CN115366909B - Dynamic early warning method and device for driver accidents in long and large longitudinal slope section and electronic equipment - Google Patents
Dynamic early warning method and device for driver accidents in long and large longitudinal slope section and electronic equipment Download PDFInfo
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- CN115366909B CN115366909B CN202211291757.1A CN202211291757A CN115366909B CN 115366909 B CN115366909 B CN 115366909B CN 202211291757 A CN202211291757 A CN 202211291757A CN 115366909 B CN115366909 B CN 115366909B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2510/00—Input parameters relating to a particular sub-units
- B60W2510/18—Braking system
- B60W2510/184—Brake temperature, e.g. of fluid, pads or discs
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/225—Direction of gaze
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/229—Attention level, e.g. attentive to driving, reading or sleeping
Abstract
The application provides a dynamic early warning method and device for accidents of a driver in a long and large longitudinal slope section and electronic equipment, and belongs to the technical field of safety early warning. The dynamic early warning method for the accidents of the driver on the long and large longitudinal slope section judges the opening and closing state of eyes by utilizing the image of the working area of the driver and determines the fatigue state of the driver; judging whether the steering wheel rotates within a preset time or not by acquiring steering wheel angle value data; and predicting the brake temperature at the end of the downhill according to the road section information of the long and large longitudinal slope and the vehicle information of the driving vehicle. When potential driving risks exist, early warning is carried out on a driver, and traffic accidents are reduced.
Description
Technical Field
The application relates to the technical field of safety early warning, in particular to a dynamic early warning method and device for a driver accident in a long and large longitudinal slope section and electronic equipment.
Background
In mountain areas, the altitude difference is large, the terrain and geological conditions are complex, the construction difficulty of the highway is high, the design of the highway with a longer slope length and a larger slope is adopted, the possibility of traffic accidents is higher when the highway runs on the road section compared with a gentle road section in a plain area, the temperature of a brake can be increased due to frequent braking when the highway runs on a continuous long and large longitudinal slope section, and the brake can be easily failed due to rapid increase of the temperature in a short time. In addition, for trucks traveling on long and large longitudinal slope sections, long-time driving on mountain roads is prone to fatigue, fatigue driving of drivers leads to dangerous driving behaviors, traffic accidents are prone to occur, and rear-end collisions or collision with guardrails occur.
In order to provide early warning of the current driving behavior of the driver, it is necessary to provide dynamic early warning of dangerous behaviors that potentially lead to accidents.
Disclosure of Invention
An object of the embodiment of the application is to provide a dynamic early warning method, device and electronic equipment for a driver accident in a long and large longitudinal slope section, so that the driving behavior of the driver is monitored, the driving behavior with hidden danger is found in time, the driver is reminded and warned, and the road traffic safety is better guaranteed.
In order to achieve the above object, embodiments of the present application are implemented as follows:
in a first aspect, an embodiment of the present application provides a dynamic early warning method for a driver accident in a long and large longitudinal slope section, including: the method comprises the steps of obtaining an image of a working area of a driver to carry out image recognition, determining eye characteristics of the driver, judging the opening and closing state of eyes according to the eye characteristics of the driver, determining the fatigue state of the driver, and determining that a first condition is met if the driver is in the fatigue state.
And acquiring steering wheel angle value data to judge whether the steering wheel rotates within the preset time, and determining that a second condition is met if the steering wheel does not rotate within the preset time.
The method comprises the steps of obtaining road section information of a long longitudinal slope section of a navigation route, obtaining vehicle information of a driving vehicle, determining the temperature of a brake when a downhill is finished under the condition of no auxiliary braking according to the current road section information and the current vehicle information, and determining that a third condition is met when the temperature of the brake is higher than a preset temperature.
And when any one of the first condition, the second condition and the third condition is met, determining that accident potential exists in the driving state, and sending out reminding information.
With reference to the first aspect, in some embodiments, obtaining an image of a driver's work area for image recognition to determine a driver's eye characteristics, determining a driver's fatigue state based on the eye opening and closing state determined based on the driver's eye characteristics, includes
Carrying out face detection on the image of the working area of the driver, determining parameters of the width and the height of the face, carrying out eye detection on the face area, carrying out primary positioning on the iris, and determining the position parameter of the iris of the current frame image; based on an adjacent frame difference method, acquiring an adjacent frame difference binary image by using an absolute value of an adjacent frame difference of a front frame image and a rear frame image, judging whether the front frame image and the rear frame image have an intersection or not based on the adjacent frame difference binary image, repeating the previous step if the front frame image and the rear frame image do not have the intersection, detecting a face movement parameter if the front frame image and the rear frame image have the intersection, and determining a position parameter of an iris in a current frame image according to the movement parameter; detecting the vertical edge according to a Sobel operator, acquiring an iris area image, and identifying open-eye and closed-eye images; performing edge detection on the image of the open eye iris region to obtain the junction of the iris and the upper eyelid and the lower eyelid, determining the length of the eye according to the edge of the upper eyelid and the lower eyelid, and defining the opening value of the eye according to the ratio of the iris exposure area to the eye length; obtaining working area images in equal time intervals within a preset time period T according to the time sequence, and obtaining eye opening values of corresponding frame images according to the steps; drawing a curve by taking the time sequence as an abscissa and the eye opening value of the corresponding frame image as an ordinate, acquiring a region area S formed by the curve and the abscissa in a surrounding manner, and determining the eye opening of the time period according to the ratio of the region area S to the time period T; and comparing the opening degree with a preset threshold value, and determining that the driver is in a fatigue state when the opening degree is smaller than the preset threshold value.
