CN112070927A - Highway vehicle microscopic driving behavior analysis system and analysis method - Google Patents
Highway vehicle microscopic driving behavior analysis system and analysis method Download PDFInfo
- Publication number
- CN112070927A CN112070927A CN202010889142.3A CN202010889142A CN112070927A CN 112070927 A CN112070927 A CN 112070927A CN 202010889142 A CN202010889142 A CN 202010889142A CN 112070927 A CN112070927 A CN 112070927A
- Authority
- CN
- China
- Prior art keywords
- driving
- data
- driver
- vehicle
- driving behavior
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
- G07C5/0866—Registering performance data using electronic data carriers the electronic data carrier being a digital video recorder in combination with video camera
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
Abstract
The invention belongs to the technical field of vehicles and discloses an analysis system and an analysis method for microscopic driving behaviors of vehicles on a highway, wherein an image acquisition module acquires driving image data of a driver by utilizing camera equipment; the data acquisition module acquires state data related to the vehicle; the environmental data acquisition module acquires weather data and road data; the driving behavior evaluation module evaluates the driving behavior based on the acquired data; the alarm module gives an alarm for the driving behavior of which the evaluation result does not reach a preset value; and the result output module sends the driving behavior evaluation result to the mobile terminal of the driver. The invention comprehensively analyzes the driving behaviors from a plurality of aspects such as vehicle state, vehicle speed, driver behavior, driver state and the like based on a plurality of data, can comprehensively, accurately, scientifically and objectively evaluate the driving behaviors, gives corresponding summary and warning to the driver based on the evaluation result of the driving behaviors and can timely remind the driver to correct the bad driving behaviors.
Description
Technical Field
The invention belongs to the technical field of vehicles, and particularly relates to a system and a method for analyzing microscopic driving behaviors of vehicles on a highway.
Background
At present: with the improvement of living standard of people, automobiles become one of main transportation means for people to go out, and meanwhile, along with the occurrence of bad driving behaviors, the bad driving behaviors of users easily cause traffic accidents.
In the prior art, various driving behavior analysis methods and analysis systems are proposed, for example, a method for determining a driving state of a vehicle based on an acceleration sensor, disclosed in chinese patent document CN102167041A, in which the acceleration sensor is used to collect raw data, and the driving state of the vehicle is determined by analyzing and processing three axial accelerations, so as to know the driving behavior and the driving state of a driver, thereby helping a vehicle manager to standardize the driving behavior, prevent dangerous driving behavior, and ensure driving safety. However, this method can only identify and analyze the speeding behavior, and cannot fully analyze other driving behaviors.
In order to improve the driving safety of an automobile, a technology for automatically detecting whether the driver has abnormal driving behaviors is adopted at present, and the image of the driver is collected and analyzed so as to determine whether the abnormal driving behaviors exist. However, the current image analysis method is easy to misjudge, and the detection accuracy is low.
Through the above analysis, the problems and defects of the prior art are as follows: the prior art can not comprehensively and accurately analyze the driving behaviors. And the existing image analysis method is easy to misjudge and has low detection accuracy.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a system and a method for analyzing the microscopic driving behavior of a highway vehicle.
The invention is realized in this way, a system and method for analyzing the microscopic driving behavior of vehicles on the highway, the system for analyzing the microscopic driving behavior of vehicles on the highway comprises:
image acquisition module, data acquisition module, environmental data acquisition module, central control module, driving behavior evaluation module, alarm module and result output module
The image acquisition module is connected with the central control module and is used for acquiring driving image data of a driver by utilizing the camera equipment;
the data acquisition module is connected with the central control module, comprises a vehicle basic data acquisition unit, a speed acquisition unit, a transmitter speed acquisition unit and a positioning unit and is used for acquiring vehicle-related state data;
the environment data acquisition module is connected with the central control module and comprises a weather data acquisition unit and a road data acquisition unit; the system is used for acquiring weather data and road data;
the central control module is connected with the image acquisition module, the data acquisition module, the environmental data acquisition module, the driving behavior evaluation module, the alarm module and the result output module and is used for controlling each module to normally work by utilizing a single chip microcomputer or a controller;
the driving behavior evaluation module is connected with the central control module and used for evaluating the driving behavior based on the acquired data;
the alarm module is connected with the central control module and used for giving an alarm to the driving behavior of which the evaluation result does not reach the preset value;
and the result output module is connected with the central control module and used for sending the driving behavior evaluation result to the mobile terminal of the driver.
