Driver state monitoring system and method based on PVDF sensor

Abstract

The invention discloses a driver state monitoring system and method based on a PVDF sensor. The driver state monitoring system comprises a data acquisition module, a data processing module and a state monitoring module. Relates to the technical field of driving safety and solves the technical problem that the monitoring result of the fatigue state of a driver is not accurate enough in the prior art. The driving characteristic time of a driver is obtained by collecting posture data of the driver; calculating a fatigue evaluation coefficient of the driver based on the driving sitting posture and the driving characteristic time; determining a fatigue risk level of the driver based on the fatigue evaluation coefficient and the driving characteristic time; and reminding the driver based on the fatigue risk level. According to the method, the getting-on time and the current time of the driver are obtained, the driving duration is divided into the fatigue-prone driving duration and the fatigue-free driving duration, and the influence degree of the biological clock rule of the driver on fatigue driving is comprehensively considered, so that the accuracy of monitoring the fatigue state of the driver is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of driving safety, and in particular relates to a driver status monitoring system and method based on a PVDF sensor. Background Art

[0002] Fatigue driving is one of the main causes of traffic accidents, which seriously threatens people's lives and property safety. When the driver is tired, his judgment ability is significantly reduced, his reaction is slow, and his operating errors increase. If he still reluctantly drives the vehicle, it may cause a traffic accident. In the process of driving, in addition to the driver's driving fatigue, the vehicle's own state, the vehicle's driving route, and the environment near the vehicle will all have an impact on driving safety. How to accurately judge the driver's fatigue driving state through the intelligent driving system and comprehensively consider the driver's state, the vehicle's own state and the influence of environmental factors in the intelligent driving system is an important factor in improving the intelligence and safety of intelligent driving.

[0003] The existing technology counts the frequency of the driver's sitting posture changes within a set time, and compares the frequency of sitting posture changes with the corresponding threshold value, and determines whether the driver is in a fatigue state based on the comparison result; however, in the actual vehicle driving process, the degree of influence of the driver's driving posture on physical fatigue varies. For example, the driver will be more easily fatigued if he maintains the same driving posture for a long time. The driver's body weight is more easily delayed when it is not against the lumbar support and headrest when it is reasonably distributed on the seat cushion, lumbar support and headrest. The existing technology is difficult to measure the impact of different driving postures on fatigue, resulting in inaccurate monitoring results of the driver's fatigue state; in addition, the driver's fatigue state will be affected by the law of the biological clock. For example, the driver's sleepiness begins to gradually increase after 22:00. At this time, the driver's risk of fatigue driving will be higher than during the day. The existing technology is difficult to obtain the driver's fatigue state according to the time period of driving the vehicle, resulting in inaccurate monitoring results of the driver's fatigue state.

[0004] The present invention proposes a driver status monitoring system and method based on a PVDF sensor to solve the above technical problems. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a driver status monitoring system and method based on a PVDF sensor, which is used to solve the problem that the prior art is difficult to measure the impact of different driving postures on fatigue, resulting in inaccurate monitoring results of the driver's fatigue status; in addition, the prior art is difficult to obtain the driver's fatigue status according to the time period of driving the vehicle, resulting in inaccurate monitoring results of the driver's fatigue status.

[0006] To achieve the above object, the first aspect of the present invention provides a driver status monitoring system based on a PVDF sensor, comprising: a data processing module, and a data acquisition module and a status monitoring module connected thereto;

[0007] The data acquisition module is used to collect the driver's posture data and obtain the driver's driving characteristic time; the data acquisition module is composed of a number of PVDF sensors, which are respectively installed at the headrest, waist support and seat cushion; wherein the driving characteristic time includes the boarding time and the current time;

[0008] The data processing module: obtains the driver's driving posture based on the posture data; calculates the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time;

[0009] The state monitoring module determines the driver's fatigue risk level based on the fatigue assessment coefficient and the driving characteristic time; and reminds the driver based on the fatigue risk level.

