CN111415524A - Intelligent processing method and system for fatigue driving - Google Patents
Intelligent processing method and system for fatigue driving Download PDFInfo
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Abstract
The invention discloses an intelligent processing method and system for fatigue driving, which comprises the steps of monitoring whether abnormal dynamic states occur to a driver and a vehicle in real time; if the abnormal dynamic state occurs, early warning and emergency processing are carried out; retrieving a surrounding rest area and implementing route navigation of the nearest rest area; whether the vehicle goes to the rest area or not is monitored in real time, alarm processing is carried out when the vehicle deviates from the route of the rest area, and the alarm is turned off until the route returns to the right state, so that the problem that the current truck driver is frequently fatigue-driven to cause frequent traffic accidents is solved, and the safety of public traffic and the smoothness of truck driving are improved.
Description
Technical Field
The invention relates to the technical field of vehicle artificial intelligence, in particular to an intelligent processing method and system for fatigue driving.
Background
Trucks, also called trucks, commonly referred to as vans, refer to vehicles primarily intended for transporting goods, and sometimes also to vehicles that may tow other vehicles, and belong to the category of commercial vehicles. Generally, the vehicle can be classified into a heavy type and a light type according to the weight of the vehicle. Most trucks use a diesel engine as a power source, but some light trucks use gasoline, petroleum gas, or natural gas.
At present, trucks play an irreplaceable role in engineering construction, cargo transportation and the like, and with the rapid development of intelligent auxiliary driving of vehicles in recent years, leading-edge technologies applied to trucks are more and more. Considering that truck drivers often fatigue driving to obtain higher income and serious traffic accidents are easily caused, it is important to seek an intelligent means to avoid fatigue driving.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The invention has been made in view of the above-mentioned problems that the driver of the existing truck often fatigues to drive.
Therefore, the technical problem solved by the invention is as follows: the problem of current truck driver frequent traffic accidents that leads to often tiredly driving is solved.
In order to solve the technical problems, the invention provides the following technical scheme: an intelligent processing method for fatigue driving comprises the steps of monitoring whether abnormal dynamic occurs to a driver and a vehicle in real time; if the abnormal dynamic state occurs, early warning and emergency processing are carried out; retrieving a surrounding rest area and implementing route navigation of the nearest rest area; and monitoring whether the vehicle goes to the rest area in real time, and implementing alarm processing when the vehicle deviates from the route of the rest area until the alarm is turned off after the route returns to the right.
As a preferable aspect of the intelligent processing method for fatigue driving according to the present invention, wherein: monitoring in real time whether the abnormal dynamics of the driver and the vehicle occur includes acquiring whether a fatigue phenomenon in the abnormal dynamics of the driver occurs through a facial recognition algorithm; acquiring whether the vehicle has the route continuous deviation in the abnormal dynamic state through a path track algorithm; and feeding back the obtained result to the intelligent auxiliary system.
As a preferable aspect of the intelligent processing method for fatigue driving according to the present invention, wherein: when the single eye closing time of the driver exceeds 0.5s, the fatigue phenomenon of the driver is defined.
As a preferable aspect of the intelligent processing method for fatigue driving according to the present invention, wherein: monitoring whether the vehicle experiences sustained deviation of the route in the anomalous dynamic condition comprises obtaining a theoretical width of a road traveled by the vehicle in real time; when the vehicle travels in a direction deviating from the original traveling route, acquiring a safety threshold of a travel distance in real time; when the vehicle travels to the safety threshold value of the travel distance in the direction deviating from the original traveling route, the continuous deviation of the vehicle route is defined.
As a preferable aspect of the intelligent processing method for fatigue driving according to the present invention, wherein: the safety threshold for the distance traveled is obtained in real time by the following formula,
the safety threshold value of the traveling distance is v, the real-time speed of the vehicle is L, the theoretical width of the traveling road of the vehicle is measured by a sensor in real time, Z is the real-time length of the vehicle from the head to the roads on two sides in the real-time traveling direction, and a is the real-time acceleration of the vehicle.
