CN111038498A - Driving behavior monitoring method, terminal and readable storage medium - Google Patents
Driving behavior monitoring method, terminal and readable storage medium Download PDFInfo
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- 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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
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- B60T7/12—Brake-action initiating means for automatic initiation; for initiation not subject to will of driver or passenger
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- 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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
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Abstract
The application discloses a driving behavior monitoring method, a terminal and a computer readable storage medium, when the speed of a monitored vehicle is detected to be not zero, acquiring personnel state information of a driver of the monitored vehicle and environment state information outside the monitored vehicle; judging whether the driver is in a preset unsafe driving environment or not according to the personnel state information and the environment state information; if the driver is in a preset unsafe driving environment, outputting alarm information to remind the driver to stop the monitored vehicle within preset time; if the driver does not brake the monitoring vehicle within the preset time, the monitoring vehicle is automatically braked and locked, so that the monitoring and control of the driving behavior of the driver of the monitoring vehicle are realized, and the driving behavior that the driver harms the life safety of the driver or others due to self reasons or external factors in the driving process of the vehicle is prevented.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a driving behavior monitoring method, a terminal, and a readable storage medium.
Background
At present, with the rapid increase of automobile keeping quantity in China, traffic accidents caused by fatigue driving or dangerous driving behaviors of drivers or dangerous interference are high every year. With the development of the internet of things technology and the computer science technology, driving behavior analysis is becoming a hot spot. In the prior art, driving behaviors are monitored and analyzed, so that the driving behavior rules can be obtained. However, when the driver is tired of driving or has other dangerous driving behaviors, or the driver is interfered by dangers in the driving process, the driving safety problem cannot be solved.
Disclosure of Invention
The main purpose of the present application is to provide a driving behavior monitoring method, a terminal and a computer storage medium, which aim to solve the technical problem in the prior art that the driving safety problem cannot be solved when the driver is tired to drive or has other dangerous driving behaviors or suffers dangerous interference during driving.
In order to achieve the above object, an embodiment of the present application provides a driving behavior monitoring method, where the driving behavior monitoring method includes the following steps:
when the speed of a monitored vehicle is detected to be not zero, acquiring personnel state information of a driver of the monitored vehicle and environment state information outside the monitored vehicle;
judging whether the driver is in a preset unsafe driving environment or not according to the personnel state information and the environment state information;
if the driver is in a preset unsafe driving environment, outputting alarm information to remind the driver to stop the monitored vehicle within preset time;
and if the driver does not brake the monitoring vehicle within the preset time, automatically braking and locking the monitoring vehicle.
Optionally, after the step of automatically stopping and locking the monitoring vehicle, the method further comprises:
outputting preset prompt information to the driver to confirm whether the locking state of the monitored vehicle is released or not;
and if the received information fed back by the driver meets a preset rule, releasing the locking state of the monitored vehicle.
Optionally, the step of acquiring the information about the state of the person monitoring the driver of the vehicle includes:
acquiring images of a driver of the monitored vehicle;
identifying the driver image to obtain the eye opening, mouth opening and facial expression of the monitored vehicle driver;
and taking the eye opening degree, the mouth opening degree and the facial expression as the personnel state information of the monitored vehicle driver.
Optionally, the step of acquiring the environmental status information outside the monitoring vehicle includes:
acquiring an environment image outside the monitoring vehicle;
identifying the environment image to obtain surrounding obstacle information of the monitored vehicle and traffic information applicable to the monitored vehicle, wherein the surrounding obstacle information comprises the moving speed of surrounding obstacles and the distance between the monitored vehicle and the surrounding obstacles, and the traffic information applicable to the monitored vehicle comprises a lane line, a traffic light and a traffic indicator of the driving environment of the monitored vehicle;
and taking the information of the obstacles around the monitoring vehicle and the traffic information applicable to the monitoring vehicle as the external environment state information of the monitoring vehicle.
Optionally, the step of determining whether the driver is in a preset unsafe driving environment according to the person state information and the environment state information includes:
obtaining a body and mind state score of the driver based on the eye opening degree, the mouth opening degree and the facial expression of the monitored vehicle driver, wherein the body and mind state score is higher when the similarity of the eye opening degree, the mouth opening degree and the facial expression with a preset body and mind model is higher;
comparing the body and mind state score with a first preset threshold value;
and when the mind and body state score is smaller than the first preset threshold value, judging that the driver is in a preset unsafe driving environment.
Optionally, the step of determining whether the driver is in a preset unsafe driving environment according to the person state information and the environment state information further includes:
obtaining a driving environment score of the monitored vehicle based on the moving speed of the obstacle around the monitored vehicle, the distance between the monitored vehicle and the obstacle around the monitored vehicle, and a lane line, a traffic light and a traffic indication mark of the driving environment of the monitored vehicle, wherein the driving environment score is higher when the similarity of the moving speed, the distance, the lane line, the traffic light and the traffic indication mark with a preset environment model is higher;
comparing the driving environment score with a second preset threshold value;
and when the driving environment score is smaller than the second preset threshold value, judging that the driver is in a preset unsafe driving environment.
