CN114228724B - Intelligent automobile driving system based on brain waves and control method - Google Patents

Intelligent automobile driving system based on brain waves and control method Download PDF

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CN114228724B
CN114228724B CN202111525461.7A CN202111525461A CN114228724B CN 114228724 B CN114228724 B CN 114228724B CN 202111525461 A CN202111525461 A CN 202111525461A CN 114228724 B CN114228724 B CN 114228724B
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vehicle
brain wave
signal
signals
driving
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CN114228724A (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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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W40/09—Driving style or behaviour
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A61B5/372—Analysis of electroencephalograms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
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    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
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    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/18—Conjoint control of vehicle sub-units of different type or different function including control of braking systems
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    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
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    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/24—Conjoint control of vehicle sub-units of different type or different function including control of energy storage means
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    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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    • B60—VEHICLES IN GENERAL
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    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
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    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • B60W2050/143—Alarm means
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    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
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    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/408—Radar; Laser, e.g. lidar
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    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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Abstract

An intelligent driving system of an automobile based on brain waves and a control method thereof, wherein the system comprises a brain wave signal sensor for acquiring brain wave signals of the brain of a person; the Butterworth band-pass filter is used for carrying out band-pass filtering with the 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 the electroencephalogram signals of different types with maximum differentiation through the AR model spectrum estimation features and extracting feature vectors effective for driving the vehicle; the normalization processing module is used for carrying out normalization processing on the data of the AR model spectrum estimation characteristic extraction module to obtain an electroencephalogram command of a driving vehicle; and the driving behavior rationality analysis module is used for judging whether the driving brain electrical signals made by the driver are reasonable or not according to the sensor information obtained by the sensors installed on the vehicle. The system can release the limbs of the driver, so that the driver can feel easier to drive the automobile.

Description

Intelligent automobile driving system based on brain waves and control method
Technical Field
The application 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 art are used for reminding a driver through signals such as lamplight, sound, seat and backrest vibration when the driver is tired, attentive and the like by detecting brain wave signals of the driver, so that the driver is attentive, and dangerous situations are avoided. Such brain wave based vehicle systems are mainly based on driver safety, and their main driving operations are also accomplished through the driver's limbs. In addition, there is a signal for braking a vehicle, which is generated based on brain waves of a driver, and the signal is processed to realize braking of the vehicle. The vehicle system based on brain waves can enable the vehicle to be braked through brain wave signals, and part of limb operation of a driver is relieved. However, the driving modes such as acceleration, steering, uniform speed, reversing and the like cannot be realized through the brain wave signals of the driver.
In recent years, intelligent driving technology is rapidly developed, and a man-machine interaction system has various interaction methods and modes, for example, a four-wheel independent driving intelligent trolley system controlled by brain waves and a control method thereof are disclosed in patent CN107065850A, and the brain wave signals are processed and then run by using an STM32 controller, so that the movement of the four-wheel trolley is realized by collecting the brain wave signals and passing through four direct current motors. However, since steering braking and the like are performed by a direct current motor, control accuracy is hardly ensured, and a control method thereof is hardly used in a passenger car with an operating mechanism such as a steering wheel, a brake pedal and the like.
Disclosure of Invention
The application aims to provide an intelligent automobile driving system based on brain waves, which can release limbs of a driver, so that the driver can feel easier to drive an automobile, and can also well assist disabled people in driving the automobile, so that the disabled people experience the pleasure of driving the automobile while using the automobile to replace walking.
In order to achieve the above purpose, the application adopts the following technical scheme:
an intelligent driving system of an automobile based on brain waves comprises a brain wave signal sensor, a Butterworth band-pass filter, an AR model spectrum estimation characteristic 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 the vehicle runs in the next step according to the external environment and the running condition of the vehicle;
the Butterworth band-pass filter is used for carrying out band-pass filtering with the 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 the electroencephalogram signals of different types with maximum differentiation through the AR model spectrum estimation features and extracting feature vectors effective for driving the vehicle; wherein, the AR model is:
in the method, in the process of the application,is a predicted value of the signal sample value x (n); c pj Is a weight parameter; p is the order of the model, and x (n) is the nth sample value;
e p (n) is a forward error of the AR model, representing a deviation between the predicted value and the actual value:
namely:
taking the Z transform, and converting from the time domain to the frequency domain:
therefore, the calculation formula for the power spectrum estimation of the AR model is:
wherein w is angular frequency and is acquired from brain wave signals; j is an imaginary number;
the normalization processing module is used for carrying out normalization processing on the data of the AR model spectrum estimation characteristic extraction module to obtain an electroencephalogram command of a driving vehicle; wherein, the normalization processing formula is:
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the intensity of acceleration, steering and braking signals;
the driving behavior rationality analysis module is used for judging whether the driving electroencephalogram signals made by the driver are reasonable according to the sensor information obtained by the sensors installed on the vehicle, if the electroencephalogram signals are reasonable, the driving behavior rationality analysis module transmits the driving electroencephalogram signals to the whole vehicle controller, and the whole vehicle controller transmits the obtained signals to the bottom layer executor; if the signal is not reasonable, the signal is transmitted to the reminding device.
