CN114228724A - Brain wave-based intelligent automobile driving system and control method - Google Patents

Brain wave-based intelligent automobile driving system and control method Download PDF

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CN114228724A
CN114228724A CN202111525461.7A CN202111525461A CN114228724A CN 114228724 A CN114228724 A CN 114228724A CN 202111525461 A CN202111525461 A CN 202111525461A CN 114228724 A CN114228724 A CN 114228724A
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vehicle
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brain wave
sensor
driving
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CN114228724B (en
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马芳武
张伟洲
袁道发
邢彪
吴量
孙博华
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Jilin University
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Jilin University
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Abstract

An intelligent automobile driving system based on brain waves and a control method thereof are disclosed, wherein the system comprises a brain wave signal sensor for collecting brain wave signals of human brain; the Butterworth band-pass filter is used for performing band-pass filtering with 10-order Butterworth frequency range of 8-30HZ on brain wave signal data obtained by the brain wave signal sensor; the AR model spectrum estimation feature extraction module is used for extracting maximum differentiation different types of electroencephalogram signals from the filtered electroencephalogram signals through AR model spectrum estimation features, and extracting a feature vector effective for driving a vehicle; the normalization processing module is used for performing normalization processing on the data of the AR model spectrum estimation feature extraction module to obtain an electroencephalogram command for driving a vehicle; and the driving behavior reasonability analysis module is used for judging whether the driving electroencephalogram signal made by the driver is reasonable according to the sensor information obtained by the sensor arranged on the vehicle. The system can release the limbs of the driver, so that the driver feels easier to drive the automobile.

Description

Brain wave-based intelligent automobile driving system and control method
Technical Field
The invention belongs to the technical field of automatic driving, and particularly relates to an intelligent automobile driving system based on brain waves and a control method.
Background
At present, most of patents disclosed in the related fields remind the driver of the fatigue driving and the inattention by detecting the brain wave signals of the driver through signals such as light, sound, vibration of a seat and a backrest when the driver is tired and the driver is inattentive, so that the attention of the driver is concentrated and the dangerous situation is avoided. Such brain wave-based vehicle systems are mainly based on driver safety, and their main driving operations are performed by the limbs of the driver. In addition, there is another method in which a signal for braking the vehicle is generated based on the brain wave of the driver, and the signal is processed to brake the vehicle. Such a brain wave-based vehicle system can complete vehicle braking by using brain wave signals, thereby freeing up a part of the limb operations of the driver. But the driving modes such as acceleration, steering, uniform speed, backing and the like cannot be realized through the brain wave signals of the driver.
In recent years, intelligent driving technology is rapidly developed, and various interaction methods and modes of a human-computer interaction system appear, for example, a brain wave controlled four-wheel independent drive intelligent trolley system and a control method thereof are disclosed in patent CN107065850A, wherein brain wave signals of the system are processed and then used for driving a trolley by using an STM32 controller, and the brain wave signals are collected to realize the motion of the four-wheel trolley by four direct current motors. However, since the steering brake and the like are all performed by the dc motor, the control accuracy thereof is difficult to be ensured, and the control method thereof is difficult to be used in a passenger car with an operating mechanism such as a steering wheel and a brake pedal.
Disclosure of Invention
The invention aims to provide an intelligent automobile driving system based on brain waves, which can release the limbs of a driver, so that the driver feels easier to drive an automobile, and can well assist the disabled to drive the automobile, so that the disabled can experience the pleasure of driving the automobile while riding instead of walking.
