Fatigue driving recognition method and device, electronic equipment and storage medium

Abstract

The application discloses a fatigue driving recognition method, device, electronic equipment and storage medium. The fatigue driving recognition method comprises the following steps: determining the distance between the current position of a vehicle and the next rest area, the pupil information of a driver and the continuous driving time length; determining a first fatigue influence factor according to the distance between the current position of the vehicle and the next rest area; determining a second fatigue influence factor according to the pupil information of the driver; determining a third fatigue influence factor according to the continuous driving time length; and determining the fatigue degree of the driver based on the first fatigue influence factor, the second fatigue influence factor and the third fatigue influence factor. The recognition accuracy of fatigue driving is improved, and the driving safety of the vehicle is improved, and the road public safety is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fatigue driving, and in particular to a fatigue driving recognition method and device, an electronic device and a storage medium. BACKGROUND

[0002] With the progress of technology and the development of society, the popularity of cars is gradually increasing, and basically every family has at least one car, which has become a basic means of transportation. The resulting chain phenomenon is that the number of traffic accidents continues to increase, and through big data analysis, most traffic accidents are caused by driver fatigue driving. When the vehicle speed is above 80km / h, if the driver is in a fatigue state, the eyes are closed to open, and the driving distance of the vehicle can exceed 15m or more, and in this distance, the vehicle is basically in an unmanned driving state, which is easy to cause traffic accidents. Therefore, fatigue driving is becoming one of the "number one killers" that threaten the safety of drivers and road safety.

[0003] Therefore, the design of the automobile driver fatigue driving prevention system is an important guarantee for traffic safety. The current mature driver fatigue driving recognition method is to determine whether the driver is in a fatigue driving state according to the driver's mental state (facial features, eye opening and closing), and vehicle driving parameters (such as steering wheel operation angle, speed change, engine working time) and the like. It can be seen that in the existing driver fatigue driving recognition scheme, the fatigue influencing factors are limited, which leads to limited recognition accuracy, and therefore, the driver fatigue driving recognition scheme still has room for improvement.

[0004] Therefore, the present application is proposed. SUMMARY

[0005] The following gives a brief summary of one or more aspects to provide a basic understanding of these aspects. This summary is not an exhaustive overview of all contemplated aspects, and neither is it intended to identify key or critical elements of all aspects nor to delineate the scope of any or all aspects. Its only purpose is to give some concepts of one or more aspects in a simplified form as a prelude to the more detailed description given later.

[0006] In view of the problem of low recognition accuracy in the existing driver fatigue driving recognition scheme, the present application provides a fatigue driving recognition method, device, electronic device and storage medium, which has the beneficial effect of improving the recognition accuracy of fatigue driving, thereby improving the driving safety of the vehicle and improving the public safety of the road.

[0007] In a first aspect, the present application provides a fatigue driving recognition method, comprising:

[0008] determining a distance from a current position of the vehicle to a next rest area, pupil information of the driver, and a continuous driving time length;

[0009] determining a first fatigue influence factor according to the distance from the current position of the vehicle to the next rest area;

[0010] determining a second fatigue influence factor according to the pupil information of the driver;

[0011] determining a third fatigue influence factor according to the continuous driving time length;

[0012] determining a fatigue degree of the driver based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor.

[0013] Further, the determining of the distance from the current position of the vehicle to the next rest area comprises:

[0014] determining the distance from the current position of the vehicle to the next rest area based on a vehicle navigation and positioning system;

[0015] Alternatively, determining the distance from the current position of the vehicle to the next rest area at a current time based on a position of the vehicle at a time, real-time speeds of the vehicle at each sampling point from the time to the current time, and a distance from the position at the time to the next rest area.