As a preferable aspect of the intelligent processing method for fatigue driving according to the present invention, wherein: when the abnormal dynamic state occurs, performing early warning and emergency treatment, including reducing the speed of the vehicle to a speed safety threshold value and continuously alarming when the fatigue phenomenon of the driver is monitored; and when the continuous deviation of the route of the vehicle is monitored, emergency braking is carried out, the speed of the vehicle is reduced to 0km/h, and the alarm is continuously given.
As a preferable aspect of the intelligent processing method for fatigue driving according to the present invention, wherein: obtaining the speed safety threshold comprises obtaining a speed safety threshold,
detecting an obstacle in front of the vehicle;
if an obstacle appears in front of the vehicle, acquiring the relative distance and the relative speed between the vehicle and the obstacle;
the speed safety threshold is obtained by the following formula,
wherein P represents the speed safety threshold value, α represents the relative speed relationship, β represents the relative position relationship, d represents the parallax of the vision sensor, f represents the focal length of the vision sensor, H represents the distance from the obstacle to the vehicle, and V represents the real-time speed of the vehicle.
In order to solve the technical problems, the invention provides the following technical scheme: an intelligent processing system for fatigue driving comprises a monitoring module, a control module and a control module, wherein the monitoring module is used for monitoring whether abnormal dynamic occurs to a driver and a vehicle; the processing module is used for carrying out early warning and emergency processing after the abnormal dynamic state occurs; a retrieval module for retrieving a surrounding rest area after the abnormal dynamics occurs and performing a route navigation of the nearest rest area; and the tracking alarm module is used for monitoring whether the vehicle goes to the rest area or not, and implementing alarm processing when the vehicle deviates from the route of the rest area until the alarm is turned off after the route returns to the right.
As a preferable aspect of the intelligent processing system for fatigue driving according to the present invention, wherein: the monitoring module comprises an observation unit for observing the single eye closing time of the driver and the theoretical width of the vehicle traveling road; the acquisition unit is used for acquiring a safety threshold of the travel distance in real time; the judging unit is used for acquiring whether the driver has fatigue phenomenon and whether the vehicle has continuous deviation of the route; and the feedback unit is used for feeding back the judgment result of the judgment unit to the intelligent auxiliary system.
As a preferable aspect of the intelligent processing system for fatigue driving according to the present invention, wherein: the processing module comprises a detection unit for detecting an obstacle in front of the vehicle; the second acquisition unit is used for acquiring the relative distance and the relative speed between the vehicle and the obstacle and calculating a speed safety threshold; a braking unit for braking the vehicle when the abnormal dynamic state occurs; and the alarm unit is used for giving an alarm when the abnormal dynamic state occurs.
The invention has the beneficial effects that: by the intelligent processing method and system for fatigue driving, the problem that traffic accidents frequently occur due to frequent fatigue driving of a truck driver at present is solved, and the safety of public transportation and the smoothness of truck driving are improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. Wherein:
FIG. 1 is a flow chart of a method of the intelligent processing method for fatigue driving provided by the invention;
FIG. 2 is a block diagram of an intelligent processing system for fatigue driving provided by the present invention;
FIG. 3 is a diagram of the actual effect of installing a vision sensor in the intelligent processing method for fatigue driving according to the present invention;
fig. 4 is a schematic view of an angle setting of a sensor camera in the intelligent processing method for fatigue driving provided by the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
At present, in order to obtain higher income, a truck driver often drives fatigue, and serious traffic accidents are easily caused.
Therefore, referring to fig. 1, fig. 3 and fig. 4, the present invention provides an intelligent processing method for fatigue driving: an intelligent processing method for fatigue driving, comprising:
monitoring whether abnormal dynamic occurs to a driver and a vehicle in real time;
if abnormal dynamic state occurs, early warning and emergency processing are carried out;
retrieving surrounding rest areas and implementing route navigation of the nearest rest area;
and monitoring whether the vehicle goes to the rest area in real time, and implementing alarm processing when the vehicle deviates from the route of the rest area until the alarm is turned off after the route returns to the right.
Further, the abnormal dynamic state during the driving process of the truck is defined as: the fatigue phenomenon of a driver and the continuous deviation of a vehicle route are both direct causes of traffic accidents. It is understood that fatigue of the driver may cause driving dangers, and the continuous deviation of the vehicle route may cause the driver to be distracted, watch the mobile phone, drive fatigue, and the like, and traffic accidents are easily caused.