In order to achieve the purpose, the invention adopts the following technical scheme:
an intelligent automobile driving system based on brain waves comprises a brain wave signal sensor, a Butterworth band-pass filter, an AR model spectrum estimation feature extraction module, a normalization processing module, a driving behavior rationality analysis module and a reminding device;
the brain wave signal sensor is used for collecting brain wave signals of a human brain for judging how to drive the vehicle in the next step according to the external environment and the driving condition of the vehicle;
the Butterworth band-pass filter is used for performing band-pass filtering with 10-order Butterworth frequency range of 8-30HZ on brain wave signal data obtained by the brain wave signal sensor to obtain a vehicle motion signal generated by a driver;
the AR model spectrum estimation feature extraction module is used for extracting maximum differentiation different types of electroencephalogram signals from the filtered electroencephalogram signals through AR model spectrum estimation features, and extracting a feature vector effective for driving a vehicle; wherein, the AR model is:
Figure BDA0003410211420000021
in the formula (I), the compound is shown in the specification,
Figure BDA0003410211420000022
is a predicted value of the signal sample value x (n); c. CpjIs a weight parameter; p is the order of the model, x (n) is the nth sample value;
ep(n) is the forward error of the AR model, representing the deviation between the predicted and actual values:
Figure BDA0003410211420000023
namely:
Figure BDA0003410211420000024
taking Z transform, converting from time domain to frequency domain:
Figure BDA0003410211420000025
therefore, the calculation formula for the power spectrum estimation of the AR model is:
Figure BDA0003410211420000026
wherein, w is angular frequency and is collected from brain wave signals; j is an imaginary number;
the normalization processing module is used for performing normalization processing on the data of the AR model spectral estimation feature extraction module to obtain an electroencephalogram command for driving a vehicle; wherein, the normalization processing formula is as follows:
Figure BDA0003410211420000027
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the strength of acceleration, steering and braking signals;
the driving behavior reasonability analysis module is used for judging whether a driving electroencephalogram signal made by a driver is reasonable according to sensor information obtained by a sensor mounted on a vehicle, if so, transmitting the signal to the vehicle control unit, and the vehicle control unit transmits the obtained signal to a bottom actuator; if the signal is not reasonable, the signal is transmitted to the reminding device.
Preferably, the vehicle-mounted sensor includes a camera, a millimeter wave radar, a speed sensor, an acceleration sensor, and a steering angle sensor; the pedestrian, surrounding vehicles and road condition information are identified through the camera and the millimeter wave radar sensor, and the vehicle running state information is obtained through the speed sensor, the acceleration sensor and the steering angle sensor of the vehicle.
Preferably, the reminding device comprises a sound reminding device and/or a light reminding device, when the electroencephalogram signal is judged to be unreasonable by the driving behavior rationality analysis module, the reason why the electroencephalogram signal for driving the vehicle is unreasonable is fed back to the driver through the sound and/or the light signal, the driver is reminded to make a correct driving signal, and meanwhile, the driver is reminded to make a proper suggestion.
Preferably, the vehicle control unit processes the acquired electroencephalogram signals and then respectively transmits the processed electroencephalogram signals to the electric power steering system, the four hub motors and the electronic parking braking system, and the vehicle makes corresponding motion according to the signals; meanwhile, the electric power steering system feeds back the steering angle to the vehicle control unit and displays the steering angle through an instrument panel; the rotating speed and the torque of the four hub motors are fed back to the whole vehicle controller and are displayed through an instrument panel; the electronic parking braking system feeds back the braking state to the vehicle control unit and displays whether braking is carried out or not through an instrument.
