, and a sight distance sensor. Among them, the control module is a component with control and data processing functions; the horn is an electric horn or an air horn. When the control module outputs a driving signal to the horn, the horn is driven by a coil or driven by gas to vibrate and emit a sound, thereby honking the horn; the behavior sensor is a general term for sensors used to detect driving behavior information, which may include speed sensors, acceleration sensors, and roll sensors that can detect the overall movement of the car, and may also include sensors that can detect specific operations made by the driver when driving the car, such as steering wheel angle sensors, throttle depth sensors, brake depth sensors, etc., and may also include sensors that can detect the driver's personal status when driving the car, such as image sensors that can capture the driver's facial image for emotion recognition, heart rate sensors that can collect the driver's heart rate for emotion recognition, and gas concentration sensors that can collect the carbon dioxide concentration in the cockpit for fatigue status recognition; the sound sensor collects the sound of the car's environment, that is, the sound from the car. For sounds outside the car, the sound sensor can be in the form of an array, that is, there are multiple sound sensors, which are respectively set at positions facing various directions outside the car, so that the sound information from all directions of the car can be fully collected; the line-of-sight sensor's perception target is the car's environment, that is, vehicles, pedestrians, obstacles or traffic facilities outside the car. The line-of-sight sensor can be an ultrasonic sensor, a visible light camera, an infrared camera or a laser camera. It perceives external targets by collecting visible light from the outside, or by emitting ultrasonic, infrared, laser and other signals and collecting the returned signals. Since ultrasonic, infrared and laser signals generally propagate in a straight line, the sensing range of the line-of-sight sensor is within the line of sight and can obtain higher perception accuracy. The line-of-sight sensor can be in the form of an array, that is, there are multiple line-of-sight sensors, which are respectively set at positions facing various directions outside the car, so that the target information from all directions of the car can be fully collected.

[0047] In this embodiment, the structure is as follows Figure 1 The car that performs the method for controlling the automatic horn of a car is referred to as the "car". Specifically, each step in the method for controlling the automatic horn of a car can be performed by a control module, and the control module can call other components of the car when performing the steps. Figure 2 The method for controlling the automatic horn of a car comprises the following steps:

[0048] S1. Detect the driving behavior information of the vehicle;

[0049] S2. Detecting road conditions in the vehicle's environment;

[0050] S3. Control the vehicle to honk based on the driving behavior information and road condition information.

[0051] In step S1, the control module can use the behavior sensor to detect the vehicle's driving behavior information. The driving behavior information indicates whether the vehicle has experienced sudden acceleration or braking, and / or indicates the specific driving operations performed by the driver on the vehicle, such as acceleration, braking, and steering, and / or indicates the driver's mood and fatigue status.

[0052] In step S2, the control module can use the sound sensor and the line-of-sight sensor to sense the vehicle's external environment. The external sounds collected by the sound sensor come at least in part from traffic participants such as nearby vehicles and pedestrians, while the target information collected by the line-of-sight sensor can indicate the location and motion status of traffic participants such as nearby vehicles and pedestrians. Therefore, the information collected by both the sound sensor and the line-of-sight sensor can reflect the road conditions and thus serve as road condition information.

[0053] In step S3, the control module decides to generate and send a driving signal to the horn at a specific moment based on the driving behavior information and the road condition information. The horn emits a horn sound under the drive of the driving signal, thereby realizing automatic honking at a specific moment with parameters such as specific sound intensity; therefore, by executing steps S1-S3, the vehicle can automatically perceive the driving behavior information and road condition information, wherein the driving behavior information represents the state of the vehicle itself, and the road condition information represents the traffic state of the environment in which the vehicle is located. According to the state of the vehicle itself and the traffic state requirements of the environment in which the vehicle is located, the horn can accurately identify the honking requirement and automatically control the horn to perform the honking at the appropriate time, thereby assisting the driver in honking the horn, improving the problem of the driver's manual honking operation being difficult to standardize due to reliance on personal skill level, experience and physical health status, so that the car's honking function can fully play the role of reminding traffic participants, which is conducive to reducing traffic safety risks.

[0054] In this embodiment, when executing step S2, that is, the step of detecting the road condition information of the vehicle's environment, the following steps may be specifically performed:

[0055] S201A captures images of the vehicle's environment to obtain external images;

[0056] S202A. Target search for external images to determine traffic notice information in external images;

[0057] S203A. Perform semantic recognition on traffic notice information to obtain semantic information;

[0058] S204A. Use semantic information as road condition information.