With reference to the first aspect, in some embodiments, the steering wheel angle value data is acquired by a steering wheel angle sensor.
With reference to the first aspect, in some embodiments, the reminder information is an audible alert information and/or a light alert information.
With reference to the first aspect, in some embodiments, when any one of the first condition, the second condition, and the third condition is satisfied, it is determined that an accident potential exists in the driving state, and a warning message is sent, specifically: when any one of the first condition, the second condition and the third condition is only met, the reminding information is sound alarm information; when only two conditions of the first condition, the second condition and the third condition are met, the reminding information is light alarm information; when any one of the first condition, the second condition and the third condition is met, the reminding information is sound alarm information and light alarm information. With reference to the first aspect, in some embodiments, the road segment information comprises: road segment number, road segment length, and road segment grade.
With reference to the first aspect, in some embodiments, the vehicle information of the driven vehicle includes a vehicle number, a vehicle mass, a vehicle speed, and a brake current temperature.
With reference to the first aspect, in some embodiments, determining the brake temperature at the end of the downhill under no-auxiliary-braking conditions based on the current road section information and the current vehicle information comprises:
simplifying continuous road conditions of the long and large longitudinal slope section, neglecting transitional continuous slopes among different longitudinal slopes, regarding the long and large longitudinal slope section as a longitudinal slope with the same slope, wherein the starting point of the longitudinal slope with the same slope is the starting point of the long and large longitudinal slope section before simplification,
the long and large longitudinal slope section is assumed to havenSection-continuous longitudinal slope, then
The length of the longitudinal slope with the same gradient is defined as
L=L 1 + L 2 + L 3 …+L n Wherein, in the step (A),Lthe length of the slope is the length of the slope,L 1 is the slope length of the 1 st section continuous longitudinal slope,L 2 the slope length of the 2 nd continuous longitudinal slope,L 3 is the slope length of the 3 rd continuous longitudinal slope,L n is as followsnThe length of the continuous longitudinal slope.
The gradient of the longitudinal slope with the same gradient is defined as
I=（I 1 L 1 +I 2 L 2 +I 3 L 3 …+I 1 L n ）/（L 1 +L 2 +L 3 …+L n ），
Wherein the content of the first and second substances,Iin order to be the slope of the slope,I 1 is the gradient of the 1 st section continuous longitudinal slope,I 2 is the gradient of the 2 nd continuous longitudinal slope,I 3 the slope of the 3 rd section continuous longitudinal slope,I n is a firstnThe slope of the continuous longitudinal slope.
The vehicle speed is assumed to be constant asVAccording to the simplified large longitudinal slopeAnd road section parameters, namely the temperature of the brake at the end of the downhill under the condition of no auxiliary braking.
In combination with the first aspect, in some embodiments, the brake temperature at the end of the downhill slope
When the gradient of the longitudinal slope with the same gradient is more than 2 percent and I is less than or equal to 5 percent,
when the gradient of the longitudinal slope with the same gradient is I more than 5 percent,
in the formula (I), the compound is shown in the specification,
the running time of the continuous longitudinal slope; h is the height difference between the starting point and the end point before the simplification of the continuous longitudinal slope; m is the total mass of the vehicle, and>
in order to be the acceleration of the gravity,kin order to correct the coefficient (when the gradient is above 5%, every time the gradient is increased by 1%,kthe value increases by 0.1, wherein, at a gradient of 5%,K=1），P 0 is the current temperature of the brake>
Brake temperature at the end of the downhill slope.
In a second aspect, an embodiment of the present application provides a dynamic early warning device for driver accidents in long and large longitudinal slope sections, including: the first judgment module is used for acquiring an image of a working area of a driver to perform image recognition, determining the eye characteristics of the driver, judging the opening and closing state of eyes according to the eye characteristics of the driver, determining the fatigue state of the driver, and determining that a first condition is met if the driver is in the fatigue state.
And the second judgment module is used for acquiring steering wheel angle value data to judge whether the steering wheel rotates within the preset time, and if the steering wheel does not rotate within the preset time, the second judgment module determines that a second condition is met.
The third judgment module is used for acquiring the road section information of the long and large longitudinal slope road section of the navigation route, acquiring the vehicle information of the driving vehicle, determining the brake temperature when the downhill is finished under the condition of no auxiliary braking according to the current road section information and the current vehicle information, and determining that the third condition is met when the brake temperature is higher than the preset temperature.