Further, the data acquisition module includes:
a vehicle basic data acquiring unit for acquiring the type of the vehicle, the check load and other basic data;
the speed acquisition unit is used for acquiring the real-time running speed of the vehicle by using the speed sensor;
the engine data acquisition unit is used for acquiring the opening degree of an accelerator of a vehicle, the rotating speed of an engine, torque, a brake switch signal and other related information;
and the positioning unit is used for acquiring longitude and latitude, direction, elevation and acceleration information of the vehicle through a Beidou satellite navigation system.
Further, the environment data obtaining module includes:
the weather data acquisition unit is used for establishing data connection with the highway monitoring system and determining weather data of an area where the vehicle is located based on the current position of the vehicle;
and the road data acquisition unit is used for determining the speed limit or time limit data of the expressway where the vehicle is located based on the current position of the vehicle.
Further, the driving behavior evaluation module includes:
a vehicle state determination unit for determining whether the vehicle is in a normal state based on the acquired vehicle state data;
the fatigue driving judging unit is used for judging whether the driver is in fatigue driving or not based on the acquired driving image data of the driver;
a driving attention judging unit for judging whether the driving behavior of the driver is attention-dispersed based on the acquired driving image data of the driver;
a dangerous driving judgment unit for judging whether there is a behavior of dangerous driving based on the acquired data;
and the scoring unit is used for scoring the driving behaviors by integrating the vehicle state judgment result, the fatigue driving judgment result, the driving attention judgment result and the dangerous driving judgment result.
Further, the dangerous driving behaviors include, but are not limited to: rapid acceleration, rapid deceleration, neutral sliding, overlong idle speed, refueling door in a parking state, overspeed, overtravel, lane departure and too close following.
Another object of the present invention is to provide a highway vehicle micro-driving behavior analysis method applied to the highway vehicle micro-driving behavior analysis system, the highway vehicle micro-driving behavior analysis method comprising:
the method comprises the following steps that firstly, an image acquisition module acquires driving image data of a driver by utilizing camera equipment; the data acquisition module acquires state data related to the vehicle; the environmental data acquisition module acquires weather data and road data;
step two, the central control module controls the driving behavior evaluation module to compare the acquired vehicle state data with normal vehicle data and judge whether the vehicle is in fault;
thirdly, judging whether the vehicle runs at an overspeed or not by the driving behavior evaluation module based on the acquired vehicle speed data; judging whether the vehicle is abnormally driven in an illegal way or is driven at night based on the acquired weather data and the vehicle data;
fourthly, the driving behavior evaluation module judges whether the driver is in fatigue driving or not based on the acquired driving image data of the driver; judging whether the driving behavior of the driver is a distraction type or not based on the acquired driving image data of the driver; a behavior for judging whether there is dangerous driving based on the acquired data;
fifthly, calculating the grade of the driving behavior based on the judgment results of the third step and the fourth step and the corresponding weight coefficient by the driving behavior evaluation module; the alarm module gives an alarm for the driving behavior of which the evaluation result does not reach a preset value; and the result output module sends the driving behavior evaluation result to the mobile terminal of the driver.
Further, in step four, before the driving behavior evaluation module determines whether the driver is tired and whether the driver is distracted, the driving behavior evaluation module first preprocesses the acquired driving image data of the driver, and the adopted preprocessing method includes:
separating the foreground and the background of the original image by using a difference technology, and separating a middle foreground image and a background image of the original image to obtain a foreground image;
carrying out convolution operation on the foreground image and the high-pass filtering template to find out the boundary contour of the object, and separating out an independent object according to the continuity and the closure of the contour;
and carrying out normalization processing on the image of each object, and carrying out convolution operation on the image and the human body characteristic template to obtain a processed image.
