A smart cockpit control system and method for long-term driving mode

Abstract

This disclosure provides an intelligent cockpit control system and method for long-term driving, relating to the field of intelligent cockpit technology. It includes a driving information acquisition module, a vehicle controller, a body controller, an in-vehicle interaction module, and an air conditioning control unit. The driving information acquisition module collects information about the vehicle itself, external roads, and external vehicles, and transmits this information to the vehicle controller. The vehicle controller receives and processes this information, identifies the driver's fatigue state, and sends control commands to adjust window raising and lowering, seat and lighting adjustments, and temperature and fan speed adjustments for the air conditioning system. It also collects steering wheel angle and force signals, calculates the amplitude and phase spectral density functions of the signals with time as the abscissa, and plots the amplitude and phase spectral density functions with frequency as the abscissa to determine the driver's fatigue level.

Description

Technical Field

[0001] This disclosure relates to the field of intelligent cockpit technology, specifically to an intelligent cockpit control system and method for long-duration driving. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] In modern society, many people frequently drive long distances due to work, life, and travel needs. Prolonged driving can lead to physical fatigue and mental stress, and drowsy driving is an extremely dangerous behavior. It not only causes serious harm to the driver but also poses a threat to other vehicles and pedestrians on the road. First, drowsy driving impairs a driver's reaction time and judgment. In a fatigued state, a driver's reaction time is significantly prolonged, and their ability to handle unexpected situations is greatly reduced. This may prevent the driver from making timely and correct judgments and reactions, leading to traffic accidents. Second, drowsy driving can easily cause drivers to doze off and lose concentration. These phenomena further weaken the driver's alertness and attention, making them unable to effectively control the vehicle and increasing the likelihood of accidents. Furthermore, drowsy driving also affects a driver's vision, hearing, and hand-eye coordination. In a fatigued state, drivers may experience blurred vision, impaired hearing, and poor hand-eye coordination, all of which can lead to traffic accidents. Most importantly, drowsy driving also poses a significant threat to passengers in the same vehicle, other vehicles on the road, and pedestrians. When fatigued, drivers may become unstable, change lanes improperly, or engage in other behaviors that could lead to collisions with other vehicles or pedestrians and cause serious traffic accidents.

[0004] Current technologies primarily focus on monitoring driver fatigue to provide individual reminders; however, this technology overlooks the discomfort caused to other passengers by prolonged driving. When a driver drives for extended periods, not only will the driver feel fatigued, but other passengers may also experience discomfort due to prolonged sitting and lack of movement.

[0005] However, current technologies primarily focus on monitoring driver fatigue and reminding drivers to rest via alerts or other means. While this approach can indeed reduce traffic accidents caused by drowsy driving to some extent, it does not consider the comfort and health of other passengers. Therefore, it is necessary to further develop new technologies to monitor and mitigate the discomfort caused to other passengers by long-distance driving. Summary of the Invention

[0006] To address the aforementioned issues, this disclosure proposes an intelligent cockpit control system and method for long-duration driving modes. By combining various data, it determines whether the driver is in long-duration driving mode, thereby achieving vehicle control and improving the long-duration driving experience.

[0007] According to some embodiments, the present disclosure adopts the following technical solutions:

[0008] A smart cockpit control system for long-term driving mode includes a driving information acquisition module, a vehicle controller, a body controller, an in-vehicle interaction module, and an air conditioning control unit. The driving information acquisition module collects its own vehicle information, external road information, and external vehicle information, and transmits them to the vehicle controller. The vehicle controller receives and processes various information, identifies the fatigue state of the driver and passengers, and sends control commands to the body controller, the in-vehicle interaction module, and the air conditioning control unit to respectively realize the raising and lowering of the windows, the adjustment of the seats and lights, and the adjustment of the temperature and fan speed of the air conditioning system.

