Self-adaptive light change interaction method of light-emitting identifier for automobile

Abstract

The invention provides a control method of a light-emitting identification self-adaptive optical variable system for an automobile, which comprises the following steps: S1, after a user starts the light-emitting identification self-adaptive optical variable system, continuously monitoring environmental parameters by using a light sensing module; s2, carrying out data sampling and analysis once every 100ms by utilizing a central processing unit; s3, detecting ambient light change in real time by using a light sensing module, and starting ambient light adjustment when the ambient light exceeds a threshold value or a user interaction signal; s4, calculating an optimal optical parameter combination by utilizing a neural network algorithm module according to the current scene and the historical preference of the user by utilizing a central processing unit; s5, accurately controlling each LED channel through a PWM signal by using an adaptive light source module to realize a smooth transition light-variable effect; s6, continuously monitoring user feedback by using an interaction identification module, and dynamically and finely adjusting the optical parameters; step S7, realizing self-adaptive light environment adjustment; the method has the advantage that the user experience and the intelligent level of the system are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle identification technology, and specifically to an adaptive light-changing interactive method for automotive luminous identification. Background Technology

[0002] Adaptive optics, a method to improve image quality by correcting wavefront distortion in real time, was first proposed by Julius Babcock in 1953. Its core components include a wavefront sensor, deformable mirrors, and a control system, and it is primarily used in fields such as astronomical observation and laser fusion. With technological advancements, photorefractive adaptive heterodyne detection technology has gradually emerged. This technology, based on atmospheric optics principles, can be used to measure optical parameters such as atmospheric transmittance and turbulence.

[0003] However, existing technologies in the field of human-computer interaction have significant shortcomings. Traditional display systems and interaction methods have failed to effectively address the problems caused by changes in ambient light. For example, Chinese Patent 01128777.2 discloses a photorefractive adaptive heterodyne detection method, which suffers from low signal-to-noise ratio and difficulty in adjusting the optical path. In practical applications, ambient light interference leads to inaccurate interaction data, especially in mobile devices and augmented reality scenarios, where rapid changes in lighting conditions severely impact the user experience.

[0004] Current adaptive optics technologies primarily focus on specialized measurement fields. For example, while pulsed laser photorefractive detection technology can measure optical parameters along atmospheric propagation paths, it is not optimized for human-computer interaction scenarios. Although graphics processing technologies such as adaptive temporal anti-aliasing (ATAA) can solve some rendering problems, their adaptability to real-world lighting changes remains insufficient.

[0005] Especially in varying lighting environments, existing interactive systems lack the ability to perceive and adaptively adjust to the lighting environment in real time, resulting in problems such as poor visibility of displayed content, low accuracy of gesture recognition, and failure of eye tracking. These shortcomings limit the application of human-computer interaction technology in outdoor scenarios and across different lighting conditions, and there is an urgent need for an innovative method that can perceive changes in ambient light in real time and dynamically adjust interaction parameters. Summary of the Invention

[0006] In view of the above problems, the purpose of this invention is to provide an adaptive light-changing interaction method for automotive luminous signs, which can more flexibly and efficiently adapt to various complex environmental conditions, significantly improve imaging quality and user experience, and overcome the shortcomings of the prior art.

[0007] This invention provides a control method for an adaptive light-changing system for automotive luminous signs, comprising the following steps:

[0008] Step S1: After the user starts the luminous sign adaptive light-changing system, the light sensing module continuously monitors environmental parameters.

[0009] Step S2: The central processing unit performs data sampling and analysis every 100ms;

[0010] Step S3: Detect changes in ambient light in real time using the light sensing module. When the ambient light exceeds the threshold or a user interaction signal is received, start ambient light adjustment.

[0011] Step S4: The central processing unit calculates the optimal combination of light parameters based on the current scene and the user's historical preferences using a neural network algorithm module;

[0012] Step S5: Use the adaptive light source module to precisely control each LED channel through PWM signal to achieve a smooth transition of light change effect;

[0013] Step S6: Continuously monitor user feedback using the interactive recognition module and dynamically fine-tune the light parameters;

[0014] Step S7: The neural network algorithm module of the central processing unit automatically optimizes the algorithm parameters every 24 hours to achieve adaptive light environment adjustment.

[0015] As a preferred embodiment of the present invention, it further includes: step S8: human-machine interaction control mode.

[0016] Step S81: Gesture recognition interaction, using millimeter-wave radar to capture user gestures and achieve natural interactions such as waving to adjust the brightness and clenching a fist to turn on / off;

[0017] Step S82: Context-aware mode, using the light sensing module to identify user activity scenarios (reading, resting, meeting, etc.) and match preset light environment parameters;

[0018] Step S83: Synchronize biological rhythms. Use the light sensing module to sense seasonal changes and user physiological data, and use the adaptive light source module to dynamically adjust color temperature and brightness to promote the health of the human biological clock.