And the reminding module is used for determining that accident potential exists in the driving state and sending reminding information when any one of the first condition, the second condition and the third condition is met.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory and a processor, where the memory is configured to store information including program instructions, and the processor is configured to control execution of the program instructions, where the program instructions are loaded and executed by the processor to implement the dynamic early warning method for driver accidents on a long and steep longitudinal slope section according to the first aspect or any one of possible implementation manners of the first aspect.
According to the dynamic early warning method for the driver accidents on the long and large longitudinal slope section, the opening and closing state of the eyes is judged by using the image of the working area of the driver, and the fatigue state of the driver is determined; judging whether the steering wheel rotates within a preset time or not by acquiring data of steering wheel angle values; and predicting the brake temperature at the end of the downhill according to the road section information of the long and large longitudinal slope and the vehicle information of the driving vehicle. When potential driving risks exist, early warning is carried out on a driver, and traffic accidents are reduced.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a flowchart of a dynamic early warning method for a driver accident in a long and large longitudinal slope section according to an embodiment of the present application;
fig. 2 is a schematic view of a dynamic early warning device for an accident of a driver on a long and large longitudinal slope section according to an embodiment of the present application;
fig. 3 is a schematic view of an electronic device according to an embodiment of the present application.
Icon: 10-a dynamic early warning device for accidents of drivers on long and large longitudinal slope sections; 11-a first judgment module; 12-a second judgment module; 13-a third judgment module; 14-a reminder module; 20-an electronic device; 21-a memory; 22-a communication module; 23-a bus; 24-a processor.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, fig. 1 is a flowchart of a dynamic early warning method for an accident of a driver on a long and large longitudinal slope section according to an embodiment of the present application. In this embodiment, the dynamic early warning method for the driver accident in the long and large longitudinal slope section may be executed by an electronic device, where the electronic device may be a server (e.g., a cloud server, a server cluster, etc.) or a terminal (e.g., a personal computer, a notebook computer, etc.), and is not limited herein.
In this embodiment, the dynamic early warning method for the accident of the driver on the long and large longitudinal slope section may include step S10, step S20, step S30 and step S40.
In order to dynamically early warn the driver of the long and large longitudinal slope section of the accident, the electronic device may perform step S10.
Step S10: the method comprises the steps of obtaining an image of a working area of a driver to perform image recognition, determining eye characteristics of the driver, judging the opening and closing state of eyes according to the eye characteristics of the driver, determining the fatigue state of the driver, and determining that a first condition is met if the driver is in the fatigue state.
In this embodiment, the electronic device may determine the driver fatigue state. The fatigue state of the driver can be mainly obtained by the following method:
and carrying out face detection on the image of the working area of the driver, determining parameters of the width and the height of the face, carrying out eye detection on the face area, carrying out primary positioning on the iris, and determining the position parameter of the iris of the current frame image.
Based on an adjacent frame difference method, acquiring an adjacent frame difference binary image by using an absolute value of an adjacent frame difference of a front frame image and a rear frame image, judging whether the front frame image and the rear frame image have an intersection or not based on the adjacent frame difference binary image, repeating the previous step if the front frame image and the rear frame image have no intersection, detecting a face movement parameter if the front frame image and the rear frame image have the intersection, and determining a position parameter of an iris in a current frame image according to the movement parameter.
And detecting the vertical edge according to a Sobel operator, acquiring an iris area image, and identifying open-eye and closed-eye images.
Performing edge detection on the image of the open eye iris region, acquiring the boundary of the iris and the upper eyelid and the lower eyelid, regarding the region between the upper eyelid and the lower eyelid as the exposed area of the iris, determining the length of the eye according to the edge of the upper eyelid and the lower eyelid, and defining the eye opening value according to the ratio of the exposed area of the iris to the length of the eye.
And obtaining working area images in equal time intervals within a preset time period T according to the time sequence, and obtaining eye opening values of corresponding frame images according to the steps.
And drawing a curve by taking the time sequence as an abscissa and the eye opening value of the corresponding frame image as an ordinate, acquiring a region area S formed by the curve and the abscissa in a surrounding manner, and determining the eye opening of the time period by using the ratio of the region area S to the time period T.
And comparing the opening degree with a preset threshold value, and determining that the driver is in a fatigue state when the opening degree is smaller than the preset threshold value.
The method comprises the steps of firstly carrying out face detection on a driver working area image, determining face width and height parameters, carrying out primary positioning on an iris position, then obtaining a binary image of an adjacent frame difference value by using an absolute value of an adjacent frame difference of two frames of images before and after the driver working area image based on an adjacent frame difference method, judging whether the two frames of images before and after the driver working area image have an intersection or not based on the binary image of the adjacent frame difference value, detecting a face moving parameter if the two frames of images before and after the driver working area image have the intersection, and determining a position parameter of the iris in a current frame image according to the moving parameter. The inventor finds in practice that in a non-iris area, vertical edge information is little, and the edge detection effect is better by using a Sobel operator. After obtaining the iris area image and identifying the open eye image and the closed eye image, the edge detection is performed on the open eye image again, the boundary of the iris, the upper eyelid and the lower eyelid is obtained, and the eye opening value of the corresponding frame image is defined. And finally, determining the eye opening degree in unit time by adopting a graphic method, and representing the fatigue state of the driver by using the eye opening degree.