Optionally, if the driver is in a preset unsafe driving environment, the step of sending an alarm message to remind the driver to stop the monitored vehicle within a preset time includes:
determining a drivable area and a parking area of the monitored vehicle in the preset unsafe driving environment according to the information of the obstacles around the monitored vehicle and the traffic information applicable to the monitored vehicle;
determining a preset time for the driver to brake the monitoring vehicle based on the drivable region and the parking available region in combination with the speed of the monitoring vehicle;
and outputting alarm information comprising the preset time to the driver to remind the driver to stop the monitored vehicle within the preset time.
Optionally, if the driver does not brake the monitoring vehicle within the preset time, the automatically braking and locking the monitoring vehicle includes:
determining an automatic braking mode of the monitored vehicle based on the parkable area in combination with a speed of the monitored vehicle, the automatic braking mode including hard braking and slow braking;
and braking the monitoring vehicle according to the automatic braking mode and locking the driving monitoring vehicle.
The present application further provides a terminal, the terminal including: a memory, a processor and a driving behaviour monitoring program stored on the memory and executable on the processor, the driving behaviour monitoring program when executed by the processor implementing the steps of the driving behaviour monitoring method as described above.
The present application further provides a computer storage medium having a driving behavior monitoring program stored thereon, where the driving behavior monitoring program, when executed by a processor, implements the steps of the driving behavior monitoring method as described above.
In the driving behavior monitoring process, when the speed of a monitored vehicle is detected to be not zero, acquiring personnel state information of a driver of the monitored vehicle and environment state information outside the monitored vehicle; judging whether the driver is in a preset unsafe driving environment or not according to the personnel state information and the environment state information; if the driver is in a preset unsafe driving environment, outputting alarm information to remind the driver to stop the monitored vehicle within preset time; and if the driver does not brake the monitoring vehicle within the preset time, automatically braking and locking the monitoring vehicle. This application is monitored the driving action, suffers dangerous interference when taking place driver fatigue or other dangerous driving actions or driver driving in-process, sends out to report an emergency and ask for help or increased vigilance suggestion driver initiative brake or the automatic car that stops of driving action monitored control system under the prerequisite of guaranteeing safety, guarantees driver driving safety and the safety of other members on road.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a schematic diagram of a hardware structure of an optional terminal according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating an embodiment of a driving behavior monitoring method according to the present application;
FIG. 3 is a schematic diagram of additional process steps added after step S40 in FIG. 2;
FIG. 4 is a detailed flowchart of step S10 in FIG. 2;
FIG. 5 is a schematic view of another detailed flow chart of step S10 in FIG. 2;
FIG. 6 is a detailed flowchart of step S20 in FIG. 2;
FIG. 7 is a schematic view of another detailed flow chart of step S20 in FIG. 2;
FIG. 8 is a detailed flowchart of step S30 in FIG. 2;
fig. 9 is a detailed flowchart of step S40 in fig. 2.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for the convenience of description of the present application, and have no specific meaning by themselves. Thus, "module", "component" or "unit" may be used mixedly.
As shown in fig. 1, fig. 1 is a schematic terminal structure diagram of a hardware operating environment according to an embodiment of the present application.
The terminal in the embodiment of the application can be a fixed terminal, such as an internet of things intelligent device, and comprises an intelligent air conditioner, an intelligent lamp, an intelligent power supply, an intelligent router and other intelligent homes; the system can also be a mobile terminal, and comprises a smart phone, a wearable networking AR/VR device, a smart sound box, an automatic driving automobile and other networking equipment.
As shown in fig. 1, the architecture of the driving behavior monitoring system includes nodes and servers, and the device structure of the driving behavior monitoring system may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. The communication bus 1002 is used for realizing connection communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the driving behavior monitoring system may further include a user interface, a network interface, a camera, RF (radio frequency) circuitry, a sensor, audio circuitry, a WiFi module, and the like. The user interface may include a Display screen (Display), touch screen, camera (including AR/VR devices), etc., and the optional user interface may also include a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface, bluetooth interface, probe interface, 3G/4G/5G networking communication interface, etc.).
Those skilled in the art will appreciate that the driving behavior monitoring system configuration shown in FIG. 1 does not constitute a limitation of the driving behavior monitoring system, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, and a driving behavior monitoring program. The operating system is a program that manages and controls the hardware and software resources of the driving behavior monitoring system, supporting the operation of the driving behavior monitoring program as well as other software and/or programs. The network communication module is used to implement communication between the components inside the memory 1005 and with other hardware and software in the driving behavior monitoring system.