[0016] Further, the determining of the distance from the current position of the vehicle to the next rest area at the current time based on the position of the vehicle at the time, the real-time speeds of the vehicle at each sampling point from the time to the current time, and the distance from the position at the time to the next rest area comprises:

[0017] determining the distance from the current position of the vehicle to the next rest area by the following expression:

[0018]

[0019] wherein L1 represents the distance from the current position of the vehicle to the next rest area, L represents the distance from the position at the time to the next rest area, and v(t) represents the real-time speed of the vehicle at the sampling point.

[0020] Further, the determining of the first fatigue influence factor according to the distance from the current position of the vehicle to the next rest area comprises:

[0021] determining a ratio of the distance from the current position of the vehicle to the next rest area to a distance reference value as the first fatigue influence factor.

[0022] Further, the determining of the second fatigue influence factor according to the pupil information of the driver comprises:

[0023] The ratio between the average pupil area of ​​the driver and the reference pupil area within a preset time period is determined as the second fatigue influence factor.

[0024] Furthermore, determining the third fatigue influencing factor based on the continuous driving duration includes:

[0025] Based on the preset mapping relationship between duration and fatigue impact factor, the data corresponding to the continuous driving duration is determined as the third fatigue impact factor.

[0026] Furthermore, determining the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor includes:

[0027] Determine the sum of the first fatigue influence factor and the second fatigue influence factor;

[0028] The driver's fatigue level is determined by multiplying the third fatigue influence factor with the sum.

[0029] Secondly, the present invention provides a fatigue driving recognition device, comprising:

[0030] The first determining module is used to determine the distance of the vehicle's current position from the next rest area, the driver's pupil information, and the continuous driving time;

[0031] The second determining module is used to determine the first fatigue influence factor based on the distance of the vehicle's current position from the next rest area;

[0032] The third determining module is used to determine the second fatigue influencing factor based on the driver's pupil information;

[0033] The fourth determining module is used to determine the third fatigue influence factor based on the continuous driving duration;

[0034] The fifth determining module is used to determine the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor.

[0035] Thirdly, the present invention also provides an electronic device, the electronic device comprising:

[0036] One or more processors;

[0037] Storage device for storing one or more programs;

[0038] When the one or more programs are executed by the one or more processors, the one or more processors implement the fatigue driving recognition method as described above.

[0039] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the fatigue driving recognition method as described above.

[0040] This invention discloses a fatigue driving identification method that determines the distance of the vehicle's current location from the next rest area, the driver's pupil information, and the continuous driving duration; determines a first fatigue influence factor based on the distance of the vehicle's current location from the next rest area; determines a second fatigue influence factor based on the driver's pupil information; determines a third fatigue influence factor based on the continuous driving duration; and determines the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor. This method aims to improve the accuracy of fatigue driving identification, vehicle driving safety, and road public safety. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating a fatigue driving identification method provided in an embodiment of the present invention.

[0043] Figure 2 This is a schematic diagram of the structure of a fatigue driving recognition device provided in an embodiment of the present invention;

[0044] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0045] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0046] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0047] Figure 1This is a flowchart illustrating a fatigue driving identification method proposed in this application. The method is used to detect whether a driver is exhibiting fatigue driving behavior. This fatigue driving identification method can be executed by a fatigue driving identification device, which can be implemented through software and / or hardware and integrated into a vehicle controller or server.

[0048] like Figure 1 As shown, the fatigue driving identification method includes the following steps:

[0049] S110, determine the vehicle's current location, distance to the next rest area, driver's pupil information, and continuous driving duration.

[0050] In some implementations, the driver fatigue recognition method provided in this application is activated when a vehicle is detected entering a highway. Specifically, in response to detecting a vehicle entering a highway, the distance of the vehicle's current location from the next rest area, the driver's pupil information, and the duration of continuous driving are determined.

[0051] For example, determining the distance of the vehicle's current location from the next rest area includes:

[0052] The vehicle's current location and distance to the next rest area are determined based on the in-vehicle navigation and positioning system.

[0053] Alternatively, the distance between the vehicle's current position and the next rest area can be determined based on the vehicle's position at a given moment, the real-time speed at each sampling point during the time interval from that moment to the current moment, and the distance between the vehicle's position at that moment and the next rest area.

