CN111968341A - Fatigue driving detection system and method - Google Patents
Fatigue driving detection system and method Download PDFInfo
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Abstract
The invention relates to the technical field of fatigue driving detection, and particularly discloses a fatigue driving detection system, which comprises: the system comprises a driver physiological characteristic detection device, a vehicle driving data acquisition device, a fatigue driving data model device and a fatigue state display and early warning device; the driver physiological characteristic detection device is used for measuring the breathing and heart rate change conditions of the driver; the vehicle running data acquisition device is used for acquiring vehicle running state information and driving state information of a driver; the fatigue driving data model device is used for establishing a vehicle driving state and fatigue driving situation data model according to the breathing and heart rate change condition of a driver and the driving state information of the driver; the fatigue state display and early warning device is used for displaying the fatigue state and giving out early warning prompts to the fatigue driving state. The invention also discloses a fatigue driving detection method. The fatigue driving detection system provided by the invention avoids direct contact with a driver, and is high in usability.
Description
Technical Field
The invention relates to the technical field of fatigue driving detection, in particular to a fatigue driving detection system and a fatigue driving detection method.
Background
Along with the rapid development of the transportation industry, the road traffic accidents therewith also show an increasing trend, fatigue driving is already taken as a main hidden danger of the traffic accidents, the research on the fatigue detection technology of drivers has an important significance for preventing the traffic accidents, and a plurality of detection devices for fatigue driving also appear aiming at the fatigue driving. The fatigue driving detection is mainly based on the physiological parameter characteristics or visual characteristics of a driver, and is combined with the behavior characteristics of the driver in fatigue to detect the fatigue index of the driver in real time, so that whether fatigue occurs is detected. In the prior art, mainly with non-contact fatigue detection technique as the main, infer driver's fatigue state through driver's facial feature based on visual identification, eye signal, head motility etc. the advantage of this kind of mode is convenient to use, does not need the driver to have any extra operation, but this kind of detection based on vision receives external environment influences such as light, weather more easily, and the driver can not wear shelter such as sunglasses, gauze mask moreover, and the camera directly shoots the problem that has the privacy aspect to the driver simultaneously. Another contact type fatigue detection method needs a driver to wear a body-contacting sensor to acquire physiological signals such as electroencephalogram, electrocardiogram, respiration and skin electrical conduction and extract fatigue indexes of the driver, the physiological signals obtained in the method are directly from a human body, information can be detected more accurately and reliably, but measurement noise caused by body actions of the driver can also exist, and the driver can feel uncomfortable after wearing the sensors, so that the sensor has a conflict psychology and is less in use.
Disclosure of Invention
The invention provides a fatigue driving detection system and a fatigue driving detection method, which solve the problems of inaccurate detection mode and the need of contact to realize detection in the related technology.
As a first aspect of the present invention, there is provided a fatigue driving detection system, comprising: the system comprises a driver physiological characteristic detection device, a vehicle driving data acquisition device, a fatigue driving data model device and a fatigue state display and early warning device, wherein the driver physiological characteristic detection device and the vehicle driving data acquisition device are both in communication connection with the fatigue driving data model device, and the fatigue driving data model device is in communication connection with the fatigue state display and early warning device;
the driver physiological characteristic detection device is used for measuring the breathing and heart rate change conditions of a driver;
the vehicle running data acquisition device is used for acquiring vehicle running state information and driving state information of a driver;
the fatigue driving data model device is used for establishing a vehicle driving state and fatigue driving situation data model according to the breathing and heart rate change condition of a driver and the driving state information of the driver, so that the fatigue driving state can be judged, and the active prediction control of the fatigue driving state can be realized;
the fatigue state display and early warning device is used for displaying the fatigue state and giving out early warning prompts to the fatigue driving state.
Further, the driver physiological characteristic detection device includes: the device comprises a millimeter wave signal transmitting unit, a transmitting signal control unit, a millimeter wave signal receiving unit, a received signal preprocessing unit and a detected data characteristic identification unit, wherein the millimeter wave signal transmitting unit is in communication connection with the transmitting signal control unit, the millimeter wave signal receiving unit is in communication connection with the received signal preprocessing unit, the received signal preprocessing unit is in communication connection with the transmitting signal control unit, and the detected data characteristic identification unit is in communication connection with the received signal preprocessing unit;
the millimeter wave signal transmitting unit is used for transmitting a millimeter wave detection signal to the outside;
the transmission signal control unit is used for controlling the signal characteristics of the millimeter wave detection signal transmitted by the millimeter wave signal transmission unit;
the millimeter wave signal receiving unit is used for receiving millimeter wave echo signals reflected by a driver;
the received signal preprocessing unit is used for performing signal processing on the millimeter wave echo signal reflected by the driver to obtain a target signal in a detection range;
the detection data characteristic identification unit is used for extracting effective target signals of the target signals in the detection range to obtain detection results of the respiration and heart rate signals.