In the driving behavior monitoring system shown in fig. 1, the processor 1001 is configured to execute a driving behavior monitoring program stored in the memory 1005, and implement the following steps:
when the speed of a monitored vehicle is detected to be not zero, acquiring personnel state information of a driver of the monitored vehicle and environment state information outside the monitored vehicle;
judging whether the driver is in a preset unsafe driving environment or not according to the personnel state information and the environment state information;
if the driver is in a preset unsafe driving environment, outputting alarm information to remind the driver to stop the monitored vehicle within preset time;
and if the driver does not brake the monitoring vehicle within the preset time, automatically braking and locking the monitoring vehicle.
Further, the processor 1001 may call the driving behavior monitoring program stored in the memory 1005, and also perform the following operations:
outputting preset prompt information to the driver to confirm whether the locking state of the monitored vehicle is released or not;
and if the received information fed back by the driver meets a preset rule, releasing the locking state of the monitored vehicle.
Further, the processor 1001 may call the driving behavior monitoring program stored in the memory 1005, and also perform the following operations:
acquiring images of a driver of the monitored vehicle;
identifying the driver image to obtain the eye opening, mouth opening and facial expression of the monitored vehicle driver;
and taking the eye opening degree, the mouth opening degree and the facial expression as the personnel state information of the monitored vehicle driver.
Further, the processor 1001 may call the driving behavior monitoring program stored in the memory 1005, and also perform the following operations:
acquiring an environment image outside the monitoring vehicle;
identifying the environment image to obtain surrounding obstacle information of the monitored vehicle and traffic information applicable to the monitored vehicle, wherein the surrounding obstacle information comprises the moving speed of surrounding obstacles and the distance between the monitored vehicle and the surrounding obstacles, and the traffic information applicable to the monitored vehicle comprises a lane line, a traffic light and a traffic indicator of the driving environment of the monitored vehicle;
and taking the information of the obstacles around the monitoring vehicle and the traffic information applicable to the monitoring vehicle as the external environment state information of the monitoring vehicle.
Further, the processor 1001 may call the driving behavior monitoring program stored in the memory 1005, and also perform the following operations:
obtaining a body and mind state score of the driver based on the eye opening degree, the mouth opening degree and the facial expression of the monitored vehicle driver, wherein the body and mind state score is higher when the similarity of the eye opening degree, the mouth opening degree and the facial expression with a preset body and mind model is higher;
comparing the body and mind state score with a first preset threshold value;
and when the mind and body state score is smaller than the first preset threshold value, judging that the driver is in a preset unsafe driving environment.
Further, the processor 1001 may call the driving behavior monitoring program stored in the memory 1005, and also perform the following operations:
obtaining a driving environment score of the monitored vehicle based on the moving speed of the obstacle around the monitored vehicle, the distance between the monitored vehicle and the obstacle around the monitored vehicle, and a lane line, a traffic light and a traffic indication mark of the driving environment of the monitored vehicle, wherein the driving environment score is higher when the similarity of the moving speed, the distance, the lane line, the traffic light and the traffic indication mark with a preset environment model is higher;
comparing the driving environment score with a second preset threshold value;
and when the driving environment score is smaller than the second preset threshold value, judging that the driver is in a preset unsafe driving environment.
Further, the processor 1001 may call the driving behavior monitoring program stored in the memory 1005, and also perform the following operations:
determining a drivable area and a parking area of the monitored vehicle in the preset unsafe driving environment according to the information of the obstacles around the monitored vehicle and the traffic information applicable to the monitored vehicle;
determining a preset time for the driver to brake the monitoring vehicle based on the drivable region and the parking available region in combination with the speed of the monitoring vehicle;
and outputting alarm information comprising the preset time to the driver to remind the driver to stop the monitored vehicle within the preset time.
Further, the processor 1001 may call the driving behavior monitoring program stored in the memory 1005, and also perform the following operations:
determining an automatic braking mode of the monitored vehicle based on the parkable area in combination with a speed of the monitored vehicle, the automatic braking mode including hard braking and slow braking;
and braking the monitoring vehicle according to the automatic braking mode and locking the driving monitoring vehicle.
Based on the hardware structure, various embodiments of the driving behavior monitoring method are provided.
Referring to fig. 2, a first embodiment of a driving behavior monitoring method of the present application provides a driving behavior monitoring method, including:
step S10, when the speed of the monitoring vehicle is detected to be not zero, acquiring the personnel state information of the driver of the monitoring vehicle and the environment state information outside the monitoring vehicle;
the method comprises the steps that the behavior of a driver of a running vehicle is monitored, and because the vehicle which is stationary in situ does not affect the safety of the driver, when the speed of the vehicle is required to be detected to be not zero, the driving behavior of the vehicle is monitored, namely the running vehicle is used as a detection and monitoring vehicle; when the speed of the monitoring vehicle is detected to be not zero, namely the vehicle is not static, the personnel state information of the driver of the monitoring vehicle and the environment state information outside the monitoring vehicle are obtained.