[0019] Step S84: Multi-user priority management. When the light sensing module detects multiple users, the central processing unit automatically allocates lighting control rights based on user identity and activity importance.

[0020] Step S85: Haptic feedback adjustment. When the capacitive touch sensor of the interactive recognition module dims the area, haptic feedback is provided through a micro vibration motor to enhance the interactive experience.

[0021] As a preferred embodiment of the present invention, it further includes: step S9: adaptive light variation control.

[0022] Step S91: Use the neural network algorithm module of the central processing unit to predict ambient light and pre-adjust the light source 0.5-2 seconds in advance to eliminate the response delay of traditional systems;

[0023] Step S92: Analyze the user's subtle adjustment habits to the light environment using an ambient light sensor array, a human infrared sensor, and a camera to establish a personalized light environment mode;

[0024] Step S93: Using the adaptive light source module, a zone-based independent control mode is adopted to control the differentiated lighting information in different locations within the space to meet the different needs of multiple people;

[0025] Step S94: Use the central processing unit to detect user attention and automatically reduce the frequency of interfering light changes when the user is focused on work.

[0026] As a preferred embodiment of the present invention, the system includes: a light sensing module, a central processing unit, an adaptive light source module, an interactive recognition module, and a wireless communication module;

[0027] The light sensing module is connected via I 2 The C interface connects to the central processing unit to transmit environmental data in real time. The light sensing module includes an ambient light sensor array, a human infrared sensor, and a camera. The ambient light sensor array is used to collect ambient light intensity information, the human infrared sensor is used to collect color temperature data and user position, and the camera is used to collect user posture information.

[0028] The central processing unit is connected to the adaptive light source module via a PWM signal line to control the brightness and color temperature of each channel LED. The central processing unit uses an ARM Cortex-M7 microcontroller, which has a built-in neural network algorithm module. The neural network algorithm module is responsible for analyzing the sensed data and generating control commands.

[0029] The adaptive light source module consists of a multi-channel LED array, which includes cool white light, warm white light and RGB full-color LEDs. The brightness can be precisely controlled from 0.1% to 100% through a PWM dimming module.

[0030] The interactive recognition module communicates with the central processing unit through the SPI interface to convert user interaction intentions into control signals. The interactive recognition module includes a capacitive touch sensor, a millimeter-wave radar, and a voice recognition unit module. The capacitive touch sensor is used to realize interactive touch recognition, the millimeter-wave radar is used to identify and detect targets around the vehicle, and the voice recognition unit module is used to receive voice commands.

[0031] The wireless communication module is connected to the central processing unit via UART to realize device status uploading and remote command reception. The wireless communication module is used to realize device interconnection and remote control. The wireless communication module supports Wi-Fi 6, Bluetooth 5.0 and Zigbee protocols.

[0032] The advantages and positive effects of this invention are:

[0033] 1. This invention enables real-time adaptive adjustment of the brightness, color, and dynamic effects of car logos / ambient lights, improving environmental adaptability.

[0034] 2. This invention achieves truly adaptive light environment adjustment through multi-sensor fusion and intelligent algorithms. At the same time, the innovative interaction method allows users to interact with the lighting system in a more natural and intuitive way, significantly improving the user experience and the level of system intelligence.

[0035] 3. This invention reduces system energy consumption and is compatible with existing vehicle architecture.

[0036] 4. This invention has the advantages of improving vehicle safety, with dynamic light effects enhancing environmental perception and reducing the risk of accidents; it also has the advantages of optimizing user experience, supporting personalized customization and scenario-based interaction; and it has the advantages of controllable cost, reusing existing vehicle sensors without the need for additional hardware. Attached Figure Description

[0037] Figure 1 This is a system architecture diagram of the present invention.

[0038] Figure 2 This is a circuit diagram of the optical sensing module of the present invention.

[0039] Figure 3 This is a circuit diagram of the central processing unit of the present invention.

[0040] Figure 4 This is a circuit diagram of the adaptive light source module of the present invention.

[0041] Figure 5 This is a circuit diagram of the interactive recognition module of the present invention.

[0042] Figure 6 This is a circuit diagram of the wireless communication module of the present invention.

[0043] Figure 7 This is a circuit diagram of the camera of the present invention.

[0044] Figure 8 This is a circuit diagram of the speech recognition module of the present invention.