[0054] Here, "a moment in time" can refer to any point in the vehicle's journey. For example, the vehicle's position at a moment in time could refer to the location of the tollbooth when the vehicle enters the highway; if the vehicle has rested at a service area, then that service area can be considered the vehicle's position at that moment. The logic for determining whether a vehicle has rested at a service area can be: based on the vehicle's position, determine whether the vehicle has entered the service area; if the vehicle has entered the service area, it can be considered that the vehicle has rested at the service area. Furthermore, to improve the accuracy of the determination, based on the vehicle entering the service area, further determine the duration of the vehicle's speed being 0; if the duration of the vehicle's speed being 0 reaches a threshold, then it is considered that the vehicle has rested at the service area. It is understandable that, based on the vehicle entering the service area, if the vehicle is turned off, it is determined that the vehicle has rested at the service area.

[0055] The next rest area can be determined based on the vehicle's navigation route. When the vehicle has not set a navigation route, the driver's destination can be determined through interaction with the driver. Then, the driving route can be automatically planned based on the determined destination, and the location of the next rest area can be determined based on the planned driving route, thereby determining the distance between the vehicle's current location and the next rest area.

[0056] The vehicle's location at any given moment can be determined based on the vehicle's navigation and positioning system.

[0057] For example, determining the distance from the vehicle's current position to the next rest area based on the vehicle's position at a given moment, the real-time speed at each sampling point during the time interval from that moment to the current moment, and the distance between the vehicle's position at that moment and the next rest area includes:

[0058] The distance from the vehicle's current location to the next rest area is determined using the following expression:

[0059]

[0060] Where L1 represents the distance from the vehicle's current position to the next rest area, L represents the distance from the vehicle's current position to the next rest area, and v(t) represents the vehicle's real-time speed at the sampling point. This represents the distance the vehicle has traveled from its position at the given time to the current time, which is the distance between the given time and the current position.

[0061] S120. Determine the first fatigue impact factor based on the distance of the vehicle's current location from the next rest area.

[0062] In other words, the first fatigue impact factor K1 is related to the location of the next rest area (on highways, a rest area generally refers to a service area). The magnitude of K1 characterizes the influence of the distance from the vehicle's current location to the next service area on the degree of fatigue. The distance from the vehicle's current location to the next service area directly affects the time the driver needs to drive, thus affecting whether the driver is more prone to fatigue. Since at a certain moment, the distance is constant, but the time to reach the service area changes with the speed, the first fatigue impact factor K1 also characterizes the time and speed at which the vehicle travels from its current location to the next service area.

[0063] A distance reference value L0 is set, which is the limit of distance that a driver can drive without fatigue. This distance reference value is set differently for different drivers. Before the vehicle leaves the factory, it is tested based on a certain sample, and a default distance reference value is set based on the experimental data. Subsequently, the driver can change the value of the distance reference value L0 according to their own driving ability, but the changed value is not allowed to exceed the specified threshold L.max (the threshold L) max (This can be determined through calibration). By setting different distance reference values ​​for different drivers, the differences between drivers can be fully considered, enabling personalized identification of different drivers and thus improving the accuracy of fatigue driving identification.

[0064] The actual distance L1 from the vehicle's current location to the next service area is obtained based on the navigation information.

[0065] For example, determining the first fatigue impact factor based on the distance of the vehicle's current location to the next rest area includes:

[0066] The ratio of the distance from the vehicle's current location to the next rest area to a distance reference value is determined as the first fatigue influencing factor, namely:

[0067]

[0068] Wherein, K1 represents the first fatigue influencing factor, L1 represents the distance from the vehicle's current position to the next rest area, and L0 represents the distance reference value. The distance reference value L0 is set differently for different drivers, representing the limit distance at which the driver can drive without fatigue. By setting different distance reference values ​​for different drivers, the differences between drivers can be fully considered, enabling personalized identification of different drivers and thus improving the accuracy of fatigue driving identification.

