CN110789534A - Lane departure early warning method and system based on road condition detection - Google Patents

Lane departure early warning method and system based on road condition detection Download PDF

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Publication number
CN110789534A
CN110789534A CN201911079517.3A CN201911079517A CN110789534A CN 110789534 A CN110789534 A CN 110789534A CN 201911079517 A CN201911079517 A CN 201911079517A CN 110789534 A CN110789534 A CN 110789534A
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vehicle
lane
road
unmanned aerial
point
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常绿
颜瑨
朱思达
刘硕
胡晓明
张载梅
刘永臣
戴建国
夏晶晶
徐礼超
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Huaiyin Institute of Technology
Huaian Vocational College of Information Technology
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Huaiyin Institute of Technology
Huaian Vocational College of Information Technology
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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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/08—Interaction between the driver and the control system
    • B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
    • 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
    • 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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/10—Path keeping
    • B60W30/12—Lane keeping
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography

Abstract

The invention discloses a lane departure early warning method and system based on road condition detection, which are characterized in that information of a road in front of a vehicle is collected through an image processing technology, the road condition is identified, whether barriers or damaged parts exist at the edge of the lane of the road in front or not is judged, a lane edge line and a lane auxiliary line are fitted, lane departure time is calculated by combining vehicle speed information and vehicle relative yaw angle information, and the lane departure time is compared with an early warning time threshold value to judge and make specific dangerous case early warning. The method can improve the calculation precision of lane departure time and guarantee traffic safety under the condition that obstacles or damages exist at the edge of the lane.

Description

Lane departure early warning method and system based on road condition detection
Technical Field
The invention belongs to the technical field of road traffic safety, and particularly relates to a lane departure early warning method and system based on road condition detection.
Background
The lane departure time refers to the remaining time of the vehicle from the current position to the lane boundary line, and is a judgment basis for lane departure early warning, so that the accurate calculation of the lane departure time is important. The existing lane departure early warning method generally aims at the calculation of lane departure time on a normal road, and does not consider whether obstacles or damaged parts exist at the edge of a road section in front of the road. For example, the invention with application number 201811161132.7 discloses a method and a device for early warning of vehicle deviation, which includes performing gray processing on a road image to be detected to obtain a corresponding gray image, determining a target lane line in the gray image, and determining whether to send a vehicle deviation early warning signal according to the target lane line and an early warning trigger condition. The method does not consider the condition that the obstacle or the damaged part exists at the edge of the front road section, and the obtained lane departure time has errors and potential safety hazards.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects of the prior art, the invention provides a lane departure early warning method based on road condition detection, and the lane departure early warning method can improve the calculation precision of lane departure time and guarantee traffic safety under the condition that obstacles or damages exist at the edge of a lane.
It is another object of the present invention to provide a system for carrying out the above method.
The technical scheme is as follows: the invention relates to a lane departure early warning method based on road condition detection, which comprises the following steps:
(1) releasing and controlling the vehicle-mounted unmanned aerial vehicle to fly according to the planned driving route of the vehicle, shooting the vehicle traveling road section through the vehicle-mounted unmanned aerial vehicle, and collecting road information in front of the vehicle;
(2) identifying whether the front road is a straight road or a curve, the position information of the vehicle in the lane and whether the edge of the lane has an obstacle or a damaged part according to the information of the front road of the vehicle, and fitting out a lane edge line;
(3) if the lane edge has the obstacle or the damaged part, calculating the geometric dimension of the obstacle or the damaged part, and fitting the lane edge line to the missing part according to the fitted lane edge line;
(4) calculating the maximum width of the obstacle or damaged part inwards along the lane edge line according to the geometric dimension of the obstacle or damaged part at the lane edge, finding out a maximum width point, and fitting a lane auxiliary line according to the maximum width point and the fitted lane edge line, wherein the distance between the lane auxiliary line and the lane edge line is the maximum width, and the lane auxiliary line is arranged on the inner side of the lane edge line;
(5) acquiring vehicle speed information, vehicle acceleration information and vehicle relative yaw angle information;
(6) and calculating the vehicle departure time according to the lane auxiliary line, comparing the vehicle departure time with an early warning time threshold value, judging whether lane departure occurs or not, and giving a specific dangerous case early warning.