Another object of the present invention is to provide a method for controlling an intelligent driving system of an automobile based on brain waves, the method comprising the steps of:
step S1, collecting a brain wave signal of a driver through a brain wave signal sensor, and transmitting the obtained brain wave signal of the driver to a Butterworth band-pass filter;
s2, filtering out brain wave signals with the frequency range of 8-30HZ by a Butterworth band-pass filter to obtain vehicle motion signals generated by a driver;
s3, extracting the brain wave signals after filtering through AR model spectrum estimation features, and extracting the brain wave signals of the automobile motion instructions; wherein, the AR model is:
Figure BDA0003410211420000031
in the formula (I), the compound is shown in the specification,
Figure BDA0003410211420000032
is a predicted value of the signal sample value x (n); c. CpjIs a weight parameter; p is the order of the model, x (n) is the nth sample value;
ep(n) is the forward error of the AR model, representing the deviation between the predicted and actual values:
Figure BDA0003410211420000033
namely:
Figure BDA0003410211420000034
taking Z transform, converting from time domain to frequency domain:
Figure BDA0003410211420000035
therefore, the calculation formula for the power spectrum estimation of the AR model is:
Figure BDA0003410211420000036
wherein, w is angular frequency and is collected from brain wave signals; j is an imaginary number;
step S4, obtaining an automobile driving instruction signal through normalization processing; wherein, the normalization processing formula is as follows:
Figure BDA0003410211420000037
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the strength of acceleration, steering and braking signals;
and step S5, obtaining a command signal transmitted to the vehicle control unit through analysis of the driving behavior rationality analysis module.
Preferably, in step S5, the acceleration command signal is transmitted to the in-wheel motor controller through the vehicle control unit, the in-wheel motor controller controls the rotation speed of the in-wheel motor according to the acceleration signal, and the magnitude of the acceleration signal represents the acceleration speed of the in-wheel motor; the steering command signal is transmitted to the steer-by-wire controller through the vehicle controller, the steer-by-wire controller controls the turning angle of the vehicle according to the steering signal, and the magnitude of the steering signal represents the magnitude of the steering angle of the vehicle; the braking command signal is transmitted to the braking controller through the vehicle control unit, and the braking controller brakes the vehicle according to the braking signal, wherein the magnitude of the braking signal represents the magnitude of the braking force.
Preferably, the vehicle control unit acquires the rotating speed of the hub motor through a sensor, and the rotating speed of the hub motor is acquired through the sensor
Figure BDA0003410211420000041
Converting the speed into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle control unit acquires a vehicle steering corner through a steering sensor and displays the size of the corner on an instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the vehicle controller is powered onThe battery management system obtains the electric quantity information of the battery and displays the electric quantity of the battery on the instrument panel.
The invention has the advantages and positive effects that: the invention designs an intelligent automobile driving system based on brain waves, which is characterized in that brain wave signals of a driver are collected through a brain wave signal sensor, vehicle motion signals generated by the driver are obtained through a Butterworth band-pass filter, the maximum differentiation different types of brain wave signals are extracted through AR model spectrum estimation characteristics, and a characteristic vector effective for driving the vehicle is extracted; and finally, obtaining the electroencephalogram command for driving the vehicle through normalization processing. The system can release the limbs of a driver, so that the driver can feel easier when driving the vehicle, and simultaneously, the limb of the driver can be completely released, so that the disabled can drive the vehicle, and the disabled can realize the pleasure of driving the vehicle while using the vehicle to ride instead of walk.
