Intelligent vehicle switch control method and system with user-defined function

Abstract

The invention discloses an intelligent vehicle switch control method and system with a self-defined function, and aims to improve the driving experience of a vehicle owner through an intelligent means, a user interacts with the system through a touch screen, voice control, gesture recognition, physical buttons and other modes, and precise control over vehicle windows, seat heating, air conditioners and other equipment is achieved. Through sensor data of temperature, humidity, vehicle speed and the like, in combination with an automatic control rule and a machine learning algorithm, automatic adjustment and optimization of equipment are realized, and it is ensured that an optimal control strategy is provided under different driving modes and environment conditions. A multi-verification mechanism, data encryption, identity verification and other security measures are designed, and misoperation and data leakage are avoided. Through efficient hardware integration, intelligent control logic and safety guarantee measures, intelligent, personalized and reliable vehicle-mounted equipment control experience is provided for a vehicle owner.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control of in-vehicle switches, and in particular to an intelligent vehicle switch control method and system with customized functions. Background Art

[0002] Traditional vehicle-mounted equipment control often relies on multiple independent physical buttons and knobs, which are cumbersome and scattered in operation, easily distracting the driver's attention and increasing driving safety risks. With the improvement of the level of vehicle intelligence, how to simplify control operations and improve user experience has become an urgent problem to be solved. There are large differences in the needs of different drivers for in-vehicle equipment, and traditional vehicle-mounted control systems often cannot automatically adjust according to user preferences or real-time environmental conditions (such as temperature, humidity, vehicle speed, etc.). In modern vehicles, various vehicle-mounted equipment and systems (such as air conditioning, seat heating, windows, audio, etc.) are usually managed independently by different control units, lacking effective coordination and integration. How to achieve linkage and intelligent control between different devices to ensure the efficiency and consistency of the system is an important challenge. By integrating functions such as intelligent control, automatic adjustment, personalized settings, safety assurance, and remote updates, the present invention effectively solves these problems and improves the vehicle's intelligence level, user experience, and driving safety. Summary of the invention

[0003] A method for controlling a smart vehicle switch with a customized function comprises the following steps: S1. Requirements analysis and function definition: Identify the devices or systems that need to be controlled (such as windows, seat heating, lights, audio systems, etc.), design customized control functions, and automatically adjust the status of in-vehicle devices according to driving mode and weather conditions: automatically enable seat heating in winter and cold weather, and automatically adjust window switches according to vehicle speed and temperature; S2. Hardware preparation: Select appropriate smart switch hardware (such as touch screen, button, voice control, gesture recognition or physical switch) and connect it to the vehicle's CAN bus or other vehicle communication network, and determine the sensors (temperature sensor, humidity sensor, seat sensor, etc.) and actuators (motor, heater, dimming light, etc.) related to switch control; S3. System integration and communication: Develop intelligent control units to process data input from users or collected from sensors, perform corresponding control operations, and realize communication between intelligent switches and various systems inside the vehicle (such as seats, air conditioning, etc.) through CAN bus, LIN bus or other vehicle network protocols; S4. Rule design and control logic: Process user input (such as through touch screen, voice recognition, physical buttons or gesture control), voice control parses user voice commands and converts them into switch control commands, integrates sensor data such as temperature, humidity, vehicle speed, etc., generates the optimal control strategy based on different environmental conditions and random forest regression algorithm, and integrates the control strategy model , where Control represents the optimal control strategy, It means to find the operation that maximizes a certain objective function. is the reward at time step t: comfort, energy saving, is the discount factor, is the maximum number of time steps, intelligently adjust the control logic, for example, when the temperature inside the car is too high, the system automatically turns on the air conditioner, custom rules and scene settings: allow users to customize different scene modes (driving mode, parking mode, rest mode), and automatically adjust the vehicle's switch function in different modes, control feedback: design a control feedback mechanism to ensure that users know the current switch status (visual, sound or vibration feedback); S5. Security and stability assurance: To avoid misoperation, multiple verifications or linkage logic between physical buttons and touch interfaces are designed to ensure the security of user data and system operations, including data encryption, identity authentication and other measures; S6. User testing and feedback: Conduct multiple rounds of testing in the car to ensure the stability, response speed and smoothness of user interaction of the system. Through the actual operation feedback of users, use data analysis and clustering algorithms to analyze user usage behavior, find problems in the system and further optimize the control method and interface design according to needs; S7. Maintenance and Update: Through the OTA (Over-the-Air) function, regular updates of the control system are pushed to enhance system functions or fix problems. A remote fault diagnosis function is designed for the system to automatically detect problems and provide repair solutions.