Specifically, when the vehicle deviation time is calculated and the current road is a straight road, the method for calculating the vehicle deviation time includes:
Figure BDA0002263442260000021
Figure BDA0002263442260000022
in the formula, SsThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; y isrIs the lateral distance of the front wheel position point on the yaw side of the vehicle from the lane auxiliary line, theta is the relative yaw angle of the vehicle, TSThe vehicle deviation time is a straight road section, and v is a vehicle speed.
When the road in front is a curve and the vehicle is deflected to the inner side of the curve, the point O is the circle center of the curve section, A is the position point of the front wheel on the yaw side of the vehicle, B is the intersection point of AO and the lane auxiliary line, C is the intersection point of the lane auxiliary line crossed by the vehicle along the yaw direction, and E is the foot hanging from the circle center O of the curve section to the line segment AC:
LAE＝(R+yr)sinθ
Figure BDA0002263442260000023
Sbr＝LAE-LCE
Figure BDA0002263442260000024
in the formula, LAEIs the distance from point A to point E; l isCEThe distance from the point C to the point E is shown; r is a lane auxiliary radius which is fitted according to a lane auxiliary line, namely BO; sbrThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; y isrIs the lateral distance of the front wheel position point on the yaw side of the vehicle from the lane auxiliary line, theta is the relative yaw angle of the vehicle, TbrThe vehicle departure time is a curve section, and v is a vehicle speed.
When the road in front is a curve and the vehicle is deflected to the outer side of the curve, recording the mark O as the circle center of the curve section, A as the position point of the front wheel at the yaw side of the vehicle, B as the intersection point of AO and the edge line of the inner side lane, C as the intersection point of the vehicle crossing the lane auxiliary line along the yaw direction, and E as the foot hanging from the circle center O of the curve section to the line segment AC:
LAE＝(R0+yl)sinθ
Figure BDA0002263442260000031
Sbl＝LAE+LCE
Figure BDA0002263442260000032
in the formula, LAEIs the distance from point A to point E; l isCEThe distance from the point C to the point E is shown; r0Length of BO, i.e. lane radius; y islIs the length of AB, i.e., the lateral distance of the front wheel position point on the yaw side of the vehicle from the inner lane minor edge line, SblThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; t isblThe vehicle departure time for a curve section, W the width of the lane, and v the vehicle speed.
The early warning time threshold value K is determined according to the lane parameters and the vehicle speed, when the vehicle deviation time T is larger than K, no dangerous case is judged, and otherwise, the dangerous case occurs.
Corresponding to the lane departure early warning method based on road condition detection, the technical scheme adopted by the system for implementing the method is that the system comprises a vehicle-mounted unmanned aerial vehicle and a vehicle-mounted processing system, wherein the vehicle-mounted unmanned aerial vehicle is provided with an unmanned aerial vehicle control system, the unmanned aerial vehicle control system receives a command of the vehicle-mounted processing system, controls the vehicle-mounted unmanned aerial vehicle to fly according to a planned driving route of the vehicle, shoots a vehicle traveling road section to acquire road information in front of the vehicle, and transmits data to the vehicle-mounted processing system; the vehicle-mounted processing system sends commands to the unmanned aerial vehicle control system to control the unmanned aerial vehicle to release and recover, receives data of the unmanned aerial vehicle control system, processes the road section pictures, fits the lane auxiliary line of the road section, calculates vehicle departure time according to the lane auxiliary line, compares the vehicle departure time with an early warning time threshold value, judges whether lane departure occurs or not, and gives specific dangerous case early warning.