[0009] The driving information acquisition module includes a steering wheel angle sensor and a steering wheel force sensor. It collects the steering wheel angle signal and force signal and transmits them to the vehicle controller for time-domain analysis. With time as the abscissa, it calculates the corresponding amplitude spectral density and phase spectral density functions of the signal, and then plots the curves of the amplitude spectral density function and phase spectral density function with frequency as the abscissa to determine the driver's fatigue level.

[0010] According to some embodiments, the present disclosure adopts the following technical solutions:

[0011] A control method for an intelligent cockpit control system in a long-term driving mode, wherein a driving information acquisition module collects its own vehicle information, external road information, and external vehicle information, and transmits them to the vehicle controller. The vehicle controller receives and processes various information, identifies the fatigue state of the driver and passengers, and sends control commands to the body controller, the in-vehicle interaction module, and the air conditioning control unit, respectively realizing the raising and lowering of the windows, the adjustment of the seats and lights, and the adjustment of the temperature and fan speed of the air conditioning system.

[0012] The driving information acquisition module includes a steering wheel angle sensor and a steering wheel force sensor. It collects the steering wheel angle signal and force signal and transmits them to the vehicle controller for time-domain analysis. With time as the abscissa, the corresponding amplitude spectral density and phase spectral density functions of the signal are calculated respectively. Then, with frequency as the abscissa, the curves of the amplitude spectral density function and phase spectral density function are plotted respectively to determine the driver's fatigue level, thereby realizing various intelligent control and adjustment of the whole vehicle.

[0013] According to some embodiments, the present disclosure adopts the following technical solutions:

[0014] A non-transitory computer-readable storage medium is provided for storing computer instructions, which, when executed by a processor, implement the control method of an intelligent cockpit control system in a long-duration driving mode.

[0015] According to some embodiments, the present disclosure adopts the following technical solutions:

[0016] An electronic device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute a control method for implementing an intelligent cockpit control system in a long-duration driving mode.

[0017] Compared with the prior art, the beneficial effects of this disclosure are as follows:

[0018] This disclosure discloses an intelligent cockpit control system and method for long-term driving modes. It utilizes onboard sensors and control algorithms to identify and locate the cockpit environment, setting different modes while considering the comfort of both front and rear passengers. It prioritizes both driving safety and enhanced comfort, monitoring and mitigating discomfort caused to other passengers during long drives through measures such as seat massage, improved in-vehicle air quality, and increased interior space and stretching. These measures allow passengers to feel more comfortable and relaxed during long car journeys, improving the overall driving experience.

[0019] This disclosure discloses an intelligent cockpit control system and method for long-term driving mode. When one or more of the curves obtained after calculation and conversion of the data collected by the steering wheel angle signal sensor and force signal sensor, namely the angle variance, pressure value, amplitude spectral density function, and phase spectral density function, differ significantly from the range of the corresponding curves stored in the database for normal driving mode, it is determined that the current driver is likely to be driving while fatigued. Therefore, the intelligent cockpit needs to take some safety measures to remind the driver. For example, the voice system can play a short beep and provide a voice prompt: "The system determines that you have a tendency to drive while fatigued. Please pay attention to your current driving status." The ambient lighting inside the vehicle can also change to red at this time and change with a higher frequency breathing effect to achieve a warning effect. Attached Figure Description

[0020] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0021] Figure 1 This is a flowchart illustrating driver fatigue monitoring according to an embodiment of the present disclosure;

[0022] Figure 2 This is a flowchart illustrating passenger seat fatigue monitoring according to an embodiment of the present disclosure;

[0023] Figure 3 This is a system architecture diagram of an embodiment of the present disclosure. Detailed Implementation

[0024] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0025] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0027] Example 1

[0028] One embodiment of this disclosure provides an intelligent cockpit control system for long-term driving mode, including a driving information acquisition module, a vehicle controller, a body controller, an in-vehicle interaction module, and an air conditioning control unit. The driving information acquisition module collects its own vehicle information, external road information, and external vehicle information, and transmits them to the vehicle controller. The vehicle controller receives and processes various information, identifies the fatigue state of the driver and passengers, and sends control commands to the body controller, the in-vehicle interaction module, and the air conditioning control unit to respectively realize the raising and lowering of the windows, the adjustment of the seats and lights, and the adjustment of the temperature and fan speed of the air conditioning system.

