CN117818608B - Lane merging identification method, system and automobile - Google Patents
Lane merging identification method, system and automobileInfo
- Publication number
- CN117818608B CN117818608B CN202211213177.0A CN202211213177A CN117818608B CN 117818608 B CN117818608 B CN 117818608B CN 202211213177 A CN202211213177 A CN 202211213177A CN 117818608 B CN117818608 B CN 117818608B
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- lane
- vehicle
- merging
- width
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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
- B60W30/18—Propelling the vehicle
- B60W30/18009—Propelling the vehicle related to particular drive situations
- B60W30/18163—Lane change; Overtaking manoeuvres
-
- 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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
-
- 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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Traffic Control Systems (AREA)
- Image Processing (AREA)
Abstract
本发明公开一种车道并道识别方法、系统及汽车，所述方法包括如下步骤：S1、基于t时刻及t+1时刻单目相机采集到的前方车道图像，确定t+1时刻本车所在车道在行驶前方的车道宽度；S2、将行驶前方的车道宽度用于车道并道检测，并发出提醒。实现了基于单目相机的车道并道预判，使得车辆能够跟随并道线引导汇入主车道，提高车辆驾驶的安全性。
This invention discloses a lane merging recognition method, system, and vehicle. The method includes the following steps: S1, determining the lane width ahead at time t+1 based on the images of the lane ahead captured by a monocular camera at time t and time t+1; S2, using the lane width ahead for lane merging detection and issuing a warning. This achieves lane merging prediction based on a monocular camera, enabling vehicles to follow the merging lane guide and merge into the main lane, improving driving safety.
Description
Technical Field
The invention belongs to the technical field of vehicle auxiliary driving, and particularly relates to a lane merging identification method, a lane merging identification system and an automobile.
Background
The existing vehicle recognizes the lane line through the monocular camera, the recognized lane line has certain random error and steady-state error, under the condition of no high-precision navigation positioning, whether the front side has the lane merging cannot be accurately judged only through the lane line curve equation, and under the condition of no accurate recognition and lane merging in advance, certain uncertainty and potential safety hazard can be added to auxiliary driving. For example, the function suddenly exits when merging, controls the vehicle to leave the own lane, collides with the guard rail, collides with the vehicle on the adjacent lane, and the like.
Disclosure of Invention
The invention provides a lane merging recognition method, which aims to improve the merging recognition precision of a monocular camera.
The invention is realized in such a way, a lane merging recognition method, the method specifically comprises the following steps:
S1, determining the width of a lane in front of a vehicle on which the vehicle is positioned on the basis of front lane images p t acquired by a monocular camera at the time t and the time t+1;
s2, using the width of the lane in front of driving for lane merging detection and sending out reminding.
Further, the method for determining the width of the lane in front of the driving of the vehicle comprises the following steps:
S11, dividing a lane where the vehicle is located in a front image p t into n lane segments along the running direction of the vehicle;
S12, calculating the average value W t [ n ] of the lane widths of all the n lane segments, and predicting the average value of the lane widths of all the lane segments at the time t+1
S13, fitting lane line curves of lane lines on two sides of the vehicle, and calculating the lane width z t+1 [ n ] of each lane segment in n lane segments at the time t+1;
s14, predicting average value of lane width And fusing the lane width values z t+1 [ n ] to form the lane width W t+1 [ n ] of each lane segment in the n lane segments at the time of t+1.
Further, the calculation formula of the lane width W t+1 [ n ] of each lane segment at the time t+1 is specifically as follows:
Wherein, K n is the confidence, And R < n > is the measurement error, which is the variance of the lane widths of n lane segments at time t+1.
Further, the average value of the lane width at time t+1The calculation formula is specifically as follows:
further, the variance of the lane widths of the n lane segments at time t+1 The calculation formula is specifically as follows:
Wherein, Q is the process noise variance, and the process noise variance Q takes the value and the vehicle speed v ego and the yaw rate psi ego at the moment t are related.
Further, the lane merging detection specifically includes the following steps:
S21, detecting whether the vehicle moves straight or not, wherein the included angle between the vehicle and the lane where the vehicle is positioned is smaller than an angle threshold value, and if the detected result is yes, executing a step S22;
S22, acquiring a target vehicle in front of a lane where the target vehicle is located from a front image acquired by a monocular camera at the time t+1, detecting whether the target vehicle is located within a set distance in front of the vehicle, and if the detection result is negative, executing a step S24;
s24, detecting whether the preceding vehicle and the lane where the preceding vehicle is located meet the following conditions, and if the detection result is yes, sending out a lane merging prompt;
241 The confidence coefficient of the left and right lane lines of the lane where the own vehicle is located is larger than the confidence coefficient threshold value,
242 The curvature of a short lane line in lane lines on two sides of a lane where the vehicle is located is small, and the curvature of a long lane line is large;
243 The two lane lines are crossed;
244 The lane width of the lane section of the lane where the own vehicle is located is in a decreasing trend.
Further, if the target vehicle is positioned in the set distance in front of the vehicle, detecting whether the front vehicle and the lane where the front vehicle is positioned meet the following conditions, and if the detection result is yes, sending a lane merging prompt;
231 A front car is changing lanes;
232 The confidence coefficient of the left lane line and the right lane line of the lane where the vehicle is located is larger than a confidence coefficient threshold value;
233 The curvature of a short lane line in lane lines at two sides of a lane where the vehicle is located is small, and the curvature of a long lane line is large.