Further, the vehicle travel data acquisition device includes: the driving habit data acquisition unit is used for acquiring relevant parameters of vehicle running.
Further, the vehicle driving data acquisition device further includes: and the automobile bus communication control unit is in communication connection with the driving habit data acquisition unit and is used for realizing the communication interaction between the driving habit data acquisition unit and an automobile bus.
Further, the relevant parameters of the vehicle driving include: vehicle speed, steering wheel angle, and acceleration state.
Further, the fatigue driving data model device includes: the fatigue driving situation data model is in communication connection with the data model analysis and calculation unit,
the fatigue driving situation data model is used for carrying out information fusion on the breathing and heart rate change condition of the driver and the driving state information of the driver, and establishing a fatigue driving situation data model;
the data model analyzing and calculating unit is used for providing a data calculating platform for analyzing, judging and predicting the fatigue driving situation data model.
As another aspect of the present invention, there is provided a fatigue driving detection method implemented by applying the fatigue driving detection system described above, wherein the method includes:
the driver physiological characteristic detection device transmits millimeter wave signals outwards, receives millimeter wave echo signals reflected by a driver and processes the millimeter wave echo signals to obtain the breathing and heart rate change conditions of the driver;
the vehicle running data acquisition device acquires vehicle running state information and driver's driving state information;
the fatigue driving data model device establishes a fatigue driving situation data model according to the breathing and heart rate change condition of the driver and the driving state information of the driver, and judges the fatigue driving state so as to realize active prediction control on the fatigue driving state;
the fatigue state display and early warning device displays the fatigue state and sends out early warning prompt to the fatigue driving state.
Further, the driver physiological characteristic detection device externally transmits millimeter wave signals, receives millimeter wave echo signals reflected by the driver, processes the millimeter wave echo signals and then obtains the breathing and heart rate change conditions of the driver, and the method comprises the following steps:
the emission signal control unit emits linear frequency modulation millimeter wave signals to the outside through the millimeter wave signal emission unit and carries out signal radiation detection on the chest and abdomen part of the body of the driver;
after the millimeter wave signal receiving unit receives the millimeter wave echo signal reflected by the body of the driver, the millimeter wave signal receiving unit performs gain amplification, analog-to-digital conversion and storage on the signal and sends the signal to the received signal preprocessing unit;
the received signal preprocessing unit carries out one-dimensional Fourier transform processing on the received signal to obtain all target information in a detection distance range, extracts different target signal peak values after the one-dimensional Fourier transform processing through a peak value search algorithm, stores phase information corresponding to the target peak values and evaluates the signal-to-noise ratio of the signal received signal;
the detection data characteristic identification unit carries out digital filtering and noise reduction processing on the preprocessed signals to filter a phase information sequence according to the displacement characteristics of the chest and abdomen surfaces of the human body caused by respiration, removes stray targets and obtains target signal frequency spectrum information;
extracting a respiratory signal according to the characteristic range of the respiratory frequency of the human body;
and (4) carrying out signal processing on the higher harmonics of the respiration signal to separate out a heart rate signal.
Further, the vehicle driving data acquisition device acquires vehicle driving state information and driver's driving state information, and includes:
the automobile bus communication control unit realizes information interaction with an automobile bus through a bus communication control protocol and sends the vehicle running state information to the driving habit acquisition data unit;
the driving habit acquisition data unit acquires and reads the driving condition of the vehicle and the driving state information of the driver to obtain the related driving parameters of the vehicle.
Further, the fatigue driving data model device establishes a fatigue driving situation data model according to the breathing and heart rate change condition of the driver and the driving state information of the driver, and discriminates the fatigue driving state to realize the active predictive control of the fatigue driving state, and the method comprises the following steps:
establishing a fatigue driving situation data model according to the breathing, heart rate and driving habit data of the driver, matching and performing model analysis and calculation by combining a dynamic database of the fatigue driving situation model to obtain a personalized model of the fatigue driving state of the driver, and determining state thresholds and weight coefficients of three characteristic parameters of the breathing, heart rate and driving habit fatigue state;
updating the individualized model data of the fatigue driving state of the driver to a dynamic database of a fatigue driving situation model;
extracting thresholds of respiration, heart rate and driving habit fatigue state according to the fatigue driving state personalized model, and calculating a comprehensive threshold of the comprehensive fatigue state of the driver and the prediction of the variation trend according to the three thresholds and the weight coefficients of the three features in the personalized model;
comparing the comprehensive threshold value and the variation trend value of the comprehensive fatigue state of the driver with the real-time measured characteristic value results of the respiration, the heart rate and the driving habit data of the driver, judging whether the driver belongs to the fatigue driving state, and if so, executing a step of sending out an early warning prompt to the fatigue driving state; if not, displaying the current fatigue state and the change trend prediction information.