Drawings
FIG. 1 is a block diagram of an intelligent driving system based on brain waves for a vehicle according to the present invention;
fig. 2 is a schematic diagram of a brain wave signal vehicle-shaping control strategy.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Example 1
Referring to fig. 1 and 2, the brain wave-based intelligent driving system for the automobile provided by the invention comprises a brain wave signal sensor, a Butterworth band-pass filter, an AR model spectrum estimation feature extraction module, a normalization processing module, a driving behavior rationality analysis module and a reminding device, wherein the brain wave signal sensor is connected with the Butterworth band-pass filter;
the brain wave signal sensor is used for collecting brain wave signals of a human brain for judging how to drive the vehicle in the next step according to the external environment and the driving condition of the vehicle;
the Butterworth band-pass filter is used for performing band-pass filtering with 10-order Butterworth frequency range of 8-30HZ on brain wave signal data obtained by the brain wave signal sensor to obtain a vehicle motion signal generated by a driver;
the AR model spectrum estimation feature extraction module is used for extracting maximum differentiation different types of electroencephalogram signals from the filtered electroencephalogram signals through AR model spectrum estimation features, and extracting a feature vector effective for driving a vehicle; wherein, the AR model is:
Figure BDA0003410211420000051
in the formula (I), the compound is shown in the specification,
Figure BDA0003410211420000052
is a predicted value of the signal sample value x (n); c. CpjIs a weight parameter; p is the order of the model, x (n) is the nth sample value;
ep(n) is the forward error of the AR model, representing the deviation between the predicted and actual values:
Figure BDA0003410211420000053
namely:
Figure BDA0003410211420000054
taking Z transform, converting from time domain to frequency domain:
Figure BDA0003410211420000055
therefore, the calculation formula for the power spectrum estimation of the AR model is:
Figure BDA0003410211420000056
wherein, w is angular frequency and is collected from brain wave signals; j is an imaginary number;
the normalization processing module is used for performing normalization processing on the data of the AR model spectral estimation feature extraction module to obtain an electroencephalogram command for driving a vehicle; wherein, the normalization processing formula is as follows:
Figure BDA0003410211420000057
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the strength of acceleration, steering and braking signals;
the driving behavior reasonability analysis module is used for judging whether a driving electroencephalogram signal made by a driver is reasonable according to sensor information obtained by a sensor mounted on a vehicle, if the electroencephalogram signal is reasonable, the signal is transmitted to the vehicle control unit, the vehicle control unit transmits the obtained signal to the bottom actuator, and the bottom actuator feeds back signals of the vehicle speed, the steering direction, the electric quantity and the like to the vehicle control unit; if the signal is unreasonable, the signal is transmitted to a reminding device; wherein, the electroencephalogram signal for accelerating the driving of the automobile made by the driver is judged to be unreasonable when the following conditions exist: namely, speeding, complex road conditions (tunnels, potholes, narrow bridges, etc.), oncoming vehicles, obstacles on the front road, etc.; the electroencephalogram signals for judging that the automobile steering driving made by the driver is unreasonable when the following conditions exist: the vehicle is driven with an obstacle in the turning direction, with an oncoming vehicle in the turning direction, and so on.
The sensors mounted on the vehicle comprise a camera, a millimeter wave radar, a speed sensor, an acceleration sensor, a steering angle sensor and other sensors; the driving behavior rationality analysis module identifies information of pedestrians, surrounding vehicles and road conditions through sensors such as a camera and a millimeter wave radar, and obtains information of vehicle running states through sensors such as a speed sensor, an acceleration sensor and a steering angle sensor of the vehicle.
Further, the reminding device comprises a sound reminding device and/or a light reminding device, when the electroencephalogram signal is judged to be unreasonable by the driving behavior rationality analysis module, the reason why the electroencephalogram signal of the driving vehicle is unreasonable is fed back to the driver through the sound and/or the light signal, the driver is reminded to make a correct driving signal, and meanwhile, the driver is given appropriate suggestions.
Fig. 2 is a brain wave signal vehicle control strategy diagram, and it can be seen from fig. 2 that a reasonable brain wave signal obtained by the driving behavior rationality analysis module is transmitted to the vehicle control unit, the vehicle control unit judges the obtained signal and transmits the judged signal to the electric power steering system EPS, the four in-wheel motors, the electronic parking brake system EPB, the battery management system BMS and the like, and the vehicle makes corresponding movement according to the signal. Meanwhile, the electric power steering system feeds back the steering angle to the vehicle control unit and displays the steering angle through an instrument panel; the rotating speed and the torque of the four hub motors are fed back to the whole vehicle controller and are displayed through an instrument panel; the electronic parking braking system feeds back the braking state to the vehicle control unit and displays whether braking is carried out or not through an instrument panel; the battery management system feeds back the battery electric quantity to the vehicle control unit, displays the electric quantity through the instrument panel, and simultaneously reminds a driver to charge the battery when the battery electric quantity is insufficient.