Further, the lane width of the lane where the own vehicle is located is identified while the lane widths of the lanes on the left side and the right side of the lane where the own vehicle is located are identified, and when the lane changing operation of the own vehicle is detected, the lane width of the lane where the own vehicle is located is updated to the lane width of the lane where the own vehicle is located after the lane changing operation.
The present invention is embodied in a lane merging recognition system, the system comprising:
the monocular camera collects the front image of the vehicle and sends the front image to the processor;
the processor performs lane merging detection based on the lane merging recognition method.
The invention is realized in that a vehicle is provided with the lane merging recognition system integrated on the vehicle.
The lane merging pre-judging method based on the monocular camera achieves lane merging pre-judging based on the monocular camera, enables vehicles to be led to enter a main lane along with the merging line, and improves safety of vehicle driving.
Drawings
Fig. 1 is a flow chart of a lane merging recognition method according to an embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the invention, given by way of example only, is presented in the accompanying drawings to aid in a more complete, accurate, and thorough understanding of the inventive concepts and aspects of the invention by those skilled in the art.
Fig. 1 is a flow chart of a lane merging identification method according to an embodiment of the present invention, where the method specifically includes the following steps:
The first part is used for determining the lane width of the lane where the vehicle is located at the time t+1 in front of the running based on the front lane images acquired by the monocular cameras at the time t and the time t+1;
Firstly, determining the lane width change of a lane where the vehicle is located in front of driving;
S11, dividing a lane in a front image acquired by a monocular camera at the moment t (the last moment) and the moment t+1 (the current moment) into n lane segments along the running direction of the vehicle, and extracting n lane segments of a lane where the vehicle at the moment t is located;
In the embodiment of the invention, the lane line image is equally divided along the running direction of the vehicle, a vehicle coordinate system is defined, the midpoint of the rear axle of the vehicle is taken as the origin of coordinates, the running direction of the vehicle is taken as the x-axis in the vehicle coordinate system, the width direction of the vehicle is taken as the y-axis in the vehicle coordinate system, and the average width between two lane lines in the lane section is the lane width of the corresponding lane section.
S12, calculating the average value W t [ n ] of the lane widths and the variance P t [ n ] of each of the n lane segments, and simultaneously predicting the average value of the lane widths of each of the n lane segments at the time t+1 based on the average value W t [ n ] of the lane widths at the time t and the variance P t [ n ]Variance of
Since the time interval of the adjacent time (t, t+1) is short, the lane width mean shift of the adjacent time is small, and based on this, the prediction method is specifically as follows:
Wherein, Q is a process noise variance, its value is related to the own vehicle speed v ego at time t and the yaw rate ψ ego, when ψ ego＞0.1,Q＝(0.01736×Vego×dt)2 +0.0003, when ψ ego≤0.1,Q＝(0.01736×Vego×dt)2 +0.0008, wherein, every time the vehicle advances by one meter, the maximum change that the lane width may occur is 0.01736,0.0003, 0.0008 is a steady state error, even if the vehicle is still, the stability of visual recognition is reduced when ψ ego increases, therefore, by changing the steady state portion of the process noise variance, the ability of the filter to filter noise can be increased.
S13, fitting a lane line curve of lane lines on two sides of the vehicle at the time t, reading the abscissa x t+1 [ n ] of the midpoints of all lane line segments at the time t+1 under a vehicle coordinate system, and calculating the lane width z t+1 [ n ] of the midpoints of each lane segment at the time t+1;
in the embodiment of the invention, the fitting method of the lane line curve is specifically as follows:
extracting lane line segments of lane lines at two sides of the vehicle at the moment t, acquiring coordinates of all the lane line segments under a vehicle coordinate system, and fitting a lane line curve y t [ n ] of the lane lines at two sides of the vehicle;
The lane line curves y t [ n ] are lane line curves respectively Lane line curveLane line curveLane line curveAll are multiple curve equations, and the curve of the lane lineIs matched with the lane line curveIs the same as the fitting method of the lane line curveFor illustration, the expression is specifically as follows:
wherein, the An abscissa representing the midpoint of the nth lane line segment on the left side of the time t, an abscissa representing the distance from the origin of the vehicle coordinate system in the extending direction of the lane line,The ordinate representing the midpoint of the n-th left lane line segment at time t, the ordinate representing the distance from the origin of the vehicle coordinate system in the lane width direction, C 0、C1、C2 and C 3 representing the fitting coefficients, and, as will be described in detail, at the same time,
In the embodiment of the invention, the method for acquiring the lane width z t+1 [ n ] is specifically as follows:
Inputting the read x t+1 [ n ] of each lane line segment at t+1 time into the lane line curve Lane line curveThe longitudinal coordinates of the line segments on the two sides of each lane at the time of t+1 can be obtainedThen
Due to the measurement error existing in the lane line identification processWhere δ n denotes the measurement variance of the nth lane segment, which is related to the distance.