[0010] Preferably, the driver status monitoring system based on the PVDF sensor also includes a data transmission module, which is used to transmit the driver's fatigue assessment coefficient to a display terminal via Bluetooth; wherein the display terminal includes a mobile phone and a vehicle central control instrument.

[0011] Preferably, the data acquisition module is composed of a plurality of PVDF sensors, and the plurality of PVDF sensors are respectively installed at the headrest, the lumbar support and the seat cushion.

[0012] It should be noted that the PVDF sensor in the present invention refers to a thin film piezoelectric sensor.

[0013] Preferably, the acquiring the driver's driving posture based on the posture data comprises:

[0014] Extracting the driver's posture data; wherein the posture data includes the driver's headrest pressure, lumbar support pressure, and seat cushion pressure;

[0015] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 1;

[0016] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 2;

[0017] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 3;

[0018] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 4;

[0019] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 5;

[0020] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 6;

[0021] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 7;

[0022] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 8.

[0023] Preferably, the calculation of the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time includes:

[0024] T1: Extract the boarding time and current time in the driving feature time;

[0025] T2: Determine the characteristic driving time corresponding to each driving posture based on the boarding time and the current time; the characteristic driving time includes the fatigue-prone driving time and the non-fatigue-prone driving time;

[0026] T3: Obtaining the driver's sitting posture change frequency based on the driving time corresponding to each driving posture;

[0027] T4: By formula Calculate the driver's fatigue assessment coefficient PGX; wherein, ZBP is the sitting posture change frequency, ZYXi is the sitting posture influence coefficient corresponding to the driving sitting posture i, the value range of ZYXi is 0≤ZYXi≤1, JCXi is the fatigue-prone driving time corresponding to the driving sitting posture i, and JCYi is the non-fatigue driving time corresponding to the driving sitting posture i; i=1, 2, ..., n is the total number of driving postures; a and b are proportional coefficients greater than 0, c1 and c2 are weight coefficients, c1>c2 and c1+c2=1; e is a natural constant.

[0028] Preferably, determining the characteristic driving time corresponding to each driving posture based on the boarding time and the current time includes:

[0029] H1: Extract the driver’s boarding time and current time;

[0030] H2: Determine whether the boarding time is greater than 22:00; if yes, mark the time period between the boarding time and the current time as a fatigue-prone time period; if no, jump to H3;

[0031] H3: Determine whether the current time is less than 22:00; if yes, mark the time period between the boarding time and the current time as a time period that is not prone to fatigue; if no, mark the time period between the boarding time and 22:00 as a time period that is not prone to fatigue, and mark the time period between 22:00 and the current time as a time period that is prone to fatigue;

[0032] H4: Count the driving time of each driving posture in the fatigue-prone time period and the non-fatigue-prone time period respectively, and obtain the fatigue-prone driving time and non-fatigue-prone driving time corresponding to each driving posture.

[0033] It should be noted that the time period after 10 p.m. is a period of high fatigue according to the body's biological clock.

[0034] Preferably, the step of obtaining the driver's sitting posture change frequency based on the driving time corresponding to each driving sitting posture includes:

[0035] Obtain the driver's several sitting posture changes within the set time, extract the driving time corresponding to each sitting posture change, and mark the change duration; the set time is the time difference obtained by subtracting the boarding time from the current time;

[0036] Determine whether the change duration is greater than a set duration threshold; if yes, mark the corresponding sitting posture change as a valid change; if no, mark the corresponding sitting posture change as an invalid change;

[0037] The number of effective changes made by the driver within the set time is counted, and the number of effective changes is divided by the set time to obtain the driver's sitting posture change frequency.

[0038] It should be noted that when the sitting posture change is marked as an invalid change, the duration of the change will be counted into the driving time corresponding to the driving posture in the most recent valid change.