[0059] Steps S201A-S204A are the first execution mode of step S2.

[0060] Because a component with sufficient computing power can be used as the control module, the control module can execute steps S201A-S204A in a relatively short time. Therefore, it can be assumed that the control module can complete steps S201A-S204A in a single moment. In this embodiment, steps S201A-S204A executed by the control module at time t1 are used as an example for description.

[0061] In step S201A, the control module uses the line-of-sight sensor to capture images of the vehicle's exterior environment, obtaining an exterior image. In step S202A, the control module runs an image detection algorithm, searching the exterior image obtained in step S201A for traffic signs, school bus signs, hazardous materials transport vehicle signs, warning triangles, and other traffic guidance features. The algorithm then extracts traffic signs and other objects from the exterior image and identifies the traffic information contained on the signs.

[0062] In this embodiment, the traffic notice information may be in the form of text or images, and the specific content may include information such as "school ahead," "school bus parking," "road construction," or "temporary parking due to vehicle breakdown." In step S203A, the control module runs a semantic recognition algorithm to perform semantic recognition on the traffic notice information and obtain semantic information. The semantic information may be information such as "school ahead," "school bus parking," "road construction," or "temporary parking due to vehicle breakdown" expressed in text form. In step S204A, the control module uses the semantic information obtained in step S203A as the road condition information to be obtained for executing step S2.

[0063] In this embodiment, when executing step S2, that is, the step of detecting the road condition information of the vehicle's environment, the following steps may be specifically performed:

[0064] S201B. Perceive the vehicle's environment and obtain location information of non-visual targets;

[0065] S202B. Use the location information of the non-visual target as the road condition information.

[0066] Steps S201B-S202B are a second execution method of step S2.

[0067] The non-visible targets detected in step S201B are targets outside the vehicle's visual range, such as targets that are too far away to be seen by the driver or beyond the range of the sight sensor, or targets blocked by obstacles. After detecting the non-visible targets in step S201B, the control module determines their position information (e.g., as a displacement vector relative to the vehicle, or as coordinates in a world coordinate system). In step S202B, the control module uses the semantic information obtained in step S201B as the road condition information to be obtained in step S2.

[0068] Since a component with sufficient computing power can be used as the control module, the control module can execute steps S201B-S202B in a relatively short time. Therefore, it can be assumed that the control module can complete steps S201B-S202B in a single moment. In this embodiment, steps S201B-S202B executed by the control module at time t1 are used as an example for description.

[0069] In this embodiment, when executing step S201B, that is, sensing the environment in which the vehicle is located and obtaining the location information of the non-visual target, the following steps may be specifically performed:

[0070] S20101B calls the sound sensor to detect the vehicle's environment and obtain sound information;

[0071] S20102B performs sound source analysis on the sound information to determine the location of the sound source;

[0072] S20103B calls the line-of-sight sensor to detect the vehicle's environment and obtain the position information of the visible target;

[0073] S20104B. Determine the position information of the non-visual target based on the position information of the sound source and the position information of the visual target.

[0074] The principles of steps S20101B-S20104B are as follows Figure 3 shown.

[0075] Reference Figure 3 In step S20101B, the control module uses the sound sensor to detect the vehicle's surroundings and obtain sound information. This sound information includes the ambient noise floor, as well as sounds from nearby vehicles, pedestrians (and their pets and other animals), and other types of traffic participants (including construction workers and equipment, greenery, and traffic lights). For example, the sound of the engine and tire noise of nearby vehicles, the voices and movements of pedestrians, the sounds of animals, the sounds of greenery blowing in the wind, and the sounds of operating construction equipment all constitute the sound information detected in step S20101B.

[0076] In step S20102B, the control module may first filter the sound information detected in step S20101B to remove ambient noise. Next, the control module extracts features from the sound information detected in step S20101B, using features such as vehicle soundprints, human speech soundprints, animal sounds, wind-blown tree sounds, and mechanical equipment soundprints. This decomposes the sound information detected in step S20101B into components, each of which represents sound data emitted by a traffic participant, such as a nearby vehicle, a pedestrian, construction workers and equipment, or landscaping trees. Based on features such as the intensity of each component's sound data, the control module determines the relative position of the corresponding sound source with respect to the vehicle, thereby obtaining the positional information for each sound source.