S4, predicting average value based on lane width of each lane segment in the n lane segments at time t+1And the lane width calculation value z t+1 [ n ] is used for determining the average width W t+1 [ n ] of each lane segment, namely the lane width of each lane segment at the time t+1.
Wherein, kn is confidence, and the value range is 0-1.
The invention carries out filtering treatment on the lane width information, and the recognition error of the lane width before the treatment is 0.005+0.00034738 x2 (wherein 0.005 is C0 error and 0.00034738 is C2 error) according to the parameters of the camera, namely the error of 50 meters is 0.8734 meters. After Kalman filtering, the variance formula is represented by P (t+1) = ((P (t) +Q)/(P (t) +Q+R), wherein Q is the process noise variance, R is the measurement error, and the error of 50 meters after iteration convergence is 0.1673 meters. Therefore, the reliability of merging judgment can be greatly improved after filtering treatment.
A lane merging detection method;
s21, before lane merging judgment is carried out, whether the vehicle is in straight running or not is firstly detected, the included angle between the vehicle and the lane where the vehicle is located is smaller than an angle threshold value, when the included angle between the vehicle and the lane where the vehicle is located is too large, false alarm is easily generated due to image distortion, if the detected result is yes, the step S22 is executed, and if the detected result is no, lane merging detection is not carried out, namely the step S22 is not executed;
S22, acquiring a target vehicle in front of a lane where the target vehicle is located from a front image acquired by a monocular camera at the time t+1, detecting whether the target vehicle is located within a set distance in front of the vehicle, if so, executing a step S23, and if not, executing a step S24;
s23, detecting whether the preceding vehicle and the lane where the preceding vehicle is located meet the following conditions, and if the detection result is that the following conditions are met, sending out a lane merging prompt;
231 The front vehicle is changing the road, namely, the curvature of the front vehicle movement track and the included angle between the head speed direction and the lane line are bigger, the front vehicle turn-on lamp is turned on or the front vehicle transverse position deviates from the lane;
232 The confidence coefficient of the left lane line and the right lane line of the lane where the vehicle is located is larger than a confidence coefficient threshold value;
233 The curvature of the short lane line in the lane lines on both sides of the lane where the own vehicle is located is small, for example, less than 0.0005 (unit 1/m), and the curvature of the long lane line is large, for example, more than 0.004 (unit 1/m).
S24, detecting whether the preceding vehicle and the lane where the preceding vehicle is located meet the following conditions, and if the detection result is that the following conditions are met, sending out a lane merging prompt;
241 The confidence coefficient of the left and right lane lines of the lane where the own vehicle is located is larger than the confidence coefficient threshold value,
242 The curvature of the short lane line in the lane lines on both sides of the lane where the own vehicle is located is small, for example, less than 0.0005 (unit 1/m), while the curvature of the long lane line is large, for example, more than 0.004 (unit 1/m);
243 The two lane lines are crossed;
244 The lane width of the lane section of the lane where the own vehicle is located is in a decreasing trend.
In the embodiment of the invention, in order to be closer to the actual driving process, the vehicle needs to change the lane in the driving process, in order to ensure that the vehicle can realize lane merging identification after the lane change, the lane width of the lane at the left side and the right side of the lane is identified while the lane width of the lane at which the vehicle is positioned is identified, the identification method is the same as the identification method of the lane at which the vehicle is positioned, and when the lane changing operation of the vehicle is detected, the lane width of the lane at which the vehicle is positioned is updated to the lane width of the lane at which the vehicle is positioned after the lane changing.
The invention also provides a lane merging recognition system, which comprises:
and the monocular camera collects the front image of the vehicle and sends the front image to the processor, and the processor carries out lane merging detection based on the lane merging recognition method.
The invention also provides an automobile, wherein the lane merging recognition system is integrated on the automobile, the monocular camera is integrated on a front windshield, and the processor is independently arranged on the automobile or integrated on a whole automobile controller of the automobile.