The fatigue driving detection system provided by the invention is based on the high phase sensitivity of a millimeter wave radar receiving signal to a micro moving target, detects vibration signals generated by heartbeat and respiratory breath of a human body through millimeter wave signals, calculates and extracts the heartbeat and respiratory physiological signal characteristics of the human body by using a signal processing algorithm, establishes a fatigue driving data model based on an intelligent sensor and an information fusion and extraction technology by combining the change condition of driving habit data, performs real-time calculation and analysis on the driving fatigue model, realizes real-time and accurate detection and analysis on fatigue driving and active prediction of the fatigue state of a driver, and displays and pre-warns according to the detection result of the fatigue state. The fatigue driving detection system can avoid direct contact with a driver, is high in usability, adopts millimeter wave radar for detection, and is strong in anti-interference performance of a measured signal, high in reliability and high in accuracy.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is a block diagram of a fatigue driving detection system according to the present invention.
Fig. 2 is a flowchart of a fatigue driving detection method provided by the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged under appropriate circumstances in order to facilitate the description of the embodiments of the invention herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In this embodiment, a fatigue driving detection system is provided, and fig. 1 is a block diagram of a structure of a fatigue driving detection system provided according to an embodiment of the present invention, as shown in fig. 1, including: the system comprises a driver physiological characteristic detection device 1, a vehicle driving data acquisition device 2, a fatigue driving data model device 3 and a fatigue state display and early warning device 4, wherein the driver physiological characteristic detection device 1 and the vehicle driving data acquisition device 2 are both in communication connection with the fatigue driving data model device 3, and the fatigue driving data model device 3 is in communication connection with the fatigue state display and early warning device 4;
the driver physiological characteristic detection device 1 is used for measuring the breathing and heart rate change condition of a driver;
the vehicle running data acquisition device 2 is used for acquiring vehicle running state information and driving state information of a driver;
the fatigue driving data model device 3 is used for establishing a vehicle driving state and fatigue driving situation data model according to the breathing and heart rate change condition of the driver and the driving state information of the driver, can judge the fatigue driving state and can realize active predictive control of the fatigue driving state;
the fatigue state display and early warning device 4 is used for displaying the fatigue state and giving out early warning prompts to the fatigue driving state.
The fatigue driving detection system provided by the embodiment of the invention is based on the high phase sensitivity of a millimeter wave radar receiving signal to a micro moving target, detects vibration signals generated by heartbeat and respiratory breath of a human body through a millimeter wave signal, calculates and extracts the heartbeat and respiratory physiological signal characteristics of the human body by using a signal processing algorithm, establishes a fatigue driving data model based on an intelligent sensor and an information fusion and extraction technology by combining the change condition of driving habit data, performs real-time calculation and analysis on the driving fatigue model, realizes real-time and accurate detection and analysis on fatigue driving and active prediction of the fatigue state of a driver, and displays and pre-warns according to the detection result of the fatigue state. The fatigue driving detection system can avoid direct contact with a driver, is high in usability, adopts millimeter wave radar for detection, and is strong in anti-interference performance of a measured signal, high in reliability and high in accuracy.
Fig. 1 is a block diagram showing the structure of the fatigue driving detection system according to the present invention. The fatigue driving detection system mainly comprises a driver physiological characteristic detection device 1, a vehicle driving data acquisition device 2, a fatigue driving data model device 3 and a fatigue state display and early warning device 4. The driver physiological characteristic detection device 1 mainly adopts a detection device based on a millimeter wave radar, is mainly used for directly measuring the breathing and heart rate physiological characteristic information of a driver, and can detect the fatigue driving state through the change condition of the breathing and heart rate physiological characteristic information; the vehicle driving data acquisition device 2 is mainly used for interacting with the communication of an automobile bus, reading the vehicle driving condition and the driving condition of a driver, obtaining vehicle driving related parameters such as the speed, the steering wheel angle, the acceleration state and the like, and reflecting the fatigue degree of the driver indirectly and in real time through the driving habit data characteristics; the fatigue driving data model device 3 is mainly used for dynamic model analysis calculation, real-time judgment and prediction of a fatigue driving state, a vehicle driving state and a fatigue driving situation data model are established by fusing physiological characteristic detection information and driving habit data information, and active prediction control of the fatigue driving state can be realized while the fatigue driving state is judged in real time; the result of the analysis and calculation of the fatigue driving data model device 3 can be used for displaying state information and giving an early warning prompt of the fatigue driving state through the fatigue state display and early warning device 4.