Further, in the fourth step, the judging whether the driver is in fatigue driving based on the acquired driving image data of the driver by the driving behavior evaluation module includes:
(1) acquiring driving image data of a driver, and judging whether the driver has eye closing and yawning related behaviors in the driving image data;
(2) if yes, counting the eye closing behaviors and yawning behaviors of the driving image data for a period of time;
(3) calculating the proportion of the eye closing time to the driving time;
(4) and (3) if the statistical result in the step (2) and the calculation result in the step (3) exceed a preset threshold value, judging that the user is fatigue driving.
Further, in the step (3), the calculating the ratio of the eye-closing time to the driving time includes:
according to the state of the eyes at each moment, the time ratio F of the eyes in the state of being more than 80 percent closed is calculated, namely
N is the effective frame number of the collected videos in unit time, K is the frame number of eyes in a closed state which is more than 80% in unit time, whether a driver is tired or not is judged according to the mean value of F, when F is less than 0.25, the driver is in a wakeful state, and when F is more than 0.25, the driver belongs to a tired state.
Further, in the fourth step, the determining whether the driving behavior of the driver is the distraction type based on the acquired driving image data of the driver includes:
1) acquiring driving image data of a driver, and extracting head posture data, behavior data and eye movement data of a user from the driving image data;
2) extracting corresponding head posture data characteristics from the acquired head posture data of the user;
3) comparing the extracted head posture data features with attention-dispersed head posture features stored in a database in advance, and determining whether the user is attention-dispersed driving;
4) judging whether the user has head-down, left-right anticipation, call making, smoking or other behaviors or not based on the user behavior data, and if so, judging that the user is driving with dispersed attention;
5) and further judging whether the eye movement data of the user belongs to eye movement characteristics in distraction or distraction, and if so, judging that the user is distraction-type driving.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the highway vehicle micro driving behavior analysis method when executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the highway vehicle micro-driving behavior analysis method.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention comprehensively analyzes the driving behaviors from a plurality of aspects such as vehicle state, vehicle speed, driver behavior, driver state and the like based on a plurality of data, can comprehensively, accurately, scientifically and objectively evaluate the driving behaviors, gives corresponding summary and warning to the driver based on the evaluation result of the driving behaviors and can timely remind the driver to correct the bad driving behaviors.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
FIG. 1 is a schematic structural diagram of a system for analyzing microscopic driving behaviors of vehicles on a highway according to an embodiment of the invention;
in the figure: 1. an image acquisition module; 2. a data acquisition module; 3. an environmental data acquisition module; 4. a central control module; 5. a driving behavior evaluation module; 6. an alarm module; 7. and a result output module.
FIG. 2 is a schematic structural diagram of a data acquisition module according to an embodiment of the present invention;
in the figure: 21. a vehicle basic data acquisition unit; 22. a speed acquisition unit; 23. a transmitter speed acquisition unit; 24. a positioning unit.
FIG. 3 is a schematic structural diagram of an environment data acquiring module according to an embodiment of the present invention;
in the figure: 31. a weather data acquisition unit; 32. a road data acquisition unit.
FIG. 4 is a schematic structural diagram of a driving behavior evaluation module according to an embodiment of the present invention;
in the figure: 51. a vehicle state determination unit; 52. a fatigue driving determination unit; 53. a driving attention determination unit; 54. a dangerous driving judgment unit; 55. and (4) scoring units.