[0004] Furthermore, a method for controlling a smart vehicle switch with a customized function is provided. In step S4, the sensor data: temperature, humidity, vehicle speed are integrated, and the optimal control strategy is generated according to different environmental conditions and the random forest regression algorithm. The specific steps are as follows; S41. Data collection and preprocessing: Collect data from sensors in the car: temperature sensor, humidity sensor, speed sensor in real time, preprocess the collected data: remove noise and missing values, process abnormal values ​​(such as data anomalies caused by sensor failure), standardize temperature, humidity, and speed data to make them comparable, and avoid the value of some features being too large or too small to affect model training; S42. Feature Engineering and Data Analysis: Select key features that affect vehicle equipment control: temperature, humidity, and vehicle speed directly affect the status of air conditioning, seat heating, and window control equipment, and construct new features based on existing data: generate a "comfort index" based on temperature and humidity, and generate an "environmental adaptability" based on vehicle speed and external temperature, and identify the impact of data features on control strategies based on statistical analysis; S43. Training control strategy model: Divide the data into training set and test set to ensure the generalization ability of the model. Use the training set to train the random forest regression model and adjust the model's hyperparameters. Use the test set to evaluate the model's performance to ensure that the model has high accuracy and stability when predicting control strategies. Generate control strategies by learning the mapping relationship from environmental data to equipment control and obtain the control strategy model. , where Control represents the optimal control strategy, It means to find the operation that maximizes a certain objective function. is the reward at time step t: comfort, energy saving, is the discount factor, is the maximum number of time steps; S44. Generate control strategy: Based on the trained model, define the control strategy generated based on the environmental data: when the temperature is higher than the threshold, whether the air conditioner needs to be turned on; When the vehicle speed reaches a certain value, whether the window switch needs to be adjusted; Depending on the humidity and the in-car environment, whether the seat heating needs to be turned on or not, the real-time sensor data is input into the trained control strategy model, which will output the corresponding control strategy: adjust the air conditioning temperature, seat heating or window status, and design a system feedback mechanism. When the generated control strategy does not achieve the expected effect, it can be adjusted and optimized through user feedback or system status data; S45. Model update and optimization: Collect feedback data through vehicle sensors, user input (such as voice or touch), and system status monitoring, regularly update the model based on new data feedback, continuously optimize the control strategy, conduct A / B testing during actual driving, verify the effects of different control strategies, and monitor the performance of the model; S46. Control strategy implementation: Integrate the generated control strategy into the vehicle control system to ensure that the control instructions output by the model can accurately interact with the vehicle actuators (such as air conditioners, motors, seat heaters, etc.), trigger the actuators in real time according to sensor data, and adjust the working status of the equipment.