The real-time monitoring of whether abnormal dynamic occurs to the driver and the vehicle comprises the following steps:
acquiring whether the driver has fatigue phenomenon in abnormal dynamic state or not through a facial recognition algorithm;
acquiring whether the vehicle has route continuous deviation in abnormal dynamic state or not through a path track algorithm;
and feeding back the obtained result to the intelligent auxiliary system.
It should be noted that:
①, the abnormal dynamics are monitored by visual sensors, which may use laser scanners, linear and area CCD cameras or TV cameras, or the latest emerging digital cameras, etc.
② As shown in FIG. 3, the vision sensor is typically located on the operator's seat center console, using a general wide angle camera sensor.
Meanwhile, the invention preferably adopts three sensors to be installed by a three-point isosceles triangle installation method, the installation and installation method can realize the best detection and identification by the least number of the sensors, wherein one sensor is over against the driver seat, the other two sensors are respectively arranged in the connecting line direction of the driver seat and the left and right rearview mirrors and the direction deviated from the vehicle axis direction by 15 degrees, and the three sensors are matched together to realize the dead-angle-free identification.
③ the main reason for obtaining whether the driver has fatigue in abnormal dynamic state through the face recognition algorithm is to recognize the fatigue of the human eyes of the driver through the algorithm.
The Face recognition algorithm adopts a Face + + Face recognition emotion recognition method. The emotion recognition is to analyze and recognize various emotions of the Face in the picture and return confidence scores of the Face on various different emotions, when the confidence score of a certain emotion is higher, the emotion is considered to be closer to the emotion of the Face, and currently, Face + + can recognize 7 most important emotions such as anger, disgust, fear, happiness, calmness, injury, surprise and the like.
The face recognition algorithm is specifically a characteristic face method which is one of the classic face recognition algorithms in the prior art: acquiring a set S containing M face images; after a face vector set S is obtained, calculating to obtain an average image psi; calculating the difference phi between each image and the average image; finding M orthogonal unit vectors un; after the face is recognized, an eye model and an equation are established according to the anatomical structure of eyes, after the equation is solved, a fixation point on a screen is obtained by intersecting a visual axis and the screen, and an eyeball tracking algorithm is used for tracking, so that the method can achieve the precision of less than 3 degrees.
When the fatigue phenomenon of the driver is monitored by the face recognition algorithm, it can be judged by tracking the single closing time of the eyes in consideration of the occurrence of the fatigue phenomenon, and when the single closing time is higher than a threshold, the fatigue phenomenon of the driver is defined because the single closing time of the eyes is longer than usual when the driver is fatigued.
Specifically, the eyeball tracking algorithm is as follows:
and (4) carrying out pupil area positioning, determining a pupil area and a pupil position in a local area image containing the human eye through Haar characteristics, and establishing a difference Gaussian pyramid model calculation area extreme point of the human eye image. And secondly, fitting the pupil center, establishing a self-adaptive pupil fitting template in the pupil area image, and fitting the pupil edge and center by taking the area extreme point as the template center.
The Haar features are rectangular feature templates used for extracting simple edge feature information in the image. The characteristic template is formed by combining two or more black and white rectangular areas with different sizes, and the characteristic value of the template is the difference value between the sum of the gray values of the pixels in the white rectangular area and the sum of the gray values of the pixels in the black rectangular area:
wherein the content of the first and second substances,
is the gray value of the pixel in the white rectangular regionThe sum of the total weight of the components,
is the sum of the grey values of the pixels in the black rectangular area.