Specifically, as shown in fig. 1, the driver physiological characteristic detection apparatus 1 includes: the device comprises a millimeter wave signal transmitting unit 11, a transmitting signal control unit 12, a millimeter wave signal receiving unit 13, a received signal preprocessing unit 14 and a detected data characteristic identifying unit 15, wherein the millimeter wave signal transmitting unit 11 is in communication connection with the transmitting signal control unit 12, the millimeter wave signal receiving unit 13 is in communication connection with the received signal preprocessing unit 14, the received signal preprocessing unit 14 is in communication connection with the transmitting signal control unit 12, and the detected data characteristic identifying unit 15 is in communication connection with the received signal preprocessing unit 14;
the millimeter wave signal transmitting unit 11 is configured to transmit a millimeter wave detection signal to the outside;
the transmission signal control unit 12 is configured to control a signal characteristic of the millimeter wave detection signal transmitted by the millimeter wave signal transmission unit;
the millimeter wave signal receiving unit 13 is configured to receive a millimeter wave echo signal reflected by a driver;
the received signal preprocessing unit 14 is configured to perform signal processing on the millimeter wave echo signal reflected by the driver to obtain a target signal within a detection range;
the detection data feature recognition unit 15 is configured to perform effective target signal extraction on a target signal within a detection range to obtain detection results of respiration and heart rate signals.
Further specifically, as shown in fig. 1, the driver physiological characteristic detection apparatus 1 mainly includes: a millimeter wave signal transmitting unit 11, a transmitting signal control unit 12, a millimeter wave signal receiving unit 13, a received signal preprocessing unit 14, and a detected data feature identifying unit 15. The millimeter wave signal transmitting unit 11 is mainly used for radiating a millimeter wave signal detection signal to the outside by a fatigue driving detection system, so as to realize active signal transmission detection and perception of the chest and abdomen movement characteristics of a driver; the emission signal control unit 12 is mainly used for controlling the millimeter wave signal emission unit 11 and controlling the radiation power, the signal period, the modulation mode, the radiation center frequency and the bandwidth signal parameters of the emission signal; the millimeter wave signal receiving unit 13 is mainly used for receiving millimeter wave signals transmitted by a target, and forms a complete active signal detection transceiving loop with the millimeter wave signal transmitting unit 11; the received signal preprocessing unit 14 is mainly used for performing signal processing on the received millimeter wave signals to extract target information in a detection range, performing amplitude screening on the signals to judge the signal-to-noise ratio of the received signals, and performing feedback adjustment on the transmitted signal control unit 12 according to the signal-to-noise ratio characteristics to optimize the signal-to-noise ratio; the detection data feature recognition unit 15 is mainly used for performing final effective target signal extraction on the preprocessed target signals in combination with the respiratory and heart rate frequency spectrum features to obtain respiratory and heart rate signal detection results.
Specifically, as shown in fig. 1, the vehicle travel data collection device 2 includes: the driving habit data acquisition unit 21 is used for acquiring relevant parameters of vehicle running by the driving habit data acquisition unit 21.
Specifically, the vehicle travel data acquisition device 2 further includes: and the automobile bus communication control unit 22 is used for realizing the communication interaction between the driving habit data acquisition unit 21 and an automobile bus, and the automobile bus communication control unit 22 is in communication connection with the driving habit data acquisition unit 21.
In some embodiments, the vehicle travel related parameters include: vehicle speed, steering wheel angle, and acceleration state.
As shown in fig. 1, the vehicle travel data collection 2 mainly includes: a driving habit acquisition data unit 21 and an automobile bus communication control unit 22; the driving habit acquisition data unit 21 acquires and reads the driving condition of the vehicle and the driving condition of the driver, and obtains parameters related to vehicle driving, such as vehicle speed, steering wheel angle, acceleration state and the like; the vehicle bus communication control unit 22 is mainly used for communication interaction between the driving habit data collecting unit 21 and the vehicle bus.
