Automobile tail light control system based on vision and artificial intelligence

Abstract

The invention designs an automobile tail light control system based on vision and artificial intelligence. The automobile tail light control system mainly comprises a main control module, a power module, a camera module, a driving circuit module and a user interaction module. The system collects a video stream through a vehicle body camera, and applies a pre-training model in a main control module to predict danger information, so that a taillight is controlled in time to carry out danger warning. Compared with an existing automobile tail lamp control system, the automobile tail lamp control system has the advantages that the risk of accidents caused by the fact that the automobile is too close to the automobile is effectively reduced, and the defects of the existing tail lamp control system in the aspects of reliability, practicability, responsiveness, functional diversity and information transmission are overcome.

Description

Technical Field

[0001] The invention relates to a vehicle taillight control system based on vision and artificial intelligence. Background Art

[0002] With the rapid development of artificial intelligence technology in recent years, the automotive industry has also ushered in a revolutionary change. Although the traditional car taillight control system can collect data through sensors and work based on preset rules, with the rapid increase in the number of vehicles, the traditional car taillight control system is gradually unable to adapt to the complex and changeable road traffic conditions. Therefore, in order to overcome the limitations of traditional car taillight control systems, many car manufacturers and scientific researchers have begun to integrate machine vision and artificial intelligence into car taillight control systems, realizing the use of on-board cameras, deep learning algorithms and real-time data processing technology to analyze road traffic conditions and even the driving status of the car in real time, thereby realizing intelligent adjustment of the taillights.

[0003] However, the existing automobile taillight control system still has the shortcomings of poor reliability, low practicality, limited collection and response capabilities, relatively fixed functions and modes, lack of personalization, and untimely or inaccurate information transmission. There is still room for further improvement. Summary of the invention

[0004] In view of the above-mentioned problems existing in the existing automobile taillight control systems, the purpose of the present invention is to provide an automobile taillight control system based on vision and artificial intelligence, which has a simple structural design, strong reliability, strong practicality and high scalability. The video stream is collected through the vehicle body camera, and on the one hand it is displayed on the touch screen, and on the other hand it is transmitted to the microprocessor, and the trained and deployed model is used to predict dangers. The OLED dot matrix display screen at the rear of the car is driven by the control drive circuit to display the designed pattern or words. At the same time, the touch screen, control buttons and hardware interface of the user interaction module are used to realize a relatively complete user interaction function.

[0005] To achieve the above purpose, the present invention adopts the following technical solution: The present invention provides a car taillight control system based on vision and artificial intelligence, including a main control module, a power module, a camera module, a drive circuit module and a user interaction module. The main control module mainly includes a microprocessor, the power module mainly includes a car battery, the camera module mainly includes a body camera, the drive circuit module includes a drive circuit unit and an OLED dot matrix display screen at the rear of the car, and the user interaction module includes a touch screen, a control button and a hardware interface.

[0006] Further, specifically, the microprocessor can drive the body camera to collect video of the environment around the body, and after prediction by the trained model, control the driving circuit unit, and then control the OLED dot matrix display screen at the rear of the car to display a hazard warning. The car battery powers the entire control system. The body camera is used to collect environmental video around the vehicle, and the driving circuit unit is used to drive the OLED dot matrix display screen at the rear of the car. The OLED dot matrix display screen at the rear of the car is used to display a hazard warning. The touch screen is used to display various information, images and control interfaces to facilitate driver operation and interaction. The control buttons can be used to perform some specific functions. The hardware interface can connect external devices to achieve data exchange and function integration.

[0007] Further, specifically, the output end of the automobile battery is connected to the power input end of the microprocessor, the output end of the vehicle body camera is connected to the input end of the microprocessor, the input end of the driving circuit unit is connected to the output end of the microprocessor, the output end is connected to the input end of the OLED dot matrix display screen at the rear of the automobile, the touch screen is connected to the input and output ends of the microprocessor, the control button is connected to the input end of the microprocessor, and the hardware interface is connected to the input end of the microprocessor.

[0008] Further, specifically, the video stream data collected by the vehicle body camera is displayed on the touch screen of the user interaction module, and the video stream data collected by the vehicle body camera is input into the microprocessor for processing and then driven by the microprocessor to drive the driving circuit unit, and the OLED dot matrix display screen at the rear of the car is controlled to display different patterns according to the degree of danger of different road conditions, so as to achieve the purpose of danger warning. This solution can use artificial intelligence to calculate and predict whether the current road condition is safe according to the surrounding environment and the actual trajectory changes of the vehicle, and realize the display on the touch screen. When danger is predicted, the OLED dot matrix display screen at the rear of the car is promptly controlled to display a dangerous pattern to warn the following vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 The figure is a flowchart of a method according to an example of the present invention.

[0010] Figure 2 It is a specific flow chart of an example of the present invention. DETAILED DESCRIPTION

[0011] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be further described in detail below in conjunction with the drawings in the present invention. It should be clear that the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0012] The present invention provides a vehicle taillight control system based on vision and artificial intelligence, which has a simple structural design, strong reliability, strong practicality and high scalability. Figure 1 As shown, the automobile taillight control system includes a main control module 10 , a power module 20 , a camera module 30 , a drive circuit module 40 and a user interaction module 50 .