[0039] Preferably, determining the driver's fatigue risk level based on the fatigue assessment coefficient and the driving characteristic time includes:

[0040] Y1: Extract fatigue assessment coefficient; obtain the driver's continuous driving time, boarding time and current time, and subtract the boarding time from the current time to get the cumulative driving time;

[0041] Y2: Determine whether the continuous driving time is greater than 4 hours; if yes, mark the fatigue risk level as high risk; if no, jump to Y3;

[0042] Y3: Determine whether the cumulative driving time is greater than 8 hours; if yes, mark the fatigue risk level as high risk; if no, jump to Y4;

[0043] Y4: Determine whether the fatigue assessment coefficient is greater than the preset risk threshold; if yes, mark the fatigue risk level as high risk; if no, mark the fatigue risk level as low risk.

[0044] It should be noted that continuous driving time refers to the time the driver drives the vehicle from getting on and off the vehicle, and the cumulative driving time is the total time the driver drives the vehicle in one day.

[0045] Preferably, the reminding the driver based on the fatigue risk level includes:

[0046] Extract the driver's fatigue risk level; determine whether the fatigue risk level is high risk; if yes, generate a fatigue prompt command and issue a prompt voice according to the fatigue prompt command; if no, continue to monitor the driver's fatigue status.

[0047] A second aspect of the present invention provides a driver status monitoring method based on a PVDF sensor, comprising:

[0048] S1: Collect the driver's posture data and obtain the driver's driving characteristic time;

[0049] S2: Acquire the driver's driving posture based on the posture data;

[0050] S3: Calculate the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time;

[0051] S4: Determine the driver's fatigue risk level based on the fatigue assessment coefficient and driving characteristic time;

[0052] S5: Remind the driver based on the fatigue risk level.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] The present invention provides a method for accurately evaluating the driver's fatigue state. By systematically counting the fatigue-prone driving time and the fatigue-prone driving time under different driving postures, a corresponding sitting posture influence coefficient is set according to the influence of each driving posture on the driver's fatigue degree. At the same time, combined with the driver's sitting posture change frequency, a fatigue assessment coefficient that can accurately reflect the driver's actual fatigue condition is calculated using a specific formula, thereby improving the accuracy of monitoring the driver's fatigue state.

[0055] In addition, the present invention also takes into account the impact of the biological clock on fatigue driving. By recording the driver's boarding time and the current time and comparing them with the time node of 22:00, the driving time is subdivided into time periods that are more likely to cause fatigue and time periods that are relatively less likely to cause fatigue. This further optimizes the calculation of the fatigue assessment coefficient to ensure that it can comprehensively reflect the impact of changes in the driver's physiological rhythm on driving fatigue, and ultimately achieve more accurate and effective monitoring of the driver's fatigue status. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 is an overall flow chart of the driver status monitoring method of the present invention;

[0058] Figure 2 It is a principle schematic diagram of the driver status monitoring system of the present invention. DETAILED DESCRIPTION

[0059] The technical scheme of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] See also Figure 1-Figure 2 , the first aspect of the present invention provides a driver status monitoring system based on a PVDF sensor, comprising: a data processing module, and a data acquisition module and a status monitoring module connected thereto;

[0061] Data acquisition module: used to collect the driver's posture data and obtain the driver's driving characteristic time; the data acquisition module is composed of a number of PVDF sensors, which are respectively installed at the headrest, waist support and seat cushion; wherein the driving characteristic time includes the boarding time and the current time;

[0062] Data processing module: obtain the driver's driving posture based on posture data; calculate the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time;

[0063] Condition monitoring module: Determines the driver's fatigue risk level based on the fatigue assessment coefficient and driving characteristic time; reminds the driver based on the fatigue risk level.

[0064] In this embodiment, the driver status monitoring system based on the PVDF sensor also includes a data transmission module, which is used to transmit the driver's fatigue assessment coefficient to the display terminal via Bluetooth; wherein the display terminal includes a mobile phone and a vehicle central control instrument.

[0065] In this embodiment, the data acquisition module is composed of a number of PVDF sensors, and the several PVDF sensors are respectively installed at the headrest, lumbar support and seat cushion positions; wherein the PVDF sensor refers to a thin film piezoelectric sensor.