In the Haar feature template, because the Haar feature template has a huge number, calculating the sum of pixel gray values in a black-white area can generate a huge calculation amount, in order to accelerate the calculation speed Viola, an Integral graph (Integral Image) concept is proposed, the sum of pixel gray values in any area of the feature template can be quickly calculated, the Integral graph can be used for quickly calculating the sum of pixel gray values in any pixel point x in an Image, y is on the left side of the x coordinate of the point, and the sum of pixel gray values in an area on the upper side of the y coordinate:
thus, the sum of the gray scale values of the pixels in each column of the image is:
locating a pupil area by using a HAAR template, simultaneously downsampling a human eye image area to be one fourth of the size of an original image, performing Gaussian kernel convolution Gn (n is 1,2,3,4) with four different scales, and then subtracting adjacent Gaussian convolution images Gn and Gn +1 to establish a differential Gaussian pyramid model Dn (n is 1,2,3), wherein Gn and Dn are specifically,
Dn＝Gn+1-Gn,n＝1,2,3
finally, an ellipse fitting equation is established:
Q(xi,yi)＝Ax2+Bxy+Cy2+Dx+Ey+F
and finally, substituting the selected feature point coordinates into an ellipse equation respectively, and considering the center of the ellipse as the center of the pupil to obtain the eyeball tracking method.
Preferably, when the single eye closing time of the driver exceeds 0.5s, the fatigue phenomenon of the driver is defined. This preferred value is set to be practical considering that in most cases when the driver is driving tired, the single eye-closure time is 0.5s as a broad distinction.
④ it is obtained by the path-trajectory algorithm whether the vehicle has sustained deviation of course in abnormal dynamic.
Monitoring whether the vehicle has a sustained deviation of the course in abnormal dynamics includes:
acquiring the theoretical width of a vehicle traveling road in real time;
when the vehicle travels in a direction deviating from the original traveling route, acquiring a safety threshold of the travel distance in real time;
when the vehicle travels to a safe threshold of travel distance in a direction deviating from the original travel route, the vehicle is defined to have a continuous deviation of the travel route.
Considering that a driver may cause a continuous deviation of a route of a vehicle due to unconsciousness or other conditions affecting normal driving, since whether the vehicle has the continuous deviation of the route is monitored in real time and avoided early, it is necessary to consider a specific road condition where the vehicle is located at the moment, different road conditions provide different safety thresholds of a travel distance, when the road is wide, the safety threshold of the travel distance is relatively large, and when the road is narrow, the safety threshold of the travel distance is relatively small, and finally whether the vehicle has the continuous deviation of the route is defined according to actual conditions.
The specific path orbit algorithm is as follows:
wherein, the safety threshold of the travel distance is obtained in real time through the following formula:
the real-time acceleration of the vehicle is determined according to the real-time acceleration of the vehicle, wherein the real-time acceleration is a safety threshold value of a traveling distance, v is the real-time speed of the vehicle, L is the theoretical width of a traveling road of the vehicle (obtained by real-time measurement of a sensor), Z is the real-time length of the vehicle from the head to the roads on two sides in the real-time traveling direction, and a is the real-time acceleration.
It is worth noting that: the angle required by the sensor camera needs to cover the position of the human eye. If a 60-degree camera is used, the condition of eyes of 1-1 m five can be covered, and the position needs to be adjusted at the moment, so that the visual range of eyes of 1-m five to one-m 9 can be covered. In addition, if it is not sufficient, the camera angle needs to be increased, for example, from 60 degrees to 90 degrees or 120 degrees, as shown in fig. 4.
Further, when abnormal dynamics occur, the pre-warning and emergency treatment includes:
when the fatigue phenomenon of a driver is monitored, reducing the speed of the vehicle to a speed safety threshold value, and continuously alarming;
and when the continuous deviation of the route of the vehicle is monitored, emergency braking is carried out, the speed of the vehicle is reduced to 0km/h, and the alarm is continuously given.
It should be noted that: when the fatigue phenomenon of a driver is monitored, because the vehicle may not have the deviation of a route, the safety can be improved by reducing the speed of the vehicle to a speed safety threshold and continuously alarming, and the problem of poor smoothness caused by the emergency braking condition of the vehicle is avoided; when the continuous deviation of the route of the vehicle is monitored, the time of the accident is within a short time after the deviation, at the moment, emergency braking is needed, the speed of the vehicle is reduced to 0km/h, and the alarm is continuously given. The two different processing methods embody the characteristic of the invention combined with the reality and are more in line with the actual driving experience.