As a preferred aspect of the present application, the vehicle-mounted sensor includes a camera, a millimeter wave radar, a speed sensor, an acceleration sensor, a steering angle sensor; pedestrian, surrounding vehicles and road condition information are identified through the cameras and the millimeter wave radar sensors, and vehicle running state information is obtained through the speed sensor, the acceleration sensor and the steering angle sensor of the vehicle.
As the preferable mode of the application, the reminding device comprises a sound reminding device and/or a light reminding device, when the driving behavior rationality analysis module judges that the electroencephalogram signal is unreasonable, the reason of unreasonable electroencephalogram signal of the driving vehicle is fed back to the driver through sound and/or light signals, the driver is reminded to make a correct driving signal, and meanwhile, the driver is properly suggested.
As the optimization of the application, the whole vehicle controller processes the obtained brain electrical signals and then respectively transmits the brain electrical signals to an electric power steering system, four hub motors and an electronic parking brake system, and the vehicle makes corresponding motions according to the signals; meanwhile, the electric power steering system feeds the steering angle back to the whole vehicle controller and displays the steering angle through an instrument panel; the four hub motors feed the rotating speed and the torque back to the whole vehicle controller and display the rotating speed and the torque through an instrument panel; the electronic parking brake system feeds back the braking state of the electronic parking brake system to the whole vehicle controller and displays whether braking is performed or not through an instrument.
Another object of the present application is to provide a control method of an intelligent driving system of an automobile based on brain waves, the method comprising the steps of:
step S1, acquiring brain wave signals of a driver through a brain wave signal sensor, and transmitting the acquired brain wave signals of the driver to a Butterworth band-pass filter;
s2, filtering brain wave signals with the frequency range of 8-30HZ by using a Butterworth band-pass filter to obtain vehicle motion signals generated by a driver;
s3, extracting the brain wave signals of the automobile movement instructions through AR model spectrum estimation characteristics of the filtered brain wave signals; wherein, the AR model is:
in the method, in the process of the application,is a predicted value of the signal sample value x (n); c pj Is a weight parameter; p is the order of the model, and x (n) is the nth sample value;
e p (n) is a forward error of the AR model, representing a deviation between the predicted value and the actual value:
namely:
taking the Z transform, and converting from the time domain to the frequency domain:
therefore, the calculation formula for the power spectrum estimation of the AR model is:
wherein w is angular frequency and is acquired from brain wave signals; j is an imaginary number;
s4, obtaining an instruction signal for automobile running through normalization processing; wherein, the normalization processing formula is:
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the intensity of acceleration, steering and braking signals;
and S5, analyzing by a driving behavior rationality analysis module to obtain a command signal transmitted to the whole vehicle controller.
As the optimization of the application, the accelerating instruction signal in the step S5 is transmitted to the hub motor controller through the whole vehicle controller, the hub motor controller controls the rotating speed of the hub motor according to the accelerating signal, and the size of the accelerating signal represents the accelerating speed of the hub motor; the steering command signal is transmitted to a steer-by-wire controller through the whole 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 whole vehicle controller, 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 whole vehicle controller obtains the rotating speed of the hub motor through a sensor, and the rotating speed is obtained through the sensorConverting into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle controller obtains the steering angle of the vehicle through the steering sensor and displays the angle on the instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the whole vehicle controller 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.
The application has the advantages and positive effects that: the application relates to an intelligent driving system of an automobile based on brain waves, which is characterized in that brain wave signals of a driver are acquired through a brain wave signal sensor, vehicle motion signals generated by the driver are obtained through a Butterworth band-pass filter, different types of brain signals with maximum differentiation are extracted through AR model spectrum estimation characteristics, and feature vectors effective for driving the vehicle are extracted; and finally, obtaining an electroencephalogram command for driving the vehicle through normalization processing. The system is characterized in that the acquired reasonable electroencephalogram signals, external environment signals such as a driving road surface and the like and vehicle signals are transmitted to a whole vehicle controller VCU, the whole vehicle controller processes the acquired signals and transmits the processed signals to a steering motor controller, a braking system controller and a hub motor controller, so that the driving of the vehicle is completed, the development of the system can release limbs of a driver, the driver can feel easier when driving the vehicle, and meanwhile, the limb of the driver can be completely released, so that the disabled can drive the vehicle, and the disabled can feel fun of driving the vehicle when using the vehicle to replace the vehicle.