[0069] Furthermore, by collecting the vehicle's current speed v, the first fatigue influencing factor over a certain period of time is obtained:

[0070]

[0071] Since the control system is a discrete system, in the actual calculation process, calculations are performed based on discrete time points to further obtain the first fatigue influence factor over a certain period of time:

[0072]

[0073] S130. Determine the second fatigue influencing factor based on the driver's pupil information.

[0074] For example, determining the second fatigue influencing factor based on the driver's pupil information includes:

[0075] The ratio between the average pupil area of ​​the driver and the reference pupil area within a preset time period is determined as the second fatigue influence factor.

[0076] The second fatigue factor K2 is directly related to the driver's current fatigue state. The magnitude of K2 represents the driver's current fatigue level, mainly based on pupil area. The closer the second fatigue factor is to 0, the higher the driver's fatigue level; the closer it is to 1, the better the driver's condition.

[0077] A reference pupil area S0 is defined. When the driver first gets into the vehicle, facial recognition is performed to obtain the reference pupil area, at which point the driver is considered to be in a non-fatigue state. If the driver's facial expression is detected to be too exaggerated, the system will indicate an error during the data acquisition process. The driver's pupil area S is dynamically acquired during driving. Furthermore, since the human pupil area exhibits regular changes, the rate of change of pupil area over time is introduced:

[0078] The second fatigue influence factor K2 was obtained:

[0079]

[0080] Since the control system is a discrete system, in the actual calculation process, the calculation is performed based on discrete time points to further obtain the second fatigue influence factor K2:

[0081]

[0082] In general, determining the second fatigue influencing factor based on the driver's pupil information includes:

[0083] The ratio between the average pupil area of ​​the driver within a preset time period and the reference value of pupil area is determined as the second fatigue influencing factor. The reference value of pupil area is determined by facial recognition of the driver of the vehicle.

[0084] S140. Determine the third fatigue influence factor based on the continuous driving duration.

[0085] The third fatigue factor is related to the duration of continuous driving. Generally, the longer the continuous driving time, the more likely the driver is to become fatigued.

[0086] For example, determining the third fatigue influencing factor based on the continuous driving duration includes:

[0087] Based on a pre-defined mapping relationship between driving duration and fatigue impact factors, the data corresponding to the continuous driving duration is determined as the third fatigue impact factor. The driver's continuous driving duration can be divided into several stages, and corresponding fatigue impact factors can be determined. Specifically, a sample of drivers can be collected, and the pre-defined mapping relationship between continuous driving duration and fatigue impact factors can be determined through experiments. It is understandable that the longer the continuous driving time, the more likely the driver is to experience fatigue; therefore, the corresponding fatigue impact factor is larger.

[0088] For example, refer to the preset mapping relationship shown in Table 1.

[0089] Table 1

[0090]

[0091] S150. Determine the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor.

[0092] For example,

[0093] Determine the sum of the first fatigue influence factor and the second fatigue influence factor;

[0094] The driver's fatigue level is determined by multiplying the third fatigue influence factor with the sum.

[0095] This can be expressed as:

[0096] F2 = t0 * (K1 + K2)

[0097] Wherein, F0 represents the fatigue coefficient, t0 represents the third fatigue influence factor, K1 represents the first fatigue influence factor, and K2 represents the second fatigue influence factor.

[0098] In some implementations, for example, a driver enters a highway and drives continuously for 3 hours (corresponding to the third fatigue influence factor t0 = 0.6) without resting at a service area. At a certain moment, the vehicle's infotainment system reports a speed of 100 km / h = 27.8 m / s, and the distance to the next service area is 40 km (i.e., the distance between the vehicle's position at one moment and the next service area is 40). Assuming the current moment is 500 seconds after the first moment, then the distance traveled by the vehicle in these 500 seconds is 500 × 27.8 = 13900 m = 13.9 km. The average actual pupil area of ​​the driver calculated within these 500 seconds is S = 11 mm. 2 Reference pupil area S0 = 13 mm 2 The distance from the reference value L0 is 40km.