Fig. 5 is a flowchart of a method for analyzing microscopic driving behavior of vehicles on a highway according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems in the prior art, the present invention provides a system and a method for analyzing the microscopic driving behavior of vehicles on a highway, which are described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the system for analyzing microscopic driving behavior of a highway vehicle according to an embodiment of the present invention includes:
the system comprises an image acquisition module 1, a data acquisition module 2, an environmental data acquisition module 3, a central control module 4, a driving behavior evaluation module 5, an alarm module 6 and a result output module 7;
the image acquisition module 1 is connected with the central control module 4 and is used for acquiring driving image data of a driver by utilizing camera equipment;
the data acquisition module 2 is connected with the central control module 4, comprises a vehicle basic data acquisition unit 21, a speed acquisition unit 22, a transmitter speed acquisition unit 23 and a positioning unit 24, and is used for acquiring vehicle-related state data;
the environment data acquisition module 3 is connected with the central control module 4 and comprises a weather data acquisition unit 31 and a road data acquisition unit 32; the system is used for acquiring weather data and road data;
the central control module 4 is connected with the image acquisition module 1, the data acquisition module 2, the environmental data acquisition module 3, the driving behavior evaluation module 5, the alarm module 6 and the result output module 7 and is used for controlling each module to normally work by utilizing a single chip microcomputer or a controller;
the driving behavior evaluation module 5 is connected with the central control module 4 and used for evaluating the driving behavior based on the acquired data;
the alarm module 6 is connected with the central control module 4 and used for giving an alarm to the driving behavior of which the evaluation result does not reach the preset value;
and the result output module 7 is connected with the central control module 4 and is used for sending the driving behavior evaluation result to the mobile terminal of the driver.
As shown in fig. 2, the data obtaining module 2 provided in the embodiment of the present invention includes:
a vehicle basic data obtaining unit 21 for obtaining the type of the vehicle, the verification load, and other basic data;
a speed acquisition unit 22 for acquiring a real-time running speed of the vehicle using a speed sensor;
the engine data acquisition unit 23 is used for acquiring the opening degree of an accelerator of the vehicle, the rotating speed of the engine, the torque, a brake switch signal and other related information;
and the positioning unit 24 is used for acquiring longitude and latitude, direction, elevation and acceleration information of the vehicle through a Beidou satellite navigation system.
As shown in fig. 3, the environment data acquiring module 3 according to the embodiment of the present invention includes:
a weather data acquisition unit 31, configured to determine weather data of an area where the vehicle is located based on a current position of the vehicle by establishing a data connection with the highway monitoring system;
and the road data acquisition unit 32 is used for determining the speed limit or time limit data of the expressway where the vehicle is located currently based on the current position of the vehicle.
As shown in fig. 4, the driving behavior evaluation module 5 according to the embodiment of the present invention includes:
a vehicle state determination unit 51 for determining whether the vehicle is in a normal state based on the acquired vehicle state data;
a fatigue driving determination unit 52 for determining whether the driver is fatigue driving based on the acquired driving image data of the driver;
a driving attention judging unit 53 for judging whether the driving behavior of the driver is attention-dispersed type based on the acquired driving image data of the driver;
a dangerous driving determination unit 54 for determining whether there is a behavior of dangerous driving based on the acquired data;
and the scoring unit 55 is used for scoring the driving behaviors by integrating the vehicle state judgment result, the fatigue driving judgment result, the driving attention judgment result and the dangerous driving judgment result.
Dangerous driving behaviors provided by the embodiment of the invention include, but are not limited to: rapid acceleration, rapid deceleration, neutral sliding, overlong idle speed, refueling door in a parking state, overspeed, overtravel, lane departure and too close following.
As shown in fig. 5, the method for analyzing the microscopic driving behavior of the highway vehicle according to the embodiment of the present invention includes:
s101, an image acquisition module acquires driving image data of a driver by using camera equipment; the data acquisition module acquires state data related to the vehicle; the environmental data acquisition module acquires weather data and road data;
s102, the central control module controls the driving behavior evaluation module to compare the acquired vehicle state data with normal vehicle data and judge whether the vehicle has a fault;
s103, judging whether the vehicle runs at an overspeed or not by the driving behavior evaluation module based on the acquired vehicle speed data; judging whether the vehicle is abnormally driven in an illegal way or is driven at night based on the acquired weather data and the vehicle data;
s104, the driving behavior evaluation module judges whether the driver is in fatigue driving or not based on the acquired driving image data of the driver; judging whether the driving behavior of the driver is a distraction type or not based on the acquired driving image data of the driver; a behavior for judging whether there is dangerous driving based on the acquired data;
s105, the driving behavior evaluation module calculates the grade of the driving behavior based on the corresponding weight coefficient based on the judgment results of the step S103 and the step S104; the alarm module gives an alarm for the driving behavior of which the evaluation result does not reach a preset value; and the result output module sends the driving behavior evaluation result to the mobile terminal of the driver.