Drawings
FIG. 1 is a block diagram of an intelligent driving system for an automobile based on brain waves;
fig. 2 is a schematic diagram of a brain wave signal vehicle control strategy.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1
Referring to fig. 1 and 2, the intelligent driving system for the automobile based on brain waves provided by the application comprises a brain wave signal sensor, a butterworth band-pass filter, an AR model spectrum estimation characteristic 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 the vehicle runs in the next step according to the external environment and the running condition of the vehicle;
the Butterworth band-pass filter is used for carrying out band-pass filtering with the 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 the electroencephalogram signals of different types with maximum differentiation through the AR model spectrum estimation features and extracting feature vectors effective for driving the vehicle; wherein, the AR model is:
in the method, in the process of the application,is a predicted value of the signal sample value x (n); c pj Is a weight parameter; p is the order of the model, and x (n) is the nth sample value;
e p (n) is a forward error of the AR model, representing a deviation between the predicted value and the actual value:
namely:
taking the Z transform, and converting from the time domain to the frequency domain:
therefore, the calculation formula for the power spectrum estimation of the AR model is:
wherein w is angular frequency and is acquired from brain wave signals; j is an imaginary number;
the normalization processing module is used for carrying out normalization processing on the data of the AR model spectrum estimation characteristic extraction module to obtain an electroencephalogram command of a driving vehicle; wherein, the normalization processing formula is:
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the intensity of acceleration, steering and braking signals;
the driving behavior rationality analysis module is used for judging whether driving electroencephalogram signals made by a driver are reasonable according to sensor information obtained by sensors installed on a vehicle, if the electroencephalogram signals are reasonable, the signals are transmitted to the whole vehicle controller, the whole vehicle controller transmits the obtained signals to a bottom layer actuator, and the bottom layer actuator feeds back signals such as vehicle speed, steering, electric quantity and the like to the whole vehicle controller; if the signal is unreasonable, the signal is transmitted to the reminding device; the electroencephalogram signals of the accelerated running of the automobile made by the driver are judged to be unreasonable when the following conditions exist: i.e. overspeed driving, complex road conditions (tunnels, depressions, narrow bridges, etc.), obstacles on oncoming vehicles and front roads, etc.; the electroencephalogram signal of the steering running of the automobile made by the driver is judged to be unreasonable when the following conditions exist: the vehicle is driven with an obstacle in the steering direction, an incoming vehicle in the steering direction, etc.
The sensors arranged 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 pedestrians, surrounding vehicles and road condition information through sensors such as cameras and millimeter wave radars, and obtains vehicle running state information 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 driving behavior rationality analysis module judges that the electroencephalogram signal is unreasonable, the reason that the electroencephalogram signal of the driving vehicle is unreasonable is fed back to the driver through sound and/or light signals, the driver is reminded to make a correct driving signal, and meanwhile appropriate advice is given to the driver.