The information of the personnel state of the monitored vehicle driver refers to the information of the driver, is the state information relative to the outside of the monitored vehicle, and comprises three parts of information of the eye opening, the mouth opening and the facial expression of the monitored vehicle driver; the monitoring of the environment state information outside the vehicle refers to five parts of information including monitoring of the moving speed of obstacles around the vehicle, monitoring of the distance between the vehicle and the obstacles around the vehicle, monitoring of lane lines of the running environment of the vehicle, traffic lights and traffic indication marks.
Step S20, judging whether the driver is in the preset unsafe driving environment or not according to the personnel state information and the environment state information;
the preset unsafe driving environment refers to a driving environment that may pose a threat to the life safety of a driver or other drivers, passengers, and pedestrians on a road, or may cause a road congestion or a traffic accident.
Step S30, if the driver is in the preset unsafe driving environment, outputting alarm information to remind the driver to stop monitoring the vehicle within the preset time;
when the driver of the monitored vehicle is judged to be in a preset unsafe driving environment, firstly calculating the time allowing the driver to safely stop through an algorithm, namely the preset time, and outputting and displaying the preset time to the driver through alarm information to check so as to remind the driver to actively stop the driven vehicle within the specified preset time; and when the driver is not judged to be in the preset unsafe driving environment, continuously acquiring the state information of the driver and the state information of the environment in real time to monitor whether the subsequent driving environment is safe or not.
And step S40, if the driver does not brake the monitoring vehicle within the preset time, automatically braking and locking the monitoring vehicle.
The automatic braking and locking of the monitored vehicle means that the driving behavior monitoring system automatically cuts off the accelerator of the driven vehicle, so that the vehicle stops and does not move any more (continues to move forward or move backward and the like); the locking means that the accelerator of the vehicle is locked (the driver does not respond before unlocking, namely the driver cannot refuel the vehicle), and the accelerator is unlocked until the driver of the monitored vehicle correctly answers the problem in the preset prompt message, namely the driver confirms that the driving environment is recovered to be safe, so that the locked state of the accelerator is released, and the safety of restarting after automatic parking is ensured.
In the embodiment, when the speed of the monitoring vehicle is detected to be not zero, the personnel state information of the driver of the monitoring vehicle and the environment state information outside the monitoring vehicle are acquired; judging whether the driver is in a preset unsafe driving environment or not according to the personnel state information and the environment state information; if the driver is in a preset unsafe driving environment, outputting alarm information to remind the driver to stop the monitored vehicle within preset time; and if the driver does not brake the monitoring vehicle within the preset time, automatically braking and locking the monitoring vehicle. This application is monitored the driving action, suffers dangerous interference when taking place driver fatigue or other dangerous driving actions or driver driving in-process, sends out to report an emergency and ask for help or increased vigilance suggestion driver initiative brake or the automatic car that stops of driving action monitored control system under the prerequisite of guaranteeing safety, guarantees driver driving safety and the safety of other members on road.
Further, in another embodiment of the driving behavior monitoring method of the present application, referring to fig. 3, after step S40, the method includes:
step S50, outputting preset prompting information to the driver to confirm whether the locking state of the monitored vehicle is released;
when the feedback information answered by the driver for the preset prompt information conforms to the preset rule, namely the answer conforms to the preset answer, the mental state and road conditions of the driver can be confirmed to allow the locked vehicle to be unlocked and to continue driving.
And step S60, if the received information fed back by the driver meets the preset rule, the locking state of the monitored vehicle is released.
In the present embodiment, after the drive monitoring vehicle is locked, a preset prompting message is first sent to the driver of the locked vehicle to confirm whether to release the locked state of the locked driven vehicle, and the locked state of the driven vehicle is released only when the information fed back by the driver meets a preset rule. At present, a driver dozes off, plays a mobile phone, is not concentrated in driving, or phenomena of passengers and a driver noise rack, beating the driver, robbing a steering wheel and the like often occur, so that numerous accidents are caused, and personal safety of people on the vehicle and people outside the vehicle is seriously threatened. The design of the driving behavior monitoring system does not depend on a driver, when a dangerous condition occurs and the driver does not actively brake and stop the automobile within the preset time of safe parking, the driving automobile is braked and locked, a special unlocking link is arranged, and the driving safety is reliably ensured.
Further, in another embodiment of the driving behavior monitoring method of the present application, referring to fig. 4, step S10 includes:
step S11, collecting images of a driver of a monitoring vehicle;
images of the driver of the monitored vehicle can be captured by the camera device, primarily to obtain information from the images to determine whether the driver's status is appropriate for continuing to drive the monitored vehicle.
Step S12, recognizing the driver image to obtain the eye opening, mouth opening and facial expression of the monitored vehicle driver;
in step S13, the eye opening, mouth opening, and facial expression are used as the person state information for monitoring the vehicle driver.