The driving behavior evaluation module provided by the embodiment of the invention comprises the following steps of judging whether the driver is in fatigue driving based on the acquired driving image data of the driver:
(1) acquiring driving image data of a driver, and judging whether the driver has eye closing and yawning related behaviors in the driving image data;
(2) if yes, counting the eye closing behaviors and yawning behaviors of the driving image data for a period of time;
(3) calculating the proportion of the eye closing time to the driving time;
(4) and (3) if the statistical result in the step (2) and the calculation result in the step (3) exceed a preset threshold value, judging that the user is fatigue driving.
Further, in the step (3), the calculating the ratio of the eye-closing time to the driving time includes:
according to the state of the eyes at each moment, the time ratio F of the eyes in the state of being more than 80 percent closed is calculated, namely
N is the effective frame number of the collected videos in unit time, K is the frame number of eyes in a closed state which is more than 80% in unit time, whether a driver is tired or not is judged according to the mean value of F, when F is less than 0.25, the driver is in a wakeful state, and when F is more than 0.25, the driver belongs to a tired state.
The method for judging whether the driving behavior of the driver is distractive or not based on the acquired driving image data of the driver, provided by the embodiment of the invention, comprises the following steps:
1) acquiring driving image data of a driver, and extracting head posture data, behavior data and eye movement data of a user from the driving image data;
2) extracting corresponding head posture data characteristics from the acquired head posture data of the user;
3) comparing the extracted head posture data features with attention-dispersed head posture features stored in a database in advance, and determining whether the user is attention-dispersed driving;
4) judging whether the user has head-down, left-right anticipation, call making, smoking or other behaviors or not based on the user behavior data, and if so, judging that the user is driving with dispersed attention;
5) and further judging whether the eye movement data of the user belongs to eye movement characteristics in distraction or distraction, and if so, judging that the user is distraction-type driving.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.
Claims (10)
1. A highway vehicle microscopic driving behavior analysis method is characterized by comprising the following steps:
the method comprises the following steps that firstly, an image acquisition module acquires driving image data of a driver by utilizing camera equipment; the data acquisition module acquires state data related to the vehicle; the environmental data acquisition module acquires weather data and road data;
step two, the central control module controls the driving behavior evaluation module to compare the acquired vehicle state data with normal vehicle data and judge whether the vehicle is in fault;
thirdly, judging whether the vehicle runs at an overspeed or not by the driving behavior evaluation module based on the acquired vehicle speed data; judging whether the vehicle is abnormally driven in an illegal way or is driven at night based on the acquired weather data and the vehicle data;
fourthly, the driving behavior evaluation module judges whether the driver is in fatigue driving or not based on the acquired driving image data of the driver; judging whether the driving behavior of the driver is a distraction type or not based on the acquired driving image data of the driver; a behavior for judging whether there is dangerous driving based on the acquired data;
the driving behavior evaluation module judges whether the driver is in fatigue driving based on the acquired driving image data of the driver, and the judging comprises the following steps:
(1) acquiring driving image data of a driver, and judging whether the driver has eye closing and yawning related behaviors in the driving image data;
(2) if yes, counting the eye closing behaviors and yawning behaviors of the driving image data for a period of time;
(3) calculating the proportion of the eye closing time to the driving time;
(4) if the statistical result in the step (2) and the calculation result in the step (3) exceed a preset threshold value, determining that the user is fatigue driving;
the judging whether the driving behavior of the driver is a distraction type based on the acquired driving image data of the driver includes:
1) acquiring driving image data of a driver, and extracting head posture data, behavior data and eye movement data of a user from the driving image data;
2) extracting corresponding head posture data characteristics from the acquired head posture data of the user;
3) comparing the extracted head posture data features with attention-dispersed head posture features stored in a database in advance, and determining whether the user is attention-dispersed driving;
4) judging whether the user has head-down, left-right anticipation, call making, smoking or other behaviors or not based on the user behavior data, and if so, judging that the user is driving with dispersed attention;
5) further judging whether the eye movement data of the user belong to eye movement characteristics in distraction or distraction, and if so, judging that the user is distraction-type driving;
fifthly, calculating the grade of the driving behavior based on the judgment results of the third step and the fourth step and the corresponding weight coefficient by the driving behavior evaluation module; the alarm module gives an alarm for the driving behavior of which the evaluation result does not reach a preset value; and the result output module sends the driving behavior evaluation result to the mobile terminal of the driver.
