CN116039622A - Intelligent vehicle steering control method and control system - Google Patents
Intelligent vehicle steering control method and control system Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/18—Conjoint control of vehicle sub-units of different type or different function including control of braking systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/229—Attention level, e.g. attentive to driving, reading or sleeping
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/80—Spatial relation or speed relative to objects
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Abstract
The invention discloses an intelligent vehicle steering control system which comprises an intelligent vehicle-mounted single chip microcomputer, a detection radar and an anti-collision device, wherein the intelligent vehicle-mounted single chip microcomputer is internally preset with an intelligent vehicle emergency avoidance steering control system, a model test vehicle emergency avoidance steering database, an intelligent vehicle emergency braking control system, a road condition data acquisition module and a lane keeping auxiliary system. The invention also discloses an intelligent vehicle steering control method, which comprises the following steps: s1, emergency steering avoidance and braking of an intelligent vehicle, S2, continuing normal running and S3 after emergency steering avoidance of the intelligent vehicle, avoiding secondary collision and intelligent auxiliary driving caused by emergency steering avoidance of the intelligent vehicle, and having an auxiliary driving steering function, emergency steering avoidance and braking and secondary collision avoiding function through an emergency steering control system, an emergency braking control system and an automatic driving system.
Description
Technical Field
The invention relates to the technical field of intelligent vehicle steering control, in particular to an intelligent vehicle steering control method and system.
Background
The intelligent vehicle is capable of automatically identifying a route and tracing the route by taking electromagnetic waves, laser waves or cameras as sensors, the speed of the intelligent vehicle is higher and higher, the control requirement on the vehicle is higher and higher, in a control system of the intelligent vehicle, the emergency steering avoidance during emergency is particularly important, however, the existing intelligent vehicle steering control system and the control method thereof are only suitable for normal driving, have no functions of emergency steering avoidance and braking and avoiding secondary collision when the emergency exists during intelligent auxiliary driving, and cannot judge the state of a driver and form driving interference under certain conditions, so that the automatic switching into auxiliary driving is realized without real-time identification of whether the driver has illegal behaviors.
The prior patent (publication number CN 113200086A) discloses an intelligent vehicle steering control system and a control method thereof, wherein the control system comprises an acquisition data module, a deep learning module and a neural network steering model actual measurement module, the acquisition data module is used for acquiring running information of an intelligent vehicle, the acquisition data module comprises image information processing, a data acquisition vehicle, seven paths of electromagnetic intensity data and steering engine steering angles, the deep learning module comprises a data set established by the acquisition data module, the deep learning module further comprises a neural network steering control model, a training model and a testing model, and the neural network steering model actual measurement module comprises a neural network model, seven paths of real-time electromagnetic intensity data, a model testing vehicle, steering angles and steering engines; the control system creates a data set, trains and tests a neural network model on the basis, designs a novel software control algorithm, forms a closed-loop feedback control mode, and greatly improves the running stability of the intelligent vehicle; in the implementation process of the scheme, the intelligent steering control system is only suitable for normal driving, has no functions of emergency steering avoidance and braking and avoiding secondary collision due to emergency when intelligent auxiliary driving exists, cannot judge the state of a driver and can form driving interference under certain conditions, and further has no function of automatically switching to auxiliary driving by identifying whether the driver has illegal behaviors in real time.
For this reason, it is necessary to provide an intelligent vehicle steering control method and control system.
Disclosure of Invention
The invention provides an intelligent vehicle steering control method and a control system, which solve the technical problems that the existing intelligent vehicle steering control system and the control method thereof are only suitable for normal driving, have no functions of emergency steering avoidance and braking and avoiding secondary collision caused by emergency situations in intelligent auxiliary driving, cannot judge the state of a driver and can not form driving interference under certain conditions, and further have no technical problems of automatically switching to an auxiliary driving function by identifying whether the driver has illegal behaviors in real time.