After acquiring the fatigue state of the driver, the electronic device may perform step S20.
Step S20: and acquiring steering wheel angle value data to judge whether the steering wheel rotates within the preset time, and determining that a second condition is met if the steering wheel does not rotate within the preset time.
Here, the steering wheel angle value data is acquired by the steering wheel angle sensor, and is not limited herein.
When a driver is in a fatigue state, the operation action is sluggish, sometimes even the driver forgets to operate, even the driver sleeps for a short time, and the steering wheel does not rotate for a long time. The steering wheel angle value is acquired through the steering wheel angle sensor, and the warning can be given when the steering wheel does not rotate for a long time.
After determining whether the steering wheel is rotated within the preset time, the electronic device may perform step S30.
Step S30: the method comprises the steps of obtaining road section information of a long longitudinal slope section of a navigation route, obtaining vehicle information of a driving vehicle, determining the temperature of a brake when a downhill is finished under the condition of no auxiliary braking according to the current road section information and the current vehicle information, and determining that a third condition is met when the temperature of the brake is higher than a preset temperature.
Here, determining the brake temperature at the end of a downhill without auxiliary braking conditions from current road section information (e.g., road section number, road section length, and road section grade) and current vehicle information (vehicle number, vehicle mass (including driver and cargo weight), vehicle speed, and brake current temperature) includes:
simplifying continuous road conditions of the long and large longitudinal slope section, neglecting transitional continuous slopes among different longitudinal slopes, regarding the sections as longitudinal slopes with the same gradient, wherein the starting point of the longitudinal slope with the same gradient is the starting point of the long and large longitudinal slope section before simplification,
the long and large longitudinal slope section is assumed to havenSection-continuous longitudinal slope, then
The length of the longitudinal slope with the same gradient is defined as
L=L 1 + L 2 + L 3 …+L n Wherein, in the process,Lthe length of the slope is the length of the slope,L 1 is the slope length of the 1 st section continuous longitudinal slope,L 2 is the slope length of the 2 nd continuous longitudinal slope,L 3 the slope length of the 3 rd section continuous longitudinal slope,L n is as followsnThe length of the continuous longitudinal slope.
The gradient of the longitudinal slope with the same gradient is defined as
I=（I 1 L 1 +I 2 L 2 +I 3 L 3 …+I 1 L n ）/（L 1 +L 2 +L 3 …+L n ），
Wherein, the first and the second end of the pipe are connected with each other,Iin order to be the slope of the slope,I 1 is the gradient of the 1 st section continuous longitudinal slope,I 2 is the gradient of the 2 nd section continuous longitudinal slope,I 3 the slope of the 3 rd section continuous longitudinal slope,I n is as followsnThe slope of the continuous longitudinal slope.
Assuming that the vehicle runs down a long and large longitudinal slope sectionThe velocity is constant atVAnd determining the brake temperature at the end of the downhill under the condition of no auxiliary braking by combining the temperature rising rules under different slopes based on energy conservation and simplified long and large longitudinal slope section parameters.
When the gradient of the longitudinal slope with the same gradient is more than 2 percent and I is less than or equal to 5 percent,
when the gradient of the longitudinal slope with the same gradient is I more than 5 percent,
in the formula (I), the compound is shown in the specification,
the running time of the continuous longitudinal slope; h is the height difference between the starting point and the end point before the simplification of the continuous longitudinal slope; m is the total mass of the vehicle, and>
in order to be the acceleration of the gravity,kin order to correct the coefficient (when the gradient is above 5%, every time the gradient is increased by 1%,kthe value increases by 0.1, wherein, at a gradient of 5%,K=1），P 0 is the current temperature of the brake>
Brake temperature at the end of the downhill slope.
In the method, transition continuous slopes are arranged among different longitudinal slopes of the existing long continuous longitudinal slope, the gradient of the transition continuous slopes is relatively slow, the design is also convenient for reducing the speed of the vehicle, and the buffer section is generally shorter than the longitudinal slope section and can be ignored. The early warning difficulty of the long and large longitudinal slope section is that the slope length and the slope gradient of different sections are different, so that the application provides a new design idea, the long and large continuous longitudinal slope section is simplified into a single slope, the slope gradient and the slope length of the single slope are redefined, and then the temperature rise model under the condition of no auxiliary braking is respectively determined according to the slope gradient of the long and large longitudinal slope, so that when a driver enters the long and large longitudinal slope section, the temperature rise condition of the brake is predicted on the assumption that the driver does not perform auxiliary braking operation, early warning is performed, and the driver is reminded of possibly adopting auxiliary braking and reasonably decelerates.
After determining the end-of-descent brake temperature, the electronic device may perform step S40.
Step S40: and when any one of the first condition, the second condition and the third condition is met, determining that accident potential exists in the driving state, and sending out reminding information.