2. The method for analyzing microscopic driving behavior of vehicles on expressways according to claim 1, wherein in step four, the driving behavior evaluation module first preprocesses the acquired driving image data of the driver before determining whether the driver is tired and distracted, and the preprocessing method comprises:
separating the foreground and the background of the original image by using a difference technology, and separating a middle foreground image and a background image of the original image to obtain a foreground image;
carrying out convolution operation on the foreground image and the high-pass filtering template to find out the boundary contour of the object, and separating out an independent object according to the continuity and the closure of the contour;
and carrying out normalization processing on the image of each object, and carrying out convolution operation on the image and the human body characteristic template to obtain a processed image.
3. The method for analyzing microscopic driving behavior of highway vehicles according to claim 1, wherein in step (3), the calculating the ratio of the eye-closing time to the driving time comprises:
according to the state of the eyes at each moment, the time ratio F of the eyes in the state of being more than 80 percent closed is calculated, namely
N is the effective frame number of the collected videos in unit time, K is the frame number of eyes in a closed state which is more than 80% in unit time, whether a driver is tired or not is judged according to the mean value of F, when F is less than 0.25, the driver is in a wakeful state, and when F is more than 0.25, the driver belongs to a tired state.
4. A highway vehicle micro-driving behavior analysis system for implementing the highway vehicle micro-driving behavior analysis method according to any one of claims 1 to 3, wherein the highway vehicle micro-driving behavior analysis system comprises:
the system comprises an image acquisition module, a data acquisition module, an environmental data acquisition module, a central control module, a driving behavior evaluation module, an alarm module and a result output module;
the image acquisition module is connected with the central control module and is used for acquiring driving image data of a driver by utilizing the camera equipment;
the data acquisition module is connected with the central control module, comprises a vehicle basic data acquisition unit, a speed acquisition unit, a transmitter speed acquisition unit and a positioning unit and is used for acquiring vehicle-related state data;
the environment data acquisition module is connected with the central control module and comprises a weather data acquisition unit and a road data acquisition unit; the system is used for acquiring weather data and road data;
the central control module is connected with the image acquisition module, the data acquisition module, the environmental data acquisition module, the driving behavior evaluation module, the alarm module and the result output module and is used for controlling each module to normally work by utilizing a single chip microcomputer or a controller;
the driving behavior evaluation module is connected with the central control module and used for evaluating the driving behavior based on the acquired data;
the alarm module is connected with the central control module and used for giving an alarm to the driving behavior of which the evaluation result does not reach the preset value;
and the result output module is connected with the central control module and used for sending the driving behavior evaluation result to the mobile terminal of the driver.
5. The highway vehicle micro-driving behavior analysis system of claim 1, wherein the data acquisition module comprises:
a vehicle basic data acquiring unit for acquiring the type of the vehicle, the check load and other basic data;
the speed acquisition unit is used for acquiring the real-time running speed of the vehicle by using the speed sensor;
the engine data acquisition unit is used for acquiring the opening degree of an accelerator of a vehicle, the rotating speed of an engine, torque, a brake switch signal and other related information;
and the positioning unit is used for acquiring longitude and latitude, direction, elevation and acceleration information of the vehicle through a Beidou satellite navigation system.
