Method for intelligently controlling loudspeaker based on unmanned driving

Abstract

The invention discloses a method for intelligently controlling a horn based on unmanned driving, which comprises the following steps of: S1, judging whether initialization is successful or not, and if so, entering a step S2; otherwise, giving an alarm prompt; s2, data acquisition; s3, deep learning data processing is carried out based on the collected data; and S4, outputting a corresponding result according to whether whistling is needed or not currently. According to the invention, the disadvantage that the use environment of the traditional unmanned vehicle is single is solved, the state and use of the horn can be intelligently adjusted by judging the current driving state of the vehicle and the current environment state of the vehicle, the driving safety and intelligence are improved, and a safer, more efficient and more humanized traffic environment is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile electrical control methods, and more particularly to a method for intelligently controlling a horn based on unmanned driving. Background Art

[0002] Traditional driverless vehicles do not have horns or only have one horn tone, and cannot adapt to the needs of various scenarios. Summary of the invention

[0003] The purpose of the present invention is to provide a method for intelligently controlling a horn based on unmanned driving, in order to solve the technical problems existing in the background technology. In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0004] A method for intelligently controlling a horn based on unmanned driving comprises the following steps:

[0005] S1: Determine whether the initialization is successful, if so, proceed to step S2; otherwise, issue an alarm;

[0006] S2: Data collection;

[0007] S3: Perform deep learning data processing based on the collected data;

[0008] S4: Output corresponding results according to whether the whistle needs to be sounded currently.

[0009] In some embodiments, the S2: data collection includes: collecting vehicle density, vehicle speed, location information, no honking signs, number of pedestrians and horn status.

[0010] In some embodiments, the S3: performing deep learning data processing based on the collected data includes:

[0011] Determine the distance between the front and rear vehicles. If the current distance between the rear vehicles exceeds the preset distance, the vehicle is located in the suburbs or the wild and the ambient noise is high, the air horn will be switched to the state intelligently.

[0012] If the distance to the vehicle behind is within the preset distance and there are pedestrians or houses, the horn will be switched to the electric horn mode and the volume and frequency will be adjusted appropriately.

[0013] When there is an emergency around, it intelligently switches to the voice speaker state, issues an alarm "Danger, please pay attention" message to the surroundings, and transmits the information back to the remote control end for remote takeover. The control personnel issues a reminder to the nearby people through the voice speaker.

[0014] In some embodiments, the S4: outputting corresponding results according to whether there is a current need to honk the horn includes: when there is a need to use the horn, executing according to the current output values ​​of the horn type, horn volume, and horn frequency, otherwise not executing.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] The present invention solves the drawback of the single use environment of traditional unmanned vehicles. It can intelligently adjust the horn status and use by judging the current driving status of the vehicle and the current environmental status of the vehicle, thereby improving driving safety and intelligence and achieving a safer, more efficient and more humane traffic environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 :Control principle diagram

[0018] Figure 2 : Control Flow Diagram DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below in conjunction with the drawings in the preferred embodiments of the present application. In the drawings, the same or similar reference numerals throughout represent the same or similar parts or parts with the same or similar functions. The described embodiments are part of the embodiments of the present application, not all of the embodiments. The embodiments described below with reference to the drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limitations on the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0020] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0021] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, or it can be an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0022] In the description of the present application, it should be understood that the terms "upper", "lower", "front", "back", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are orientations or positional relationships based on the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0023] In addition, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or display that includes a series of steps or elements is not necessarily limited to those steps or elements explicitly listed but may include other steps or elements not explicitly listed or inherent to such process, method, product, or display.

[0024] The following will be combined Figure 1 , a method for intelligently controlling a horn based on unmanned driving involved in an embodiment of the present application is described in detail. It is worth noting that the following embodiments are only used to explain the present application and do not constitute a limitation on the present application.

[0025] Embodiment 1:

[0026] A method for intelligently controlling a horn based on unmanned driving comprises the following steps:

[0027] S1: Determine whether the initialization is successful, if so, proceed to step S2; otherwise, issue an alarm;

[0028] S2: Data collection; data collection includes: collecting vehicle density, vehicle speed, location information, no honking signs, number of pedestrians and horn status.