Wherein, when monitoring that the driver is tired, obtaining the speed safety threshold comprises:
detecting an obstacle in front of the vehicle;
if an obstacle appears in front of the vehicle, acquiring the relative distance and the relative speed between the vehicle and the obstacle;
the speed safety threshold is obtained by the following formula,
wherein P represents a speed safety threshold value, α represents a relative speed relationship, β represents a relative position relationship, d represents a visual sensor parallax, f represents a visual sensor focal length, H represents a distance from an obstacle to a vehicle, and V represents a real-time speed of the vehicle.
The method is characterized in that the relative position relation between an object and a vehicle is measured by combining a binocular sensor, the distance is measured by using the binocular sensor, and the direct difference (namely parallax d) of the transverse coordinates of the target point imaged on the left view and the right view is in inverse proportion to the distance H from an obstacle to the vehicle. With the matrix:
and obtaining the focal length f, the parallax d and the camera center distance Tx to obtain the three-dimensional coordinates of the target point.
After the relative positional relationship is obtained, the movement L of the relative position is measured within a given unit time t (for example, 0.5s), and the relative velocity relationship is calculated by α ═ L/t.
What needs to be additionally stated is that: before a driver drives, the driver needs to open the wireless hotspot of the carried intelligent equipment in advance, so that the intelligent auxiliary driving system can be connected with the network of the intelligent equipment and search and navigate in a rest area.
To verify the effectiveness of the present invention, 20 trucks were loaded with the present invention and the prior art was used for the other 20 trucks, and the comparison results after 6 months are shown in table 1 below:
table 1: comparison table of half-year effect of the invention and the prior art
As is apparent from the above table 1, compared with the prior art, the number of accidents occurring within half a year is obviously reduced, the probability of occurrence of danger is obviously reduced, the safety and smoothness of truck driving are improved, and the occurrence rate of traffic accidents caused by driving fatigue and the like is effectively solved.
Example 2
Referring to fig. 2, a first embodiment of an intelligent processing system for fatigue driving according to the present invention is shown: an intelligent processing system for fatigue driving, comprising:
a monitoring module 100 for monitoring whether abnormal dynamics occur in the driver and the vehicle;
a processing module 200, configured to perform early warning and emergency processing after abnormal dynamics occurs;
a retrieving module 300 for retrieving a surrounding rest area after the abnormal dynamics occurs and performing a route navigation of a nearest rest area;
and the tracking alarm module 400 is used for monitoring whether the vehicle goes to the rest area or not, and implementing alarm processing when the vehicle deviates from the route of the rest area until the alarm is turned off after the route returns to the right.
Further, the monitoring module 100 includes:
an observation unit for observing a single eye-closing time of a driver and a theoretical width of a vehicle travel road;
the acquisition unit is used for acquiring a safety threshold of the travel distance in real time;
the judging unit is used for acquiring whether the driver has fatigue phenomenon and whether the vehicle has continuous deviation of the route;
and the feedback unit is used for feeding back the judgment result of the judgment unit to the intelligent auxiliary system.
Further, the processing module 200 includes:
a detection unit for detecting an obstacle in front of the vehicle;
the second acquisition unit is used for acquiring the relative distance and the relative speed between the vehicle and the obstacle and calculating a speed safety threshold;
a braking unit for braking the vehicle when abnormal dynamics occur;
and the alarm unit is used for giving an alarm when abnormal dynamic occurs.
It should be recognized that embodiments of the present invention can be realized and implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer-readable storage medium configured with the computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, according to the methods and figures described in the detailed description. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, the operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or combinations thereof. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable interface, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RAM, ROM, or the like, such that it may be read by a programmable computer, which when read by the storage medium or device, is operative to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described herein includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein. A computer program can be applied to input data to perform the functions described herein to transform the input data to generate output data that is stored to non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display.
As used in this application, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between two or more computers. In addition, these components can execute from various computer readable media having various data structures thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (10)
1. An intelligent processing method for fatigue driving is characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
monitoring whether abnormal dynamic occurs to a driver and a vehicle in real time;
if the abnormal dynamic state occurs, early warning and emergency processing are carried out;
retrieving a surrounding rest area and implementing route navigation of the nearest rest area;
and monitoring whether the vehicle goes to the rest area in real time, and implementing alarm processing when the vehicle deviates from the route of the rest area until the alarm is turned off after the route returns to the right.