[0013] Please also read Figure 2 , Figure 2 The main control module 10 mainly includes a microprocessor 100, the power module 20 mainly includes a car battery 200, the camera module 30 mainly includes a body camera 300, the drive circuit module 40 includes a drive circuit unit 400 and an OLED dot matrix display screen 401 at the rear of the car, and the user interaction module 50 includes a touch screen 500, a control button 501 and a hardware interface 502.

[0014] The video stream is collected through the vehicle body camera 300 and displayed on the touch screen 500 on the one hand, and transmitted to the microprocessor 100 on the other hand, and the danger prediction is carried out using the trained and deployed model, and the OLED dot matrix display screen 401 at the rear of the car is driven by the control driving circuit 400 to display the designed pattern or words. At the same time, the touch screen 500, control button 501 and hardware interface 502 of the user interaction module 50 are used to realize a relatively complete user interaction function.

[0015] To achieve the above object, the present invention adopts the following technical solutions:

[0016] The output end of the automobile battery 200 is connected to the power input end of the microprocessor 100, the output end of the vehicle body camera 300 is connected to the input end of the microprocessor 100, the input end of the driving circuit unit 400 is connected to the output end of the microprocessor 100, and the output end is connected to the input end of the OLED dot matrix display screen 401 at the rear of the automobile, the touch screen 500 is connected to the input end and output end of the microprocessor 100, the control button 501 is connected to the input end of the microprocessor 100, and the hardware interface 502 is connected to the input end of the microprocessor 100.

[0017] Although the traditional automobile taillight control system can collect data through sensors and work based on preset rules, with the rapid increase in the number of vehicles, the traditional automobile taillight control system gradually cannot adapt to the complex and changeable road traffic conditions. The microprocessor 100 can drive the body camera 300 to collect the video of the environment around the body, and after prediction by the trained model, control the driving circuit unit 400, and then control the OLED dot matrix display screen 401 at the rear of the car to display a danger warning. The car battery 200 supplies power to the entire control system. The body camera 300 is used to collect the environment video around the vehicle. The driving circuit unit 400 is used to drive the OLED dot matrix display screen 401 at the rear of the car. The OLED dot matrix display screen 401 at the rear of the car is used to display a danger warning. The touch screen 500 is used to display various information, images and control interfaces to facilitate the driver to operate and interact. The control button 501 can be used to operate some specific functions. The hardware interface 502 can be connected to external devices to achieve data exchange and function integration.

[0018] The video stream data collected by the vehicle body camera 300 is displayed on the touch screen 500 of the user interaction module 50. The video stream data collected by the vehicle body camera 300 is input into the microprocessor 100 for processing and then driven by the microprocessor 100 to drive the driving circuit unit 400, and the OLED dot matrix display screen 401 at the rear of the vehicle is controlled to display different patterns according to the degree of danger of different road conditions, so as to achieve the purpose of danger warning. This solution can use artificial intelligence to calculate and predict whether the current road condition is safe according to the surrounding environment and the actual trajectory changes of the vehicle, and realize the display on the touch screen 500. When danger is predicted, the OLED dot matrix display screen 401 at the rear of the vehicle is controlled to display a dangerous pattern to warn the following vehicle in a timely manner.

Claims

1. A car taillight control system based on vision and artificial intelligence, characterized by: It includes a main control module, a power module, a camera module, a drive circuit module and a user interaction module, wherein: the main control module includes a microprocessor; the power module is connected to the main control module to power the entire system; the camera module includes at least one body camera, which is used to collect video data of the vehicle's surrounding environment in real time and transmit the video data to the main control module; the drive circuit module is connected to the main control module to drive the OLED dot matrix display screen located at the rear of the car to display danger warning information according to the control signal of the main control module; the user interaction module includes a touch screen, control buttons and a hardware interface, and the touch screen is used to display system status information and an operation interface.

2. The automobile taillight control system according to claim 1, characterized in that: The microprocessor analyzes the video stream collected by the vehicle body camera through a pre-trained artificial intelligence model, and generates a control signal to drive the driving circuit module according to the analysis result.

3. The automobile taillight control system according to claim 1, characterized in that: The power module includes a car battery, and the car battery distributes electric energy to the main control module, the camera module, the drive circuit module and the user interaction module through a power management circuit.

4. The automobile taillight control system according to claim 1, characterized in that: The OLED dot matrix display screen can display different patterns or text information for warning according to the degree of danger of the vehicle's surrounding environment; the control button is used to perform control operations of specific functions; The hardware interface is used to connect external devices to achieve data exchange and function expansion.

5. The automobile taillight control system according to claim 1, characterized in that: The touch screen can display the vehicle surrounding environment video stream collected by the vehicle body camera in real time, and provide visual feedback of vehicle status information and hazard warnings.

6. The automobile taillight control system according to claim 1, characterized in that: The artificial intelligence model is trained based on pre-collected vehicle driving data, and is able to identify different types of road conditions and vehicle trajectory changes, and generate corresponding danger warning signals when potential dangers are detected.

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