In this embodiment, the reminding information is sound alarm information and/or light alarm information. Exemplarily, when any one of the first condition, the second condition and the third condition is satisfied, it is determined that there is an accident potential in the driving state, and a warning message is sent, specifically:
when any one of the first condition, the second condition and the third condition is only met, the reminding information is sound alarm information; when only two conditions of the first condition, the second condition and the third condition are met, the reminding information is light alarm information; and when any one of the first condition, the second condition and the third condition is met, the reminding information is sound alarm information and light alarm information.
Therefore, the driver can be reminded in a differentiated mode according to the conditions of the current behavior of the driver, and when the driver is in an extremely dangerous condition, the driver can be reminded through sound alarm information and light alarm information.
Therefore, according to the dynamic early warning method for the accidents of the driver on the long and large longitudinal slope section, the opening and closing state of the eyes is judged by utilizing the image of the working area of the driver, and the fatigue state of the driver is determined; judging whether the steering wheel rotates within a preset time or not by acquiring steering wheel angle value data; and predicting the brake temperature at the end of the downhill according to the road section information of the long and large longitudinal slope and the vehicle information of the driving vehicle. When potential driving risks exist, early warning is carried out on a driver, and traffic accidents are reduced.
Referring to fig. 2, fig. 2 is a schematic view of a dynamic early warning device for an accident of a driver on a long and large longitudinal slope section according to an embodiment of the present application.
In this embodiment, the dynamic early warning device 10 for driver accident in long and large longitudinal slope section may include:
the first judging module 11 is configured to acquire an image of a work area of a driver to perform image recognition, determine eye characteristics of the driver, judge an opening and closing state of eyes according to the eye characteristics of the driver, determine a fatigue state of the driver, and determine that a first condition is met if the driver is in the fatigue state.
The second judging module 12 is configured to obtain steering wheel angle value data, judge whether the steering wheel rotates within a preset time, and determine that a second condition is satisfied if the steering wheel does not rotate within the preset time.
The third judging module 13 is configured to acquire road information of a long and large longitudinal slope road section of the navigation route, acquire vehicle information of a driving vehicle, determine a brake temperature at the end of a downhill under a condition without auxiliary braking according to the current road information and the current vehicle information, and determine that a third condition is satisfied when the brake temperature is greater than a preset temperature.
And the reminding module 14 is configured to determine that the driving state has accident potential and send out reminding information when any one of the first condition, the second condition and the third condition is met.
In addition, referring to fig. 3, fig. 3 is a schematic view of an electronic device 20 according to an embodiment of the present disclosure.
In this embodiment, the electronic device 20 may be a terminal, such as a tablet computer, a personal computer, etc.; the electronic device 20 may also be a server, such as a cloud server, a server cluster, etc., and is not limited herein.
Illustratively, the electronic device 20 may include: a communication module 22 connected to the outside world via a network, one or more processors 24 for executing program instructions, a bus 23, and a different form of memory 21, such as a disk, ROM, or RAM, or any combination thereof. The memory 21, the communication module 22, and the processor 24 may be connected by a bus 23.
Illustratively, the memory 21 has stored therein a program. The processor 24 may call and run the programs from the memory 21, so that the dynamic early warning method for the driver accident in the long and large longitudinal slope section can be realized by running the programs.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (7)
1. A dynamic early warning method for accidents of drivers in long and large longitudinal slope sections is characterized by comprising the following steps:
acquiring an image of a working area of a driver for image recognition, determining the eye characteristics of the driver, judging the opening and closing state of eyes according to the eye characteristics of the driver, determining the fatigue state of the driver, and determining that a first condition is met if the driver is in the fatigue state;
acquiring steering wheel angle value data to judge whether the steering wheel rotates within preset time, and determining that a second condition is met if the steering wheel does not rotate within the preset time;
acquiring road section information of a long and large longitudinal slope road section of a navigation route, acquiring vehicle information of a driving vehicle, determining the temperature of a brake at the end of a downhill under the condition of no auxiliary braking according to the current road section information and the current vehicle information, and determining that a third condition is met when the temperature of the brake is greater than a preset temperature;
when any one of the first condition, the second condition and the third condition is met, determining that accident potential exists in the driving state, and sending out reminding information;
wherein the link information includes: the method comprises the steps of obtaining vehicle information of a driving vehicle, including a vehicle number, vehicle mass, vehicle speed and current temperature of a brake, according to the length of a road section and the gradient of the road section;
determining the brake temperature at the end of a downhill under the condition of no auxiliary braking according to the current road section information and the current vehicle information, wherein the method comprises the following steps:
