Driver fatigue monitoring system based on vehicle behavior and temperature

Abstract

The invention relates to the technical field of logistics transportation monitoring, in particular to a driver fatigue monitoring system based on vehicle behaviors and temperature. The system comprises the steps of S1, hardware installation and data acquisition; s2, feature extraction and fatigue score weighted calculation: setting a corresponding weighted score for each obtained feature, and setting a feature weighting rule, the fatigue score = basic score 50 + feature weighted score + context adjustment score; s3, updating the context adjustment score; and S4, performing fatigue evaluation and graded response. The current running state of the vehicle is judged by analyzing the micro-action of the steering wheel and the actions of the accelerator pedal and the brake pedal, meanwhile, the fatigue condition of the driver is comprehensively judged by combining the working duration of the driver and the current temperature in a cab, the system further sets corresponding weights for all the characteristics, the balance among all the characteristics is synthesized, and the fatigue condition of the driver is judged. Multi-aspect judgment of the fatigue degree is achieved, and when the system judges the current fatigue degree of the driver, corresponding early warning and adjusting measures are taken.

Description

Technical Field

[0001] This invention relates to the field of logistics transportation monitoring technology, and in particular to a driver fatigue monitoring system based on vehicle behavior and temperature. Background Technology

[0002] In the logistics and transportation sector, drivers of transfer vehicles need to drive for long periods of time, and driver fatigue is a major factor causing traffic accidents. Therefore, it is crucial to detect whether drivers are fatigued and the degree of fatigue. Current technologies for detecting driver fatigue generally rely on working hours, i.e., after driving continuously for a certain period of time, a broadcast reminds the driver to take a break. It is difficult to accurately determine the driver's fatigue level through single-variable detection, especially when driving at night or in high temperatures. Even if the working time is short, high fatigue may occur. Therefore, we consider collecting multiple features inside the vehicle and combining them with factors such as working hours and temperature to achieve a comprehensive assessment of fatigue and corresponding early warning. Summary of the Invention

[0003] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description and other accompanying drawings.

[0004] The purpose of this invention is to overcome the above-mentioned shortcomings and provide a driver fatigue monitoring system based on vehicle behavior and temperature. By analyzing the micro-movements of the steering wheel, the accelerator pedal, and the brake pedal, the system determines the current operating state of the vehicle. At the same time, it combines the driver's working hours and the current temperature in the cockpit to comprehensively determine the driver's fatigue level. The system also sets corresponding weights for each feature and integrates the balance between the features to achieve a multi-faceted judgment of fatigue. When the system determines the driver's current fatigue level, it takes corresponding warning and adjustment measures to achieve safe driving.

[0005] This invention provides a driver fatigue monitoring system based on vehicle behavior and temperature, comprising: S1. Hardware Installation and Data Acquisition: A temperature sensor, a driver identification module, and a vehicle status acquisition module are installed in the cab of the logistics vehicle. The temperature sensor is used to detect the current temperature inside the cab. The driver identification module is used to identify the logistics transporter and record the corresponding working time. The vehicle status acquisition module specifically includes steering wheel CAN signal, brake pedal signal, and accelerator pedal signal, which are used to collect the current status of the vehicle. S2. Feature extraction and fatigue score weighting calculation: Feature extraction is performed on the steering wheel CAN signal, vehicle pedal signal and accelerator pedal signal. A corresponding weighting score is set for each obtained feature. At the same time, feature weighting rules are set. Fatigue score = base score 50 + feature weighting score + context adjustment score. S3. Context Adjustment Score Update: The system also considers three external factors, including continuous driving time, cabin temperature and time period: Context adjustment scores are set for the obtained external factors, and after being combined with feature weighted scores and base scores, the total fatigue score is updated. S4. Fatigue Assessment and Graded Response: Based on the fatigue score, fatigue is divided into multiple levels, and different early warning mechanisms are set up to realize fatigue monitoring and timely early warning.

[0006] In some embodiments, the specific content of feature extraction in step S2 includes: Feature extraction of steering wheel CAN signal: Count the number of small steering wheel rotations within 30 seconds to obtain the average frequency of micro-movements; divide the steering wheel rotation amplitude into 10 levels, calculate the degree of disorder of various rotation amplitudes within 30 seconds to obtain the operation entropy value; calculate the proportion of time the steering wheel is stationary within 30 seconds to obtain the stationary time proportion. Feature extraction of accelerator pedal signal: Calculate the standard deviation of accelerator change rate in the last 10 seconds to obtain the accelerator change rate; Feature extraction of brake pedal signals: detect whether there is sudden braking and obtain brake abnormality indicators; The proportion of steering wheel rotation direction and throttle change rate that are consistent is statistically analyzed to obtain behavioral coordination characteristics.