[0029] S3: Perform deep learning data processing based on the collected data;

[0030] Determine the distance between the front and rear vehicles. If the current distance between the rear vehicles exceeds the preset distance, the vehicle is located in the suburbs or the wild and the ambient noise is high, the air horn will be switched to the state intelligently.

[0031] If the distance to the vehicle behind is within the preset distance and there are pedestrians or houses, the horn will be switched to the electric horn mode and the volume and frequency will be adjusted appropriately.

[0032] When there is an emergency around, it intelligently switches to the voice speaker state, issues an alarm "Danger, please pay attention" message to the surroundings, and transmits the information back to the remote control end for remote takeover. The control personnel issues a reminder to the nearby people through the voice speaker.

[0033] S4: Output corresponding results according to whether the whistle needs to be sounded currently.

[0034] When there is a need to use the speaker, it is executed according to the current output values ​​of speaker type, speaker volume, and speaker frequency, otherwise it is not executed.

[0035] See also Figure 1The technical solution of this application uses a deep learning algorithm based on the autonomous driving domain controller to intelligently control the sound type (air horn, electric horn, vocal horn), volume, and sound frequency of the horn by collecting positioning information of high-precision maps, image data of cameras, point cloud data of lidar, vehicle speed and other information.

[0036] The control process of this application is as follows: power on to perform initialization detection of software and hardware (autonomous driving domain controller, horn), issue an alarm prompt when there is a fault, and enter normal operation if there is no fault. Then the autonomous driving domain controller collects data and obtains location information through high-precision maps (for example, cities, suburbs, and the wild. At the same time, local regulations on the use of horns can be obtained based on the location). Cameras and radars obtain information such as vehicle density, number of pedestrians, no honking signs, weather conditions, etc. in the current environment. The CAN bus network obtains vehicle speed. These data are comprehensively analyzed by the deep learning algorithm of the autonomous driving domain controller to obtain the horn type, horn volume, and horn frequency required for using the horn in the current environment. When there is a need to use the horn, it is executed according to the current output value (horn type, horn volume, horn frequency), otherwise it is not executed.

[0037] See also Figure 2 , effect example: when the distance to the rear vehicle is far, in the suburbs or the wild, and the ambient noise is large, it will intelligently switch to the air horn state to effectively remind the vehicle in front; if the distance to the surrounding vehicles is close, and there are pedestrians or residences, it will intelligently switch to the electric horn state and adjust the appropriate volume and frequency to avoid noise pollution or scaring pedestrians; when there is an emergency around, it will intelligently switch to the human voice horn state, issue alarms such as "Danger Attention" and send back information to the remote control end for remote takeover, and the control personnel can use the human voice horn to remind nearby people.

[0038] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for intelligently controlling a horn based on unmanned driving, characterized in that: The following steps are involved: S1: Determine whether the initialization is successful, if so, proceed to step S2; otherwise, issue an alarm; S2: Data collection; S3: Perform deep learning data processing based on the collected data; S4: Output corresponding results according to whether the whistle needs to be sounded currently.

2. The method for controlling a speaker based on unmanned driving according to claim 1, characterized in that: The S2: data collection includes: collecting vehicle density, vehicle speed, location information, no honking signs, number of pedestrians and horn status.

3. The method for controlling a speaker based on unmanned driving according to claim 1, characterized in that: S3: performing deep learning data processing based on the collected data includes: Determine the distance between the front and rear vehicles. If the current distance between the rear vehicles exceeds the preset distance, the vehicle is located in the suburbs or the wild and the ambient noise is high, the air horn will be switched to the state intelligently. If the distance to the vehicle behind is within the preset distance and there are pedestrians or houses, the horn will be switched to the electric horn mode and the volume and frequency will be adjusted appropriately. When there is an emergency around, it intelligently switches to the voice speaker state, issues an alarm "Danger, please pay attention" message to the surroundings, and transmits the information back to the remote control end for remote takeover. The control personnel issues a reminder to the nearby people through the voice speaker.

4. The method for controlling a speaker based on unmanned driving according to claim 1, characterized in that: S4: outputting corresponding results according to whether the horn is currently needed, including: when there is a need to use the horn, executing according to the current output values ​​of horn type, horn volume, and horn frequency, otherwise not executing.

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