The vehicle-mounted processing system comprises an image processing module, a vehicle-mounted central control module, a vehicle-mounted attitude sensor and a vehicle-mounted information processing module; the image processing module processes the road section picture to obtain the position parameter of the vehicle on the road section and the geometrical size of the obstacle or damaged part, and transmits data to the vehicle-mounted central control module; the vehicle-mounted central control module sends a command to the unmanned aerial vehicle control system, controls the vehicle-mounted unmanned aerial vehicle to release and recover, receives data transmitted by the unmanned aerial vehicle control system, the image processing module and the vehicle-mounted attitude sensor, and transmits the received data to the vehicle-mounted information processing module; and the vehicle-mounted information processing module fits a lane auxiliary line according to the received data, calculates the vehicle departure time, compares the vehicle departure time with the early warning time threshold value and judges whether lane departure occurs or not.
Further, the vehicle-mounted processing system further comprises a vehicle-mounted early warning module, and the vehicle-mounted early warning module receives the information transmitted by the vehicle-mounted information processing module and gives specific dangerous case early warning according to the information.
Further, unmanned aerial vehicle control system still includes atmospheric pressure sensing module, atmospheric pressure sensing module sets up in on-vehicle unmanned aerial vehicle's the fuselage, atmospheric pressure sensing module is according to the height that preset atmospheric pressure parameter and atmospheric pressure change adjustment unmanned aerial vehicle fly.
Has the advantages that: the lane departure early warning method and system based on road condition detection collect information of a road in front of a vehicle through an image processing technology, recognize road conditions, judge whether the edge of the lane of the road in front has an obstacle or a damaged part, fit a lane edge line and a lane auxiliary line, calculate lane departure time by combining vehicle speed information and vehicle relative yaw angle information, compare the lane departure time with an early warning time threshold value, judge and make specific dangerous case early warning. The method can improve the calculation precision of lane departure time and guarantee traffic safety under the condition that obstacles or damages exist at the edge of the lane.
Drawings
FIG. 1 is a flow chart of a lane departure warning method based on road condition detection according to the present invention;
FIG. 2 is a schematic view of a vehicle deviation on a straight road section in accordance with the present invention;
FIG. 3 is a schematic view of a vehicle deviating to the inside of a curve on a curved road section according to the present invention;
FIG. 4 is a schematic view of a vehicle deviating to the outside of a curve on a curved road section according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, a system implementing the method includes a vehicle-mounted unmanned aerial vehicle and a vehicle-mounted processing system, and the vehicle-mounted unmanned aerial vehicle is provided with an unmanned aerial vehicle control system. The unmanned aerial vehicle control system receives the vehicle-mounted processing system command, controls the vehicle-mounted unmanned aerial vehicle to fly according to the planned driving route of the vehicle, shoots the vehicle traveling road section to acquire the road information in front of the vehicle, and transmits the data to the vehicle-mounted processing system. The vehicle-mounted processing system sends commands to the unmanned aerial vehicle control system to control the unmanned aerial vehicle to release and recover, receives data of the unmanned aerial vehicle control system, processes pictures of road sections in front of the vehicle, fits lane auxiliary lines of the road sections, calculates vehicle departure time according to the lane auxiliary lines, compares the vehicle departure time with an early warning time threshold value, judges whether lane departure occurs or not, and gives specific dangerous case early warning.
Specifically, the vehicle-mounted processing system comprises an image processing module, a vehicle-mounted central control module, a vehicle-mounted attitude sensor, a vehicle-mounted information processing module and a vehicle-mounted early warning module. The image processing module processes the road section picture to obtain the position parameter of the vehicle on the road section and the geometrical size of the obstacle or the damaged part, and transmits the data to the vehicle-mounted central control module. The vehicle-mounted central control module sends a command to the unmanned aerial vehicle control system, controls the vehicle-mounted unmanned aerial vehicle to release and recover, receives data transmitted by the unmanned aerial vehicle control system, the image processing module and the vehicle-mounted attitude sensor, and transmits the received data to the vehicle-mounted information processing module. And the vehicle-mounted information processing module fits a lane auxiliary line according to the received data, calculates the vehicle departure time, compares the vehicle departure time with the early warning time threshold value and judges whether lane departure occurs or not. And the vehicle-mounted early warning module receives the information transmitted by the vehicle-mounted information processing module and gives specific dangerous case early warning according to the information.