In this embodiment, after obtaining the driver image, the driver image is subjected to face recognition and facial information sampling, and the sampling information mainly includes monitoring glasses opening (which can represent whether the driver dozes off), mouth opening (which can represent whether yawn is done), and facial expression (which can represent whether the driver breaks a disease, etc.) of the vehicle driver.
Further, in another embodiment of the driving behavior monitoring method of the present application, referring to fig. 5, step S10 further includes:
step S14, collecting an environment image outside the monitoring vehicle;
the environment image outside the monitoring vehicle can be collected through the camera equipment, and the traffic state and the obstacle state of the environment outside the monitoring vehicle are determined mainly in order to obtain information from the image, so that whether the monitoring vehicle is suitable for continuously running or not is determined.
Step S15, recognizing an environment image to obtain obstacle information around a monitored vehicle and traffic information applicable to the monitored vehicle, wherein the obstacle information around the monitored vehicle comprises the moving speed of obstacles around the monitored vehicle and the distance between the monitored vehicle and the obstacles around the monitored vehicle, and the traffic information applicable to the monitored vehicle comprises a lane line, a traffic light and a traffic indication mark for monitoring the driving environment of the monitored vehicle;
monitoring obstacles around a vehicle, such as hills, residential buildings, pedestrians, other vehicles or vehicles, etc., may be stationary or moving (ground referenced),
in step S16, the obstacle information around the monitoring vehicle and the traffic information applicable to the monitoring vehicle are used as the environmental state information outside the monitoring vehicle.
In the embodiment, the information of obstacles around the monitored vehicle and the traffic information applicable to the monitored vehicle are obtained by acquiring the environment image outside the detected vehicle; the two pieces of information are mainly obtained as evaluation standards for judging whether the driver is in the preset unsafe driving environment or not, so that the external environment information of the monitored vehicle can be comprehensively obtained, and whether the monitored vehicle is suitable for continuous driving or not is determined according to the external environment information, namely whether the driver is in the preset unsafe driving environment or not when the vehicle is in a meeting state.
Further, in another embodiment of the driving behavior monitoring method of the present application, referring to fig. 6, step S20 includes:
step S21, obtaining a body and mind state score of the driver based on monitoring the eye opening, mouth opening and face expression of the vehicle driver, wherein the body and mind state score is higher when the similarity of the eye opening, mouth opening and face expression and a preset body and mind model is higher;
the mind and body state score refers to a consideration score based on monitoring the mind and body state of the vehicle driver. If the driver is dozed and yawned in the image of the driver, the more times of dozing and yawning represent that the mental state of the driver is poor, or the facial expression of the driver is painful, the driver is possibly indicated to have sudden illness and poor physical state; the better the psychosomatic state, the higher the score.
The body and mind state score of the driver can be obtained by calculating and monitoring the eye opening, mouth opening and facial expression of the driver of the vehicle.
The eye opening degree means that the ratio of the minimum value of the eye opening degree to the mode of the eye opening degree in a preset time period does not exceed a preset threshold value, the eye opening degree is normal, and if the ratio exceeds the preset threshold value, the eye opening degree is abnormal. The sampling of the eye opening calculation may include the blink and squint of the driver, and the human eyelid blinks about 15 times per minute. The driving behavior monitoring system blinks once every 4 seconds approximately, in order to avoid the situation that a plurality of blinks are sampled, the sampling interval is set to 3 seconds, the sampling result is fed back to the driving behavior monitoring system in real time, the eye opening value is obtained through the preset algorithm and the blink and squint times, and meanwhile, the sampling interval is optimized, so that the purposes of improving the working efficiency of the driving behavior monitoring system and improving the accuracy of the sampling result are achieved; the larger the difference value of the eye opening ratio value and the preset threshold value is, the more normal the eye opening of the driver is, and the higher the score of the eye opening in the physical and mental state is.
The mouth opening degree means that the ratio of the maximum value of the mouth opening degree to the mode of the mouth opening degree in a preset time period does not exceed a preset threshold value, the mouth opening degree is normal, and if the ratio exceeds the preset threshold value, the mouth opening degree is abnormal. If the preset threshold value is set to be 30 degrees, in one minute, the statistics shows that the mouth opening mode is 10 degrees and the maximum value of the mouth opening is 70 degrees, the difference value between the maximum value of the mouth opening and the mouth opening mode is 60 degrees and exceeds the preset threshold value by 30 degrees, and therefore the condition that the mouth opening parameter is abnormal is judged, and the situation that the driver is likely yawning can be inferred; the larger the difference between the mouth opening ratio and the preset threshold value is, the more normal the mouth opening of the driver is, and the score of the mouth opening in the physical and mental state is higher.
The driving behavior monitoring system identifies and acquires facial expression state information of a driver through facial expressions such as frown, facial muscle tension and the like, then performs statistical analysis and compares the facial expressions of the driver with a preset expression model to confirm whether the driver breaks out of illness or is uncomfortable in body or not; in the preset expression model, the more moderate and quiet the facial expression is, the higher the score is, and the more disconcerting and distressing the expression is, the lower the score is; and when the similarity between the facial expression of the driver and the preset expression model is higher, the score of the facial expression in the physical and mental states is higher.