Example 2
The invention provides a control method of an intelligent automobile driving system based on brain waves, which comprises the following steps:
step S1, collecting a brain wave signal of a driver through a brain wave signal sensor, and transmitting the obtained brain wave signal of the driver to a Butterworth band-pass filter;
s2, filtering out brain wave signals with the frequency range of 8-30HZ by a Butterworth band-pass filter to obtain vehicle motion signals generated by a driver;
s3, extracting the brain wave signals after filtering through AR model spectrum estimation features, and extracting the brain wave signals of the automobile motion instructions; wherein, the AR model is:
Figure BDA0003410211420000071
in the formula (I), the compound is shown in the specification,
Figure BDA0003410211420000072
is a predicted value of the signal sample value x (n); c. CpjIs a weight parameter; p is the order of the model, x (n) is the nth sample value;
ep(n) is the forward error of the AR model, representing the deviation between the predicted and actual values:
Figure BDA0003410211420000073
namely:
Figure BDA0003410211420000074
taking Z transform, converting from time domain to frequency domain:
Figure BDA0003410211420000075
therefore, the calculation formula for the power spectrum estimation of the AR model is:
Figure BDA0003410211420000076
wherein, w is angular frequency and is collected from brain wave signals; j is an imaginary number;
step S4, obtaining an automobile driving instruction signal through normalization processing; wherein, the normalization processing formula is as follows:
Figure BDA0003410211420000077
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the strength of acceleration, steering and braking signals;
s5, obtaining a command signal transmitted to the vehicle control unit through analysis of a driving behavior rationality analysis module; the hub motor controller controls the rotating speed of the hub motor according to the acceleration signal, and the magnitude of the acceleration signal represents the acceleration speed of the hub motor; the steering command signal is transmitted to the steer-by-wire controller through the vehicle controller, the steer-by-wire controller controls the turning angle of the vehicle according to the steering signal, and the magnitude of the steering signal represents the magnitude of the steering angle of the vehicle; the braking command signal is transmitted to the braking controller through the vehicle control unit, and the braking controller brakes the vehicle according to the braking signal, wherein the magnitude of the braking signal represents the magnitude of the braking force.
Further, the vehicle control unit obtains the rotating speed of the hub motor through a sensor, and the rotating speed of the hub motor is obtained through the sensor
Figure BDA0003410211420000078
Converting the speed into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle control unit acquires a vehicle steering corner through a steering sensor and displays the size of the corner on an instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the vehicle control unit obtains the electric quantity information of the battery through the battery management system and displays the electric quantity of the battery on the instrument panel.
Example 3
When the automobile normally runs on the asphalt pavement, when a driver sends out an automobile brain wave command for accelerating running, steering or braking, the brain wave signal sensor transmits the acquired driver brain wave signal to the Butterworth band-pass filterFiltering out brain wave signals with the frequency range of 8-30HZ by a Butterworth band-pass filter, extracting the brain wave signals after filtering through AR model spectrum estimation characteristics, extracting brain wave signals of automobile motion instructions, obtaining instruction signals of automobile driving through normalization processing, and finally obtaining instruction signals transmitted to the whole automobile controller through analysis of a driving behavior rationality analysis module; the hub motor controller controls the rotating speed of the hub motor according to the acceleration signal, and the magnitude of the acceleration signal represents the acceleration speed of the hub motor; the steering command signal is transmitted to the steer-by-wire controller through the vehicle controller, the steer-by-wire controller controls the turning angle of the vehicle according to the steering signal, and the magnitude of the steering signal represents the magnitude of the steering angle of the vehicle; the braking command signal is transmitted to the braking controller through the vehicle control unit, and the braking controller brakes the vehicle according to the braking signal, wherein the magnitude of the braking signal represents the magnitude of the braking force. In addition, the vehicle control unit acquires the rotating speed of the hub motor through a sensor
Figure BDA0003410211420000081
Converting the speed into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle control unit acquires a vehicle steering corner through a steering sensor and displays the size of the corner on an instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the vehicle control unit obtains the electric quantity information of the battery through the battery management system and displays the electric quantity of the battery on the instrument panel.