Fig. 2 is a schematic diagram of a vehicle control strategy based on brain wave signals, and it can be seen from fig. 2 that reasonable brain wave signals obtained through a driving behavior rationality analysis module are transmitted to a vehicle control unit, the vehicle control unit determines the obtained signals and transmits the signals to an electric power steering system EPS, four hub motors, an electronic parking brake system EPB, a battery management system BMS and the like, and the vehicle makes corresponding motions according to the signals. Meanwhile, the electric power steering system feeds the steering angle back to the whole vehicle controller and displays the steering angle through an instrument panel; the four hub motors feed the rotating speed and the torque back to the whole vehicle controller and display the rotating speed and the torque through an instrument panel; the electronic parking brake system feeds back the braking state of the electronic parking brake system to the whole vehicle controller and displays whether braking is performed or not through an instrument panel; the battery management system feeds the battery electric quantity back to the whole vehicle controller and 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 application provides a control method of an intelligent driving system of an automobile based on brain waves, which comprises the following steps:
step S1, acquiring brain wave signals of a driver through a brain wave signal sensor, and transmitting the acquired brain wave signals of the driver to a Butterworth band-pass filter;
s2, filtering brain wave signals with the frequency range of 8-30HZ by using a Butterworth band-pass filter to obtain vehicle motion signals generated by a driver;
s3, extracting the brain wave signals of the automobile movement instructions through AR model spectrum estimation characteristics of the filtered brain wave signals; wherein, the AR model is:
in the method, in the process of the application,is a predicted value of the signal sample value x (n); c pj Is a weight parameter; p is the order of the model, and x (n) is the nth sample value;
e p (n) is a forward error of the AR model, representing a deviation between the predicted value and the actual value:
namely:
taking the Z transform, and converting from the time domain to the frequency domain:
therefore, the calculation formula for the power spectrum estimation of the AR model is:
wherein w is angular frequency and is acquired from brain wave signals; j is an imaginary number;
s4, obtaining an instruction signal for automobile running through normalization processing; wherein, the normalization processing formula is:
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the intensity of acceleration, steering and braking signals;
s5, analyzing by a driving behavior rationality analysis module to obtain a command signal transmitted to the whole vehicle controller; the speed-up command signal is transmitted to the hub motor controller through the whole vehicle controller, the hub motor controller controls the rotating speed of the hub motor according to the speed-up signal, and the speed-up signal represents the speed of the hub motor; the steering command signal is transmitted to a steer-by-wire controller through the whole 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 whole vehicle controller, 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 whole vehicle controller obtains the rotating speed of the hub motor through a sensor, and the rotating speed of the hub motor passes throughConverting into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle controller obtains the steering angle of the vehicle through the steering sensor and displays the angle on the instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the whole vehicle controller 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 an automobile normally runs on an asphalt pavement, and at the moment, when a driver sends out brain wave instructions of accelerating running, steering or braking of the automobile, the brain wave signal sensor transmits the acquired brain wave signals of the driver to a Butterworth band-pass filter, the Butterworth band-pass filter filters brain wave signals with the frequency range of 8-30HZ, the filtered brain wave signals are extracted through AR model spectrum estimation characteristics, brain wave signals of automobile movement instructions are extracted, instruction signals of automobile running are obtained through normalization processing, and finally instruction signals transmitted to a whole vehicle controller are obtained through analysis of a driving behavior rationality analysis module; the speed-up command signal is transmitted to the hub motor controller through the whole vehicle controller, the hub motor controller controls the rotating speed of the hub motor according to the speed-up signal, and the speed-up signal represents the speed of the hub motor; the steering command signal is transmitted to the drive-by-wire through the whole vehicle controllerThe steering controller is used for controlling the turning angle of the vehicle according to the steering signal, and the magnitude of the steering signal represents the magnitude of the turning angle of the vehicle; the braking command signal is transmitted to the braking controller through the whole vehicle controller, 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 whole vehicle controller obtains the rotating speed of the hub motor through a sensor, and the rotating speed of the hub motor is obtained throughConverting into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle controller obtains the steering angle of the vehicle through the steering sensor and displays the angle on the instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the whole vehicle controller 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 surface with the speed limit of 60km/h, and the speed u of the automobile meets the expressionAt the moment, the driver gives an electroencephalogram signal for accelerating running, and the electroencephalogram signal is filtered by a Butterworth filter, extracted by AR model spectrum estimation characteristics and normalized to finally obtain an instruction signal transmitted to the whole vehicle controller; however, at this time, due to the fact that overspeed running is about to occur and the acceleration condition is not met, the driving behavior rationality analysis module can consider that the electroencephalogram signal of the driving vehicle is unreasonable, and reminds the driver of the unreasonable electroencephalogram signal of the driving vehicle through the reminding device because of '60 km/h of the current road speed limit, please pay attention to the vehicle speed'.
The foregoing description of the application has been presented for purposes of illustration and description, and is not intended to be limiting. Several simple deductions, modifications or substitutions may also be made by a person skilled in the art to which the application pertains, based on the idea of the application.