[0029] The driving information acquisition module includes a steering wheel angle sensor and a steering wheel force sensor. It collects the steering wheel angle signal and force signal and transmits them to the vehicle controller for time-domain analysis. With time as the abscissa, it calculates the corresponding amplitude spectral density and phase spectral density functions of the signal, and then plots the curves of the amplitude spectral density function and phase spectral density function with frequency as the abscissa to determine the driver's fatigue level.

[0030] As one embodiment, the present disclosure discloses an intelligent cockpit control system for long-term driving mode, including a driving information acquisition module, a vehicle controller (5), a body controller (6), an in-vehicle interaction module, and an air conditioning control unit (10); the driving information acquisition module includes an intelligent driving sensor (1), a steering wheel angle sensor (2), a steering wheel force sensor (3), and a seat pressure sensor (4). The intelligent driving sensor (1) is used to collect and process external vehicle information, including road information, external vehicle information, and pedestrian information; the steering wheel angle sensor (2) is used to collect steering wheel angle information; the steering wheel force sensor (3) is used to collect steering wheel pressure information; and the seat pressure sensor (4) is used to collect pressure information at the seat position.

[0031] The vehicle controller (5) is used to receive external vehicle information sent by the intelligent driving sensor (1), process it, and then send control commands to other relevant controllers.

[0032] The body control unit (6) is used to receive instructions from the vehicle control unit (5) and operate the raising and lowering of the windows;

[0033] The voice interaction system (7) in the vehicle interaction module is used to receive instructions from the vehicle controller (5) and control the voice interaction system (7), interior light controller (8), and massage seat controller (9), respectively controlling the on / off switch and color or rhythm adjustment of the voice interaction system and interior ambient light system, and the massage switch and intensity adjustment of the massage seat.

[0034] The air conditioning control unit (10) is used to receive instructions from the vehicle controller (5) and control the temperature or wind speed of the air conditioning system.

[0035] Furthermore, the intelligent driving sensor (1), steering wheel angle sensor (2), steering wheel force sensor (3) and seat pressure sensor (4) in the driving information acquisition module are connected to the vehicle controller (5) through the vehicle CAN network. The vehicle controller (5) is connected to the body controller (6), the in-vehicle interaction module - voice interaction system (7), interior light controller (8), massage seat controller (9) and the air conditioning control unit (10) in the cabin through the CAN network.

[0036] Furthermore, the driver's weight, posture, and behavioral characteristics are collected by the seat pressure sensor (4) to identify and determine whether the current driver is a person who has been driving the vehicle for a long time. A pressure sensor is installed under the seat to record the force and distribution of the driver's contact with the seat during driving. Through data integration, the driver's weight, posture, and behavioral characteristics are reflected. The collected signals are amplified by an amplification circuit and filtered by a filtering circuit to remove noise and interference. Then, the signals are converted into digital information by an A / D conversion circuit so that they can be processed by a computer or other digital devices. Finally, a model is built on the collected data, and statistical analysis, pattern recognition, and other means are used to associate the pressure distribution with the driver's identity. When new pressure data is collected, the data can be compared with the model to determine the current driver's identity. This data may include the driver's driving style, behavioral patterns, habits, etc.

[0037] (2) Steering wheel angle and force signals are collected using steering wheel pressure and force sensors. Time-domain analysis is performed on the collected signals. With time as the abscissa, curves of the variance or square difference of the angle signal and the force signal are plotted, and the corresponding functions are derived. After plotting, the functions are Fourier transformed to obtain the corresponding amplitude spectral density and phase spectral density functions. Then, with frequency as the abscissa, curves of the amplitude spectral density function and the phase spectral density function are plotted. Finally, the range covered by the above curves (taking the maximum and minimum values) is statistically analyzed to determine whether the driver is driving the car under normal conditions. Because when a driver is fatigued, their control over the car decreases, the steering wheel angle swings more, and its value does not change significantly over a period of time. At the same time, the frequency of steering wheel manipulation decreases. When a driver is fatigued, the grip force on the steering wheel gradually decreases. By detecting the force applied to the steering wheel by the driver in real time through sensors, the degree of driver fatigue can be determined.