While the present invention has been described by way of example, it should be apparent that the practice of the invention is not limited by the foregoing, but rather is intended to cover various insubstantial modifications of the method concepts and teachings of the invention, either as applied to other applications without modification, or as applied directly to other applications, without departing from the scope of the invention.
Claims (9)
1. The lane merging identification method is characterized by comprising the following steps of:
S1, determining the width of a lane in front of a running lane where a vehicle is located at the time t+1 based on front lane images acquired by monocular cameras at the time t and the time t+1;
s2, using the width of the lane in front of driving for lane merging detection and sending out reminding;
The lane merging detection specifically comprises the following steps:
S21, detecting whether the vehicle moves straight or not, wherein the included angle between the vehicle and the lane where the vehicle is positioned is smaller than an angle threshold value, and if the detected result is yes, executing a step S22;
S22, acquiring a target vehicle in front of a lane where the target vehicle is located from a front image acquired by a monocular camera at the time t+1, detecting whether the target vehicle is located within a set distance in front of the vehicle, and if the detection result is negative, executing a step S24;
s24, detecting whether the preceding vehicle and the lane where the preceding vehicle is located meet the following conditions, and if the detection result is yes, sending out a lane merging prompt;
241 The confidence coefficient of the left and right lane lines of the lane where the own vehicle is located is larger than the confidence coefficient threshold value,
242 The curvature of a short lane line in lane lines on two sides of a lane where the vehicle is located is small, and the curvature of a long lane line is large;
243 The two lane lines are crossed;
244 The lane width of the lane section of the lane where the own vehicle is located is in a decreasing trend.
2. The lane merging recognition method according to claim 1, wherein the method of determining the lane width of the lane in which the host vehicle is located in front of the travel comprises the steps of:
s11, dividing a lane where a host vehicle is located in a front image into n lane segments along the running direction of the vehicle;
S12, calculating the average value W t [ n ] of the lane widths of all the n lane segments, and predicting the average value of the lane widths of all the lane segments at the time t+1
S13, fitting lane line curves of lane lines on two sides of the vehicle, and calculating the lane width z t+1 [ n ] of each lane segment in n lane segments at the time t+1;
s14, predicting average value of lane width And fusing the lane width values z t+1 [ n ] to form the lane width W t+1 [ n ] of each lane segment in the n lane segments at the time of t+1.
3. The lane merging recognition method according to claim 2, wherein the calculation formula of the lane width W t+1 [ n ] of each lane segment at time t+1 is specifically as follows:
Wherein, K n is the confidence, And R < n > is the measurement error, which is the variance of the lane widths of n lane segments at time t+1.
4. A lane merging recognition method according to claim 2 or 3, wherein the average value of the lane widths at time t+1The calculation formula is specifically as follows:
5. The lane merging recognition method as claimed in claim 3, wherein the variance of the lane widths of n lane segments at time t+1 The calculation formula is specifically as follows:
Wherein, Q is the process noise variance, and the process noise variance Q takes the value and the vehicle speed v ego and the yaw rate psi ego at the moment t are related.
6. The lane merging recognition method according to claim 1, wherein if a target vehicle is located within a set distance in front of the host vehicle, whether the preceding vehicle and the lane where the target vehicle is located meet the following conditions is detected, and if the detection result is yes, a merging reminder is sent;
231 A front car is changing lanes;
232 The confidence coefficient of the left lane line and the right lane line of the lane where the vehicle is located is larger than a confidence coefficient threshold value;
233 The curvature of a short lane line in lane lines at two sides of a lane where the vehicle is located is small, and the curvature of a long lane line is large.
7. The lane-merging recognition method according to claim 1, wherein the lane width of the lane in which the own vehicle is located is recognized while the lane widths of the lanes on the left and right sides of the lane in which the own vehicle is located are recognized, and when the lane-changing operation of the own vehicle is detected, the lane width of the lane in which the own vehicle is located is updated to the lane width of the lane in which the own vehicle is located after the lane change.
8. A lane merging recognition system, the system comprising:
the monocular camera collects the front image of the vehicle and sends the front image to the processor;
The processor performs lane merging detection based on the lane merging recognition method according to any one of claims 1 to 7.
9. An automobile having integrated thereon the lane merging recognition system of claim 8.
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| CN109476306A (en) * | 2016-07-06 | 2019-03-15 | 日产自动车株式会社 | Driving control method and driving control device |
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| JP6946754B2 (en) * | 2017-06-06 | 2021-10-06 | トヨタ自動車株式会社 | Lane change support device |
| JP7096215B2 (en) * | 2019-08-05 | 2022-07-05 | 本田技研工業株式会社 | Vehicle control devices, vehicle control methods, and programs |
| CN112703506B (en) * | 2020-04-22 | 2022-04-08 | 华为技术有限公司 | Lane line detection method and device |
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