[0077] For example, Figure 3 As shown, since the sounds emitted by traffic participants have strong propagation and obstacle-circumventing capabilities, the control module can call on the sound sensor to detect the location information of more sound sources beyond visual range, including the location information of those sound sources that are blocked by obstacles from the vehicle.

[0078] In this embodiment, Figure 3 As shown, by executing steps S20101B to S20102B, multiple sound sources such as sound source 1, sound source 2, sound source 3, sound source 4, sound source 5, sound source 6 and sound source 7 and their position information can be determined.

[0079] In step S20103B, the control module uses the line-of-sight sensor to detect the vehicle's surroundings and obtain the position information of visible targets. Since the line-of-sight sensor generally only detects targets within its line of sight, targets that are too far away from the vehicle or blocked by obstacles will not be detected by the line-of-sight sensor.

[0080] In this embodiment, Figure 3 As shown, sound sources 1, 2, 3, and 5 are all within the sight range of the vehicle, and are thus identified as visible targets by the sight sensor and their position information is obtained.

[0081] In step S20104B, the control module can match the positions of the sound source with the visual target based on the position information of the sound source and the position information of the visual target. For example, sound source 1 is detected as a visual target by the line-of-sight sensor. Therefore, there will be a visual target whose position information is the same as that of sound source 1 (or whose deviation is less than a threshold), thus matching sound source 1 with a visual target. Conversely, sound sources 4, 6, and 7 are not detected by the line-of-sight sensor due to obstacles, etc. Therefore, there is no visual target whose position information is the same as that of sound source 4, 6, or 7 (or whose deviation is less than a threshold). Therefore, sound sources 4, 6, and 7 cannot be matched with visual targets. Based on this principle, sound sources 4, 6, and 7, which cannot be matched with visual targets, can be determined as non-visual targets. Taking sound source 4 as an example, the position information of sound source 4 represents its location. Therefore, the position information of sound source 4 is the position information of sound source 4, a pedestrian, as a non-visual target.

[0082] In this embodiment, by executing steps S20101B-S20104B, the beyond-visual-range detection and wide detection range characteristics of the sound sensor, as well as the high detection accuracy of the line-of-sight sensor, can be utilized to identify traffic participants near the vehicle as visible targets or non-visual targets, and obtain the location information of each visible target and non-visual target.

[0083] In this embodiment, when executing step S3, that is, controlling the vehicle to honk the horn based on the driving behavior information and the road condition information, the following steps may be specifically performed:

[0084] S301A. During a driving process, continuously collect road condition information to obtain a time series of road condition information;

[0085] S302A traffic information time series information accumulation, obtain information accumulation value;

[0086] S303A. Determine driving concentration based on driving behavior information;

[0087] S304A. When the information accumulation value is greater than the first threshold and the driving concentration is less than the second threshold, control the vehicle to automatically honk the horn.

[0088] Steps S301A-S304A are a first execution method of step S3.

[0089] In the embodiments of steps S201A-S204A and steps S20101B-S20104B, the specific process of detecting road condition information at time t1 is described respectively. Similarly, at multiple times such as time t2, time t3, time t4, etc., the road condition information can be detected in the same manner as at time t1. Therefore, when executing step S301A, multiple times such as time t1, t2, t3, t4, etc. can be set during a driving process.

[0090] Table 1

[0091]

[0092] In step S302A, the control module may perform quantization processing on each piece of traffic condition information in the traffic condition information time series shown in Table 1.

[0093] For example, for the time series of road condition information obtained by executing steps S201A-S204A in Table 1, the quantization value can be determined based on the degree to which the situation represented by the traffic notice information affects traffic safety. For example, the situations "school ahead" and "school bus stop" require a high level of attention from all traffic participants to ensure traffic safety, so the quantization value of these two road condition information can be determined to be a large 10. The situation "road construction" requires a moderate level of attention from all traffic participants to ensure traffic safety, so the quantization value of this road condition information can be determined to be a medium 5.