[0005] Furthermore, a method for controlling a smart vehicle switch with a customized function is provided. In step S5, the linkage logic between multiple verifications, physical buttons and touch interfaces is designed to ensure the security of user data and system operations, as follows; Multiple verification design: Password verification: Before inputting on the touch screen or physical buttons, users need to go through the password interface. Car owners must enter a preset PIN code before operating in-vehicle devices (such as air conditioning, seat heating, windows, etc.); Location verification: Combined with the vehicle's GPS data, when the system detects that the vehicle is in certain specific areas (such as the owner's home or workplace), certain advanced operations (such as unlocking the vehicle, starting the vehicle, etc.) are allowed. In other areas, the system requires additional verification (such as passwords, fingerprints) Time verification: restrict certain operations according to specific time periods (such as nighttime and non-working hours). Limit the seat heating function at night to prevent misoperation and reduce power consumption. Linkage design between physical buttons and touch interface: The touch screen and physical button states are synchronized. The states of the touch screen and physical buttons should be consistent. When the physical button is pressed to control the window lifting and lowering, the interface on the touch screen should also reflect the state: the window opening and closing progress, and allow the user to make further adjustments through the touch screen. Priority setting: Set the priority between physical buttons and touch screen. Both the touch screen and physical buttons can control the windows, but the physical buttons have a higher operation priority. When the user presses the physical button, the control function of the touch screen is disabled to avoid conflicts.

[0006] Furthermore, a method for controlling a smart vehicle switch with a customized function is provided. In step S6, the user's actual operation feedback is used to analyze the user's usage behavior using data analysis and clustering algorithms to find problems in the system and optimize the control method and interface design according to needs. The specific steps are as follows; S61. Collect user operation data: Collect raw data of user operations through sensors, user interfaces and control systems. These data include: user interaction with the touch screen (click, slide, select, etc.), the frequency, duration and sequence of user use of physical buttons, user input type (such as password, voice command, gesture control, etc.), user device usage mode (such as seat heating, air conditioning adjustment, window control, etc.), combined with sensor data (temperature, humidity, vehicle speed, etc.), collect the environmental context of each operation to understand the environmental factors behind the user's operation; S62. Data cleaning and preprocessing: Process outliers, missing values, and erroneous data in the data. You can use statistical methods (such as mean filling, median filling) or machine learning methods (such as KNN filling) to fill missing data, standardize data of different dimensions (such as vehicle speed, temperature, etc.), ensure data consistency, avoid certain features from having too much impact on the model, and calculate "operation frequency", "operation period", and "success rate" features based on the user's operating habits; S63. User behavior analysis and modeling: Use statistical analysis and visualization tools to analyze user behavior, identify common usage patterns or abnormal behaviors, use the K-means clustering algorithm to group user usage behaviors, identify the operation characteristics of different user groups, identify users who frequently operate, and detect that some operations fail to execute as expected; S64. Feedback mechanism and system update: Based on the optimized control mode and interface design, collect user feedback (through questionnaires, user interviews or directly embedding feedback functions in the system) to ensure user acceptance and satisfaction with the changes, and use users' real-time feedback and behavior data for dynamic optimization. Based on user feedback evaluation (such as common usage problems, functional requirements or interface design suggestions), regularly update the system (for example, through OTA updates) and push improved functions.

[0007] A smart vehicle switch control system with a custom function, the smart vehicle switch control system with a custom function is used to implement a smart vehicle switch control method with a custom function; the smart vehicle switch control system with a custom function comprises: a data collection module, a control logic and rule engine module, a security and verification module, a feedback and prompt module, and a data analysis and learning module; The data collection module is responsible for interacting with users, providing multiple operation modes to control in-vehicle devices and systems, and collecting various environmental data inside and outside the vehicle to provide input for the control system. Control logic and rule engine module: responsible for executing control operations and generating intelligent decisions based on sensor data and user input. It automatically adjusts the windows, seat heating, and air conditioning equipment based on sensor data such as temperature, humidity, and vehicle speed, allowing users to set different driving scenarios (such as driving mode, parking mode, and rest mode), and automatically adjusts the device status according to the scenario. Security and verification module: ensure the security and stability of the system, prevent misoperation and ensure data privacy; Feedback and prompt module: provides operation feedback to users to ensure that users know the status of the device. The feedback includes visual feedback, sound feedback, and vibration feedback. Data analysis and learning module: used to analyze user operating behavior and system performance, provide personalized recommendations and intelligent adjustments, conduct data analysis based on the user's historical operating behavior, provide optimization suggestions for the system, continuously optimize control strategies and interface design based on the owner's feedback and operating habits, automatically analyze the current driving situation, and adjust the control logic to improve the experience.

