阅读说明：本技术 一种基于adas系统的汽车疲劳驾驶检测控制方法 (Automobile fatigue driving detection control method based on ADAS system ) 是由 李沛焕 熊锐 于 2019-09-17 设计创作，主要内容包括：本发明提供的基于ADAS系统的汽车疲劳驾驶检测控制方法,通过安装于车辆工控PC机上的人眼定位检测系统ECU实时检测人眼开度状态,实时在线对接ADAS高级驾驶辅助系统,同时驾驶员可选择使用智能终端连接车载蓝牙,便于多终端接收反馈疲劳驾驶反馈信息；当驾驶员行车过程中精神水平达到一定的疲劳驾驶阈值时,ADAS系统强制退出辅助驾驶模式,车辆操纵控制转化为人工机械操作模式,有效避免辅助驾驶条件下因为疲劳驾驶在自动巡航等行驶工况带来的危险驾驶,提高ADAS系统的行车安全性。(According to the detection control method for the fatigue driving of the automobile based on the ADAS system, the opening state of human eyes is detected in real time through the human eye positioning detection system ECU installed on the industrial Personal Computer (PC) of the automobile, the ADAS advanced driving auxiliary system is in real-time and in-line butt joint, and meanwhile, a driver can select to use an intelligent terminal to connect with a vehicle-mounted Bluetooth, so that multiple terminals can receive feedback information of the fatigue driving conveniently; when the mental level of a driver reaches a certain fatigue driving threshold value in the driving process, the ADAS system forcibly exits the auxiliary driving mode, vehicle operation control is converted into a manual mechanical operation mode, dangerous driving caused by driving conditions such as automatic cruising and the like due to fatigue driving under the auxiliary driving condition is effectively avoided, and the driving safety of the ADAS system is improved.)

1. an automobile fatigue driving detection control method based on an ADAS system is characterized by comprising the following steps:

Detecting the opening state of the human eyes in real time by using an Electronic Control Unit (ECU) of the human eye positioning detection system, and carrying out real-time online butt joint on an ADAS system;

The method comprises the steps that a CCD camera installed at the position of an interior rearview mirror is used for collecting the state information of human eyes of a driver on line in real time, and a human eye area image is obtained;

and analyzing the fatigue degree of the driver on the human eye area image, if the driving fatigue degree of the driver is greater than a preset threshold value, carrying out safety early warning, enabling the vehicle to exit from an ADAS system auxiliary driving mode, and enabling the driver to manually control the vehicle to drive.

2. The ADAS system-based automobile fatigue driving detection and control method according to claim 1, wherein the fatigue degree analysis of the human eye area image further comprises: and preprocessing the human eye region image, calculating the human eye height-width ratio, and judging the opening and closing state of human eyes.

3. The ADAS system-based vehicle fatigue driving detection control method of claim 2, wherein determining the eye opening/closing state further comprises: the number of open and closed frames of the eyes of the driver in one detection unit is counted.

4. The ADAS system-based automobile fatigue driving detection control method according to claim 1, wherein the performing of the safety precaution further comprises: and sending a dangerous driving instruction, enabling the buzzer to respond and the early warning LED lamp to be on, and prompting fatigue driving monitoring information on a vehicle UI (user interface).

5. The ADAS system-based automobile fatigue driving detection control method according to claim 1, wherein the driver in the automobile can obtain the driving assistance information of the ADAS system through a UI screen of the automobile.

6. The ADAS system-based automobile fatigue driving detection control method according to claim 1, wherein a cloud data repository is established, the fatigue driving detection capability of a driver is updated and compared, self-learning updating is performed, and more accurate fatigue driving detection control is realized.

7. The ADAS system-based automobile fatigue driving detection control method according to claim 1, wherein an automobile occupant can use an intelligent terminal to connect with a vehicle Bluetooth and receive feedback information of fatigue driving.

8. The ADAS system-based automobile fatigue driving detection control method according to claim 1, wherein the driving fatigue of the driver further comprises: the calculation method of the driving fatigue degree is that the number of frames of closed eyes of a driver in the detection unit is divided by the total number of frames of images in the detection unit.