In order to solve the technical problems, the invention provides an intelligent vehicle steering control method, which comprises the following steps:
s1, emergency steering avoidance and braking of an intelligent vehicle emergency: the detection radar monitors and monitors the dynamic and static targets in front of the intelligent vehicle in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; the anti-collision device monitors the speed of the intelligent vehicle and the distance between the front most threatening vehicle or object in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; when collision risk exists after comparison, if a driver does not respond timely, namely, the driver does not operate the intelligent vehicle steering wheel and the intelligent vehicle brake disc timely and reasonably, the intelligent vehicle-mounted single chip microcomputer judges whether measures can be taken to actively intervene and control the vehicle to steer and avoid through comparison data, and the intelligent vehicle emergency avoidance steering control system and the intelligent vehicle emergency braking control system respectively control the intelligent vehicle steering wheel and the intelligent vehicle brake disc to steer and brake.
S2, continuing normal running after emergency steering avoidance of the intelligent vehicle in emergency: when the detection radar and the anti-collision device do not monitor that the threat vehicle or the object exists in front of the intelligent vehicle through the road condition data acquisition module, the intelligent vehicle steering wheel is controlled through a lane keeping auxiliary system preset by the intelligent vehicle-mounted singlechip to ensure that the intelligent vehicle continues to normally run.
S3, avoiding secondary collision caused by emergency steering avoidance of the intelligent vehicle: the road condition data acquisition module monitors whether a threat vehicle or an object exists in front of the intelligent vehicle in real time through the detection radar and the anti-collision device, and based on collision risk of the intelligent vehicle and compared with the emergency avoidance steering database of the model test vehicle, when secondary collision risk exists after the intelligent vehicle emergently steers and avoidance, the steps S1 and S2 are repeated.
The invention also provides an intelligent vehicle steering control system, which comprises an intelligent vehicle-mounted single chip microcomputer, a detection radar and an anti-collision device, wherein the intelligent vehicle-mounted single chip microcomputer is respectively and electrically connected with the intelligent vehicle steering wheel and the intelligent vehicle brake disc, and an intelligent vehicle emergency avoidance steering control system, a model test vehicle emergency avoidance steering database, an intelligent vehicle emergency braking control system, a road condition data acquisition module and a lane keeping auxiliary system are preset in the intelligent vehicle-mounted single chip microcomputer, and the road condition data acquisition module is respectively and electrically connected with the intelligent vehicle-mounted single chip microcomputer, the detection radar and the anti-collision device.
The control system further comprises a voice broadcasting module and an intelligent vehicle automatic driving system which are preset in the intelligent vehicle-mounted single-chip microcomputer, and an intelligent vehicle-mounted sound box, an infrared night vision camera, a video intelligent analyzer and an intelligent vehicle-mounted display screen which are arranged in the intelligent vehicle.
The intelligent vehicle automatic driving system controls an intelligent vehicle steering wheel and an intelligent vehicle engine, controls steering and acceleration and deceleration in the normal running process of the intelligent vehicle, and simultaneously judges the state of a driver through an infrared night vision camera and a video intelligent analyzer and judges whether driving interference can be formed under certain conditions through an intelligent vehicle-mounted singlechip, wherein the judging states of the driver are respectively fatigue driving detection, distraction detection, dangerous driving detection, infrared blocking detection, driver off-duty detection, safety belt detection and camera shielding detection.
The fatigue driving detection is carried out by a face feature detection technology, extracting mouth region features, judging whether a yawning action exists according to the opening and closing degree of a mouth, positioning a human eye region through an eye detection algorithm, calculating the opening and closing degree of eyes in the region, and judging whether an eye closing action exists according to threshold control; the distraction detection is to detect whether the driver has a condition that the sight deviates from the road surface, and by utilizing the principle of human eye imaging, the pupil point of the driver is detected in real time to calculate the sight angle, and the normal driving sight angle value of the driver and the distracted judging range are combined to comprehensively judge whether the driver has distraction driving behaviors.