[0008] Beneficial effects of the present invention: By simplifying the control interface and providing a variety of interactive methods (such as touch screen, voice, gestures, etc.), the system effectively reduces the reliance on traditional physical buttons during driving, thereby reducing the driver's operating burden and reducing the safety risks caused by distraction. Automatically adjust the status of in-vehicle equipment according to user preferences and real-time environmental conditions (such as temperature, humidity, vehicle speed, etc.) to provide personalized control strategies. Car owners can customize different driving modes (such as driving mode, parking mode, rest mode) to make each drive meet personal needs. Through intelligent sensors and automatic control logic, the system can achieve coordinated linkage of equipment such as windows, seat heating, and air conditioning to ensure the efficient operation of different equipment in different environments, avoid energy waste, and extend the service life of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A flow chart of a method for controlling a smart vehicle switch with a customized function; DETAILED DESCRIPTION

[0010] A method for controlling a smart car switch with a custom function, the flow chart is as follows Figure 1 As shown, the following steps are included; S1. Requirements analysis and function definition: Identify the devices or systems that need to be controlled (such as windows, seat heating, lights, audio systems, etc.), design customized control functions, and automatically adjust the status of in-vehicle devices according to driving mode and weather conditions: automatically enable seat heating in winter and cold weather, and automatically adjust window switches according to vehicle speed and temperature; S2. Hardware preparation: Select appropriate smart switch hardware (such as touch screen, button, voice control, gesture recognition or physical switch) and connect it to the vehicle's CAN bus or other vehicle communication network, and determine the sensors (temperature sensor, humidity sensor, seat sensor, etc.) and actuators (motor, heater, dimming light, etc.) related to switch control; S3. System integration and communication: Develop intelligent control units to process data input from users or collected from sensors, perform corresponding control operations, and realize communication between intelligent switches and various systems inside the vehicle (such as seats, air conditioning, etc.) through CAN bus, LIN bus or other vehicle network protocols; S4. Rule design and control logic: Process user input (such as through touch screen, voice recognition, physical buttons or gesture control, etc.), for example, voice control parses the user's voice instructions and converts them into switch control commands, integrates sensor data such as temperature, humidity, vehicle speed, etc., generates the optimal control strategy based on different environmental conditions and random forest regression algorithm, and integrates the control strategy model , where Control represents the optimal control strategy, It means to find the operation that maximizes a certain objective function. is the reward at time step t: comfort, energy saving, is the discount factor, is the maximum time step, and intelligently adjusts the control logic. For example, when the temperature inside the car is too high, the system automatically turns on the air conditioner. Custom rules and scene settings: allow users to customize different scene modes (for example: driving mode, parking mode, rest mode, etc.), and automatically adjust the vehicle's switch function in different modes. Control feedback: design a control feedback mechanism to ensure that users know the current switch status (for example, visual, sound or vibration feedback); S5. Security and stability assurance: To avoid misoperation, multiple verifications or linkage logic between physical buttons and touch interfaces are designed to ensure the security of user data and system operations, including data encryption, identity authentication and other measures; S6. User testing and feedback: Conduct multiple rounds of testing in the car to ensure the stability, response speed and smoothness of user interaction of the system. Through the actual operation feedback of users, use data analysis and clustering algorithms to analyze user usage behavior, find problems in the system and further optimize the control method and interface design according to needs; S7. Maintenance and Update: Through the OTA (Over-the-Air) function, regular updates of the control system are pushed to enhance system functions or fix problems. A remote fault diagnosis function is designed for the system to automatically detect problems and provide repair solutions.