[0094] For example, for the road condition information time series obtained by executing steps S20101B-S20104B in Table 1, the quantization value can be determined based on the specific type of non-visible target (passing vehicles, pedestrians, construction workers and equipment, animals, greenery trees, etc.) and the distance between the non-visible target and the vehicle. For example, for non-visible targets such as pedestrians and construction workers, each traffic participant needs to pay a lot of attention to ensure traffic safety, so the base quantization value of this road condition information can be determined to be a large 10. For non-visible targets such as passing vehicles, construction equipment, or animals, each traffic participant needs to pay a moderate amount of attention to ensure traffic safety, so the base quantization value of this road condition information can be determined to be a medium 5. For non-visible targets such as greenery trees, each traffic participant needs to pay a relatively low amount of attention to ensure traffic safety, so the base quantization value of this road condition information can be determined to be a small 1. After determining the base quantization value, the distance between the non-visible target and the vehicle can also be considered, and the base quantization value can be negatively correlated (e.g., dividing the base quantization value by the distance between the non-visible target and the vehicle) to obtain the corresponding quantization value.

[0095] In this embodiment, by performing quantization processing on each piece of traffic condition information in the traffic condition information time series shown in Table 1, a time series of quantized values ​​of the traffic condition information shown in Table 2 can be obtained.

[0096] Table 2

[0097]

[0098]

[0099] In step S302A, the control module may accumulate information on the quantized road condition information time series shown in Table 2 to obtain an information accumulation value.

[0100] For example, assuming that the current time is t4, the quantized values ​​of the road condition information at t4 and the times before it (t1, t2, t3, t4) can be accumulated to obtain the information accumulation value at the current time (t4), as shown in Table 3.

[0101] Table 3

[0102]

[0103] In this embodiment, when calculating the information accumulation value, the time interval between the time corresponding to the road condition information and the current time may be considered to determine the weight, thereby performing weighted summation, as shown in Table 4.

[0104] Table 4

[0105]

[0106] In step S303A, for the driving behavior information detected at the current moment (t4 moment), it can be compared with the driving parameters (such as vehicle acceleration, throttle depth, brake depth, driver's mood, etc.) that the standard driving behavior under the current road conditions should have, calculate the deviation size, and determine the driving concentration according to the deviation size. Because the larger the deviation is, the more non-standard the driver's driving operation is, and it can be determined that the driver's driving is less focused, so in step S303A, the driving concentration is set to be negatively correlated with the deviation size, that is, the larger the deviation is, the smaller the driving concentration is. The control module can maximize the driving concentration when it is detected that the driver has actively used the whistle function (such as manually pressing the whistle button).

[0107] In step S304A, a fixed first threshold value (e.g., 50) is set to measure the size of the information accumulation value calculated by step S302A, and a fixed second threshold value is set to measure the size of the driving concentration calculated by step S303A. When the information accumulation value is greater than the first threshold value, it can be determined that the information accumulation value is too large. When the driving concentration is less than the second threshold value, it can be determined that the driving concentration is too small. Therefore, the control module can control the vehicle to automatically perform honking at the current moment (t4 moment). Specifically, the control module can generate a drive signal at the current moment (t4 moment) and send the drive signal to the horn, so that when the driver of the vehicle does not manually operate to issue an instruction (e.g., not issuing an instruction by pressing a horn button or other means), the horn emits a sound to honk.

[0108] In this embodiment, the principle of executing steps S301A-S304A is that the information accumulation value obtained in steps S301A-S302A can quantitatively represent the amount of attention that traffic participants need to pay to the road conditions in the environment where the vehicle is located in the past period of time from the current moment, and when executing step S302A, the weight of the road condition information is determined by the time interval between the moment corresponding to the road condition information and the current moment, and the information accumulation value is calculated by weighted summation, which can take into account the time accumulation effect of the risk of specific road conditions that has not been eliminated; in step S304A, when the information accumulation value is greater than the first threshold, it can be determined that the accumulated attention required by traffic participants in the past period has reached a large level; when the driving concentration is less than the second threshold, it can be determined that the driver of the vehicle is not focused enough on driving the car (specifically, it may be due to insufficient driving level or driving experience, negligence or physical health problems, etc.). At this time, executing step S304A to control the vehicle to automatically sound the horn can automatically assist the driver to sound the horn, thereby effectively reminding each traffic participant and reducing traffic safety risks.