[0007] In some embodiments, the calculation logic for continuous driving time in step S3 is as follows: timing starts when the vehicle starts; timing stops when the vehicle speed is less than 1 km / h and the handbrake is engaged; timing restarts from 0 when the vehicle is stopped for more than 5 minutes; timing is reset when the vehicle is turned off.

[0008] In some embodiments, the specific content of setting the context adjustment score for the obtained external factors in step S3 includes: After driving continuously for 2 hours, the fatigue score increases by 10 points for each additional hour; once the cab temperature exceeds 25°C, the fatigue score increases by 5 points for each 1°C increase; driving between 0:00-5:00 AM and 10:00-12:00 PM directly increases the fatigue score by 15 points.

[0009] In some embodiments, in step S4, the fatigue level classification and the corresponding early warning mechanism include: Under normal conditions, 0-40 minutes, indicator light is green, no special operation is required; Mild fatigue, 40-60 minutes, indicator light flashes yellow, triggers mild fatigue warning sound, cabin temperature drops by 1°C, current event is recorded locally; Moderate fatigue: 60-75 points, indicator light flashes orange, intermittent alarm sounds, cabin temperature drops by 2°C, fatigue event is uploaded to the cloud; Severe fatigue: 75-100 points, indicator light flashes red, triggers continuous alarm sound, cabin temperature drops by 3°C, maximum ventilation is activated, it is recommended to find a rest area to park, and immediately notify the fleet manager.

[0010] By adopting the above technical solution, the beneficial effects of the present invention are: This invention analyzes the micro-movements of the steering wheel, accelerator pedal, and brake pedal to determine the current operating status of the vehicle. It also combines the driver's working hours and the current temperature in the cockpit to comprehensively determine the driver's fatigue level. The system also sets corresponding weights for each feature and considers the balance between the features to achieve a multi-faceted assessment of fatigue. Once the system determines the driver's current fatigue level, it takes corresponding warning and adjustment measures to achieve safe driving.

[0011] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.

[0012] Undoubtedly, such and other objects of the present invention will become more apparent after the following detailed description of the preferred embodiments, which are illustrated in various accompanying drawings and figures.

[0013] To make the above and other objects, features and advantages of the present invention more apparent and understandable, one or more preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0014] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0015] In the accompanying drawings, the same parts use the same reference numerals, and the drawings are schematic and not necessarily drawn to actual scale.

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only one or more embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on such drawings without creative effort.

[0017] Figure 1This is a schematic diagram of the overall process of the fatigue monitoring system in some embodiments of the present invention; Figure 2 This is a schematic diagram of fatigue assessment and graded response levels in some embodiments of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0019] Furthermore, in the description of this invention, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0020] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral unit; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. However, specifying a direct connection indicates that the two main bodies are not connected through a transitional structure, but rather formed as a whole through a connecting structure. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0021] In this invention, unless otherwise expressly specified and limited, the first feature "on" or "below" the second feature may be in direct contact with the first and second features, or indirect contact through an intermediate medium. In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0022] Reference Figures 1-2 , Figure 1This is a schematic diagram of the overall process of the fatigue monitoring system in some embodiments of the present invention; Figure 2 This is a schematic diagram of fatigue assessment and graded response levels in some embodiments of the present invention.