[0011] Furthermore, a method for controlling a smart vehicle switch with a customized function is provided. In step S4, the sensor data: temperature, humidity, vehicle speed are integrated, and the optimal control strategy is generated according to different environmental conditions and the random forest regression algorithm. The specific steps are as follows; S41. Data collection and preprocessing: Collect data from sensors in the car: temperature sensor, humidity sensor, speed sensor in real time, preprocess the collected data: remove noise and missing values, process abnormal values ​​(such as data anomalies caused by sensor failure), standardize temperature, humidity, and speed data to make them comparable, and avoid the value of some features being too large or too small to affect model training; S42. Feature Engineering and Data Analysis: Select key features that affect vehicle equipment control: temperature, humidity, and vehicle speed directly affect the status of air conditioning, seat heating, and window control equipment, and construct new features based on existing data: generate a "comfort index" based on temperature and humidity, and generate an "environmental adaptability" based on vehicle speed and external temperature, and identify the impact of data features on control strategies based on statistical analysis; S43. Training control strategy model: Divide the data into training set and test set to ensure the generalization ability of the model. Use the training set to train the random forest regression model and adjust the model's hyperparameters. Use the test set to evaluate the model's performance to ensure that the model has high accuracy and stability when predicting control strategies. Generate control strategies by learning the mapping relationship from environmental data to equipment control and obtain the control strategy model. , where Control represents the optimal control strategy, It means to find the operation that maximizes a certain objective function. is the reward at time step t: comfort, energy saving, is the discount factor, is the maximum number of time steps; S44. Generate control strategy: Based on the trained model, define the control strategy generated based on the environmental data: when the temperature is higher than the threshold, whether the air conditioner needs to be turned on; When the vehicle speed reaches a certain value, whether the window switch needs to be adjusted; Depending on the humidity and the in-car environment, whether the seat heating needs to be turned on or not, the real-time sensor data is input into the trained control strategy, which will output the corresponding control strategy: adjust the air conditioning temperature, seat heating or window status, and design a system feedback mechanism. When the generated control strategy does not achieve the expected effect, it can be adjusted and optimized through user feedback or system status data; S45. Model update and optimization: Collect feedback data through vehicle sensors, user input (such as voice or touch), and system status monitoring, regularly update the model based on new data feedback, continuously optimize the control strategy, conduct A / B testing during actual driving, verify the effects of different control strategies, and monitor the performance of the model; S46. Control strategy implementation: Integrate the generated control strategy into the vehicle control system to ensure that the control instructions output by the model can accurately interact with the vehicle actuators (such as air conditioners, motors, seat heaters, etc.), trigger the actuators in real time according to sensor data, and adjust the working status of the equipment.

[0012] Furthermore, a method for controlling a smart vehicle switch with a customized function is provided. In step S5, the linkage logic between multiple verifications, physical buttons and touch interfaces is designed to ensure the security of user data and system operations, as follows; Multiple verification design: Password verification: Before inputting on the touch screen or physical buttons, users need to go through the password interface. Car owners must enter a preset PIN code before operating in-vehicle devices (such as air conditioning, seat heating, windows, etc.); Location verification: Combined with the vehicle's GPS data, when the system detects that the vehicle is in certain specific areas (such as the owner's home or workplace), certain advanced operations (such as unlocking the vehicle, starting the vehicle, etc.) are allowed. In other areas, the system requires additional verification (such as passwords, fingerprints) Time verification: restrict certain operations according to specific time periods (such as nighttime and non-working hours). Limit the seat heating function at night to prevent misoperation and reduce power consumption. Linkage design between physical buttons and touch interface: The touch screen and physical button states are synchronized. The states of the touch screen and physical buttons should be consistent. When the physical button is pressed to control the window lifting and lowering, the interface on the touch screen should also reflect the state: the window opening and closing progress, and allow the user to make further adjustments through the touch screen. Priority setting: Set the priority between physical buttons and touch screen. Both the touch screen and physical buttons can control the windows, but the physical buttons have a higher operation priority. When the user presses the physical button, the control function of the touch screen is disabled to avoid conflicts.