Specifically, as shown in fig. 1, the fatigue driving data model device 3 includes: a fatigue driving situation data model 31 and a data model analysis and calculation unit 32, wherein the fatigue driving situation data model 31 is connected with the data model analysis and calculation unit 32 in a communication way,
the fatigue driving situation data model 31 is used for carrying out information fusion on the breathing and heart rate change condition of the driver and the driving state information of the driver, and establishing a fatigue driving situation data model;
the data model analyzing and calculating unit 32 is used for providing a data calculating platform for analyzing, judging and predicting the fatigue driving situation data model.
Specifically, as shown in fig. 1, the fatigue driving data model 3 mainly includes: a fatigue driving situation data model 31 and a data model analysis calculation unit 32; the fatigue driving situation data model 31 is mainly used for carrying out information fusion on the respiration and heart rate physiological characteristic information output by the detection data characteristic identification unit 15 and the driving habit data output by the driving habit acquisition data unit 21, establishing a fatigue driving situation data model, and distinguishing a fatigue driving state in real time and carrying out active prediction through the model; the data model analysis and calculation unit 32 is mainly used for providing a data calculation platform for enabling the fatigue driving situation data model 31 to realize analysis, judgment and prediction.
The specific working principle of the fatigue driving detection system provided by the embodiment of the invention is that usually the displacement of the chest and abdomen surface caused by human respiration is 4-12 mm, the displacement of the chest wall caused by heartbeat is 1-2 mm, the respiratory frequency is 0.1-0.5 Hz, and the heartbeat is 0.8-2 Hz, and is matched with the working wavelength and the detection precision of the millimeter wave radar, and the millimeter wave radar can directly penetrate through a non-metal medium to detect the respiration and heart rate vital signs of a human body in a non-contact manner. Meanwhile, in the driving process, the breathing frequency and the heart rate of the driver can also change along with the fatigue state of the driver, and the psychological and physiological burden degree borne by the driver is objectively reflected. On the other hand, the control condition of the driver to the vehicle can be known through vehicle running characteristics such as vehicle speed, steering wheel angle, acceleration state and the like of the vehicle running related parameters, and the fatigue degree of the driver can be reflected indirectly and in real time through analysis of time domain, frequency domain and amplitude domain of the vehicle running characteristic parameters. According to the invention, the millimeter wave radar detection physiological characteristic signals of the respiration and heart rate of the driver and the vehicle running characteristic signals are subjected to information fusion, a fatigue driving state situation data model is established, and high-precision, non-contact early warning and active prediction of the fatigue driving state are realized.
As another embodiment of the present invention, there is provided a fatigue driving detection method implemented by applying the fatigue driving detection system described above, including:
the driver physiological characteristic detection device transmits millimeter wave signals outwards, receives millimeter wave echo signals reflected by a driver and processes the millimeter wave echo signals to obtain the breathing and heart rate change conditions of the driver;
the vehicle running data acquisition device acquires vehicle running state information and driver's driving state information;
the fatigue driving data model device establishes a fatigue driving situation data model according to the breathing and heart rate change condition of the driver and the driving state information of the driver, and judges the fatigue driving state so as to realize active prediction control on the fatigue driving state;
the fatigue state display and early warning device displays the fatigue state and sends out early warning prompt to the fatigue driving state.
Specifically, driver's physiology characteristic detection device launches the millimeter wave signal outward, and the millimeter wave echo signal after receiving the driver reflection obtains driver's breathing and heart rate change condition after handling, includes:
the emission signal control unit emits linear frequency modulation millimeter wave signals to the outside through the millimeter wave signal emission unit and carries out signal radiation detection on the chest and abdomen part of the body of the driver;
after the millimeter wave signal receiving unit receives the millimeter wave echo signal reflected by the body of the driver, the millimeter wave signal receiving unit performs gain amplification, analog-to-digital conversion and storage on the signal and sends the signal to the received signal preprocessing unit;
the received signal preprocessing unit carries out one-dimensional Fourier transform processing on the received signal to obtain all target information in a detection distance range, extracts different target signal peak values after the one-dimensional Fourier transform processing through a peak value search algorithm, stores phase information corresponding to the target peak values and evaluates the signal-to-noise ratio of the signal received signal;
the detection data characteristic identification unit carries out digital filtering and noise reduction processing on the preprocessed signals to filter a phase information sequence according to the displacement characteristics of the chest and abdomen surfaces of the human body caused by respiration, removes stray targets and obtains target signal frequency spectrum information;
extracting a respiratory signal according to the characteristic range of the respiratory frequency of the human body;
and (4) carrying out signal processing on the higher harmonics of the respiration signal to separate out a heart rate signal.