[0023] According to some embodiments of the present invention, the present invention provides a driver fatigue monitoring system based on vehicle behavior and temperature, comprising: S1. Hardware Installation and Data Acquisition: A temperature sensor, a driver identification module, and a vehicle status acquisition module are installed in the cab of the logistics vehicle. The temperature sensor is used to detect the current temperature inside the cab. The driver identification module is used to identify the logistics transporter and record the corresponding working hours. The vehicle status acquisition module specifically includes steering wheel CAN signal, brake pedal signal, and accelerator pedal signal to collect the current vehicle status. The driver identification module can use an RFID chip or facial recognition mode to record working hours after login. S2. Feature extraction and fatigue score weighting calculation: Feature extraction is performed on the steering wheel CAN signal, vehicle pedal signal and accelerator pedal signal. A corresponding weighting score is set for each obtained feature. At the same time, feature weighting rules are set. Fatigue score = base score 50 + feature weighting score + context adjustment score. In step S2, the specific content of feature extraction includes: Feature extraction of steering wheel CAN signals: The number of small steering wheel rotations within 30 seconds was counted to obtain the average frequency of micro-movements. The range of small rotation angles was limited to 1°-5°. The average frequency of micro-movements was obtained by dividing the number of rotations by 30 seconds. The correlation between steering wheel rotation angle and fatigue is that when the driver is fatigued, attention decreases and the number of small corrections to the direction decreases, thus reducing this frequency. The steering wheel rotation amplitude is divided into 10 levels, and the degree of disorder of each rotation amplitude within 30 seconds is calculated to obtain the operation entropy value; when fatigued, the driver's steering operation becomes irregular, and the entropy value increases; Calculate the proportion of time the steering wheel remains stationary within 30 seconds to obtain the stationary time proportion. It should be understood that the stationary steering wheel in this feature does not mean that the steering wheel is completely still, but rather that the steering wheel is almost still. For example, if the rotation speed is less than 2° / second, an increase in the stationary time proportion indicates that the driver's reaction is slower when fatigued, and the time the steering wheel remains stationary increases. Feature extraction of accelerator pedal signal: Calculate the standard deviation of accelerator pedal change rate in the last 10 seconds to obtain the accelerator pedal change rate; when fatigued, accelerator pedal control becomes unstable, sometimes pressing too hard and sometimes too soft. Feature extraction of brake pedal signal: detect whether there is sudden braking and obtain braking abnormality indicator; preferably, set the judgment criteria for sudden braking: braking depth >20% and throttle is relatively large in the first 2 seconds. When fatigued, the predictive ability decreases and sudden braking without warning is more likely to occur. The proportion of steering wheel rotation direction and throttle change rate that are consistent is statistically analyzed to obtain behavioral coordination characteristics. Under normal circumstances, deceleration is usually coordinated when turning, but this coordination decreases when fatigued. This point can be used to help judge fatigue level. The total feature weighted score is 35 points. The weighting ratios for each feature are shown in Table 1. Table 1 In actual driving, the weight ratio can be adjusted according to the actual situation and historical experience. Table 1 is only a general standard. Correspondingly, other features that affect fatigue can be added in the later stages of the system to make fatigue judgment more accurate and precise.

[0024] S3. Context Adjustment Score Update: The system also considers three external factors, including continuous driving time, cabin temperature and time period: Context adjustment scores are set for the obtained external factors, and after being combined with feature weighted scores and base scores, the total fatigue score is updated. In step S3, the calculation logic for continuous driving time is as follows: timing starts when the vehicle starts; timing stops when the vehicle speed is less than 1 km / h and the handbrake is engaged; timing restarts from 0 if the vehicle is stopped for more than 5 minutes; timing is reset when the vehicle is turned off. The specific content of setting context adjustment scores for the obtained external factors includes: After driving continuously for 2 hours, the fatigue score increases by 10 points for each additional hour, up to a maximum of 50 points; once the cab temperature exceeds 25°C, the score increases by up to 25 points for each additional degree Celsius; driving between 0:00-5:00 AM and 10:00-12:00 PM directly increases the fatigue score by 15 points.

[0025] S4. Fatigue Assessment and Grading Response: Based on the fatigue score, fatigue levels are divided into multiple levels, and different early warning mechanisms are set up to achieve fatigue monitoring and timely early warning. In step S4, fatigue level classification and the corresponding early warning mechanism include: Under normal conditions, 0-40 minutes, indicator light is green, no special operation is required; Mild fatigue, 40-60 minutes, indicator light flashes yellow, triggers mild fatigue warning sound, cabin temperature drops by 1°C, current event is recorded locally; Moderate fatigue: 60-75 points, indicator light flashes orange, intermittent alarm sounds, cabin temperature drops by 2°C, fatigue event is uploaded to the cloud; Severe fatigue: 75-100 points, indicator light flashes red, triggers continuous alarm sound, cabin temperature drops by 3°C, maximum ventilation is activated, it is recommended to find a rest area to park, and immediately notify the fleet manager.