[0013] Furthermore, a method for controlling a smart vehicle switch with a customized function is provided. In step S6, the user's actual operation feedback is used to analyze the user's usage behavior using data analysis and clustering algorithms to find problems in the system and optimize the control method and interface design according to needs. The specific steps are as follows; S61. Collect user operation data: Collect raw data of user operations through sensors, user interfaces and control systems. These data include: user interaction with the touch screen (click, slide, select, etc.), the frequency, duration and sequence of user use of physical buttons, user input type (such as password, voice command, gesture control, etc.), user device usage mode (such as seat heating, air conditioning adjustment, window control, etc.), combined with sensor data (temperature, humidity, vehicle speed, etc.), collect the environmental context of each operation to understand the environmental factors behind the user's operation; S62. Data cleaning and preprocessing: Process outliers, missing values, and erroneous data in the data. You can use statistical methods (such as mean filling, median filling) or machine learning methods (such as KNN filling) to fill missing data, standardize data of different dimensions (such as vehicle speed, temperature, etc.), ensure data consistency, avoid certain features from having too much impact on the model, and calculate "operation frequency", "operation period", and "success rate" features based on the user's operating habits; S63. User behavior analysis and modeling: Use statistical analysis and visualization tools to analyze user behavior, identify common usage patterns or abnormal behaviors, use the K-means clustering algorithm to group user usage behaviors, identify the operation characteristics of different user groups, identify users who frequently operate, and detect that some operations fail to execute as expected; S64. Feedback mechanism and system update: Based on the optimized control mode and interface design, collect user feedback (through questionnaires, user interviews or directly embedding feedback functions in the system) to ensure user acceptance and satisfaction with the changes, and use users' real-time feedback and behavior data for dynamic optimization. Based on user feedback evaluation (such as common usage problems, functional requirements or interface design suggestions), regularly update the system (for example, through OTA updates) and push improved functions.

[0014] A smart vehicle switch control system with a custom function, the smart vehicle switch control system with a custom function is used to implement a smart vehicle switch control method with a custom function; the smart vehicle switch control system with a custom function comprises: a data collection module, a control logic and rule engine module, a security and verification module, a feedback and prompt module, and a data analysis and learning module; The data collection module is responsible for interacting with users, providing multiple operation modes to control in-vehicle devices and systems, and collecting various environmental data inside and outside the vehicle to provide input for the control system. Control logic and rule engine module: responsible for executing control operations and generating intelligent decisions based on sensor data and user input. It automatically adjusts the windows, seat heating, and air conditioning equipment based on sensor data such as temperature, humidity, and vehicle speed, allowing users to set different driving scenarios (such as driving mode, parking mode, and rest mode), and automatically adjusts the device status according to the scenario. Security and verification module: ensure the security and stability of the system, prevent misoperation and ensure data privacy; Feedback and prompt module: provides operation feedback to users to ensure that users know the status of the device. The feedback includes visual feedback, sound feedback, and vibration feedback. Data analysis and learning module: used to analyze user operating behavior and system performance, provide personalized recommendations and intelligent adjustments, conduct data analysis based on the user's historical operating behavior, provide optimization suggestions for the system, continuously optimize control strategies and interface design based on the owner's feedback and operating habits, automatically analyze the current driving situation, and adjust the control logic to improve the experience.