Step S22, comparing the physical and mental state score with a first preset threshold value;
the first preset threshold refers to a reference object for evaluating the physical and mental state of the driver, namely, the minimum standard for judging whether the driver is in the preset unsafe driving environment in the aspect of the physical and mental state.
And step S23, when the physical and mental state score is smaller than a first preset threshold value, judging that the driver is in a preset unsafe driving environment.
When the body state score is smaller than a first preset threshold value, judging that the driver is in a preset unsafe driving environment; and when the physical and mental state score is greater than or equal to a first preset threshold value, judging that the driver is not in a preset unsafe driving environment.
In the embodiment, according to the state image of the driver, the eye opening, the mouth opening and the facial expression of the driver are identified, so that the three state information of the eye opening, the mouth opening and the facial expression can be evaluated in the subsequent steps, and compared with a first preset threshold value, and finally whether the driver is in the preset unsafe driving environment or not is judged through the comparison result, so that the relevant information of whether the driving environment where the driver is located is safe or not is comprehensively obtained from the physical and mental states of the driver, and the reliability of statistical data of the driving behavior monitoring system and the accuracy of data analysis are improved.
Further, in another embodiment of the driving behavior monitoring method of the present application, referring to fig. 7, step S20 further includes:
step S24, obtaining a driving environment score of the monitored vehicle based on the moving speed of the obstacles around the monitored vehicle, the distance between the monitored vehicle and the obstacles around the monitored vehicle, and the lane line, the traffic light and the traffic indication mark for monitoring the driving environment of the monitored vehicle, wherein the driving environment score is higher when the similarity of the moving speed, the distance, the lane line, the traffic light and the traffic indication mark with a preset environment model is higher;
the method comprises the steps of obtaining the moving speed of an obstacle around the body outside a monitoring vehicle and the distance between the monitoring vehicle and the obstacle around the monitoring vehicle, and mainly avoiding collision between the monitoring vehicle and the obstacle. For example, when the moving speed of the obstacle is detected to be 0 (the reference object is the ground), it represents that the obstacle belongs to a stationary object, such as a mountain slope; and then, by detecting and monitoring the distance between the vehicle and the surrounding obstacles, the collision between the vehicle and the obstacles can be estimated according to the two parameters of the moving speed and the distance of the obstacles, so as to judge whether the vehicle is in the preset unsafe driving environment. For another example, if the moving speed of the obtained obstacle is 0, the distance between the monitored vehicle and the obstacle is 10 meters, and the speed per hour of the monitored vehicle is 60km/h, it can be determined that the monitored vehicle collides with the obstacle if the monitored vehicle continues to travel forward. It is thus possible to obtain a predetermined unsafe condition of the monitored vehicle.
In the preset environment model, a safe driving area under the two conditions of the moving speed and the distance of the obstacle around the monitored vehicle is set, and the higher the similarity between the combined evaluation value (the score of the information of the obstacle around the monitored vehicle) of the moving speed and the distance of the monitored vehicle and the preset environment model is, the safer the driving environment of the monitored vehicle is.
Lane lines refer to lines printed on each road used as a guide, such as double yellow lines: the road partition board is arranged in a road section and used for partitioning the traffic which runs oppositely; solid white line: when the road is drawn in a road section, the road is used for separating a motor vehicle and a non-motor vehicle which run in the same direction;
there are two kinds of traffic lights, and the traffic light suitable for motor vehicles is called a motor vehicle light, which is a signal light composed of three colors of red, yellow and green (green is blue green) for directing traffic. When the green light is on, the vehicle is permitted to pass, and when the yellow light flickers, the vehicle which has crossed the stop line can continue to pass; and if the red light is on, the vehicle is prohibited from passing. Be applicable to pedestrian's cross walk lamp of calling people, usually indicate to constitute by two kinds of colour lamps red, green (green is blue-green) and be used for directing the current signal lamp of traffic, the red lamp stops, green lamp is gone, the traffic light of this application indicates the traffic light that is applicable to the motor vehicle calls the motor vehicle light.
Traffic signs are one of the main signs in traffic signs. The system is used for indicating the vehicles and pedestrians to travel in a specified direction and place. The color of the indicating mark is blue bottom and white pattern; the shape is divided into round, rectangular and square. The indicator indicates that only a quasi-tangential vehicle is turning left (or right). Is provided at a position before an intersection where the vehicle must turn left (or right). When there is a special specification such as time, vehicle type, etc., an auxiliary logo or an additional pattern is applied.
In the preset environment model, a safe driving area under the three conditions of a driving environment lane line of the monitored vehicle, a traffic light and a traffic indication mark is set, and the higher the similarity between the combined evaluation value (the score of the traffic information applicable to the monitored vehicle) of the driving environment lane line, the traffic light and the traffic indication mark and the preset environment model is, the safer the driving environment of the monitored vehicle is.