[0026] It should be understood that the embodiments disclosed herein are not limited to the specific processing steps or materials disclosed herein, but should be extended to equivalent substitutions of such features as understood by those skilled in the art. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0027] The term "embodiment" in this specification refers to a specific feature or characteristic described in connection with an embodiment that is included in at least one embodiment of the invention. Therefore, phrases or "embodiments" appearing in various places throughout the specification do not necessarily refer to the same embodiment.

[0028] Furthermore, the described features or characteristics can be incorporated into one or more embodiments in any other suitable manner. In the above description, specific details, such as thickness, quantity, etc., are provided to provide a comprehensive understanding of embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented without the aforementioned specific details or may be implemented using other methods, components, materials, etc.

Claims

1. A driver fatigue monitoring system based on vehicle behavior and temperature, characterized in that, include S1. Hardware Installation and Data Acquisition: A temperature sensor, a driver identification module, and a vehicle status acquisition module are installed in the cab of the logistics vehicle. The temperature sensor is used to detect the current temperature inside the cab. The driver identification module is used to identify the logistics transporter and record the corresponding working time. The vehicle status acquisition module specifically includes steering wheel CAN signal, brake pedal signal, and accelerator pedal signal, which are used to collect the current status of the vehicle. S2. Feature extraction and fatigue score weighting calculation: Feature extraction is performed on the steering wheel CAN signal, vehicle pedal signal and accelerator pedal signal. A corresponding weighting score is set for each obtained feature. At the same time, feature weighting rules are set. Fatigue score = base score 50 + feature weighting score + context adjustment score. S3. Context Adjustment Score Update: The system also considers three external factors, including continuous driving time, cabin temperature and time period: Context adjustment scores are set for the obtained external factors, and after being combined with feature weighted scores and base scores, the total fatigue score is updated. S4. Fatigue Assessment and Graded Response: Based on the fatigue score, fatigue is divided into multiple levels, and different early warning mechanisms are set up to realize fatigue monitoring and timely early warning.

2. The driver fatigue monitoring system based on vehicle behavior and temperature according to claim 1, characterized in that, In step S2, the specific content of feature extraction includes: Feature extraction of steering wheel CAN signal: Count the number of small steering wheel rotations within 30 seconds to obtain the average frequency of micro-movements; divide the steering wheel rotation amplitude into 10 levels, calculate the degree of disorder of various rotation amplitudes within 30 seconds to obtain the operation entropy value; calculate the proportion of time the steering wheel is stationary within 30 seconds to obtain the stationary time proportion. Feature extraction of accelerator pedal signal: Calculate the standard deviation of accelerator change rate in the last 10 seconds to obtain the accelerator change rate; Feature extraction of brake pedal signals: detect whether there is sudden braking and obtain brake abnormality indicators; The proportion of steering wheel rotation direction and throttle change rate that are consistent is statistically analyzed to obtain behavioral coordination characteristics.

3. The driver fatigue monitoring system based on vehicle behavior and temperature according to claim 1, characterized in that, In step S3, the calculation logic for continuous driving time is as follows: timing starts when the vehicle starts; timing stops when the vehicle speed is less than 1 km / h and the handbrake is engaged. If the vehicle is parked for more than 5 minutes, the timer will restart from 0; if the vehicle is turned off, the timer will reset.

4. The driver fatigue monitoring system based on vehicle behavior and temperature according to claim 3, characterized in that, In step S3, the specific details of setting the context adjustment score for the obtained external factors include: After driving continuously for 2 hours, the fatigue score increases by 10 points for each additional hour; once the cab temperature exceeds 25°C, the fatigue score increases by 5 points for each 1°C increase; driving between 0:00-5:00 AM and 10:00-12:00 PM directly increases the fatigue score by 15 points.

5. The driver fatigue monitoring system based on vehicle behavior and temperature according to claim 1, characterized in that, In step S4, fatigue level classification and the corresponding early warning mechanism include: Under normal conditions, 0-40 minutes, indicator light is green, no special operation is required; Mild fatigue, 40-60 minutes, indicator light flashes yellow, triggers mild fatigue warning sound, cabin temperature drops by 1°C, current event is recorded locally; Moderate fatigue: 60-75 points, indicator light flashes orange, intermittent alarm sounds, cabin temperature drops by 2°C, fatigue event is uploaded to the cloud; Severe fatigue: 75-100 points, indicator light flashes red, triggers continuous alarm sound, cabin temperature drops by 3°C, maximum ventilation is activated, it is recommended to find a rest area to park, and immediately notify the fleet manager.

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