Claims

1. A method for controlling a smart vehicle switch with a customized function, characterized in that: The steps include: S1. Requirements analysis and function definition: Identify the devices and systems that need to be controlled: windows, seat heating, lights, audio systems, design customized control functions, and automatically adjust the status of in-vehicle devices according to driving mode and weather conditions: automatically enable seat heating in winter and cold weather, and automatically adjust window switches according to vehicle speed and temperature; S2. Hardware preparation: Select smart switch hardware, including touch screen, buttons, voice control, gesture recognition and physical switches, and connect them to the vehicle's CAN bus and other on-board communication networks. Determine the sensors related to switch control: temperature sensor, humidity sensor, seat sensor and on-board actuators: motor, heater, dimming lamp; S3. System Integration and Communication: Processes data collected from user input and sensors, performs control operations, and enables communication between smart switches and various systems within the vehicle through CAN bus, LIN bus, and other in-vehicle network protocols; S4. Rule design and control logic: Process user input commands through touch screen, voice recognition, physical buttons, gesture control, and parse user voice commands and convert them into switch control commands. Integrate sensor data: temperature, humidity, vehicle speed, generate optimal control strategies based on different environmental conditions and random forest regression algorithms, and integrate them to obtain control strategy models. , where Control represents the optimal control strategy, It means to find the operation that maximizes a certain objective function. is the reward at time step t: comfort, energy saving, is the discount factor, is the maximum time step. The control logic is intelligently adjusted through the model, and the user is allowed to customize different scene modes: driving mode, parking mode, rest mode, and automatically adjust the vehicle's switch function in different modes. The control feedback mechanism is designed. The switch status feedback mechanism includes: visual, sound, and vibration feedback; S5. Security and stability assurance: To avoid misoperation, multiple verifications, linkage logic between physical buttons and touch interfaces are designed to ensure the security of user data and system operations, including data encryption and identity authentication measures; S6. User testing and feedback: Conduct multiple rounds of testing in the car to ensure the stability, response speed and smoothness of user interaction of the system. Through the actual operation feedback of users, use data analysis and clustering algorithms to analyze user usage behavior, find problems in the system and optimize the control method and interface design according to needs; S7. Maintenance and update: Through the OTA function, regular updates of the control system are pushed to enhance system functions and fix problems. A remote fault diagnosis function is designed for the system to automatically detect problems and provide repair solutions.

2. The method for controlling a smart vehicle switch with a customized function as claimed in claim 1, characterized in that: In step S4, the sensor data: temperature, humidity, vehicle speed are integrated, and the optimal control strategy is generated according to different environmental conditions and the random forest regression algorithm. The specific steps are as follows; S41. Data collection and preprocessing: Collect data from sensors in the car: temperature sensor, humidity sensor, speed sensor in real time, preprocess the collected data: remove noise, missing values, handle outliers, standardize temperature, humidity, speed data to make them comparable, and avoid the value of some features being too large or too small to affect model training; S42. Feature Engineering and Data Analysis: Select key features that affect vehicle equipment control: temperature, humidity, and vehicle speed directly affect the status of air conditioning, seat heating, and window control equipment, and construct new features based on existing data: generate a "comfort index" based on temperature and humidity, and generate an "environmental adaptability" based on vehicle speed and external temperature, and identify the impact of data features on control strategies based on statistical analysis; S43. Training control strategy model: Divide the data into training set and test set to ensure the generalization ability of the model. Use the training set to train the random forest regression model and adjust the model's hyperparameters. Use the test set to evaluate the performance of the model. Generate a control strategy by learning the mapping relationship from environmental data to device control and obtain the control strategy model. , where Control represents the optimal control strategy, It means to find the operation that maximizes a certain objective function. is the reward at time step t: comfort, energy saving, is the discount factor, is the maximum number of time steps; S44. Generate control strategy: Based on the trained model, define the control strategy generated based on environmental data: when the temperature is higher than a certain threshold, whether the air conditioner needs to be turned on; When the vehicle speed reaches a certain value, whether the window switch needs to be adjusted; Depending on the humidity and the in-car environment, whether the seat heating needs to be turned on or not, the real-time sensor data is input into the trained control strategy model, which will output the corresponding control strategy: adjust the air conditioning temperature, seat heating, and window status, and design a system feedback mechanism. When the generated control strategy does not achieve the expected effect, it will be adjusted and optimized through user feedback and system status data; S45. Model update and optimization: Collect feedback data through vehicle sensors, user input and system status monitoring, regularly update the model based on new data feedback, continuously optimize the control strategy, conduct A / B testing during actual driving, verify the effects of different control strategies, and monitor the performance of the model; S46. Control strategy implementation: Integrate the generated control strategy into the vehicle control system so that the control instructions output by the model can accurately interact with the vehicle actuators, trigger the actuators in real time according to the sensor data, and adjust the working status of the equipment.