Claims (7)

1. The 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 characteristic 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 the vehicle runs in the next step according to the external environment and the running condition of the vehicle;
the Butterworth band-pass filter is used for carrying out band-pass filtering with the 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 the electroencephalogram signals of different types with maximum differentiation through the AR model spectrum estimation features and extracting feature vectors effective for driving the vehicle; wherein, the AR model is:
in the method, in the process of the application,is a predicted value of the signal sample value x (n); c pj Is a weight parameter; p is the order of the model, and x (n) is the nth sample value;
e p (n) is a forward error of the AR model, representing a deviation between the predicted value and the actual value:
namely:
taking the Z transform, and converting from the time domain to the frequency domain:
therefore, the calculation formula for the power spectrum estimation of the AR model is:
wherein w is angular frequency and is acquired from brain wave signals; j is an imaginary number;
the normalization processing module is used for carrying out normalization processing on the data of the AR model spectrum estimation characteristic extraction module to obtain an electroencephalogram command of a driving vehicle; wherein, the normalization processing formula is:
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the intensity of acceleration, steering and braking signals;
the driving behavior rationality analysis module is used for judging whether the driving electroencephalogram signals made by the driver are reasonable according to the sensor information obtained by the sensors installed on the vehicle, if the electroencephalogram signals are reasonable, the driving behavior rationality analysis module transmits the driving electroencephalogram signals to the whole vehicle controller, and the whole vehicle controller transmits the obtained signals to the bottom layer executor; if the signal is not reasonable, the signal is transmitted to the reminding device.
2. The brain wave based automotive intelligent driving system according to claim 1, wherein said vehicle-mounted sensors include a camera, millimeter wave radar, speed sensor, acceleration sensor, steering angle sensor; pedestrian, surrounding vehicles and road condition information are identified through the cameras and the millimeter wave radar sensors, and 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 according to claim 1, wherein the reminding device comprises a sound reminding device and/or a light reminding device, when the driving behavior rationality analysis module judges that the brain wave signals are unreasonable, the reason for unreasonable brain wave signals of the driving vehicle is fed back to the driver through the sound and/or the light signals, the driver is reminded to make a correct driving signal, and meanwhile, the driver is properly suggested.
4. The intelligent driving system of the automobile based on brain waves according to claim 1, wherein the whole automobile controller processes the obtained brain waves and then transmits the processed brain waves to an electric power steering system, four hub motors and an electronic parking brake system respectively, and the automobile makes corresponding motions according to the signals; meanwhile, the electric power steering system feeds the steering angle back to the whole vehicle controller and displays the steering angle through an instrument panel; the four hub motors feed the rotating speed and the torque back to the whole vehicle controller and display the rotating speed and the torque through an instrument panel; the electronic parking brake system feeds back the braking state of the electronic parking brake system to the whole vehicle controller and displays whether braking is performed or not through an instrument.
5. The control method of the intelligent driving system of the automobile based on the brain waves is characterized by comprising the following steps of:
step S1, acquiring brain wave signals of a driver through a brain wave signal sensor, and transmitting the acquired brain wave signals of the driver to a Butterworth band-pass filter;
s2, filtering brain wave signals with the frequency range of 8-30HZ by using a Butterworth band-pass filter to obtain vehicle motion signals generated by a driver;
s3, extracting the brain wave signals of the automobile movement instructions through AR model spectrum estimation characteristics of the filtered brain wave signals; wherein, the AR model is:
in the method, in the process of the application,is a predicted value of the signal sample value x (n); c pj Is a weight parameter; p is the order of the model, and x (n) is the nth sample value;
e p (n) is a forward error of the AR model, representing a deviation between the predicted value and the actual value:
namely:
taking the Z transform, and converting from the time domain to the frequency domain:
therefore, the calculation formula for the power spectrum estimation of the AR model is:
wherein w is angular frequency and is acquired from brain wave signals; j is an imaginary number;
s4, obtaining an instruction signal for automobile running through normalization processing; wherein, the normalization processing formula is:
after normalization processing, brain wave signals are converted into numbers between 0 and 1, and the magnitude of the numerical values represents the intensity of acceleration, steering and braking signals;
and S5, analyzing by a driving behavior rationality analysis module to obtain a command signal transmitted to the whole vehicle controller.
6. The control method of the intelligent driving system of the automobile based on brain waves as claimed in claim 5, wherein in the step S5, the acceleration command signal is transmitted to the hub motor controller through the whole automobile controller, the hub motor controller controls the rotation 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 a steer-by-wire controller through the whole 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 whole vehicle controller, 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 control method of the intelligent driving system of the automobile based on brain waves as claimed in claim 5, wherein the whole automobile controller obtains the rotating speed of the hub motor through a sensor, and the control method comprises the following steps ofConverting into a vehicle speed and displaying the vehicle speed on an instrument panel; the vehicle controller obtains the steering angle of the vehicle through the steering sensor and displays the angle on the instrument panel; the vehicle control unit acquires vehicle braking information through a braking sensor and displays a braking state on an instrument panel; the whole vehicle controller 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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