[0038] When data indicates that a vehicle is being driven by the same driver, if the vehicle is recorded as traveling on a frequently used road for an extended period, it can be inferred that the driver is more prone to fatigue or inattentive driving on that road. If, after calculation and conversion, one or more of the angle variance, pressure value, amplitude spectral density function, and phase spectral density function curves obtained from the data collected by the steering wheel angle and force sensors deviate significantly from the range of the curves corresponding to the normal driving mode stored in the database, it can be determined that the current driver is highly likely to be fatigued. In such cases, the intelligent cockpit can implement safety measures to alert the driver. For example, the voice system can play a short beep and provide a voice prompt: "The system has determined that you have a tendency to drive while fatigued; please pay attention to your current driving status." The ambient lighting inside the vehicle can also change to red and exhibit a high-frequency breathing effect to serve as a warning.

[0039] Specifically, the fatigue monitoring process for the driver in the driver's seat includes:

[0040] ① If the driver is someone who drives the vehicle for a long time, the intelligent driving sensor (1) will determine whether the road where the vehicle is currently located is a high-frequency driving road and the driving time is long by collecting external road information and external vehicle data. If so, the vehicle controller (5) will activate the fatigue monitoring mode. By judging the steering angle signal collected by the steering wheel angle sensor (2) and the steering wheel pressure value collected by the steering wheel force sensor (3), the existing methods will be used to calculate and obtain the steering angle variance, pressure value and amplitude spectral density. Based on the steering angle variance, pressure value, amplitude spectral density function and phase spectral density function curves obtained after calculation and conversion, If one or more curves differ significantly from the range of the normal driving mode stored in the database, it is determined that the current driver is likely to be driving while fatigued. It is necessary to take safety measures to remind the driver in conjunction with the vehicle interaction module in the smart cockpit. The vehicle controller (5) sends an instruction to the voice interaction system (7), and the voice interaction system plays a short beep and gives a voice prompt: The system judges that you have a tendency to drive while fatigued. Please pay attention to your current driving status. The vehicle controller (5) sends an instruction to the interior light controller (8), and the ambient light inside the car changes to red and changes with a breathing effect at a higher frequency to achieve a warning effect.

[0041] ②If the driver is not a person who drives the vehicle for a long time, the vehicle will maintain its original driving mode and the fatigue monitoring mode of the vehicle controller (5) will be activated simultaneously, and the relevant monitoring and control behaviors will be consistent with those in ①.

[0042] Furthermore, pressure sensors are installed at the head, back, buttocks, and under the thighs of the seat to record the force and distribution of contact between the passenger and the seat during the journey. Data integration reflects the passenger's weight, posture, and behavioral characteristics. The collected signals are amplified by an amplifier circuit and filtered to remove noise and interference. Then, an A / D converter converts the signals into digital information for processing by a computer or other digital devices. Finally, a model is built from the collected data, and statistical analysis and pattern recognition are performed to determine the passenger's posture. If the pressure values ​​recorded at each point remain unchanged for a long period, it can be determined that the passenger's posture has been fixed for some time. In this case, a voice prompt is triggered, suggesting a change of posture and asking if the passenger would like to activate the seat massage function to alleviate discomfort from long journeys. Simultaneously, the passenger can open the windows to allow fresh air, adjust the air conditioning temperature and music volume, and adjust the ambient lighting color and rhythm, thereby improving the long-distance driving experience.