Specifically, the acquiring device of vehicle driving data acquires the vehicle driving state information and the driving state information of the driver, and includes:
the automobile bus communication control unit realizes information interaction with an automobile bus through a bus communication control protocol and sends the vehicle running state information to the driving habit acquisition data unit;
the driving habit acquisition data unit acquires and reads the driving condition of the vehicle and the driving state information of the driver to obtain the related driving parameters of the vehicle.
Specifically, the fatigue driving data model device establishes a fatigue driving situation data model according to the breathing and heart rate change condition of the driver and the driving state information of the driver, and discriminates the fatigue driving state to realize active predictive control of the fatigue driving state, and includes:
establishing a fatigue driving situation data model according to the breathing, heart rate and driving habit data of the driver, matching and performing model analysis and calculation by combining a dynamic database of the fatigue driving situation model to obtain a personalized model of the fatigue driving state of the driver, and determining state thresholds and weight coefficients of three characteristic parameters of the breathing, heart rate and driving habit fatigue state;
updating the individualized model data of the fatigue driving state of the driver to a dynamic database of a fatigue driving situation model;
extracting thresholds of respiration, heart rate and driving habit fatigue state according to the fatigue driving state personalized model, and calculating a comprehensive threshold of the comprehensive fatigue state of the driver and the prediction of the variation trend according to the three thresholds and the weight coefficients of the three features in the personalized model;
comparing the comprehensive threshold value and the variation trend value of the comprehensive fatigue state of the driver with the real-time measured characteristic value results of the respiration, the heart rate and the driving habit data of the driver, judging whether the driver belongs to the fatigue driving state, and if so, executing a step of sending out an early warning prompt to the fatigue driving state; if not, displaying the current fatigue state and the change trend prediction information.
The fatigue driving detection method provided by the embodiment of the invention is described in detail below with reference to fig. 2.
Step S1: the emission signal control unit emits and emits linear frequency modulation millimeter wave signals to the outside through the millimeter wave signal emission unit and carries out signal radiation detection on the chest and abdomen part of the body of the driver;
step S2: after the millimeter wave signal receiving unit receives the millimeter wave echo signal reflected by the body of the driver, the millimeter wave signal receiving unit performs gain amplification, analog-to-digital conversion and storage on the signal and sends the signal to the received signal preprocessing unit;
step S3: the received signal preprocessing unit carries out one-dimensional Fourier transform processing on the received signal to obtain all target information in a detection distance range, then extracts different target signal peak values subjected to one-dimensional Fourier transform processing through a peak value search algorithm, and stores phase information corresponding to the target peak values. Meanwhile, the signal-to-noise ratio of the signal receiving signal is evaluated. On one hand, the signal-to-noise ratio result of the detection signal is fed back to the transmission signal control unit, and the transmission signal control unit forms closed-loop control. On the other hand, the stored different target signal peak values and corresponding phase information are sent to a detection data characteristic identification unit, and the target information processed by the preprocessing unit not only contains signals reflected by the chest and abdomen of the driver, but also has other stray targets;
step S4: the detection data feature recognition unit performs digital filtering and noise reduction processing on the preprocessed signals to filter a phase information sequence according to the human body thoracoabdominal surface displacement features caused by respiration (the thoracoabdominal surface displacement caused by respiration is 4-12 mm, and the chest wall displacement caused by heartbeat is 1-2 mm), removes stray targets and obtains target signal frequency spectrum information;
step S5: according to the characteristic range (0.1-0.5 Hz) of the human respiratory frequency, a respiratory signal can be extracted from the target signal frequency spectrum information through a simple low-pass filter with the cut-off frequency of 0.5 Hz; and sending the extracted respiratory signals to a fatigue driving situation data model. A certain physiological coupling relation exists between the heart and the lung of a human body, the higher harmonic of a respiratory signal is completely superposed with the fundamental frequency of a heartbeat signal, and the acquisition of the heart rate signal needs to be further processed based on the respiratory signal;
step S6: and (3) performing signal processing on the higher harmonics of the respiration signal by using a self-adaptive filtering method to separate a heart rate signal. Sending the extracted heart rate signal to a fatigue driving situation data model;
step S7: the automobile bus communication control unit realizes information interaction with an automobile bus through a bus communication control protocol and sends the vehicle running state information to the driving habit acquisition data unit;
step S8: the driving habit acquisition data unit acquires and reads the driving condition of the vehicle and the driving state information of a driver, obtains parameters related to vehicle driving, such as vehicle speed, steering wheel angle, acceleration state and the like, and sends the acquired information to the fatigue driving situation data model;
step S9: establishing a fatigue driving situation data model according to the breathing, heart rate and driving habit data of the driver, matching and analyzing and calculating the model by combining a dynamic database of the fatigue driving situation model to obtain an individualized model of the fatigue driving state of the driver, and determining state thresholds and weight coefficients of three characteristic parameters of the breathing, heart rate and driving habit fatigue state;
step S10: updating the individualized model data of the fatigue driving state of the driver to a dynamic database of a fatigue driving situation model;
step S11: and extracting thresholds of respiration, heart rate and driving habit fatigue state according to the fatigue driving state personalized model, and calculating a comprehensive threshold and a variation trend prediction of the comprehensive fatigue state of the driver according to the three thresholds and weight coefficients of three features in the personalized model.