6. The highway vehicle micro-driving behavior analysis system according to claim 1, wherein the environmental data acquisition module comprises:
the weather data acquisition unit is used for establishing data connection with the highway monitoring system and determining weather data of an area where the vehicle is located based on the current position of the vehicle;
and the road data acquisition unit is used for determining the speed limit or time limit data of the expressway where the vehicle is located based on the current position of the vehicle.
7. The system for analyzing microscopic driving behavior of highway vehicles according to claim 1, wherein the driving behavior evaluation module comprises:
a vehicle state determination unit for determining whether the vehicle is in a normal state based on the acquired vehicle state data;
the fatigue driving judging unit is used for judging whether the driver is in fatigue driving or not based on the acquired driving image data of the driver;
a driving attention judging unit for judging whether the driving behavior of the driver is attention-dispersed based on the acquired driving image data of the driver;
a dangerous driving judgment unit for judging whether there is a behavior of dangerous driving based on the acquired data;
and the scoring unit is used for scoring the driving behaviors by integrating the vehicle state judgment result, the fatigue driving judgment result, the driving attention judgment result and the dangerous driving judgment result.
8. The highway vehicle micro-driving behavior analysis system of claim 4, wherein the dangerous driving behaviors include, but are not limited to: rapid acceleration, rapid deceleration, neutral sliding, overlong idle speed, refueling door in a parking state, overspeed, overtravel, lane departure and too close following.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing the method of analysis of microscopic driving behavior of highway vehicles according to any one of claims 6-8 when executed on an electronic device.
10. A computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for analyzing microscopic driving behavior of highway vehicles according to any one of claims 6-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010889142.3A CN112070927A (en) | 2020-08-28 | 2020-08-28 | Highway vehicle microscopic driving behavior analysis system and analysis method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010889142.3A CN112070927A (en) | 2020-08-28 | 2020-08-28 | Highway vehicle microscopic driving behavior analysis system and analysis method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112070927A true CN112070927A (en) | 2020-12-11 |
Family
ID=73659786
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010889142.3A Pending CN112070927A (en) | 2020-08-28 | 2020-08-28 | Highway vehicle microscopic driving behavior analysis system and analysis method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112070927A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113548057A (en) * | 2021-08-02 | 2021-10-26 | 四川科泰智能电子有限公司 | Safe driving assistance method and system based on driving trace |
| CN113628415A (en) * | 2021-07-08 | 2021-11-09 | 中铁大桥局集团有限公司 | Bridge construction pavement heavy-load vehicle driving safety early warning method and system |
| CN114842571A (en) * | 2021-02-02 | 2022-08-02 | 深圳市易流科技股份有限公司 | Method and device for determining driving behavior data |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102831670A (en) * | 2012-08-13 | 2012-12-19 | 天瀚科技(吴江)有限公司 | Driving recorder and method of analyzing driving behaviors by using same |
| CN105303830A (en) * | 2015-09-15 | 2016-02-03 | 成都通甲优博科技有限责任公司 | Driving behavior analysis system and analysis method |
| US20160046298A1 (en) * | 2014-08-18 | 2016-02-18 | Trimble Navigation Limited | Detection of driver behaviors using in-vehicle systems and methods |
| CN105575115A (en) * | 2015-12-17 | 2016-05-11 | 福建星海通信科技有限公司 | Driving behavior analysis method based on vehicle-mounted monitoring and management platform |
| CN109243006A (en) * | 2018-08-24 | 2019-01-18 | 深圳市国脉畅行科技股份有限公司 | Abnormal driving Activity recognition method, apparatus, computer equipment and storage medium |
| CN110728241A (en) * | 2019-10-14 | 2020-01-24 | 湖南大学 | Driver fatigue detection method based on deep learning multi-feature fusion |