2. The intelligent processing method for fatigue driving according to claim 1, characterized in that: monitoring in real time whether the abnormal dynamic state occurs in the driver and the vehicle includes,
acquiring whether the driver has fatigue phenomenon in the abnormal dynamic state through a facial recognition algorithm;
acquiring whether the vehicle has the route continuous deviation in the abnormal dynamic state through a path track algorithm;
and feeding back the obtained result to the intelligent auxiliary system.
3. The intelligent processing method for fatigue driving according to claim 2, characterized in that: when the single eye closing time of the driver exceeds 0.5s, the fatigue phenomenon of the driver is defined.
4. The intelligent processing method for fatigue driving according to claim 2 or 3, characterized in that: monitoring whether the vehicle experiences a sustained deviation in course of the erratic dynamic condition includes,
acquiring the theoretical width of the vehicle travelling road in real time;
when the vehicle travels in a direction deviating from the original traveling route, acquiring a safety threshold of a travel distance in real time;
when the vehicle travels to the safety threshold value of the travel distance in the direction deviating from the original traveling route, the continuous deviation of the vehicle route is defined.
5. The intelligent processing method for fatigue driving according to claim 4, wherein: the safety threshold for the distance traveled is obtained in real time by the following formula,
the safety threshold value of the traveling distance is v, the real-time speed of the vehicle is L, the theoretical width of the traveling road of the vehicle is measured by a sensor in real time, Z is the real-time length of the vehicle from the head to the roads on two sides in the real-time traveling direction, and a is the real-time acceleration of the vehicle.
6. The intelligent processing method for fatigue driving according to any one of claims 1 to 3 or 5, wherein: when the abnormal dynamic state occurs, the early warning and emergency treatment comprises,
when the fatigue phenomenon of the driver is monitored, reducing the speed of the vehicle to a speed safety threshold value, and continuously alarming;
and when the continuous deviation of the route of the vehicle is monitored, emergency braking is carried out, the speed of the vehicle is reduced to 0km/h, and the alarm is continuously given.
7. The intelligent processing method for fatigue driving according to claim 6, characterized in that: obtaining the speed safety threshold comprises obtaining a speed safety threshold,
detecting an obstacle in front of the vehicle;
if an obstacle appears in front of the vehicle, acquiring the relative distance and the relative speed between the vehicle and the obstacle;
the speed safety threshold is obtained by the following formula,
wherein P represents the speed safety threshold value, α represents the relative speed relationship, β represents the relative position relationship, d represents the parallax of the vision sensor, f represents the focal length of the vision sensor, H represents the distance from the obstacle to the vehicle, and V represents the real-time speed of the vehicle.
8. An intelligent processing system for fatigue driving, characterized by: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
a monitoring module (100) for monitoring whether abnormal dynamics of the driver and the vehicle occur;
a processing module (200) for performing early warning and emergency processing after the abnormal dynamics occur;
-a retrieval module (300) for retrieving a surrounding rest area after occurrence of said anomalous dynamic and implementing a route navigation of the nearest said rest area;
and the tracking alarm module (400) is used for monitoring whether the vehicle goes to the rest area or not and implementing alarm processing when the vehicle deviates from the route of the rest area until the alarm is turned off after the route returns to the right.
9. The intelligent processing system for fatigue driving of claim 8, wherein: the monitoring module (100) comprises a monitoring module,
an observation unit for observing a single eye-closing time of the driver and a theoretical width of the vehicle travel road;
the acquisition unit is used for acquiring a safety threshold of the travel distance in real time;
the judging unit is used for acquiring whether the driver has fatigue phenomenon and whether the vehicle has continuous deviation of the route;
and the feedback unit is used for feeding back the judgment result of the judgment unit to the intelligent auxiliary system.
10. The intelligent processing system for fatigue driving according to claim 8 or 9, wherein: the processing module (200) comprises a processor,
a detection unit for detecting an obstacle in front of the vehicle;
the second acquisition unit is used for acquiring the relative distance and the relative speed between the vehicle and the obstacle and calculating a speed safety threshold;
a braking unit for braking the vehicle when the abnormal dynamic state occurs;
and the alarm unit is used for giving an alarm when the abnormal dynamic state occurs.
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