9. The ADAS system-based automobile fatigue driving detection control method according to claim 1, wherein the predetermined threshold may be 0.4.

10. The ADAS system-based automobile fatigue driving detection control method according to claim 1, wherein the fatigue driving detection system is in communication connection with the ADAS system through a vehicle industrial PC.

Technical Field

The invention relates to the technical field of intelligent automobiles, in particular to an automobile fatigue driving detection control method based on an ADAS system.

Background

An Advanced Driver Assistance System (ADAS System) is an active safety technology that collects environmental data inside and outside a vehicle at the first time by using various sensors installed on the vehicle, such as a photosensitive sensor, a temperature sensor, a humidity sensor, a distance sensor, a speed sensor, and the like, and performs technical processing such as identification, detection, tracking, and the like of static and dynamic objects, so that a Driver can perceive a possible danger at the fastest time to draw attention and improve safety.

early ADAS technologies mainly address passive alerts and alerts motorists to abnormal vehicle or road conditions when a potential hazard is detected in a vehicle, and active intervention is also common with the latest ADAS technologies.

According to statistics, road traffic accidents caused by fatigue driving account for 15% of the total number of the traffic accidents in China, and the fatigue driving is one of the important hidden dangers of the current traffic safety. The ADAS system can reduce fatigue driving caused by high concentration of driver's spirit to a certain extent, and after a driver drives continuously for a long time, the driver is easy to generate monotonous feeling to generate drowsiness, so that a highway hypnosis phenomenon is generated.

The advanced driving assistance system ADAS at present lacks acquisition and analysis of mental level information of a driver and lacks early warning judgment of fatigue driving; the human eye positioning detection rate is low, and the human eye detection positioning effect is not good enough especially under the conditions of weak light and polarized light; interactive butt joint with an intelligent terminal is lacked, and the information feedback effect is single; when fatigue driving occurs, the early warning prompting mode is single, and even no early warning of the fatigue driving exists; the driving fatigue detection system lacks cloud storage of data; there is a lack of vehicle UI interface interaction fatigue detection information.

Disclosure of Invention

The invention provides an automobile fatigue driving detection control method based on an ADAS system, which can effectively solve the problems of lack of on-line monitoring and feedback control on the mental and physiognomic level of a driver and lack of early warning judgment on fatigue driving in the driving process.

The invention provides an automobile fatigue driving detection control method based on an ADAS system, which comprises the following steps:

Detecting the opening state of the human eyes in real time by using a human eye positioning detection system, and carrying out real-time online butt joint on an ADAS system;

The method comprises the steps that a CCD camera installed at the position of an interior rearview mirror is used for collecting the state information of human eyes of a driver on line in real time, and a human eye area image is obtained;

And analyzing the fatigue degree of the human eye area image, if the driving fatigue degree of the driver is greater than a preset threshold value, carrying out safety early warning, enabling the vehicle to exit from an ADAS system auxiliary driving mode, and forcing the driver to manually control the vehicle to drive.

Optionally, the analyzing the fatigue degree of the human eye region image further includes: and preprocessing the human eye region image, calculating the human eye height-width ratio, and judging the opening and closing state of human eyes.

Optionally, the determining the opening and closing states of the human eyes further comprises: the number of open and closed frames of the eyes of the driver in one detection unit is counted.

Optionally, the performing of the safety precaution further includes: and sending a dangerous driving instruction, enabling the buzzer to respond and the early warning LED lamp to be on, and prompting fatigue driving monitoring information on a vehicle UI (user interface).

Optionally, the vehicle occupant may obtain the driving assistance information of the ADAS system through a UI screen of the vehicle.

Optionally, a cloud data repository is established, fatigue driving detection capability of a driver is updated and compared, self-learning updating is achieved, and more accurate fatigue driving detection control is achieved.

optionally, the vehicle-mounted person can use the intelligent terminal to connect with the vehicle-mounted Bluetooth and receive feedback information of fatigue driving.

Optionally, the driving fatigue of the driver further comprises: the calculation method of the driving fatigue degree is that the number of frames of closed eyes of a driver in the detection unit is divided by the total number of frames of images in the detection unit.

Optionally, the preset threshold may be 0.4.