[0099] Then fatigue coefficient

[0100] When it is determined that the driver's fatigue level is high, i.e., the driver is fatigued, the relevant equipment in the vehicle is controlled to prompt the driver to overcome fatigue and achieve an anti-fatigue effect. For example, playing music with a strong rhythm, such as rock music; or spraying essential oils with refreshing effects in the cockpit, etc., with the aim of achieving a refreshing effect without affecting the driver's driving safety.

[0101] Figure 2 This is a schematic diagram of a fatigue driving detection device provided in an embodiment of the present invention. This fatigue driving detection device can be integrated into a vehicle or a server. Figure 2 As shown, the device includes: a first determining module 310, a second determining module 320, a third determining module 330, a fourth determining module 340, and a fifth determining module 350.

[0102] The first determining module 310 is used to determine the distance of the vehicle's current position from the next rest area, the driver's pupil information, and the continuous driving time;

[0103] The second determining module 320 is used to determine the first fatigue influence factor based on the distance of the vehicle's current position from the next rest area;

[0104] The third determining module 330 is used to determine the second fatigue influence factor based on the driver's pupil information;

[0105] The fourth determining module 340 is used to determine the third fatigue influence factor based on the continuous driving duration;

[0106] The fifth determining module 350 is used to determine the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor and the third fatigue influence factor.

[0107] Furthermore, the first determining module 310 includes a first determining unit, used to determine the distance between the vehicle's current position and the next rest area based on the vehicle navigation and positioning system; or, based on the vehicle's position at a certain moment, the real-time speed at each sampling point during the time period from the certain moment to the current moment, and the distance between the position at the certain moment and the next rest area, to determine the distance between the vehicle's current position and the next rest area at the current moment.

[0108] Furthermore, the first determining unit is specifically used for:

[0109] The distance from the vehicle's current location to the next rest area is determined using the following expression:

[0110]

[0111] Where L1 represents the distance between the vehicle's current position and the next rest area, L represents the distance between the vehicle's current position and the next rest area, and v(t) represents the vehicle's real-time speed at the sampling point.

[0112] Furthermore, the second determining module 320 is specifically used to: determine the ratio of the distance from the vehicle's current position to the next rest area to a distance reference value as the first fatigue influence factor.

[0113] Furthermore, the third determining module 330 is specifically used to: determine the ratio between the average value of the driver's pupil area and the reference value of the pupil area within a preset time period as the second fatigue influence factor.

[0114] Furthermore, the fourth determining module 340 is specifically used to: determine the data corresponding to the continuous driving time as the third fatigue influence factor based on a preset mapping relationship.

[0115] Furthermore, the fifth determining module 350 is specifically used to: determine the sum of the first fatigue influence factor and the second fatigue influence factor; and determine the driver's fatigue level based on the product of the third fatigue influence factor and the sum.

[0116] The fatigue driving recognition device provided in this embodiment determines the distance of the vehicle's current location from the next rest area, the driver's pupil information, and the continuous driving duration; determines a first fatigue influence factor based on the distance of the vehicle's current location from the next rest area; determines a second fatigue influence factor based on the driver's pupil information; determines a third fatigue influence factor based on the continuous driving duration; and determines the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor. This achieves the goal of improving the accuracy of fatigue driving recognition, vehicle driving safety, and road public safety.

[0117] The fatigue driving recognition device provided in this embodiment can execute the steps in the fatigue driving recognition method provided in this embodiment, and has the execution steps and beneficial effects, which will not be repeated here.