Dangerous driving detection is that firstly, the human face region detection is divided into ROI regions, and the ROI regions are formed
Performing behavior detection in the region; deep learning training is carried out by utilizing sample data, so that behavior characteristics such as smoking, calling and the like are learned, and detection judgment is carried out according to different behavior characteristics through hand detection and object detection; the infrared blocking detection is based on the technical principle of face detection, combines with the training form of a sunglasses, and gives a warning through a voice broadcasting module and an intelligent vehicle-mounted sound box when the biological characteristics of eyes cannot be detected; the off-duty detection of the driver is to read the real-time image acquired by the camera, and judge whether the image contains the face information or not and whether the face information is complete or not, so that the off-duty state, the on-duty state and the face shielding condition of the driver are determined.
The safety belt detection is based on a computer vision principle, a deep learning technology is used for extracting an image area of a trunk part of a driver, key points of a human body and positions of the safety belt are analyzed, and whether the safety belt is worn normally or not is judged through the relative positions of the safety belt and the body; the camera occlusion detection is based on a deep learning method, video images acquired by the camera are read, analyzed and compared with parameters, and whether the camera is occluded or not is judged.
Compared with the related art, the intelligent vehicle steering control method and system provided by the invention have the following steps of
The beneficial effects are that:
1) The detection radar monitors and monitors the dynamic and static targets in front of the intelligent vehicle in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; the anti-collision device monitors the speed of the intelligent vehicle and the distance between the front most threatening vehicle or object in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; when collision risk exists after comparison, if a driver does not respond timely, namely, the driver does not operate the intelligent vehicle steering wheel and the intelligent vehicle brake disc timely and reasonably, the intelligent vehicle-mounted single chip microcomputer judges whether measures can be taken to actively intervene and control the vehicle to steer and avoid through comparison data, and the intelligent vehicle emergency avoidance steering control system and the intelligent vehicle emergency braking control system respectively control the intelligent vehicle steering wheel and the intelligent vehicle brake disc to steer and brake.
2) When the detection radar and the anti-collision device do not monitor that the threat vehicle or the object exists in front of the intelligent vehicle through the road condition data acquisition module, the intelligent vehicle steering wheel is controlled through a lane keeping auxiliary system preset by the intelligent vehicle-mounted singlechip to ensure that the intelligent vehicle continues to normally run.
3) The road condition data acquisition module monitors whether a threat vehicle or an object exists in front of the intelligent vehicle in real time through the detection radar and the anti-collision device, and based on collision risk of the intelligent vehicle and compared with the emergency avoidance steering database of the model test vehicle, when secondary collision risk exists after the intelligent vehicle emergently steers and avoidance, the steps S1 and S2 are repeated.
4) The intelligent vehicle automatic driving system controls the intelligent vehicle steering wheel and the intelligent vehicle engine, controls steering and acceleration and deceleration in the normal running process of the intelligent vehicle, simultaneously judges the state of a driver through the infrared night vision camera and the video intelligent analyzer and judges whether driving interference can be formed under certain conditions through the intelligent vehicle-mounted single chip microcomputer, judges the state of the driver to be fatigue driving detection, distraction detection, dangerous driving detection, infrared blocking detection, driver off-duty detection, safety belt detection and camera shielding detection respectively, so as to intelligently assist driving, and has the functions of emergency steering avoidance and braking in emergency and avoiding secondary collision in the process.
Drawings
FIG. 1
The method is a flow chart for controlling the steering of the intelligent vehicle, avoiding and braking the emergency steering of the intelligent vehicle and avoiding secondary collision in a control system;
FIG. 2 is a flow chart of a method and system for controlling steering of an intelligent vehicle;
FIG. 3 is a flow chart of a method and system for intelligent vehicle steering control to determine driver status.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and are not to be construed as limiting the present invention.