Optionally, the fatigue driving detection system is in communication connection with the ADAS system through a vehicle industrial Personal Computer (PC).

according to the method for detecting and controlling the fatigue driving of the automobile based on the ADAS, a CCD camera is adopted to collect human eye information, a fatigue driving detection system is in communication interaction with the existing ADAS, fatigue driving monitoring information is displayed by using a UI (user interface) of the automobile, an in-automobile person can receive and sense fatigue driving feedback information by using an intelligent terminal, and the fatigue driving detection and identification capacity is improved by using a cloud data center; the driver fatigue level monitoring feedback control system can monitor and feedback control the mental and physical level of a driver on line, increase the feedback control of the driver fatigue level monitoring, and actively intervene to improve the driving auxiliary driving control level and the driving safety.

Drawings

FIG. 1 is a flow chart of a fatigue driving detection process in an ADAS system-based automobile fatigue driving detection control method according to the present invention;

FIG. 2 is a schematic diagram of a fatigue driving detection system in the ADAS system-based automobile fatigue driving detection control method according to the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The driving fatigue detection control method based on the ADAS system carries out positioning detection on human eyes of a driver under the continuous driving condition, carries out feedback control on the ADAS advanced auxiliary driving mode under the condition of confirming the fatigue driving state, reminds the driver to master the autonomous control right of the vehicle in time, quits the automatic driving auxiliary function, and controls an accelerator pedal and a brake pedal by the driver. The driving fatigue detection control method based on the ADAS system is simple and reliable to apply and convenient for marketization popularization.

Through installing the eyes positioning detection system ECU real-time detection eyes aperture state on vehicle industry control PC, the advanced driving auxiliary system of ADAS docks on line in real time, and the driver can choose to use intelligent terminal simultaneously, connects vehicle-mounted bluetooth for example smart mobile phone, intelligent wrist-watch, intelligent bracelet etc. and the tired driving feedback information of feedback is received to the multi-terminal of being convenient for.

When the mental level of a driver reaches a certain fatigue driving threshold value in the driving process, the ADAS system forcibly exits the auxiliary driving mode, vehicle operation control is converted into a manual mechanical operation mode, dangerous driving caused by driving conditions such as automatic cruising and the like due to fatigue driving under the auxiliary driving condition is effectively avoided, and the driving safety of the ADAS system is improved.

the advanced ADAS function related to fatigue driving comprises an ACC adaptive cruise system and adaptive light control of an automobile accelerator pedal and a brake pedal by a driver.

The driving fatigue detection system comprises a CCD camera arranged on the inside rearview mirror, a driver eye fatigue detection algorithm module and an alarm prompt module. The CCD camera is installed at the position of the rearview mirror in the automobile, the main function of the CCD camera is used for collecting the state information of human eyes of a driver on line in real time, and the human eye fatigue detection algorithm carries out fatigue analysis according to the digital signal information of the photo collected and processed by the CCD camera and is used for deciding whether the ADAS system signal needs to be changed to control an accelerator, a brake and light.

The ECU of the industrial personal computer is connected with the ACC system in a communication mode through a fatigue driving detection algorithm, when the eye closing time ratio PERCLOS algorithm detects the eye fatigue state of a driver, and when the value detected by the PERCLOS algorithm is larger than a preset threshold value, the driver is considered to be in fatigue driving. When the PERCLOS value is greater than 40%, i.e., the eye-closure duration is greater than 3 seconds, the driver is deemed to be in a drowsy state. And the ECU decides to control the vehicle to exit from the ADAS advanced assistant driving system mode, triggers a dangerous driving signal at the same time, and sends out an alarm by a buzzer and sends out an alarm LED signal light to turn red by an executive unit.

meanwhile, if a driver and passengers in the vehicle use intelligent terminals such as a smart phone, a smart watch and a smart watch, dangerous driving prompt information is received in time through vehicle-mounted Bluetooth, and the running safety of the vehicle is improved in cooperation. Further, a cloud data storage library is established, fatigue driving detection capability of a driver is updated and compared, and more accurate fatigue driving monitoring computing capability is achieved through continuous self-learning updating.