simplifying continuous road conditions of the long and large longitudinal slope section, neglecting transitional continuous slopes among different longitudinal slopes, regarding the sections as longitudinal slopes with the same gradient, wherein the starting point of the longitudinal slope with the same gradient is the starting point of the long and large longitudinal slope section before simplification,
the long and large longitudinal slope section is assumed to havenSection-continuous longitudinal slope, then
The length of the longitudinal slope with the same gradient is defined as
L=L 1 + L 2 + L 3 …+L n Wherein, in the step (A),Lthe length of the slope is the length of the slope,L 1 is the slope length of the 1 st section continuous longitudinal slope,L 2 is as followsThe slope length of the 2-section continuous longitudinal slope,L 3 is the slope length of the 3 rd continuous longitudinal slope,L n is a firstnThe slope length of the segmental continuous longitudinal slope;
the gradient of the longitudinal slope with the same gradient is defined as
I=（I 1 L 1 +I 2 L 2 +I 3 L 3 …+I 1 L n ）/（L 1 +L 2 +L 3 …+L n ），
Wherein the content of the first and second substances,Iin order to be the slope of the slope,I 1 is the gradient of the 1 st section continuous longitudinal slope,I 2 is the gradient of the 2 nd continuous longitudinal slope,I 3 the slope of the 3 rd section continuous longitudinal slope,I n is a firstnThe gradient of the segmental continuous longitudinal slope;
the vehicle speed is assumed to be constant asVDetermining the temperature of a brake at the end of a downhill under the condition of no auxiliary braking according to the simplified parameters of the long and large longitudinal slope section;
when the gradient of the longitudinal slope with the same gradient is more than 2 percent and I is less than or equal to 5 percent,
when the gradient of the longitudinal slope with the same gradient is I more than 5 percent,
in the formula (I), the compound is shown in the specification,
the running time of the continuous longitudinal slope; h is the height difference between the starting point and the end point before the simplification of the continuous longitudinal slope; m is the total mass of the vehicle, and>
is heavyThe acceleration of the force is accelerated and,kfor correcting the coefficient, when the gradient reaches more than 5 percent and every time the gradient is improved by 1 percent,kthe value increases by 0.1, wherein, at a gradient of 5%,k=1，P 0 for the current temperature of the brake>
Brake temperature at the end of the downhill slope.
2. The dynamic early warning method for the accidents of the driver on the long and long longitudinal slope road section as claimed in claim 1, wherein the image of the working area of the driver is obtained to identify the eye characteristics of the driver through image recognition, the eye opening and closing state is judged according to the eye characteristics of the driver, and the fatigue state of the driver is determined, which comprises the steps of
Carrying out face detection on the image of the working area of the driver, determining parameters of the width and the height of the face, carrying out eye detection on the face area, carrying out primary positioning on the iris, and determining the position parameter of the iris of the current frame image;
based on an adjacent frame difference method, acquiring an adjacent frame difference binary image by using an absolute value of an adjacent frame difference of a front frame image and a rear frame image, judging whether the front frame image and the rear frame image have an intersection or not based on the adjacent frame difference binary image, repeating the previous step if the front frame image and the rear frame image do not have the intersection, detecting a face movement parameter if the front frame image and the rear frame image have the intersection, and determining a position parameter of an iris in a current frame image according to the movement parameter;
detecting the vertical edge according to a Sobel operator, acquiring an iris area image, and identifying open-eye and closed-eye images;
performing edge detection on the image of the open eye iris region to obtain the junction of the iris and the upper eyelid and the lower eyelid, determining the length of the eye according to the edge of the upper eyelid and the lower eyelid, and defining the opening value of the eye according to the ratio of the iris exposure area to the eye length;
obtaining working area images in equal time intervals within a preset time period T according to the time sequence, and obtaining eye opening values of corresponding frame images according to the steps;
drawing a curve by taking the time sequence as an abscissa and the eye opening value of the corresponding frame image as an ordinate, acquiring a region area S formed by the curve and the abscissa in a surrounding manner, and determining the eye opening of the time period according to the ratio of the region area S to the time period T;
and comparing the opening degree with a preset threshold value, and determining that the driver is in a fatigue state when the opening degree is smaller than the preset threshold value.
3. The dynamic early warning method for the accidents of the drivers on the long and large longitudinal slope sections according to claim 1, wherein steering wheel angle value data is acquired by a steering wheel angle sensor.
4. The dynamic early warning method for the accidents of the drivers on the long and large longitudinal slope sections according to claim 1, wherein the reminding information is sound alarm information and/or light alarm information.
5. The dynamic early warning method for the accident of the driver on the long and large longitudinal slope section as claimed in claim 4, wherein when any one of the first condition, the second condition and the third condition is met, it is determined that the accident potential exists in the driving state, and a warning message is sent, specifically:
when any one of the first condition, the second condition and the third condition is only met, the reminding information is sound alarm information;
when only two conditions of the first condition, the second condition and the third condition are met, the reminding information is light alarm information;
and when any one of the first condition, the second condition and the third condition is met, the reminding information is sound alarm information and light alarm information.