[0066] In this embodiment, obtaining the driver's driving posture based on the posture data includes:

[0067] Extracting the driver's posture data; wherein the posture data includes the driver's headrest pressure, lumbar support pressure, and seat cushion pressure; experts in related fields set pressure thresholds A1, B1, and C1 based on experience;

[0068] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 1;

[0069] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 2;

[0070] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 3;

[0071] The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 4;

[0072] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 5;

[0073] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 6;

[0074] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 7;

[0075] The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 8.

[0076] The present invention collects the driver's posture data in real time through PVDF sensors installed on the headrest, lumbar support and seat cushion, and determines the corresponding driving posture according to each posture data and the corresponding pressure threshold, so as to facilitate the subsequent calculation of the fatigue assessment coefficient according to the driving time corresponding to the driving posture.

[0077] In this embodiment, the driver's fatigue assessment coefficient is calculated based on the driving posture and driving characteristic time, including:

[0078] T1: Extract the boarding time and current time in the driving feature time;

[0079] T2: Determine the characteristic driving time corresponding to each driving posture based on the boarding time and the current time; the characteristic driving time includes the fatigue-prone driving time and the non-fatigue-prone driving time;

[0080] T3: Obtaining the driver's sitting posture change frequency based on the driving time corresponding to each driving posture;

[0081] T4: By formula Calculate the driver's fatigue assessment coefficient PGX; wherein, ZBP is the sitting posture change frequency, ZYXi is the sitting posture influence coefficient corresponding to the driving sitting posture i, the value range of ZYXi is 0≤ZYXi≤1, JCXi is the fatigue-prone driving time corresponding to the driving sitting posture i, and JCYi is the non-fatigue driving time corresponding to the driving sitting posture i; i=1, 2, ..., n is the total number of driving postures; a and b are proportional coefficients greater than 0, c1 and c2 are weight coefficients, c1>c2 and c1+c2=1; e is a natural constant.

[0082] For example, the proportional coefficients a=100, b=0.8, the weight coefficients c1=0.6, c2=0.4, and the sitting posture change frequency ZBP=7 times / hour are set;

[0083] The sitting posture influence coefficient ZYXi, fatigue-prone driving time JCXi, and non-fatigue-prone driving time JCYi corresponding to each driving posture are shown in the following table:

[0084]

[0085] The driver's fatigue assessment coefficient PGX≈100.49 is calculated by the formula.

[0086] The present invention respectively counts the fatigue-prone driving time and the non-fatigue-prone driving time of each driving posture, sets a corresponding posture influence coefficient according to the degree of influence of each driving posture on fatigue, and calculates the fatigue assessment coefficient through a formula in combination with the driver's posture change frequency, so that the calculated fatigue assessment coefficient can accurately reflect the driver's actual fatigue state, which is beneficial to improving the accuracy of monitoring the driver's fatigue state.

[0087] In this embodiment, the characteristic driving time corresponding to each driving posture is determined based on the boarding time and the current time, including:

[0088] H1: Extract the driver’s boarding time and current time;

[0089] H2: Determine whether the boarding time is greater than 22:00; if yes, mark the time period between the boarding time and the current time as a fatigue-prone time period; if no, jump to H3;

[0090] H3: Determine whether the current time is less than 22:00; if yes, mark the time period between the boarding time and the current time as a time period that is not prone to fatigue; if no, mark the time period between the boarding time and 22:00 as a time period that is not prone to fatigue, and mark the time period between 22:00 and the current time as a time period that is prone to fatigue;

[0091] H4: Count the driving time of each driving posture in the fatigue-prone time period and the non-fatigue-prone time period respectively, and obtain the fatigue-prone driving time and non-fatigue-prone driving time corresponding to each driving posture.