[0045] Figure 9 This is a circuit diagram of the gesture recognition sensor of the present invention. Detailed Implementation

[0046] In the following description, numerous specific details are set forth for illustrative purposes and to provide a thorough understanding of one or more embodiments. However, it will be apparent that these embodiments may also be implemented without these specific details. In other instances, well-known structures and devices are shown in block diagram form for ease of description of one or more embodiments.

[0047] Example 1

[0048] This embodiment provides a control method for an adaptive light-changing system for automotive illuminated signs, comprising the following steps:

[0049] Step S1: After the user starts the luminous sign adaptive light-changing system, the light sensing module continuously monitors environmental parameters.

[0050] Step S2: The central processing unit performs data sampling and analysis every 100ms;

[0051] Step S3: Detect changes in ambient light in real time using the light sensing module. When the ambient light exceeds the threshold or a user interaction signal is received, start ambient light adjustment.

[0052] Step S4: The central processing unit calculates the optimal combination of light parameters based on the current scene and the user's historical preferences using a neural network algorithm module;

[0053] Step S5: Use the adaptive light source module to precisely control each LED channel through PWM signal to achieve a smooth transition of light change effect;

[0054] Step S6: Continuously monitor user feedback using the interactive recognition module and dynamically fine-tune the light parameters;

[0055] Step S7: The neural network algorithm module of the central processing unit automatically optimizes the algorithm parameters every 24 hours to achieve adaptive light environment adjustment.

[0056] Example 2

[0057] This embodiment presents a human-machine interaction control method for an adaptive light-changing system for automotive luminous signs.

[0058] Step S81: Gesture recognition interaction, using millimeter-wave radar to capture user gestures and achieve natural interactions such as waving to adjust the brightness and clenching a fist to turn on / off;

[0059] Step S82: Context-aware mode, using the light sensing module to identify user activity scenarios (reading, resting, meeting, etc.) and match preset light environment parameters;

[0060] Step S83: Synchronize biological rhythms. Use the light sensing module to sense seasonal changes and user physiological data, and use the adaptive light source module to dynamically adjust color temperature and brightness to promote the health of the human biological clock.

[0061] Step S84: Multi-user priority management. When the light sensing module detects multiple users, the central processing unit automatically allocates lighting control rights based on user identity and activity importance.

[0062] Step S85: Haptic feedback adjustment. When the capacitive touch sensor of the interactive recognition module dims the area, haptic feedback is provided through a micro vibration motor to enhance the interactive experience.

[0063] Example 3

[0064] This embodiment presents an adaptive light-changing control method for an adaptive light-changing system for automotive luminous signs.

[0065] Step S91: Use the neural network algorithm module of the central processing unit to predict ambient light and pre-adjust the light source 0.5-2 seconds in advance to eliminate the response delay of traditional systems;

[0066] Step S92: Analyze the user's subtle adjustment habits to the light environment using an ambient light sensor array, a human infrared sensor, and a camera to establish a personalized light environment mode;

[0067] Step S93: Using the adaptive light source module, a zone-based independent control mode is adopted to control the differentiated lighting information in different locations within the space to meet the different needs of multiple people;

[0068] Step S94: Use the central processing unit to detect user attention and automatically reduce the frequency of interfering light changes when the user is focused on work.

[0069] Example 4

[0070] An adaptive light-changing system for automotive illuminated signage according to this embodiment includes: a light sensing module, a central processing unit, an adaptive light source module, an interactive recognition module, and a wireless communication module;

[0071] The light sensing module is connected via I 2 The C interface connects to the central processing unit to transmit environmental data in real time. The light sensing module includes an ambient light sensor array, a human infrared sensor, and a camera. The ambient light sensor array is used to collect ambient light intensity information, the human infrared sensor is used to collect color temperature data and user position, and the camera is used to collect user posture information.

[0072] The central processing unit is connected to the adaptive light source module via a PWM signal line to control the brightness and color temperature of each channel LED. The central processing unit uses an ARM Cortex-M7 microcontroller, which has a built-in neural network algorithm module. The neural network algorithm module is responsible for analyzing the sensed data and generating control commands.

[0073] The adaptive light source module consists of a multi-channel LED array, which includes cool white light, warm white light and RGB full-color LEDs. The brightness can be precisely controlled from 0.1% to 100% through a PWM dimming module.

[0074] The interactive recognition module communicates with the central processing unit through the SPI interface to convert user interaction intentions into control signals. The interactive recognition module includes a capacitive touch sensor, a millimeter-wave radar, and a voice recognition unit module. The capacitive touch sensor is used to realize interactive touch recognition, the millimeter-wave radar is used to identify and detect targets around the vehicle, and the voice recognition unit module is used to receive voice commands.