[0043] Specifically, the passenger seat uses seat pressure sensors (4) to collect pressure values ​​at different points on the seat. The system identifies and determines whether the pressure values ​​at each point on the current passenger seat remain unchanged for a long period (e.g., 30 minutes). If so, it sends an instruction to the vehicle controller (5). The vehicle controller (5) then sends an instruction to the voice interaction system (7), which prompts and asks whether to activate the cabin fatigue mode. If a positive response is received, the voice interaction system (7) asks:

[0044] ① Whether it is necessary to adjust the color and brightness of the ambient light. If so, the voice interaction system (7) sends a command to the vehicle controller (5), and the vehicle controller (5) then forwards the signal to the interior light controller (8) to control the status of the ambient light.

[0045] ②Whether the seat massage mode needs to be turned on, as well as the massage area and intensity. If so, the voice interaction system (7) sends a command to the vehicle controller (5), and the vehicle controller (5) then forwards the signal to the massage seat controller (9) to control the state of the massage seat.

[0046] ③ Whether it is necessary to raise / lower the car window glass. If so, the voice interaction system (7) sends an instruction to the vehicle controller (5), and the vehicle controller (5) then forwards the signal to the body controller (6) to control the raising and lowering of the car window glass.

[0047] ④ Whether it is necessary to turn the air conditioner on / off or adjust the air conditioner temperature and wind speed. If so, the voice interaction system (7) sends a command to the vehicle controller (5), and the vehicle controller (5) then forwards the signal to the air conditioning control unit (10) in the cabin to control the status of the air conditioner.

[0048] Example 2

[0049] One embodiment of this disclosure provides a control method for an intelligent cockpit control system in a long-duration driving mode, including:

[0050] The driving information collection module collects its own vehicle information, external road information, and external vehicle information, and transmits them to the vehicle controller. The vehicle controller receives and processes various information, identifies the fatigue state of the driver and passengers, and sends control commands to the body controller, the in-vehicle interaction module, and the air conditioning control unit to respectively realize the raising and lowering of the windows, the adjustment of the seats and lights, and the adjustment of the temperature and fan speed of the air conditioning system.

[0051] The driving information acquisition module includes a steering wheel angle sensor and a steering wheel force sensor. It collects the steering wheel angle signal and force signal and transmits them to the vehicle controller for time-domain analysis. With time as the abscissa, the corresponding amplitude spectral density and phase spectral density functions of the signal are calculated respectively. Then, with frequency as the abscissa, the curves of the amplitude spectral density function and phase spectral density function are plotted respectively to determine the driver's fatigue level, thereby realizing various intelligent control and adjustment of the whole vehicle.

[0052] The specific implementation process is the process and method described in Example 1.

[0053] Example 3

[0054] One embodiment of this disclosure provides a non-transitory computer-readable storage medium for storing computer instructions. When these computer instructions are executed by a processor, they implement the control method of an intelligent cockpit control system under long-duration driving mode.

[0055] Example 4

[0056] One embodiment of this disclosure provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute a control method for implementing an intelligent cockpit control system in a long-duration driving mode.

[0057] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0058] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0059] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. An intelligent cockpit control system for long-duration driving mode, characterized in that, The system includes a driving information acquisition module, a vehicle controller, a body controller, an in-vehicle interaction module, and an air conditioning control unit. The driving information acquisition module collects information about its own vehicle, external roads, and external vehicles, and transmits it to the vehicle controller. The vehicle controller receives and processes various information, identifies the fatigue state of the driver and passengers, and sends control commands to the body controller, the in-vehicle interaction module, and the air conditioning control unit to respectively control the raising and lowering of windows, the adjustment of interior seats and lights, and the adjustment of temperature and fan speed of the air conditioning system. The driving information acquisition module includes a steering wheel angle sensor and a steering wheel force sensor. It collects the steering wheel angle signal and force signal and transmits them to the vehicle controller for time-domain analysis. With time as the abscissa, it calculates the corresponding amplitude spectral density and phase spectral density functions of the signal, and then plots the curves of the amplitude spectral density function and phase spectral density function with frequency as the abscissa to determine the driver's fatigue level.