Step S12: comparing the comprehensive fatigue state threshold value and the variation trend value of the driver with the real-time measured results of the three characteristic values of the respiration, the heart rate and the driving habit data of the driver, judging whether the driver is in the fatigue driving state, and if so, entering step S14; if not, go to step S13;
step S13: displaying the fatigue state detection information and the change trend prediction information which are calculated currently;
step S14: a buzzer, a motor and an LED lamp are adopted or a plurality of devices are adopted simultaneously to carry out sound-light alarm to remind a driver.
In conclusion, the fatigue driving detection method provided by the invention overcomes the defects in the existing contact type or non-contact type fatigue driving detection method, provides the non-contact type millimeter wave radar detection method which can eliminate environmental interference, improve identification accuracy and has high safety, can effectively detect the fatigue condition of the driver in real time, can predict the fatigue condition of the driver before the driver is tired, and has higher applicability. In addition, the fatigue driving detection method provided by the invention adopts a non-contact non-visual measurement mode, and has the advantages of simple installation and effective protection of driver privacy.
It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.
Claims (10)
1. A fatigue driving detection system, comprising: the system comprises a driver physiological characteristic detection device, a vehicle driving data acquisition device, a fatigue driving data model device and a fatigue state display and early warning device, wherein the driver physiological characteristic detection device and the vehicle driving data acquisition device are both in communication connection with the fatigue driving data model device, and the fatigue driving data model device is in communication connection with the fatigue state display and early warning device;
the driver physiological characteristic detection device is used for measuring the breathing and heart rate change conditions of a driver;
the vehicle running data acquisition device is used for acquiring vehicle running state information and driving state information of a driver;
the fatigue driving data model device is used for establishing a vehicle driving state and fatigue driving situation data model according to the breathing and heart rate change condition of a driver and the driving state information of the driver, so that the fatigue driving state can be judged, and the active prediction control of the fatigue driving state can be realized;
the fatigue state display and early warning device is used for displaying the fatigue state and giving out early warning prompts to the fatigue driving state.
2. The fatigue driving detection system according to claim 1, wherein the driver physiological characteristic detection means includes: the device comprises a millimeter wave signal transmitting unit, a transmitting signal control unit, a millimeter wave signal receiving unit, a received signal preprocessing unit and a detected data characteristic identification unit, wherein the millimeter wave signal transmitting unit is in communication connection with the transmitting signal control unit, the millimeter wave signal receiving unit is in communication connection with the received signal preprocessing unit, the received signal preprocessing unit is in communication connection with the transmitting signal control unit, and the detected data characteristic identification unit is in communication connection with the received signal preprocessing unit;
the millimeter wave signal transmitting unit is used for transmitting a millimeter wave detection signal to the outside;
the transmission signal control unit is used for controlling the signal characteristics of the millimeter wave detection signal transmitted by the millimeter wave signal transmission unit;
the millimeter wave signal receiving unit is used for receiving millimeter wave echo signals reflected by a driver;
the received signal preprocessing unit is used for performing signal processing on the millimeter wave echo signal reflected by the driver to obtain a target signal in a detection range;
the detection data characteristic identification unit is used for extracting effective target signals of the target signals in the detection range to obtain detection results of the respiration and heart rate signals.
3. The fatigue driving detection system according to claim 1, wherein the vehicle travel data acquisition means includes: the driving habit data acquisition unit is used for acquiring relevant parameters of vehicle running.
4. The fatigue driving detection system according to claim 3, wherein the vehicle travel data acquisition device further includes: and the automobile bus communication control unit is in communication connection with the driving habit data acquisition unit and is used for realizing the communication interaction between the driving habit data acquisition unit and an automobile bus.
5. The fatigue driving detection system according to claim 3, wherein the vehicle travel-related parameters include: vehicle speed, steering wheel angle, and acceleration state.