Further, unmanned aerial vehicle control system still includes atmospheric pressure sensing module, atmospheric pressure sensing module sets up in on-vehicle unmanned aerial vehicle's the fuselage, atmospheric pressure sensing module is according to the height that preset atmospheric pressure parameter and atmospheric pressure change adjustment unmanned aerial vehicle fly.
As shown in connection with fig. 2-4, the method comprises the steps of:
(1) releasing and controlling the vehicle-mounted unmanned aerial vehicle to fly according to the planned driving route of the vehicle, shooting the vehicle traveling road section through the vehicle-mounted unmanned aerial vehicle, and collecting road information in front of the vehicle;
(2) identifying whether the front road is a straight road or a curve, the position information of the vehicle in the lane and whether the edge of the lane has an obstacle or a damaged part according to the information of the front road of the vehicle 10, and fitting out a lane edge line;
(3) if the obstacle 3 or the damaged part 3 exists at the edge of the lane, calculating the geometric dimension of the obstacle 3 or the damaged part 3, and fitting a lane edge line 1 to the missing part according to the fitted lane edge line;
(4) according to the geometric dimension of the obstacle or the damaged part at the edge of the lane, calculating the maximum width of the obstacle or the damaged part inwards along the edge line 1 of the lane, finding out a maximum width point P, and fitting a lane auxiliary line 2 according to the maximum width point and the fitted edge line of the lane, wherein the distance between the lane auxiliary line 2 and the edge line 1 of the lane is the maximum width, and the lane auxiliary line 2 is arranged on the inner side of the edge line 1 of the lane; if the lane edge has no obstacle or is damaged, the lane auxiliary line is the lane edge line.
(5) Acquiring vehicle speed information, vehicle acceleration information and vehicle relative yaw angle information;
(6) and calculating the vehicle departure time according to the lane auxiliary line, comparing the vehicle departure time with an early warning time threshold value, judging whether lane departure occurs or not, and giving a specific dangerous case early warning.
Specifically, when calculating the vehicle deviation time, as shown in fig. 2, when the front road is a straight road, the method of calculating the vehicle deviation time includes:
Figure BDA0002263442260000051
Figure BDA0002263442260000052
in the formula, SsThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; y isrIs the lateral distance of the front wheel position point on the yaw side of the vehicle from the lane auxiliary line, theta is the relative yaw angle of the vehicle, TSThe vehicle deviation time is a straight road section, and v is a vehicle speed.
When the road ahead is a curve, as shown in fig. 3, when the vehicle is deflected to the inside of the curve, point O is the center of the curve section, point a is the position point of the front wheel on the yaw side of the vehicle, point B is the intersection point of AO and the lane auxiliary line, point C is the intersection point of the vehicle crossing the lane auxiliary line in the yaw direction, and point E is the foot hanging from the center O of the curve section to the line segment AC:
LAE＝(R+yr)sinθ
Figure BDA0002263442260000061
Sbr＝LAE-LCE
Figure BDA0002263442260000062
in the formula, LAEIs the distance from point A to point E; l isCEThe distance from the point C to the point E is shown; r is a lane auxiliary radius which is fitted according to a lane auxiliary line, namely BO, the BO is the sum of the maximum width (denoted as p) of an obstacle or a damaged part inwards along a lane edge line 1 and the lane radius, namely R is p + R0，R0Is the radius of the lane; sbrFor vehicle offset distance, i.e. extending in the yaw direction of the vehicle when the vehicle is yawingDistance at the intersection with the lane assist line; y isrIs the lateral distance of the front wheel position point on the yaw side of the vehicle from the lane auxiliary line, theta is the relative yaw angle of the vehicle, TbrThe vehicle departure time is a curve section, and v is a vehicle speed.