And synchronously displaying the real-time driving mode of the ADAS system and receiving and displaying real-time online human eye fatigue detection data information by the UI user interface in the vehicle. When the vehicle is continuously driven, for example, the vehicle is continuously driven on a highway for a long distance, the vehicle can perform an ADAS advanced driving assistance system according to the needs of a user, so that the continuous driving fatigue degree of the driver is reduced, at the moment, the automobile can perform lane keeping driving, adaptive cruise and lane line deviation functions on the highway, and the personnel in the automobile can acquire ADAS assisted driving information, such as cruise speed, driving time, speed change and the like, through a UI screen of the vehicle. Meanwhile, a vehicle is fused to enter a fatigue driving detection system, the fatigue driving detection process of a driver is shown in the attached drawing 1, the fatigue detection system acquires a human eye region image through a CCD camera, the acquired human eye region image is preprocessed, namely, an Adaboost algorithm is used for human face detection, the human eye height-width ratio is calculated, the human eye opening and closing state is calculated according to a human eye positioning technology for judgment, the opening and closing frame number of eyes in a detection unit is counted, wherein the percentage PERCLOS of the eye closing time in unit time is defined as:

N is the number of frames of the closed eyes of the driver in the detection time, and N is the total number of frames of the images in the detection time. When the PERCLOS value is greater than a predetermined threshold, it is considered that fatigue may occur. Assuming that the preset threshold value is 0.4, if the calculated PERCLOS >0.4, the driving fatigue is considered to occur; if PERCLOS is less than or equal to 0.4, counting the eye state of continuous 30 frames in the detection unit, if the continuous 30 frames are in the eye opening state, considering that the eyes are in the vague nerve, otherwise, considering that the eyes are in the normal state.

As shown in fig. 2, in order to improve the recognition capability of fatigue detection recognition capability for a single driver, the detection result is transmitted online to enter a cloud database for comparison and update, and the fatigue driving judgment for the same driver is more accurate in the process of performing fatigue driving again; the fatigue driving detection system is in communication connection with the ADAS advanced driving auxiliary system through a vehicle industrial control PC.

Once the system judges that the driver fatigue is established, ECU sends dangerous driving instruction immediately, buzzer response and early warning LED lamp are bright, vehicle UI interface shows the suggestion of driver fatigue information, and further, if the intelligent terminal of driver or other members in the car such as smart mobile phone, intelligent wrist-watch, intelligent bracelet etc. carries out the car networking connection through on-vehicle bluetooth this moment, intelligent terminal also can receive tired driving dangerous information simultaneously, further strengthens driving safety early warning.

Meanwhile, the vehicle timely exits from the ADAS auxiliary driving mode, the buzzer and the early warning LED work until the driver manually controls an accelerator pedal and a brake pedal, the steering wheel is manually mastered, fine adjustment of the steering wheel is carried out according to the road driving condition, the lane line is kept under stable control, and the driving danger of unknown danger which is about to occur when the vehicle continuously runs under the fatigue state or even the completely vague state of the driver is avoided.

According to the method for detecting and controlling the fatigue driving of the automobile based on the ADAS system, a CCD camera is adopted to collect human eye information, so that any extra limb contact influence on a driver under the existing driving condition is avoided; the fatigue driving detection system is communicated and interacted with the existing ADAS system and is executed in an industrial PC ECU, and data connection can be adjusted and updated; displaying fatigue driving monitoring information by using a vehicle UI interface; the passengers in the same vehicle, such as a driver and passengers, can receive and sense fatigue driving feedback information by using an intelligent terminal, such as a smart phone, a smart watch, a smart bracelet and the like; the cloud data center monitors fatigue driving information, makes up for the deficiency of online updating capability of an ECU algorithm, and improves fatigue driving recognition capability due to the existence of cloud data through comparison and detection; the alarm prompting capability in special environments such as noisy environments, tunnels and the like is improved by utilizing the dual visual and auditory early warning functions of the buzzer and the early warning LED lamp.

The method for detecting and controlling the fatigue driving of the automobile based on the ADAS system can monitor and feedback control the mental and physical level of the driver on line, increase the feedback control of the monitoring of the fatigue level of the driver, actively intervene to improve the driving auxiliary driving control level and the driving safety, and is simple to apply, high in reliability and convenient for market popularization.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.