[0092] Exemplarily, the boarding time is set to 20:00 and the current time is set to 23:00; since the boarding time is less than 22:00 and the current time is greater than 22:00, the time period (20, 22) between the boarding time and 22:00 is marked as the non-fatigue time period, and the time period (22, 23) between 22:00 and the current time is marked as the easy fatigue time period; the driving time of each driving posture in the easy fatigue time period and the non-fatigue time period are counted respectively, and the easy fatigue driving time and non-fatigue driving time corresponding to each driving posture are obtained.

[0093] It should be noted that the time period after 10 p.m. is a period of high fatigue according to the body's biological clock.

[0094] The present invention obtains the driver's boarding time and current time, and divides the driving time into fatigue-prone driving time and non-fatigue-prone driving time according to the chronological relationship among the boarding time, current time and 22:00, and comprehensively considers the influence of the driver's biological clock on fatigue driving, thereby facilitating improving the accuracy of monitoring the driver's fatigue state.

[0095] In this embodiment, the driver's sitting posture change frequency is obtained based on the driving time corresponding to each driving sitting posture, including:

[0096] Obtain the driver's several sitting posture changes within the set time, extract the driving time corresponding to each sitting posture change, and mark the change duration; the set time is the time difference obtained by subtracting the boarding time from the current time;

[0097] Determine whether the change duration is greater than a set duration threshold; if yes, mark the corresponding sitting posture change as a valid change; if no, mark the corresponding sitting posture change as an invalid change;

[0098] The number of effective changes made by the driver within the set time is counted, and the number of effective changes is divided by the set time to obtain the driver's sitting posture change frequency.

[0099] It should be noted that when the sitting posture change is marked as an invalid change, the duration of the change will be counted into the driving time corresponding to the driving posture in the most recent valid change.

[0100] Exemplarily, the duration threshold is set to 2 minutes; assuming that the driver maintains driving sitting posture 1 for 6 minutes, and then changes to driving sitting posture 3 and maintains it for 1 minute; since the change to driving sitting posture 3 is maintained for 1 minute, which is less than the set duration threshold of 2 minutes, this sitting posture change is marked as an invalid change; assuming that the set time is 3 hours, and the driver makes 21 effective changes within the set time, the sitting posture change frequency is 7 times / hour.

[0101] The present invention counts the number of times the driver changes his sitting posture within a set time, compares the change retention time after the sitting posture change with a time threshold to obtain the number of effective changes, and divides the number of effective changes by the set time to obtain the sitting posture change frequency; the sitting posture change frequency is used to calculate the fatigue assessment coefficient, so that the calculation of the fatigue assessment coefficient is more accurate, which is beneficial to improving the accuracy of monitoring the driver's fatigue state.

[0102] In this embodiment, the driver's fatigue risk level is determined based on the fatigue assessment coefficient and the driving characteristic time, including:

[0103] Y1: Extract fatigue assessment coefficient; obtain the driver's continuous driving time, boarding time and current time, and subtract the boarding time from the current time to get the cumulative driving time;

[0104] Y2: Determine whether the continuous driving time is greater than 4 hours; if yes, mark the fatigue risk level as high risk; if no, jump to Y3;

[0105] Y3: Determine whether the cumulative driving time is greater than 8 hours; if yes, mark the fatigue risk level as high risk; if no, jump to Y4;

[0106] Y4: Determine whether the fatigue assessment coefficient is greater than the preset risk threshold; if yes, mark the fatigue risk level as high risk; if no, mark the fatigue risk level as low risk;

[0107] Among them, the risk threshold is set based on the experience of experts in relevant fields.

[0108] Exemplarily, the fatigue assessment coefficient PGX is set to 100.49, the risk threshold is 90, the driver's continuous driving time is 3 hours, and the cumulative driving time is 3 hours by subtracting the boarding time 20 o'clock from the current time 23:00; since the continuous driving time is 3 hours and less than 4 hours, it jumps to Y3; since the cumulative driving time is 3 hours and less than 8 hours, it jumps to Y4; since the fatigue assessment coefficient PGX=100.49 is greater than the preset risk threshold, the fatigue risk level is marked as high risk.