As shown in fig. 4, when the vehicle is steered to the outside of the curve, point O is the center of the curve section, point a is the position point of the front wheel on the yaw side of the vehicle, point B is the intersection point of AO and the edge line of the inner lane, point C is the intersection point of the lane crossing auxiliary line of the vehicle along the yaw direction, and point E is the foot hanging from the center O of the curve section to the line segment AC:
LAE＝(R0+yl)sinθ
Figure BDA0002263442260000063
Sbl＝LAE+LCE
in the formula, LAEIs the distance from point A to point E; l isCEThe distance from the point C to the point E is shown; r0Length of BO, i.e. lane radius; y islIs the length of AB, i.e., the lateral distance of the front wheel position point on the yaw side of the vehicle from the inner lane minor edge line, SblThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; t isblThe vehicle departure time for a curve section, W the width of the lane, and v the vehicle speed.
The early warning time threshold value K is determined according to the lane parameters and the vehicle speed, when the vehicle deviation time T is larger than K, no dangerous case is judged, otherwise, the dangerous case occurs, and an alarm is given out.

Claims (9)

1. A lane departure early warning method based on road condition detection is characterized by comprising the following steps:
(1) releasing and controlling the vehicle-mounted unmanned aerial vehicle to fly according to the planned driving route of the vehicle, shooting the vehicle traveling road section through the vehicle-mounted unmanned aerial vehicle, and collecting road information in front of the vehicle;
(2) identifying whether the front road is a straight road or a curve, the position information of the vehicle in the lane and whether the edge of the lane has an obstacle or a damaged part according to the information of the front road of the vehicle, and fitting out a lane edge line;
(3) if the lane edge has the obstacle or the damaged part, calculating the geometric dimension of the obstacle or the damaged part, and fitting the lane edge line to the missing part according to the fitted lane edge line;
(4) calculating the maximum width of the obstacle or damaged part inwards along the lane edge line according to the geometric dimension of the obstacle or damaged part at the lane edge, finding out a maximum width point, and fitting a lane auxiliary line according to the maximum width point and the fitted lane edge line, wherein the distance between the lane auxiliary line and the lane edge line is the maximum width, and the lane auxiliary line is arranged on the inner side of the lane edge line;
(5) acquiring vehicle speed information, vehicle acceleration information and vehicle relative yaw angle information;
(6) and calculating the vehicle departure time according to the lane auxiliary line, comparing the vehicle departure time with an early warning time threshold value, judging whether lane departure occurs or not, and giving a specific dangerous case early warning.
2. The lane departure warning method based on road condition detection as claimed in claim 1, wherein when the front road is a straight road, the method for calculating the time of the vehicle departure comprises:
Figure FDA0002263442250000011
Figure FDA0002263442250000012
in the formula, SsThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; y isrFor the front wheel position point on the yaw side of the vehicle to be away from the laneThe lateral distance of the auxiliary line, theta, the relative yaw angle of the vehicle, TSThe vehicle deviation time is a straight road section, and v is a vehicle speed.
3. The method of claim 1, wherein when the road at the front side is a curve and the vehicle is steered toward the inside of the curve, the heading O is the center of the curve section, a is the position of the front wheel at the yaw side of the vehicle, B is the intersection of AO and the lane guide line, C is the intersection of the lane guide line crossed by the vehicle in the yaw direction, and E is the foot hanging from the center O of the curve section to the line segment AC:
LAE＝(R+yr)sinθ
Figure FDA0002263442250000013
Sbr＝LAE-LCE
Figure FDA0002263442250000021
in the formula, LAEIs the distance from point A to point E; l isCEThe distance from the point C to the point E is shown; r is a lane auxiliary radius which is fitted according to a lane auxiliary line, namely BO; sbrThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; y isrIs the lateral distance of the front wheel position point on the yaw side of the vehicle from the lane auxiliary line, theta is the relative yaw angle of the vehicle, TbrThe vehicle departure time is a curve section, and v is a vehicle speed.