When the automobile runs on the road with the speed limit of 60km/h, and the speed u at the time meets the expression
Figure BDA0003410211420000082
At the moment, the driver gives an electroencephalogram signal for accelerating driving, and the electroencephalogram signal is filtered by a Butterworth filter, subjected to AR model spectrum estimation feature extraction and normalization processing, and finally subjected to an instruction signal transmitted to the vehicle control unit; however, at this time, since the vehicle is about to run at an overspeed and the acceleration condition is not satisfied, the driving behavior is appropriateThe rational analysis module can think that the electroencephalogram signal of the driving vehicle is unreasonable, and reminds the driver of the unreasonable reason of the electroencephalogram signal of the driving vehicle, namely that the current road speed limit is 60km/h and the driver needs to pay attention to the speed, through the reminding device.
The present invention has been described in terms of specific examples, which are provided to aid understanding of the invention and are not intended to be limiting. For a person skilled in the art to which the invention pertains, several simple deductions, modifications or substitutions may be made according to the idea of the invention.

Claims (7)

1. An intelligent automobile driving system based on brain waves is characterized by comprising a brain wave signal sensor, a Butterworth band-pass filter, an AR model spectrum estimation feature extraction module, a normalization processing module, a driving behavior rationality analysis module and a reminding device, wherein the brain wave signal sensor is connected with the Barterworth band-pass filter;
the brain wave signal sensor is used for collecting brain wave signals of a human brain for judging how to drive the vehicle in the next step according to the external environment and the driving condition of the vehicle;
the Butterworth band-pass filter is used for performing band-pass filtering with 10-order Butterworth frequency range of 8-30HZ on brain wave signal data obtained by the brain wave signal sensor to obtain a vehicle motion signal generated by a driver;
the AR model spectrum estimation feature extraction module is used for extracting maximum differentiation different types of electroencephalogram signals from the filtered electroencephalogram signals through AR model spectrum estimation features, and extracting a feature vector effective for driving a vehicle; wherein, the AR model is:
Figure FDA0003410211410000011
in the formula (I), the compound is shown in the specification,
Figure FDA0003410211410000012
is a predicted value of the signal sample value x (n); c. CpjIs a weight parameter; p is the order of the model, x (n) is the nth sample value;
ep(n) is the forward error of the AR model, representing the deviation between the predicted and actual values:
Figure FDA0003410211410000013
namely:
Figure FDA0003410211410000014
taking Z transform, converting from time domain to frequency domain:
Figure FDA0003410211410000015
therefore, the calculation formula for the power spectrum estimation of the AR model is:
Figure FDA0003410211410000016
wherein, w is angular frequency and is collected from brain wave signals; j is an imaginary number;
the normalization processing module is used for performing normalization processing on the data of the AR model spectral estimation feature extraction module to obtain an electroencephalogram command for driving a vehicle; wherein, the normalization processing formula is as follows:
Figure FDA0003410211410000017
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the strength of acceleration, steering and braking signals;
the driving behavior reasonability analysis module is used for judging whether a driving electroencephalogram signal made by a driver is reasonable according to sensor information obtained by a sensor mounted on a vehicle, if so, transmitting the signal to the vehicle control unit, and the vehicle control unit transmits the obtained signal to a bottom actuator; if the signal is not reasonable, the signal is transmitted to the reminding device.
2. The brain wave-based intelligent driving system for an automobile according to claim 1, wherein the vehicle-mounted sensors include a camera, a millimeter wave radar, a speed sensor, an acceleration sensor, a steering angle sensor; the pedestrian, surrounding vehicles and road condition information are identified through the camera and the millimeter wave radar sensor, and the vehicle running state information is obtained through the speed sensor, the acceleration sensor and the steering angle sensor of the vehicle.