3. The method for controlling a smart vehicle switch with a customized function as claimed in claim 1, characterized in that: In step S5, the linkage logic between multiple verifications, physical buttons and touch interfaces is designed to ensure the security of user data and system operations, as follows; Multiple verification design: Password verification: Before inputting on the touch screen or physical buttons, users need to go through the password interface. Car owners must enter the preset PIN code before operating the onboard equipment: air conditioning, seat heating, and windows; Location verification: Combined with the vehicle's GPS data, when the system detects that the vehicle is in certain specific areas: the owner's home, workplace, it allows operations such as unlocking the vehicle and starting the vehicle. In other areas, the system requires additional verification: password, fingerprint; Time verification: restrict operation according to specific time periods at night and during non-working hours: restrict seat heating function at night to prevent misoperation and reduce power consumption; Linkage design between physical buttons and touch interface: The touch screen and physical button states are synchronized. The states of the touch screen and physical buttons should be consistent. When the physical button is pressed to control the window lifting and lowering, the interface on the touch screen reflects the state: the window opening and closing progress, and allows the user to make further adjustments through the touch screen. Priority setting: Set the priority between physical buttons and touch screen. Both the touch screen and physical buttons can control the windows, but the physical buttons have a higher operation priority. When the user presses the physical button, the control function of the touch screen is disabled to avoid conflicts.

4. The method for controlling a smart vehicle switch with a customized function as claimed in claim 1, characterized in that: In step S6, the user's actual operation feedback is used to analyze the user's usage behavior using data analysis and clustering algorithms to find problems in the system and optimize the control method and interface design according to needs. The specific steps are as follows; S61. Collect user operation data: Collect raw data of user operations through sensors, user interfaces and control systems. These data include: user interaction with the touch screen, frequency, duration and sequence of user use of physical buttons, user input type, user device usage pattern, and combine sensor data to collect the environmental context of each operation and the environmental factors behind the user's operation; S62. Data cleaning and preprocessing: Process outliers, missing values ​​and erroneous data in the data, use statistical methods to fill missing data, standardize data of different dimensions, ensure data consistency, avoid excessive impact of certain features on the model, and calculate "operation frequency", "operation period" and "success rate" features based on user operation habits; S63. User behavior analysis and modeling: Use statistical analysis and visualization tools to analyze user behavior, identify common usage patterns and abnormal behaviors, and use the K-means clustering algorithm to group user usage behaviors and identify the operating characteristics of different user groups; S64. Feedback mechanism and system update: Based on the optimized control method and interface design, collect user feedback, perform dynamic optimization based on users' real-time feedback and behavior data, regularly update the system based on user feedback and evaluation, and push improved functions.

5. An intelligent vehicle switch control system with customized functions, characterized in that: The intelligent vehicle switch control system with a custom function is used to implement the intelligent vehicle switch control method with a custom function as described in any one of claims 1 to 4; the intelligent vehicle switch control system with a custom function comprises: a data collection module, a control logic and rule engine module, a security and verification module, a feedback and prompt module, and a data analysis and learning module; The data collection module is responsible for interacting with users, providing multiple operation modes to control in-vehicle devices and systems, and collecting various environmental data inside and outside the vehicle to provide input for the control system. Control logic and rule engine module: responsible for executing control operations and generating intelligent decisions based on sensor data and user input. It automatically adjusts the windows, seat heating, and air conditioning equipment based on temperature, humidity, and vehicle speed sensor data, allowing users to set different driving scenarios and automatically adjust the device status according to the scenario. Security and verification module: ensure the security and stability of the system, prevent misoperation and ensure data privacy; Feedback and prompt module: provides operation feedback to users, including visual feedback, sound feedback, and vibration feedback; Data analysis and learning module: used to analyze user operating behavior and system performance, provide personalized recommendations and intelligent adjustments, conduct data analysis based on the user's historical operating behavior, provide optimization suggestions for the system, continuously optimize control strategies and interface design based on the owner's feedback and operating habits, automatically analyze the current driving situation, and adjust the control logic to improve the experience.

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