6. The fatigue driving detection system of claim 1, wherein the fatigue driving data model means comprises: the fatigue driving situation data model is in communication connection with the data model analysis and calculation unit,
the fatigue driving situation data model is used for carrying out information fusion on the breathing and heart rate change condition of the driver and the driving state information of the driver, and establishing a fatigue driving situation data model;
the data model analyzing and calculating unit is used for providing a data calculating platform for analyzing, judging and predicting the fatigue driving situation data model.
7. A fatigue driving detection method implemented by applying the fatigue driving detection system according to any one of claims 1 to 6, comprising:
the driver physiological characteristic detection device transmits millimeter wave signals outwards, receives millimeter wave echo signals reflected by a driver and processes the millimeter wave echo signals to obtain the breathing and heart rate change conditions of the driver;
the vehicle running data acquisition device acquires vehicle running state information and driver's driving state information;
the fatigue driving data model device establishes a fatigue driving situation data model according to the breathing and heart rate change condition of the driver and the driving state information of the driver, and judges the fatigue driving state so as to realize active prediction control on the fatigue driving state;
the fatigue state display and early warning device displays the fatigue state and sends out early warning prompt to the fatigue driving state.
8. The fatigue driving detection method according to claim 7, wherein the driver physiological characteristic detection device emits millimeter wave signals to the outside, and receives millimeter wave echo signals reflected by the driver, and processes the millimeter wave echo signals to obtain the breathing and heart rate variation of the driver, and the method comprises:
the emission signal control unit emits linear frequency modulation millimeter wave signals to the outside through the millimeter wave signal emission unit and carries out signal radiation detection on the chest and abdomen part of the body of the driver;
after the millimeter wave signal receiving unit receives the millimeter wave echo signal reflected by the body of the driver, the millimeter wave signal receiving unit performs gain amplification, analog-to-digital conversion and storage on the signal and sends the signal to the received signal preprocessing unit;
the received signal preprocessing unit carries out one-dimensional Fourier transform processing on the received signal to obtain all target information in a detection distance range, extracts different target signal peak values after the one-dimensional Fourier transform processing through a peak value search algorithm, stores phase information corresponding to the target peak values and evaluates the signal-to-noise ratio of the signal received signal;
the detection data characteristic identification unit carries out digital filtering and noise reduction processing on the preprocessed signals to filter a phase information sequence according to the displacement characteristics of the chest and abdomen surfaces of the human body caused by respiration, removes stray targets and obtains target signal frequency spectrum information;
extracting a respiratory signal according to the characteristic range of the respiratory frequency of the human body;
and (4) carrying out signal processing on the higher harmonics of the respiration signal to separate out a heart rate signal.
9. The fatigue driving detecting method according to claim 7, wherein the vehicle travel data acquiring device acquires vehicle travel state information and driver's drive state information, including:
the automobile bus communication control unit realizes information interaction with an automobile bus through a bus communication control protocol and sends the vehicle running state information to the driving habit acquisition data unit;
the driving habit acquisition data unit acquires and reads the driving condition of the vehicle and the driving state information of the driver to obtain the related driving parameters of the vehicle.
10. The fatigue driving detection method according to claim 7, wherein the fatigue driving data model device establishes a fatigue driving situation data model according to the breathing and heart rate variation of the driver and the driving state information of the driver, and discriminates the fatigue driving state to realize active predictive control of the fatigue driving state, and the method comprises:
establishing a fatigue driving situation data model according to the breathing, heart rate and driving habit data of the driver, matching and performing model analysis and calculation by combining a dynamic database of the fatigue driving situation model to obtain a personalized model of the fatigue driving state of the driver, and determining state thresholds and weight coefficients of three characteristic parameters of the breathing, heart rate and driving habit fatigue state;
updating the individualized model data of the fatigue driving state of the driver to a dynamic database of a fatigue driving situation model;
extracting thresholds of respiration, heart rate and driving habit fatigue state according to the fatigue driving state personalized model, and calculating a comprehensive threshold of the comprehensive fatigue state of the driver and the prediction of the variation trend according to the three thresholds and the weight coefficients of the three features in the personalized model;
comparing the comprehensive threshold value and the variation trend value of the comprehensive fatigue state of the driver with the real-time measured characteristic value results of the respiration, the heart rate and the driving habit data of the driver, judging whether the driver belongs to the fatigue driving state, and if so, executing a step of sending out an early warning prompt to the fatigue driving state; if not, displaying the current fatigue state and the change trend prediction information.
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