6. A dynamic early warning device for accidents of drivers on long and large longitudinal slope sections is characterized by comprising
The first judgment module is used for acquiring images of a working area of a driver to perform image recognition, determining the eye characteristics of the driver, judging the opening and closing state of eyes according to the eye characteristics of the driver, determining the fatigue state of the driver, and determining that a first condition is met if the driver is in the fatigue state;
the second judgment module is used for acquiring steering wheel angle value data to judge whether the steering wheel rotates within the preset time, and if the steering wheel does not rotate within the preset time, the second judgment module determines that a second condition is met;
the third judgment module is used for acquiring the road section information of a long and large longitudinal slope road section of the navigation route, acquiring the vehicle information of a driving vehicle, determining the brake temperature at the end of a downhill under the condition of no auxiliary brake according to the current road section information and the current vehicle information, and determining that a third condition is met when the brake temperature is greater than a preset temperature;
the reminding module is used for determining that accident potential exists in the driving state and sending reminding information when any one of the first condition, the second condition and the third condition is met;
wherein the link information includes: the method comprises the steps of obtaining vehicle information of a driving vehicle, including a vehicle number, vehicle mass, vehicle speed and current temperature of a brake, according to the length of a road section and the gradient of the road section;
determining the brake temperature at the end of a downhill under the condition of no auxiliary braking according to the current road section information and the current vehicle information, wherein the method comprises the following steps:
simplifying continuous road conditions of the long and large longitudinal slope section, neglecting transitional continuous slopes among different longitudinal slopes, regarding the sections as longitudinal slopes with the same gradient, wherein the starting point of the longitudinal slope with the same gradient is the starting point of the long and large longitudinal slope section before simplification,
the long and large longitudinal slope section is assumed to havenSection-continuous longitudinal slope, then
The length of the longitudinal slope with the same gradient is defined as
L=L 1 + L 2 + L 3 …+L n Wherein, in the step (A),Lthe length of the slope is the length of the slope,L 1 is the slope length of the 1 st section continuous longitudinal slope,L 2 the slope length of the 2 nd continuous longitudinal slope,L 3 slope of 3 rd continuous longitudinal slopeThe length of the utility model is long,L n is as followsnThe length of the section of continuous longitudinal slope;
the gradient of the longitudinal slope with the same gradient is defined as
I=（I 1 L 1 +I 2 L 2 +I 3 L 3 …+I 1 L n ）/（L 1 +L 2 +L 3 …+L n ），
Wherein the content of the first and second substances,Iin order to be the slope of the slope,I 1 is the gradient of the 1 st section continuous longitudinal slope,I 2 is the gradient of the 2 nd section continuous longitudinal slope,I 3 the slope of the 3 rd section continuous longitudinal slope,I n is as followsnThe gradient of the segmental continuous longitudinal slope;
the vehicle speed is assumed to be constant during the downhill process of a long and large longitudinal slope sectionVDetermining the temperature of a brake at the end of a downhill under the condition of no auxiliary braking according to the simplified parameters of the long and large longitudinal slope section;
when the gradient of the longitudinal slope with the same gradient is more than 2 percent and I is less than or equal to 5 percent,
when the gradient of the longitudinal slope with the same gradient is I more than 5 percent,
in the formula (I), the compound is shown in the specification,
the running time of the continuous longitudinal slope; h is the height difference between the starting point and the end point before the simplification of the continuous longitudinal slope; m is the total mass of the vehicle, based on the sum of the measured values>
In order to be the acceleration of the gravity,kfor correcting the coefficient, when the gradient reaches more than 5 percent, the gradientEvery time the yield is increased by 1 percent,kthe value increases by 0.1, wherein, at a gradient of 5%,k=1，P 0 is the current temperature of the brake>
Brake temperature at the end of the downhill slope.
7. An electronic device, comprising a memory for storing information including program instructions and a processor for controlling execution of the program instructions, wherein the program instructions are loaded and executed by the processor to implement the dynamic early warning method for accidents of drivers on long and long longitudinal slope sections as claimed in any one of claims 1 to 5.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105404746A (en) * | 2015-12-01 | 2016-03-16 | 桂林电子科技大学 | Reliability design method for long and steep downhill highway |