| CN111079476A (en) * | 2018-10-19 | 2020-04-28 | 上海商汤智能科技有限公司 | Driving state analysis method and device, driver monitoring system and vehicle |
-
2020
- 2020-08-28 CN CN202010889142.3A patent/CN112070927A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102831670A (en) * | 2012-08-13 | 2012-12-19 | 天瀚科技(吴江)有限公司 | Driving recorder and method of analyzing driving behaviors by using same |
| US20160046298A1 (en) * | 2014-08-18 | 2016-02-18 | Trimble Navigation Limited | Detection of driver behaviors using in-vehicle systems and methods |
| CN105303830A (en) * | 2015-09-15 | 2016-02-03 | 成都通甲优博科技有限责任公司 | Driving behavior analysis system and analysis method |
| CN105575115A (en) * | 2015-12-17 | 2016-05-11 | 福建星海通信科技有限公司 | Driving behavior analysis method based on vehicle-mounted monitoring and management platform |
| CN109243006A (en) * | 2018-08-24 | 2019-01-18 | 深圳市国脉畅行科技股份有限公司 | Abnormal driving Activity recognition method, apparatus, computer equipment and storage medium |
| CN111079476A (en) * | 2018-10-19 | 2020-04-28 | 上海商汤智能科技有限公司 | Driving state analysis method and device, driver monitoring system and vehicle |
| CN110728241A (en) * | 2019-10-14 | 2020-01-24 | 湖南大学 | Driver fatigue detection method based on deep learning multi-feature fusion |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114842571A (en) * | 2021-02-02 | 2022-08-02 | 深圳市易流科技股份有限公司 | Method and device for determining driving behavior data |
| CN113628415A (en) * | 2021-07-08 | 2021-11-09 | 中铁大桥局集团有限公司 | Bridge construction pavement heavy-load vehicle driving safety early warning method and system |
| CN113548057A (en) * | 2021-08-02 | 2021-10-26 | 四川科泰智能电子有限公司 | Safe driving assistance method and system based on driving trace |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112070927A (en) | Highway vehicle microscopic driving behavior analysis system and analysis method | |
| CN110164130B (en) | Traffic incident detection method, device, equipment and storage medium | |
| CN111311914B (en) | Vehicle driving accident monitoring method and device and vehicle | |
| US20120245758A1 (en) | Driving behavior detecting method and apparatus | |
| EP2584548A1 (en) | System and method for determining vehicle driving status information-based driver concentration | |
| CN110866427A (en) | Vehicle behavior detection method and device | |
| CN106448265A (en) | Collecting method and device of driver's driving behavior data | |
| CN110660270B (en) | Method for establishing vehicle collision risk evaluation model and collision risk evaluation method | |
| CN108454633B (en) | Method and device for standardizing driving behaviors of driver | |
| CN111401414B (en) | Natural driving data-based dangerous scene extraction and classification method | |
| CN113753059B (en) | Method for predicting takeover capacity of driver under automatic driving system | |
| CN107672600A (en) | A kind of pilotless automobile security system and method for controlling security | |
| CN108230717B (en) | Intelligent traffic management system | |
| CN112835790A (en) | Test method, device, equipment and medium for automatic driving software | |
| Hermawan et al. | Acquisition, modeling, and evaluating method of driving behavior based on OBD-II: A literature survey | |
| Yarlagadda et al. | Heterogeneity in the driver behavior: an exploratory study using real-time driving data | |
| CN116001800B (en) | Vehicle driving risk information acquisition method and device, electronic equipment and medium | |
| KR20150066308A (en) | Apparatus and method for determining driving condition of deiver | |
| CN110909641A (en) | Method, device and system for detecting overload of motorcycle | |
| CN111341106B (en) | Traffic early warning method, device and equipment | |
| CN111775948B (en) | Driving behavior analysis method and device | |
| CN115384540A (en) | Vehicle-mounted safe driving detection device | |
| CN109767627B (en) | Traffic violation intelligent voice snapshot method and system | |
| CN113327409A (en) | Driving behavior analysis system based on intelligent recognition monitoring | |
| KR20160100264A (en) | Method for generating fuel consumption prediction model using dtg big data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201211 |
|
| RJ01 | Rejection of invention patent application after publication |