In the description of the present invention, it should be understood that if there are terms such as "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc., the indicated azimuth or positional relationship is based on the azimuth or positional relationship shown in the drawings, it is merely for convenience of description and simplification of the description, and does not indicate or imply that the indicated apparatus or element must have a specific azimuth, be constructed and operated in a specific azimuth, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the description of the present invention, it should be noted that the terms "mounted," "connected," and "coupled" are to be construed broadly, as well as, for example, fixedly coupled, detachably coupled, or integrally coupled, unless otherwise specifically indicated and defined. Either mechanically or electrically. Can be directly connected or indirectly connected through an intermediate medium, and can be communicated with the inside of two elements or the interaction relationship of the two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
As shown in fig. 1-3, an intelligent vehicle steering control method includes the steps of:
s1, emergency steering avoidance and braking of an intelligent vehicle emergency: the detection radar monitors and monitors the dynamic and static targets in front of the intelligent vehicle in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; the anti-collision device monitors the speed of the intelligent vehicle and the distance between the front most threatening vehicle or object in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; when collision risk exists after comparison, if a driver does not respond timely, namely, the driver does not operate the intelligent vehicle steering wheel and the intelligent vehicle brake disc timely and reasonably, the intelligent vehicle-mounted single chip microcomputer judges whether measures can be taken to actively intervene and control the vehicle to steer and avoid through comparison data, and the intelligent vehicle emergency avoidance steering control system and the intelligent vehicle emergency braking control system respectively control the intelligent vehicle steering wheel and the intelligent vehicle brake disc to steer and brake.
S2, continuing normal running after emergency steering avoidance of the intelligent vehicle in emergency: when the detection radar and the anti-collision device do not monitor that the threat vehicle or the object exists in front of the intelligent vehicle through the road condition data acquisition module, the intelligent vehicle steering wheel is controlled through a lane keeping auxiliary system preset by the intelligent vehicle-mounted singlechip to ensure that the intelligent vehicle continues to normally run.
S3, avoiding secondary collision caused by emergency steering avoidance of the intelligent vehicle: the road condition data acquisition module monitors whether a threat vehicle or an object exists in front of the intelligent vehicle in real time through the detection radar and the anti-collision device, and based on collision risk of the intelligent vehicle and compared with the emergency avoidance steering database of the model test vehicle, when secondary collision risk exists after the intelligent vehicle emergently steers and avoidance, the steps S1 and S2 are repeated.
The method further comprises the following:
fatigue driving detection, extracting mouth region characteristics through a face characteristic detection technology, judging whether yawning behaviors exist according to opening and closing degrees of a mouth, positioning a human eye region through an eye detection algorithm, calculating opening and closing degrees of eyes in the region, judging whether eye closing behaviors exist according to threshold control, performing intelligent analysis on detailed characteristics of faces, eyes, body states and the like of a driver, helping to accurately identify whether fatigue driving exists, and defining fatigue monitoring level alarm strategies by combining dimensions such as vehicle speed, continuous driving duration, driving time period and the like, for example: mild fatigue, moderate fatigue and high fatigue, and is convenient to apply in different use scenes of commercial vehicles; the dimension parameters can be flexibly defined, and include monitoring the opening degree of the mouth, the eye closing time, the eye blinking frequency and the gesture of head movement, wherein the monitoring of the opening degree of the mouth is performed through the difference of the vertical distance between lips and the difference of the opening and closing time of the mouth, for example, the time of yawning the mouth is obviously longer than the time of speaking the mouth, the eye closing time is monitored as usual daily blinking, which is a very short time, namely, people can quickly close eyes and open eyes, but when people doze, the eye closing time can be obviously increased, even the eye closing time can be up to several seconds, the eye closing time can be about to enter a comatose interval, if the infrared camera shooting hair is in the night vision of the driver is increasing, in particular, by calculating the maximum frame number from the eye closing to the opening, the more the number of frames is, the longer the closing time is, the more serious the fatigue degree of the driver is, the eye blink frequency is monitored to be higher when the driver is in a fatigue state than when the driver is in a wake state, the eyes are closed to be blinked once, the blink times in a period of time are accumulated, as one parameter of fatigue judgment, the gesture of head movement is monitored to be that the driver frequently clicks head in a fatigue state, the head tilts forward, the infrared night vision camera is used for collecting the distance between eyes and edges of a photo of the driver and the distance between chin and lower edges of the photo of the driver, when the driver is tired, the distance between eyes and edges of the photo of the driver is increased and the distance between the chin and the lower edges of the photo of the driver is reduced when the driver frequently clicks, and if the data frequently happens in a short period of time, the intelligent vehicle-mounted singlechip judges that the driver is in a fatigue driving state through the video intelligent analyzer, and controls the intelligent vehicle steering wheel and the intelligent vehicle engine through the intelligent vehicle automatic driving system.