[0075] The wireless communication module is connected to the central processing unit via UART to realize device status uploading and remote command reception. The wireless communication module is used to realize device interconnection and remote control. The wireless communication module supports Wi-Fi 6, Bluetooth 5.0 and Zigbee protocols.

[0076] In this embodiment, five light sensing modules are distributed, three adaptive light source modules cover the area, the central control unit is installed, and user interaction points are marked. The technical parameters include a coverage area of ​​50㎡, a response time of <200ms, and support for multiple users to use simultaneously.

[0077] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A control method for an adaptive light-changing system for automotive luminous signs, characterized in that, Includes the following steps: Step S1: After the user starts the luminous sign adaptive light-changing system, the light sensing module continuously monitors environmental parameters. Step S2: The central processing unit performs data sampling and analysis every 100ms; Step S3: Detect changes in ambient light in real time using the light sensing module. When the ambient light exceeds the threshold or a user interaction signal is received, start ambient light adjustment. Step S4: The central processing unit calculates the optimal combination of light parameters based on the current scene and the user's historical preferences using a neural network algorithm module; Step S5: Use the adaptive light source module to precisely control each LED channel through PWM signal to achieve a smooth transition of light change effect; Step S6: Continuously monitor user feedback using the interactive recognition module and dynamically fine-tune the light parameters; Step S7: The neural network algorithm module of the central processing unit automatically optimizes the algorithm parameters every 24 hours to achieve adaptive light environment adjustment.

2. The control method for an adaptive light-changing system for automotive luminous signs according to claim 1, characterized in that, It also includes: Step S8: Human-machine interaction control method, Step S81: Gesture recognition interaction, using millimeter-wave radar to capture user gestures and achieve natural interactions such as waving to adjust the brightness and clenching a fist to turn on / off; Step S82: Context-aware mode, using the light sensing module to identify the user's activity scene and match preset light environment parameters; Step S83: Synchronize biological rhythms, using the light sensing module to sense seasonal changes and user physiological data, and using the adaptive light source module to dynamically adjust color temperature and brightness; Step S84: Multi-user priority management. When the light sensing module detects multiple users, the central processing unit automatically allocates lighting control rights based on user identity and activity importance. Step S85: Haptic feedback adjustment. When the capacitive touch sensor of the interactive recognition module dims the area, haptic feedback is provided through a micro vibration motor to enhance the interactive experience.

3. The control method for an adaptive light-changing system for automotive luminous signs according to claim 1, characterized in that, It also includes: Step S9: Adaptive light variation control, Step S91: Use the neural network algorithm module of the central processing unit to predict ambient light and pre-adjust the light source 0.5-2 seconds in advance to eliminate the response delay of traditional systems; Step S92: Analyze the user's habits of adjusting the light environment using an ambient light sensor array, a human infrared sensor, and a camera to establish a personalized light environment mode; Step S93: Using the adaptive light source module, a zone-based independent control mode is adopted to control the differentiated lighting information in different locations within the space to meet the different needs of multiple people; Step S94: Use the central processing unit to detect user attention and automatically reduce the frequency of interfering light changes when the user is focused on work.

4. The control method for an adaptive light-changing system for automotive luminous signs according to claim 1, characterized in that, The system includes: a light sensing module, a central processing unit, an adaptive light source module, an interactive recognition module, and a wireless communication module; The light sensing module is connected via I 2 The C interface connects to the central processing unit to transmit environmental data in real time. The light sensing module includes an ambient light sensor array, a human infrared sensor, and a camera. The ambient light sensor array is used to collect ambient light intensity information, the human infrared sensor is used to collect color temperature data and user position, and the camera is used to collect user posture information. The central processing unit is connected to the adaptive light source module via a PWM signal line to control the brightness and color temperature of each channel LED. The central processing unit uses an ARM Cortex-M7 microcontroller, which has a built-in neural network algorithm module. The neural network algorithm module is responsible for analyzing the sensed data and generating control commands. The adaptive light source module consists of a multi-channel LED array, which includes cool white light, warm white light and RGB full-color LEDs. The brightness can be precisely controlled from 0.1% to 100% through a PWM dimming module. The interactive recognition module communicates with the central processing unit through the SPI interface to convert user interaction intentions into control signals. The interactive recognition module includes a capacitive touch sensor, a millimeter-wave radar, and a voice recognition unit module. The capacitive touch sensor is used to realize interactive touch recognition, the millimeter-wave radar is used to identify and detect targets around the vehicle, and the voice recognition unit module is used to receive voice commands. The wireless communication module is connected to the central processing unit via UART to realize device status uploading and remote command reception. The wireless communication module is used to realize device interconnection and remote control. The wireless communication module supports Wi-Fi 6, Bluetooth 5.0 and Zigbee protocols.

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