[0109] It should be noted that continuous driving time refers to the time the driver drives the vehicle from getting on and off the vehicle, and the cumulative driving time is the total time the driver drives the vehicle in one day.

[0110] In this embodiment, the driver is reminded based on the fatigue risk level, including:

[0111] Extract the driver's fatigue risk level; determine whether the fatigue risk level is high risk; if yes, generate a fatigue prompt command and issue a prompt voice according to the fatigue prompt command; if no, continue to monitor the driver's fatigue status.

[0112] Exemplarily, if the driver's fatigue risk level is set to high risk, a fatigue prompt command is generated, and a voice prompt is issued according to the fatigue prompt command to remind the driver to stop and rest. The content of the voice prompt is "You are in a fatigue driving state, please pay attention to driving safety and pull over to the side of the road to rest for a while."

[0113] A second aspect of the present invention provides a driver status monitoring method based on a PVDF sensor, comprising:

[0114] S1: Collect the driver's posture data and obtain the driver's driving characteristic time;

[0115] S2: Acquire the driver's driving posture based on the posture data;

[0116] S3: Calculate the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time;

[0117] S4: Determine the driver's fatigue risk level based on the fatigue assessment coefficient and driving characteristic time;

[0118] S5: Remind the driver based on the fatigue risk level.

[0119] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0120] Working principle of the present invention:

[0121] The present invention acquires the driver's driving characteristic time by collecting the driver's posture data; acquires the driver's driving sitting posture based on the posture data; calculates the driver's fatigue assessment coefficient based on the driving sitting posture and the driving characteristic time; determines the driver's fatigue risk level based on the fatigue assessment coefficient and the driving characteristic time; and reminds the driver based on the fatigue risk level.

[0122] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. Driver status monitoring system based on PVDF sensor, including: The data processing module, and the data acquisition module and status monitoring module connected thereto are characterized in that: The data collection module is used to collect the driver's posture data and obtain the driver's driving characteristic time; wherein the driving characteristic time includes the boarding time and the current time; The data processing module: obtains the driver's driving posture based on the posture data; calculates the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time; The state monitoring module determines the driver's fatigue risk level based on the fatigue assessment coefficient and the driving characteristic time; and reminds the driver based on the fatigue risk level.

2. The driver status monitoring system based on PVDF sensor according to claim 1 is characterized in that: It also includes a data transmission module, which is used to transmit the driver's fatigue assessment coefficient to a display terminal via Bluetooth; wherein the display terminal includes a mobile phone and a central control instrument of the vehicle.

3. The driver status monitoring system based on PVDF sensor according to claim 1, characterized in that: The data acquisition module is composed of a plurality of PVDF sensors, and the plurality of PVDF sensors are respectively installed at the headrest, the lumbar support and the seat cushion.

4. The driver status monitoring system based on PVDF sensor according to claim 3 is characterized in that: The step of acquiring the driver's driving posture based on the posture data includes: Extracting the driver's posture data; wherein the posture data includes the driver's headrest pressure, lumbar support pressure, and seat cushion pressure; The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 1; The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 2; The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 3; The driver's sitting posture when the headrest pressure is greater than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 4; The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 5; The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is greater than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 6; The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is greater than the pressure threshold C1 is marked as driving sitting posture 7; The driver's sitting posture when the headrest pressure is less than the pressure threshold A1, the lumbar support pressure is less than the pressure threshold B1, and the seat cushion pressure is less than the pressure threshold C1 is marked as driving sitting posture 8.