The distraction detection is to detect whether the driver has the condition that the sight deviates from the road surface, the human eye imaging principle is utilized, the pupil point of the driver is detected in real time to calculate the sight angle, the normal driving sight angle value of the driver and the distraction judgment range are combined to comprehensively judge whether the driver has distraction driving behaviors, in the driving process, when the driver has the distraction unconscious condition, such as playing a mobile phone, finding things, and chatting, the intelligent vehicle-mounted acoustic alarm prompt is triggered by a voice broadcasting module in the intelligent vehicle-mounted singlechip, the intelligent vehicle-mounted acoustic alarm prompt is calibrated automatically, the basic parameters are continuously adjusted to achieve the relatively consistent distraction judgment results under different drivers and different driving postures through the real-time statistics of the posture of the driver, the alarm strategy can be combined with the dimensions of the speed, the continuous driving duration, the driving time period and the like, and the distraction monitoring grade alarm strategy is defined, such as: slight distraction, moderate distraction and high distraction are convenient to apply in different commercial vehicle use scenes, and each dimension parameter can be flexibly defined; the dangerous driving detection is that firstly, the human face region detection is divided into ROI regions, and the behavior detection is carried out in the ROI regions; deep learning training is carried out by utilizing sample data, so that behavior characteristics such as smoking, calling and the like are learned, detection judgment is carried out according to different behavior characteristics through hand detection and object detection, and when dangerous behavior conditions such as smoking, calling and the like occur to a driver in the driving process, intelligent vehicle-mounted audible alarm prompt is triggered; the infrared blocking detection is based on the technical principle of face detection, and combines with the training form of a sunglasses, when the biological characteristics of eyes cannot be detected, warning is given through a voice broadcasting module and an intelligent vehicle-mounted sound box, namely, when a driver wears the sunglasses with the infrared blocking function in the driving process, the intelligent monitoring functions of the face such as fatigue driving are affected, and warning is given according to a service strategy; the off-duty detection of the driver is to read a real-time image acquired by the camera, judge whether the image contains face information or not and whether the face information is complete or not, thereby determining the off-duty and on-duty states and the face shielding condition of the driver, namely detecting the off-duty state or the face shielding condition of the driver based on the face recognition technology; the safety belt detection is based on a computer vision principle, a deep learning technology is used for extracting an image area of a trunk part of a driver, human body key points and the positions of the safety belt are analyzed, whether the safety belt is worn normally or not is judged through the relative positions of the safety belt and a body, namely whether the driver ties the safety belt or not is accurately identified by combining technologies such as human body key point identification, object identification and the like, and when the situation that the driver does not tie the safety belt is detected in the driving process, a warning is given; the camera shielding detection is based on a deep learning method, video images acquired by a camera are read, analyzed and compared with parameters, whether the camera is shielded or not is judged, namely, real-time detection is carried out on a camera picture, and when abnormal situations of a lens such as video shielding and a black screen in a certain range occur, camera shielding early warning is triggered.
Dangerous driving detection, firstly, performing ROI region division on face region detection, and then performing ROI detection
Performing behavior detection in the region; deep learning training is carried out by utilizing sample data, so that behavior characteristics such as smoking, calling and the like are learned, and detection judgment is carried out according to different behavior characteristics through hand detection and object detection; the infrared blocking detection is based on the technical principle of face detection, combines with the training form of a sunglasses, and gives a warning through a voice broadcasting module and an intelligent vehicle-mounted sound box when the biological characteristics of eyes cannot be detected; the off-duty detection of the driver is to read the real-time image acquired by the camera, and judge whether the image contains the face information or not and whether the face information is complete or not, so that the off-duty state, the on-duty state and the face shielding condition of the driver are determined.