2. The intelligent cockpit control system for long-duration driving mode as described in claim 1, characterized in that, The driving information acquisition module also includes intelligent driving sensors and seat pressure sensors. The intelligent driving sensors collect vehicle external information, including road information, external vehicle and pedestrian information. The seat pressure sensors collect pressure information at the seat position and transmit it to the vehicle controller for processing through the vehicle CAN network.

3. The intelligent cockpit control system for long-duration driving mode as described in claim 1, characterized in that, The driver's seat collects pressure information through a seat pressure sensor and transmits it to the vehicle controller. The vehicle controller analyzes the driver's weight, posture, and behavioral characteristics based on the pressure information to identify and determine whether the driver is a long-term driver.

4. The intelligent cockpit control system for long-duration driving mode as described in claim 3, characterized in that, If the driver is someone who drives the vehicle for extended periods, the intelligent driving sensors will determine whether the current road is a high-frequency driving road with a long driving time by collecting external road information and vehicle data. If so, the vehicle controller will activate the fatigue monitoring mode. It will judge the steering angle signal collected by the steering wheel angle sensor and the steering wheel pressure value collected by the force sensor, and calculate and convert the angle variance, pressure value, amplitude spectral density function and phase spectral density function, and draw a curve. If one or more items in the curve differ significantly from the range of the curve corresponding to the normal driving mode stored in the database, it will be determined that the current driver is driving while fatigued.

5. The intelligent cockpit control system for long-duration driving mode as described in claim 1, characterized in that, The intelligent driving sensors, steering wheel angle sensor, steering wheel force sensor, and seat pressure sensor in the driving information acquisition module are connected to the vehicle controller via the vehicle CAN network. The vehicle controller is connected to the body controller, the in-vehicle interaction module, and the air conditioning control unit via the CAN network.

6. The intelligent cockpit control system for long-duration driving mode as described in claim 4, characterized in that, When the driver is fatigued, the vehicle controller sends control commands to the voice interaction system of the vehicle interaction module to provide voice prompts and controls the interior lighting controller of the vehicle interaction module to change the interior lighting atmosphere.

7. The intelligent cockpit control system for long-duration driving mode as described in claim 1, characterized in that, The seat pressure sensor collects pressure values ​​at different points on the seat, identifies and determines whether the pressure values ​​at each point on the current passenger seat are constant over a long period of time. If so, it sends a command to the vehicle controller, which then sends a control command to the in-vehicle interaction module to ask the passenger whether they need to activate the seat massage mode and the massage area and intensity. If so, the passenger sends a command to the vehicle controller, which then forwards the signal to the massage seat controller to control the state of the massage seat.

8. A control method for an intelligent cockpit control system in a long-duration driving mode according to any one of claims 1-7, characterized in that, The driving information collection module collects its own vehicle information, external road information, and external vehicle information, and transmits them to the vehicle controller. The vehicle controller receives and processes various information, identifies the fatigue state of the driver and passengers, and sends control commands to the body controller, the in-vehicle interaction module, and the air conditioning control unit to respectively realize the raising and lowering of the windows, the adjustment of the seats and lights, and the adjustment of the temperature and fan speed of the air conditioning system. The driving information acquisition module includes a steering wheel angle sensor and a steering wheel force sensor. It collects the steering wheel angle signal and force signal and transmits them to the vehicle controller for time-domain analysis. With time as the abscissa, the corresponding amplitude spectral density and phase spectral density functions of the signal are calculated respectively. Then, with frequency as the abscissa, the curves of the amplitude spectral density function and phase spectral density function are plotted respectively to determine the driver's fatigue level, thereby realizing various intelligent control and adjustment of the whole vehicle.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium is used to store computer instructions, which, when executed by a processor, implement the control method of an intelligent cockpit control system in a long-duration driving mode as described in claim 8.

10. An electronic device, characterized in that, include: The device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory to enable the electronic device to perform a control method for an intelligent cockpit control system in a long-duration driving mode as described in claim 8.

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