5. The driver status monitoring system based on PVDF sensor according to claim 1, characterized in that: The calculation of the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time includes: T1: Extract the boarding time and current time in the driving feature time; T2: Determine the characteristic driving time corresponding to each driving posture based on the boarding time and the current time; the characteristic driving time includes the fatigue-prone driving time and the non-fatigue-prone driving time; T3: Obtaining the driver's sitting posture change frequency based on the driving time corresponding to each driving posture; T4: By formula Calculate the driver's fatigue assessment coefficient PGX; wherein, ZBP is the sitting posture change frequency, ZYXi is the sitting posture influence coefficient corresponding to the driving sitting posture i, the value range of ZYXi is 0≤ZYXi≤1, JCXi is the fatigue-prone driving time corresponding to the driving sitting posture i, and JCYi is the non-fatigue driving time corresponding to the driving sitting posture i; i=1, 2, ..., n is the total number of driving postures; a and b are proportional coefficients greater than 0, c1 and c2 are weight coefficients, c1>c2 and c1+c2=1; e is a natural constant.

6. The driver status monitoring system based on PVDF sensor according to claim 5, characterized in that: The method of determining the characteristic driving time corresponding to each driving posture based on the boarding time and the current time includes: H1: Extract the driver’s boarding time and current time; H2: Determine whether the boarding time is greater than 22:00; if yes, mark the time period between the boarding time and the current time as a fatigue-prone time period; if no, jump to H3; H3: Determine whether the current time is less than 22:00; if yes, mark the time period between the boarding time and the current time as a time period that is not prone to fatigue; if no, mark the time period between the boarding time and 22:00 as a time period that is not prone to fatigue, and mark the time period between 22:00 and the current time as a time period that is prone to fatigue; H4: Count the driving time of each driving posture in the fatigue-prone time period and the non-fatigue-prone time period respectively, and obtain the fatigue-prone driving time and non-fatigue-prone driving time corresponding to each driving posture.

7. The driver status monitoring system based on PVDF sensor according to claim 5, characterized in that: The acquiring the driver's sitting posture change frequency based on the driving time corresponding to each driving sitting posture comprises: Obtain the driver's several sitting posture changes within the set time, extract the driving time corresponding to each sitting posture change, and mark the change duration; the set time is the time difference obtained by subtracting the boarding time from the current time; Determine whether the change duration is greater than a set duration threshold; if yes, mark the corresponding sitting posture change as a valid change; if no, mark the corresponding sitting posture change as an invalid change; The number of effective changes made by the driver within the set time is counted, and the number of effective changes is divided by the set time to obtain the driver's sitting posture change frequency.

8. The driver status monitoring system based on PVDF sensor according to claim 1, characterized in that: The method of determining the driver's fatigue risk level based on the fatigue assessment coefficient and the driving characteristic time includes: Y1: Extract fatigue assessment coefficient; obtain the driver's continuous driving time, boarding time and current time, and subtract the boarding time from the current time to get the cumulative driving time; Y2: Determine whether the continuous driving time is greater than 4 hours; if yes, mark the fatigue risk level as high risk; if no, jump to Y3; Y3: Determine whether the cumulative driving time is greater than 8 hours; if yes, mark the fatigue risk level as high risk; if no, jump to Y4; Y4: Determine whether the fatigue assessment coefficient is greater than the preset risk threshold; if yes, mark the fatigue risk level as high risk; if no, mark the fatigue risk level as low risk.

9. The driver status monitoring system based on PVDF sensor according to claim 1, characterized in that: The reminding of the driver based on the fatigue risk level includes: Extract the driver's fatigue risk level; determine whether the fatigue risk level is high risk; if yes, generate a fatigue prompt command and issue a prompt voice according to the fatigue prompt command; if no, continue to monitor the driver's fatigue status.

10. A driver status monitoring method based on a PVDF sensor, based on the operation of a driver status monitoring system based on a PVDF sensor according to any one of claims 1 to 9, characterized in that: include: S1: Collect the driver's posture data and obtain the driver's driving characteristic time; S2: Acquire the driver's driving posture based on the posture data; S3: Calculate the driver's fatigue assessment coefficient based on the driving posture and driving characteristic time; S4: Determine the driver's fatigue risk level based on the fatigue assessment coefficient and driving characteristic time; S5: Remind the driver based on the fatigue risk level.

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