[0118] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this disclosure. See below for details. Figure 3 It shows a schematic diagram of a structure suitable for implementing the electronic device 500 in the embodiments of this disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0119] like Figure 3As shown, electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes to implement the methods of the embodiments described herein, based on a program stored in read-only memory (ROM) or a program loaded from storage device 508 into random access memory (RAM). RAM 503 also stores various programs and data required for the operation of electronic device 500. Processing device 501, ROM 502, and RAM 503 are interconnected via bus 504. I / O interface 505 is also connected to bus 504. Input device 506, output device 507, storage device 508, and communication device 509 are all connected to I / O interface 505.

[0120] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts, thereby implementing the in-vehicle application layer signal processing method as described above. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of embodiments of this disclosure.

[0121] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0122] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the fatigue driving recognition method of this embodiment.

[0123] Optionally, when one or more of the above-described procedures are executed by the electronic device, the electronic device may also perform other steps described in the above embodiments.

[0124] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0125] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0126] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this invention, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A method for identifying fatigued driving, characterized in that, include: Determine the vehicle's current location, distance to the next rest area, driver's pupil information, and continuous driving duration; The ratio of the distance from the vehicle's current location to the next rest area to a distance reference value is determined as the first fatigue impact factor, where the distance reference value is the limit distance at which the driver can drive without fatigue. The second fatigue influencing factor is determined based on the driver's pupil information; The third fatigue impact factor is determined based on the continuous driving duration. The driver's fatigue level is determined based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor.

2. The fatigue driving identification method according to claim 1, characterized in that, Determining the distance from the vehicle's current location to the next rest area includes: The distance from the vehicle's current location to the next rest area is determined based on the vehicle's navigation and positioning system; Alternatively, the distance between the vehicle's current position and the next rest area can be determined based on the vehicle's position at a given moment, the real-time speed at each sampling point during the time interval from that moment to the current moment, and the distance between the vehicle's position at that moment and the next rest area.

3. The fatigue driving identification method according to claim 2, characterized in that, The method of determining the distance from the vehicle's current position to the next rest area based on the vehicle's position at a given moment, the real-time speed at each sampling point during the time interval from that moment to the current moment, and the distance between the vehicle's position at that moment and the next rest area includes: The distance from the vehicle's current location to the next rest area is determined using the following expression: in, L 1 indicates the distance of the vehicle's current location from the next rest area. L This indicates the distance between the current position and the next rest area. v ( t () indicates the real-time speed of the vehicle at the sampling point.

4. The fatigue driving identification method according to claim 1, characterized in that, The determination of the second fatigue influencing factor based on the driver's pupil information includes: The ratio between the average pupil area of ​​the driver within a preset time period and the reference value of pupil area is determined as the second fatigue influencing factor. The reference value of pupil area is determined by facial recognition of the driver of the vehicle.

5. The fatigue driving identification method according to claim 1, characterized in that, The determination of the third fatigue influencing factor based on the continuous driving duration includes: Based on the preset mapping relationship between duration and fatigue impact factor, the data corresponding to the continuous driving duration is determined as the third fatigue impact factor.

6. The fatigue driving identification method according to claim 1, characterized in that, Determining the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor includes: Determine the sum of the first fatigue influence factor and the second fatigue influence factor; The driver's fatigue level is determined by multiplying the third fatigue influence factor with the sum.

7. A fatigue driving detection device, characterized in that, include: The first determining module is used to determine the distance of the vehicle's current position from the next rest area, the driver's pupil information, and the continuous driving time; The second determining module is used to determine the ratio of the distance between the vehicle's current position and the next rest area to a distance reference value as the first fatigue influence factor, wherein the distance reference value is the limit distance at which the driver can drive without fatigue. The third determining module is used to determine the second fatigue influencing factor based on the driver's pupil information; The fourth determining module is used to determine the third fatigue influence factor based on the continuous driving duration; The fifth determining module is used to determine the driver's fatigue level based on the first fatigue influence factor, the second fatigue influence factor, and the third fatigue influence factor.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the fatigue driving recognition method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the fatigue driving recognition method as described in any one of claims 1-6.

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