Safety belt detection, namely extracting an image area of a trunk part of a driver by using a deep learning technology based on a computer vision principle, analyzing key points of a human body and positions of the safety belt, and judging whether the safety belt is worn normally or not according to the relative positions of the safety belt and the body; the camera occlusion detection is based on a deep learning method, video images acquired by the camera are read, analyzed and compared with parameters, and whether the camera is occluded or not is judged.
As shown in fig. 1, the intelligent vehicle steering control system comprises a voice broadcasting module and an intelligent vehicle automatic driving system which are preset in an intelligent vehicle-mounted single chip microcomputer, and an intelligent vehicle-mounted sound box, an infrared night vision camera, a video intelligent analyzer and an intelligent vehicle-mounted display screen which are arranged in the intelligent vehicle, wherein the intelligent vehicle automatic driving system controls an intelligent vehicle steering wheel and an intelligent vehicle engine and controls steering and acceleration and deceleration in the normal running process of the intelligent vehicle.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (4)
1. An intelligent vehicle steering control method is characterized by comprising the following steps:
s1, emergency steering avoidance and braking of an intelligent vehicle emergency: the detection radar monitors and monitors the dynamic and static targets in front of the intelligent vehicle in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; the anti-collision device monitors the speed of the intelligent vehicle and the distance between the front most threatening vehicle or object in real time, transmits measurement data to the road condition data acquisition module in real time, and compares the measurement data with a preset emergency avoidance steering database of the model test vehicle through the intelligent vehicle-mounted singlechip; when collision risk exists after comparison, if a driver does not respond timely, namely, the driver does not operate the intelligent vehicle steering wheel and the intelligent vehicle brake disc timely and reasonably, the intelligent vehicle-mounted single chip microcomputer judges whether measures can be taken to actively intervene and control the vehicle to steer and avoid through comparison data, and the intelligent vehicle emergency avoidance steering control system and the intelligent vehicle emergency braking control system respectively control the intelligent vehicle steering wheel and the intelligent vehicle brake disc to steer and brake.
S2, continuing normal running after emergency steering avoidance of the intelligent vehicle in emergency: when the detection radar and the anti-collision device do not monitor that the threat vehicle or the object exists in front of the intelligent vehicle through the road condition data acquisition module, the intelligent vehicle steering wheel is controlled through a lane keeping auxiliary system preset by the intelligent vehicle-mounted singlechip to ensure that the intelligent vehicle continues to normally run.
S3, avoiding secondary collision caused by emergency steering avoidance of the intelligent vehicle: the road condition data acquisition module monitors whether a threat vehicle or an object exists in front of the intelligent vehicle in real time through the detection radar and the anti-collision device, and based on collision risk of the intelligent vehicle and compared with the emergency avoidance steering database of the model test vehicle, when secondary collision risk exists after the intelligent vehicle emergently steers and avoidance, the steps S1 and S2 are repeated.
2. The control system for realizing the intelligent vehicle steering control method according to claim 1 is characterized by comprising an intelligent vehicle-mounted single chip microcomputer, a detection radar and an anti-collision device, wherein an intelligent vehicle emergency avoidance steering control system, a model test vehicle emergency avoidance steering database, an intelligent vehicle emergency braking control system, a road condition data acquisition module and a lane keeping auxiliary system are preset in the intelligent vehicle-mounted single chip microcomputer.
3. The intelligent vehicle steering control system of claim 2, further comprising a voice broadcast module and an intelligent vehicle autopilot system preset in the intelligent vehicle-mounted single-chip microcomputer.
4. The intelligent vehicle steering control system of claim 3, further comprising an intelligent vehicle audio, an infrared night vision camera, a video intelligent analyzer, and an intelligent vehicle display screen mounted in the intelligent vehicle, wherein the intelligent vehicle autopilot system controls the intelligent vehicle steering wheel and the intelligent vehicle engine and controls steering and acceleration and deceleration during normal travel of the intelligent vehicle.
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