[0109] For example, when executing steps S201A-S204A, executing steps S301A-S304A, if the information accumulation value in step S304A is greater than the first threshold, it indicates that the vehicle has detected multiple traffic signs, indicating that the environment in which the vehicle is located is a scene where the horn needs to be sounded to remind each traffic participant, so executing steps S301A-S304A can effectively deal with this scene; when executing steps S20101B-S20104B, executing steps S301A-S304A, if the information accumulation value in step S304A is greater than the first threshold, it indicates that there are multiple non-visual targets (or a small number of non-visual targets that are very close to the vehicle) in the environment in which the vehicle is located, so that the driver of the vehicle faces a greater potential risk of traffic accidents such as "ghosting", indicating that the environment in which the vehicle is located is a scene where the horn needs to be sounded to remind each traffic participant, so executing steps S301A-S304A can effectively deal with this scene.

[0110] In step S304A, when the driving concentration is greater than or equal to the second threshold, it indicates that the driver is driving the vehicle more attentively, and the control module may not automatically sound the horn, thereby reducing adverse effects such as noise caused by frequent honking.

[0111] In this embodiment, when executing step S3, that is, controlling the vehicle to honk the horn based on the driving behavior information and the road condition information, the following steps may be specifically performed:

[0112] S301B. During a driving process, continuously collect road condition information to obtain a time series of road condition information;

[0113] S302B traffic information time series information accumulation, obtain information accumulation value;

[0114] S303B. Determine driving concentration based on driving behavior information;

[0115] S304B when the information accumulation value is greater than the first threshold, according to the driving concentration to determine the intensity of the horn sound;

[0116] S305B. Control the vehicle to automatically honk the horn at a certain intensity.

[0117] Steps S301B-S305B are a second execution method of step S3.

[0118] The process and principle of steps S301B-S303B are the same as those of steps S301A-S303A.

[0119] In step S304B, if the accumulated information value is greater than the first threshold, it can be determined that the accumulated attention required of traffic participants over the past period has reached a significant level, necessitating honking to alert each traffic participant. In this case, the honking intensity is negatively correlated with the driver's concentration; that is, the lower the driver's concentration, the greater the honking intensity. In step S305B, the control module generates a drive signal based on the honking intensity determined in step S304B and transmits the drive signal to the horn, thereby driving the horn to emit a sound at the honking intensity determined in step S304B.

[0120] In this embodiment, the principle of executing steps S301B-S305B is that, similar to steps S301A-S304A, executing steps S301B-S305B can also automatically sound the horn when the attention required by traffic participants over the past period of time has reached a large level and the driver of this vehicle is not focused enough on driving the car, thereby effectively reminding each traffic participant and reducing traffic safety risks. Moreover, by executing steps S304B-S305B, the horn can also be controlled to automatically sound the horn when the driving concentration is not too low. At this time, since the driving concentration is not too low, the intensity of the horn sound is smaller than that of normal horn sounding. Such horn sounding can remind the driver of this vehicle and other traffic participants to pay more attention, while reducing the noise impact caused by the horn sound.

[0121] A computer program that executes the method for controlling the automatic horn of a car in this embodiment can be written and written into a computer device or storage medium. When the computer program is read out and run, the method for controlling the automatic horn of a car in this embodiment is executed, thereby achieving the same technical effect as the method for controlling the automatic horn of a car in the embodiment.

[0122] It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly fixed or connected to the other feature, or it may be indirectly fixed or connected to the other feature. In addition, the descriptions of up, down, left, right, etc. used in this disclosure are only relative to the relative positional relationships of the components of the present disclosure in the accompanying drawings. The singular forms of "a", "" and "the" used in this disclosure are also intended to include the plural forms, unless the context clearly indicates otherwise. In addition, unless otherwise defined, all technical and scientific terms used in this embodiment have the same meaning as those generally understood by those skilled in the art. The terms used in the specification of this embodiment are only for describing specific embodiments and are not intended to limit the invention. The term "and / or" used in this embodiment includes any combination of one or more related listed items.

[0123] It should be understood that, although the present disclosure may adopt the term first, second, third etc. to describe various elements, these elements should not be limited to these terms.These terms are only used to distinguish the elements of the same type from each other.For example, without departing from the scope of the present disclosure, the first element may also be referred to as the second element, and similarly, the second element may also be referred to as the first element.The use of any and all examples or exemplary language ("for example", "such as" etc.) provided by the present embodiment is only intended to better illustrate embodiments of the present invention, and unless otherwise required, the scope of the present invention will not be limited.