| CN105446391A (en) * | 2015-12-07 | 2016-03-30 | 长安大学 | Temperature rise prediction method for long downgrade driving brake for lorry |
| CN106504164A (en) * | 2016-10-19 | 2017-03-15 | 东南大学 | A kind of division methods of combination area of city and country's inferior grade road speeds control zone |
| CN108340900A (en) * | 2018-01-31 | 2018-07-31 | 中交第二公路勘察设计研究院有限公司 | Truck hub temperature predicting method of the large longitudinal slope route based on brake behavior |
| CN109017740A (en) * | 2018-07-29 | 2018-12-18 | 合肥市智信汽车科技有限公司 | A kind of temperature monitoring method for automobile |
| CN114715111A (en) * | 2022-05-07 | 2022-07-08 | 交通运输部公路科学研究所 | Freight vehicle brake temperature estimation method based on TBOX |
Family Cites Families (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS59153625A (en) * | 1983-02-18 | 1984-09-01 | Nissan Motor Co Ltd | Dozing-drive detecting apparatus |
| DE102005026456B4 (en) * | 2005-06-09 | 2017-04-20 | Daimler Ag | Method for detecting fatigue |
| CN101872171B (en) * | 2009-04-24 | 2012-06-27 | 中国农业大学 | Driver fatigue state recognition method and system based on information fusion |
| CN101692980B (en) * | 2009-10-30 | 2011-06-08 | 深圳市汉华安道科技有限责任公司 | Method and device for detecting fatigue driving |
| US8731795B2 (en) * | 2010-10-12 | 2014-05-20 | Bendix Commercial Vehicle Systems Llc | System and method for reducing brake fade |
| CN104809445B (en) * | 2015-05-07 | 2017-12-19 | 吉林大学 | method for detecting fatigue driving based on eye and mouth state |
| CN204956446U (en) * | 2015-09-30 | 2016-01-13 | 山西省交通科学研究院 | Big freight train brake drum temperature rise in downhill path highway section of growing up is reported to police and cooling system |
| CN107139934B (en) * | 2017-07-03 | 2023-04-28 | 吉林大学 | Sedan driver fatigue relieving and awakening system and method based on masking effect |
| US11040726B2 (en) * | 2017-12-15 | 2021-06-22 | Baidu Usa Llc | Alarm system of autonomous driving vehicles (ADVs) |
| CN108446600A (en) * | 2018-02-27 | 2018-08-24 | 上海汽车集团股份有限公司 | A kind of vehicle driver's fatigue monitoring early warning system and method |
| CN208515586U (en) * | 2018-03-20 | 2019-02-19 | 星展测控科技股份有限公司 | A kind of long descending control system of automobile |
| CN108720851B (en) * | 2018-05-23 | 2021-06-29 | 释码融和（上海）信息科技有限公司 | Driving state detection method, mobile terminal and storage medium |
| GB2577270B (en) * | 2018-09-19 | 2021-04-07 | Jaguar Land Rover Ltd | Apparatus and method for monitoring vehicle operation |
| CN109969083B (en) * | 2019-03-13 | 2024-01-30 | 中南大学 | Safety pre-warning and monitoring system for large trucks and trucks |
| CN112428921B (en) * | 2019-08-06 | 2022-11-04 | 上海博泰悦臻网络技术服务有限公司 | Continuous downhill road section prompting method and device and vehicle |
| CN111376909A (en) * | 2020-03-21 | 2020-07-07 | 东风汽车集团有限公司 | Indirect fatigue monitoring method |
| CN111488650A (en) * | 2020-04-07 | 2020-08-04 | 天津市市政工程设计研究院 | Expressway long downhill section danger avoiding lane early warning method |
| CN111986488B (en) * | 2020-09-14 | 2021-11-30 | 湖南三一中型起重机械有限公司 | Fatigue driving detection method and device, electronic equipment and storage medium |
| CN112802356B (en) * | 2020-12-30 | 2022-01-04 | 深圳市微网力合信息技术有限公司 | Vehicle automatic driving method and terminal based on Internet of things |
| CN112686161A (en) * | 2020-12-31 | 2021-04-20 | 遵义师范学院 | Fatigue driving detection method based on neural network |
| CN214623936U (en) * | 2021-02-22 | 2021-11-05 | 四川省交通投资集团有限责任公司 | Temperature measurement early warning system for road vehicles on long downhill section and mountain continuous downhill section |
| CN113375805A (en) * | 2021-04-23 | 2021-09-10 | 西安纳兴电子科技有限公司 | Early warning system for long downhill road section |
| CN114267169A (en) * | 2021-09-15 | 2022-04-01 | 赣南师范大学 | Fatigue driving prevention speed limit control method based on machine vision |
| CN115081756B (en) * | 2022-08-19 | 2022-11-11 | 四川省公路规划勘察设计研究院有限公司 | Road section brake drum temperature prediction and road section risk assessment method based on long and large longitudinal slope road section |
| CN115158274B (en) * | 2022-08-31 | 2022-11-29 | 四川省公路规划勘察设计研究院有限公司 | Long and large longitudinal slope dangerous road section identification method based on truck braking and heavy braking characteristics |
-
2022
- 2022-10-21 CN CN202211291757.1A patent/CN115366909B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105404746A (en) * | 2015-12-01 | 2016-03-16 | 桂林电子科技大学 | Reliability design method for long and steep downhill highway |
| CN105446391A (en) * | 2015-12-07 | 2016-03-30 | 长安大学 | Temperature rise prediction method for long downgrade driving brake for lorry |
| CN106504164A (en) * | 2016-10-19 | 2017-03-15 | 东南大学 | A kind of division methods of combination area of city and country's inferior grade road speeds control zone |
| CN108340900A (en) * | 2018-01-31 | 2018-07-31 | 中交第二公路勘察设计研究院有限公司 | Truck hub temperature predicting method of the large longitudinal slope route based on brake behavior |
| CN109017740A (en) * | 2018-07-29 | 2018-12-18 | 合肥市智信汽车科技有限公司 | A kind of temperature monitoring method for automobile |
| CN114715111A (en) * | 2022-05-07 | 2022-07-08 | 交通运输部公路科学研究所 | Freight vehicle brake temperature estimation method based on TBOX |
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