4. The method as claimed in claim 1, wherein when the road is a curved road, and the vehicle is steered to the outside of the curved road, the heading O is the center of the curved road, a is the position of the front wheel on the yaw side of the vehicle, B is the intersection of AO and the edge line of the inner lane, C is the intersection of the vehicle crossing the lane auxiliary line in the yaw direction, and E is the foot hanging from the center O of the curved road to the line segment AC:
LAE＝(R0+yl)sinθ
Figure FDA0002263442250000022
Sbl＝LAE+LCE
Figure FDA0002263442250000023
in the formula, LAEIs the distance from point A to point E; l isCEThe distance from the point C to the point E is shown; r0Length of BO, i.e. lane radius; y islIs the length of AB, i.e., the lateral distance of the front wheel position point on the yaw side of the vehicle from the inner lane minor edge line, SblThe vehicle deviation distance is the distance extending to the intersection point of the lane auxiliary line along the vehicle yaw direction when the vehicle yaws; t isblThe vehicle departure time for a curve section, W the width of the lane, and v the vehicle speed.
5. The lane departure warning method according to claim 1, wherein the warning time threshold K is determined according to the lane parameters and the vehicle speed, and when the vehicle departure time T > K, no dangerous situation is determined, otherwise, a dangerous situation occurs.
6. A system for implementing the lane departure early warning method based on road condition detection according to any one of claims 1-5, comprising a vehicle-mounted unmanned aerial vehicle and a vehicle-mounted processing system, wherein the vehicle-mounted unmanned aerial vehicle is provided with an unmanned aerial vehicle control system, the unmanned aerial vehicle control system receives the command of the vehicle-mounted processing system, controls the vehicle-mounted unmanned aerial vehicle to fly according to the planned driving route of the vehicle, shoots the vehicle traveling road section to acquire road information in front of the vehicle, and transmits the data to the vehicle-mounted processing system; the vehicle-mounted processing system sends commands to the unmanned aerial vehicle control system to control the unmanned aerial vehicle to release and recover, receives data of the unmanned aerial vehicle control system, processes the road section pictures, fits the lane auxiliary line of the road section, calculates vehicle departure time according to the lane auxiliary line, compares the vehicle departure time with an early warning time threshold value, judges whether lane departure occurs or not, and gives specific dangerous case early warning.
7. The system of claim 6, wherein the on-board processing system comprises an image processing module, an on-board central control module, an on-board attitude sensor, and an on-board information processing module; the image processing module processes the road section picture to obtain the position parameter of the vehicle on the road section and the geometrical size of the obstacle or damaged part, and transmits data to the vehicle-mounted central control module; the vehicle-mounted central control module sends a command to the unmanned aerial vehicle control system, controls the vehicle-mounted unmanned aerial vehicle to release and recover, receives data transmitted by the unmanned aerial vehicle control system, the image processing module and the vehicle-mounted attitude sensor, and transmits the received data to the vehicle-mounted information processing module; and the vehicle-mounted information processing module fits a lane auxiliary line according to the received data, calculates the vehicle departure time, compares the vehicle departure time with the early warning time threshold value and judges whether lane departure occurs or not.
8. The system of claim 7, wherein the vehicle-mounted processing system further comprises a vehicle-mounted early warning module, and the vehicle-mounted early warning module receives the information transmitted by the vehicle-mounted information processing module and gives out specific early warning of dangerous case according to the information.
9. The system of claim 6, wherein the unmanned aerial vehicle control system further comprises an air pressure sensing module, the air pressure sensing module is arranged in the body of the vehicle-mounted unmanned aerial vehicle, and the air pressure sensing module adjusts the flying height of the unmanned aerial vehicle according to preset air pressure parameters and air pressure changes.
CN201911079517.3A 2019-11-07 2019-11-07 Lane departure early warning method and system based on road condition detection Pending CN110789534A (en)

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Application publication date: 20200214