[0124] It should be appreciated that embodiments of the present invention can be implemented or practiced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The methods can be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and figures described in the specific embodiments. Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. In addition, the program can be run on a programmed application-specific integrated circuit for this purpose.

[0125] In addition, the operations of the processes described in this embodiment may be performed in any suitable order, unless otherwise indicated in this embodiment or otherwise clearly contradicted by the context. The processes described in this embodiment (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more processors, by hardware, or a combination thereof. A computer program includes multiple instructions that can be executed by one or more processors.

[0126] Furthermore, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Various aspects of the present invention can be implemented as machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, RAM, ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or portions thereof, can be transmitted over a wired or wireless network. When such media includes instructions or programs that implement the above steps in conjunction with a microprocessor or other data processor, the invention of this embodiment includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques of the present invention, the present invention also includes the computer itself.

[0127] The computer program can be applied to input data to perform the functions of the present embodiment, thereby converting the input data to generate output data that is stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on the display.

[0128] The above are merely preferred embodiments of the present invention. The present invention is not limited to the aforementioned embodiments. As long as the technical effects of the present invention are achieved by the same means, any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention. Within the scope of protection of the present invention, various modifications and variations of the technical solutions and / or implementation methods may be made.

Claims

1. A method for controlling an automatic horn of a car, characterized in that: The automobile automatic horn control method comprises: Detecting the driving behavior information of the vehicle; Detecting road condition information of the vehicle's environment; Controlling the vehicle to honk according to the driving behavior information and the road condition information; The detection of the road condition information of the vehicle's environment includes: Call the sound sensor to detect the environment where the vehicle is located and obtain sound information; Performing sound source analysis on the sound information to determine the location information of the sound source; Calling the line-of-sight sensor to detect the environment in which the vehicle is located to obtain the position information of the visible target; the visible target is the target within the visual range of the vehicle; Matching the positions of the sound source and the visual target according to the position information of the sound source and the position information of the visual target; Determining the position information of the sound source that is not matched to the visual target as the position information of the non-visual target; the non-visual target is a target outside the visual range of the vehicle; Using the position information of the non-visual target as the road condition information; The controlling the vehicle to honk the horn according to the driving behavior information and the road condition information includes: During a driving process, the road condition information is continuously collected to obtain a road condition information time series; Accumulating information on the road condition information time series to obtain an information accumulation value; determining a driving concentration level based on the driving behavior information; When the information accumulation value is greater than a first threshold, determining the intensity of the horn sound according to the driving concentration; the horn sound intensity is negatively correlated with the driving concentration; The vehicle is controlled to automatically honk the horn at the horn sound intensity.

2. The method for controlling the automatic horn of a car according to claim 1, wherein: The detection of the road condition information of the vehicle's environment includes: Capture images of the vehicle's environment to obtain exterior images; Performing target search on the image outside the vehicle to determine traffic notice information in the image outside the vehicle; Performing semantic recognition on the traffic notice information to obtain semantic information; The semantic information is used as the road condition information.

3. The method for controlling the automatic horn of a car according to claim 1, wherein: The controlling the vehicle to honk the horn according to the driving behavior information and the road condition information includes: During a driving process, the road condition information is continuously collected to obtain a road condition information time series; Accumulating information on the road condition information time series to obtain an information accumulation value; determining a driving concentration level based on the driving behavior information; When the information accumulation value is greater than a first threshold and the driving concentration is less than a second threshold, the vehicle is controlled to automatically honk the horn.

4. The method for controlling the automatic horn of a car according to any one of claims 1 to 3, characterized in that: The step of accumulating information on the time series of the road condition information to obtain an information accumulation value includes: quantizing each piece of traffic condition information in the traffic condition information time series; For any piece of traffic condition information in the traffic condition information time series, a weight is determined based on the time interval between the time corresponding to the traffic condition information and the current time; wherein the weight is positively correlated with the time interval; A weighted sum is performed based on each of the quantized road condition information and their corresponding weights to obtain the information accumulation value.

5. A computer device, characterized in that: The invention comprises a memory and a processor, wherein the memory is used to store at least one program, and the processor is used to load at least one program to execute the vehicle automatic horn control method according to any one of claims 1 to 4.

6. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to execute the automobile automatic horn control method described in any one of claims 1 to 4 when executed by the processor.

Images