The driving environment score is composed of the sum of the information score of obstacles around the monitored vehicle and the score of the traffic information applicable to the monitored vehicle.
Step S25, comparing the driving environment score with a second preset threshold value;
the second preset threshold value refers to a reference object for evaluating the external driving environment condition of the monitored vehicle, namely, the minimum standard for judging whether the driver is in the preset unsafe driving environment or not from the aspect of the external environment.
And step S26, when the driving environment score is smaller than a second preset threshold value, judging that the driver is in a preset unsafe driving environment.
When the driving environment score is smaller than a second preset threshold value, judging that the driver is in a preset unsafe driving environment; and when the driving environment score is greater than or equal to a second preset threshold value, judging that the driver is not in the preset unsafe driving environment.
In the embodiment, according to an environment image outside a monitored vehicle, obtaining an obstacle information score around the monitored vehicle and a traffic information score applicable to the monitored vehicle as a driving environment score; and comparing the driving environment score with a second preset threshold value, and finally judging whether the driver is in a preset unsafe driving environment or not according to the comparison result, so that the relevant information whether the driving environment of the driver is safe or not is comprehensively obtained from the driving environment of the driver, and the reliability of the statistical data of the driving behavior monitoring system and the accuracy of data analysis are improved.
It should be noted that, the judgment sequence of the above embodiment is not divided into front and back, that is, as long as the mind and body state score is smaller than the first preset threshold value, or the driving environment score is smaller than the second preset threshold value, it is indicated that the monitored vehicle driver is in the preset unsafe environment, so that the applicability of the driving behavior system analysis and evaluation is improved; that is, the execution sequence of the two embodiments for judging whether the driving environment is in the preset unsafe driving environment does not affect the implementation of the whole scheme of the application.
Further, in another embodiment of the driving behavior monitoring method of the present application, referring to fig. 8, step S30 includes:
step S31, determining a driving available area and a parking available area of the monitored vehicle in a preset unsafe driving environment according to the information of the obstacles around the monitored vehicle and the traffic information applicable to the monitored vehicle;
step S32, determining the preset time for the driver to brake the monitoring vehicle based on the drivable area and the parking area and in combination with the speed of the monitoring vehicle;
and step S33, outputting alarm information including preset time to the driver to remind the driver to stop monitoring the vehicle within the preset time.
In the embodiment, a travelable area and a parkable area of the monitored vehicle in a preset unsafe driving environment are determined according to obstacle information around the monitored vehicle and traffic information applicable to the monitored vehicle, wherein the travelable area is mainly used for analyzing a driving area which is provided for a driver to allow the driver to autonomously stop and monitor the monitored vehicle, such as a travelable area right ahead along the driving direction of the vehicle, or a driveway needs to be changed to another driveway for traveling, and the like, by a driving behavior monitoring system; the parking area is mainly used for monitoring the parking position of the vehicle after the driver stops the vehicle autonomously.
Further, in another embodiment of the driving behavior monitoring method of the present application, referring to fig. 9, step S40 includes:
step S41, determining an automatic braking mode of the monitored vehicle based on the parking available area and the speed of the monitored vehicle, wherein the automatic braking mode comprises an emergency brake and a slow brake;
after the parking available area is determined, determining an automatic braking mode of the monitored vehicle by combining the running speed of the monitored vehicle, wherein the automatic braking mode comprises an emergency brake and a slow brake; for example, if the monitored vehicle has a very fast running speed, the vehicle needs to be braked slowly first and then braked suddenly; the driver and the monitoring vehicle driven by the driver can be ensured to be safely stopped under the interference of the driving behavior monitoring system in the preset unsafe driving environment.
And step S42, braking the monitoring vehicle according to the automatic braking mode and locking the driving monitoring vehicle.
In this embodiment, after the monitored vehicle is braked according to the automatic brake mode, the driving behavior monitoring system is provided with a locking-unlocking link, namely, the vehicle is automatically braked and the monitored vehicle is locked, the locking link is added, so that the driving behavior of the driver can be more comprehensively controlled, the monitored vehicle is unlocked only after the danger factor (the driver answers the preset prompt information) is confirmed to be eliminated, and the life safety of the driver and other members of the road is ensured.
The present application further provides a terminal, the terminal including: the driving behavior monitoring method comprises a memory, a processor and a driving behavior monitoring program which is stored on the memory and can run on the processor, wherein the driving behavior monitoring program realizes the steps of the driving behavior monitoring method when being executed by the processor.
The present application further provides a computer-readable storage medium having a driving behavior monitoring program stored thereon, where the driving behavior monitoring program, when executed by a processor, implements the steps of the driving behavior monitoring method described above.