3. The brain wave-based intelligent driving system for automobiles of claim 1, wherein the reminding device comprises a voice reminding device and/or a light reminding device, when the driving behavior rationality analysis module judges that the electroencephalogram signal is unreasonable, the reason why the electroencephalogram signal for driving the automobile is unreasonable is fed back to the driver through the voice and/or the light signal, and the driver is reminded to make a correct driving signal and give a proper suggestion to the driver.
4. The brain wave-based intelligent driving system for the automobile according to claim 1, wherein the vehicle control unit processes the acquired brain electrical signals and then respectively transmits the processed brain electrical signals to the electric power steering system, the four hub motors and the electronic parking braking system, and the vehicle makes corresponding motions according to the signals; meanwhile, the electric power steering system feeds back the steering angle to the vehicle control unit and displays the steering angle through an instrument panel; the rotating speed and the torque of the four hub motors are fed back to the whole vehicle controller and are displayed through an instrument panel; the electronic parking braking system feeds back the braking state to the vehicle control unit and displays whether braking is carried out or not through an instrument.
5. A control method of an intelligent automobile driving system based on brain waves is characterized by comprising the following steps:
step S1, collecting a brain wave signal of a driver through a brain wave signal sensor, and transmitting the obtained brain wave signal of the driver to a Butterworth band-pass filter;
s2, filtering out brain wave signals with the frequency range of 8-30HZ by a Butterworth band-pass filter to obtain vehicle motion signals generated by a driver;
s3, extracting the brain wave signals after filtering through AR model spectrum estimation features, and extracting the brain wave signals of the automobile motion instructions; wherein, the AR model is:
Figure FDA0003410211410000021
in the formula (I), the compound is shown in the specification,
Figure FDA0003410211410000022
is a predicted value of the signal sample value x (n); c. CpjIs a weight parameter; p is the order of the model, x (n) is the nth sample value;
ep(n) is the forward error of the AR model, representing the deviation between the predicted and actual values:
Figure FDA0003410211410000023
namely:
Figure FDA0003410211410000031
taking Z transform, converting from time domain to frequency domain:
Figure FDA0003410211410000032
therefore, the calculation formula for the power spectrum estimation of the AR model is:
Figure FDA0003410211410000033
wherein, w is angular frequency and is collected from brain wave signals; j is an imaginary number;
step S4, obtaining an automobile driving instruction signal through normalization processing; wherein, the normalization processing formula is as follows:
Figure FDA0003410211410000034
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the strength of acceleration, steering and braking signals;
and step S5, obtaining a command signal transmitted to the vehicle control unit through analysis of the driving behavior rationality analysis module.
6. The method for controlling an intelligent driving system of an automobile based on brain waves of claim 5, wherein the acceleration command signal is transmitted to the in-wheel motor controller through the vehicle control unit in step S5, the in-wheel motor controller controls the rotation speed of the in-wheel motor according to the acceleration signal, and the magnitude of the acceleration signal represents the acceleration speed of the in-wheel motor; the steering command signal is transmitted to the steer-by-wire controller through the vehicle controller, the steer-by-wire controller controls the turning angle of the vehicle according to the steering signal, and the magnitude of the steering signal represents the magnitude of the steering angle of the vehicle; the braking command signal is transmitted to the braking controller through the vehicle control unit, and the braking controller brakes the vehicle according to the braking signal, wherein the magnitude of the braking signal represents the magnitude of the braking force.
7. The method for controlling the brain wave-based intelligent driving system of an automobile according to claim 5, wherein the vehicle control unit obtains the rotation speed of the hub motor through a sensor
Figure FDA0003410211410000035
Converting the speed into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle control unit acquires a vehicle steering corner through a steering sensor and displays the size of the corner on an instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the vehicle control unit obtains the electric quantity information of the battery through the battery management system and displays the electric quantity of the battery on the instrument panel.
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