In the embodiments of the driving behavior monitoring method, the terminal and the readable storage medium of the present application, all technical features of the embodiments of the driving behavior monitoring method are included, and the expanding and explaining contents of the description are basically the same as those of the embodiments of the driving behavior monitoring method, and are not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. A driving behavior monitoring method, characterized by comprising:
when the speed of a monitored vehicle is detected to be not zero, acquiring personnel state information of a driver of the monitored vehicle and environment state information outside the monitored vehicle;
judging whether the driver is in a preset unsafe driving environment or not according to the personnel state information and the environment state information;
if the driver is in a preset unsafe driving environment, outputting alarm information to remind the driver to stop the monitored vehicle within preset time;
and if the driver does not brake the monitoring vehicle within the preset time, automatically braking and locking the monitoring vehicle.
2. The driving behavior monitoring method of claim 1, wherein the step of automatically braking and locking the monitored vehicle is followed by:
outputting preset prompt information to the driver to confirm whether the locking state of the monitored vehicle is released or not;
and if the received information fed back by the driver meets a preset rule, releasing the locking state of the monitored vehicle.
3. The driving behavior monitoring method according to claim 1, wherein the step of acquiring the information on the state of the person monitoring the driver of the vehicle includes:
acquiring images of a driver of the monitored vehicle;
identifying the driver image to obtain the eye opening, mouth opening and facial expression of the monitored vehicle driver;
and taking the eye opening degree, the mouth opening degree and the facial expression as the personnel state information of the monitored vehicle driver.
4. The driving behavior monitoring method according to claim 1, wherein the step of acquiring the environmental state information outside the monitoring vehicle includes:
acquiring an environment image outside the monitoring vehicle;
identifying the environment image to obtain surrounding obstacle information of the monitored vehicle and traffic information applicable to the monitored vehicle, wherein the surrounding obstacle information comprises the moving speed of surrounding obstacles and the distance between the monitored vehicle and the surrounding obstacles, and the traffic information applicable to the monitored vehicle comprises a lane line, a traffic light and a traffic indicator of the driving environment of the monitored vehicle;
and taking the information of the obstacles around the monitoring vehicle and the traffic information applicable to the monitoring vehicle as the external environment state information of the monitoring vehicle.
5. The driving behavior monitoring method of claim 3, wherein the step of determining whether the driver is in a preset unsafe driving environment based on the personnel status information and the environmental status information comprises:
obtaining a body and mind state score of the driver based on the eye opening degree, the mouth opening degree and the facial expression of the monitored vehicle driver, wherein the body and mind state score is higher when the similarity of the eye opening degree, the mouth opening degree and the facial expression with a preset body and mind model is higher;
comparing the body and mind state score with a first preset threshold value;
and when the mind and body state score is smaller than the first preset threshold value, judging that the driver is in a preset unsafe driving environment.
6. The driving behavior monitoring method of claim 4, wherein the step of determining whether the driver is in a preset unsafe driving environment based on the personnel status information and the environmental status information further comprises:
obtaining a driving environment score of the monitored vehicle based on the moving speed of the obstacle around the monitored vehicle, the distance between the monitored vehicle and the obstacle around the monitored vehicle, and a lane line, a traffic light and a traffic indication mark of the driving environment of the monitored vehicle, wherein the driving environment score is higher when the similarity of the moving speed, the distance, the lane line, the traffic light and the traffic indication mark with a preset environment model is higher;
comparing the driving environment score with a second preset threshold value;
and when the driving environment score is smaller than the second preset threshold value, judging that the driver is in a preset unsafe driving environment.
7. The driving behavior monitoring method of claim 6, wherein the step of issuing an alert message to remind the driver to stop the monitored vehicle within a preset time if the driver is in a preset unsafe driving environment comprises:
determining a drivable area and a parking area of the monitored vehicle in the preset unsafe driving environment according to the information of the obstacles around the monitored vehicle and the traffic information applicable to the monitored vehicle;
determining a preset time for the driver to brake the monitoring vehicle based on the drivable region and the parking available region in combination with the speed of the monitoring vehicle;
and outputting alarm information comprising the preset time to the driver to remind the driver to stop the monitored vehicle within the preset time.
8. The driving behavior monitoring method of claim 7, wherein the step of automatically braking and locking the monitoring vehicle if the driver does not brake the monitoring vehicle within a preset time comprises:
determining an automatic braking mode of the monitored vehicle based on the parkable area in combination with a speed of the monitored vehicle, the automatic braking mode including hard braking and slow braking;
and braking the monitoring vehicle according to the automatic braking mode and locking the driving monitoring vehicle.
9. A terminal, characterized in that the terminal comprises: memory, a processor and a driving behaviour monitoring program stored on the memory and executable on the processor, the driving behaviour monitoring program when executed by the processor implementing the steps of the driving behaviour monitoring method according to any of claims 1 to 8.
10. A storage medium, characterized in that the storage medium has stored thereon a driving behavior monitoring program, which when executed by a processor implements the steps of the driving behavior monitoring method according to any one of claims 1 to 8.
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