CN114537446A - Lane dividing method and storage medium for target vehicle behind vehicle - Google Patents
Lane dividing method and storage medium for target vehicle behind vehicle 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
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0027—Planning or execution of driving tasks using trajectory prediction for other traffic participants
- B60W60/00272—Planning or execution of driving tasks using trajectory prediction for other traffic participants relying on extrapolation of current movement
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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
- 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
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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
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/30—Road curve radius
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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
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Abstract
The invention discloses a lane dividing method and a storage medium for a target vehicle behind a vehicle, which comprises S1, constructing a curvature queue of a lane line behind the vehicle, and acquiring information of the lane line behind the vehicle; s2, obtaining the position information of the center of mass of the target vehicle behind the vehicle; s3, acquiring the position relation between the target vehicle and the lane line according to the lane line information and the position information; and S4, acquiring the line pressing amount of the target vehicle in lanes on two sides of the lane line according to the position relation, acquiring the occupation ratio of the target vehicle in each lane according to the line pressing amount, and dividing the target vehicle into corresponding lanes according to the occupation ratio. The invention does not need to install additional sensors, thereby greatly saving the system cost. The lane changing behavior of the target can be judged in advance, so that the system is more flexible and efficient; when the lane to which the target vehicle belongs is divided, the robustness design is made in consideration of the unstable result caused by the fact that the target vehicle is likely to press the line to run, the stability of the performance of the whole system can be improved, and the lane division of the vehicle behind the target vehicle is more accurate.
Description
Technical Field
The invention belongs to the technical field of automatic driving, and particularly relates to a lane division method and a storage medium for a target vehicle behind a vehicle.
Background
The automatic driving system has great dependence on the surrounding environment of the vehicle, such as lane lines and target vehicles, and the collision can be effectively avoided only by accurately identifying the position of the target vehicle, so that the safety of the vehicle and passengers is ensured. Many automatic driving functions require accurate lane positioning of a target vehicle, for example, an automatic lane changing system (ALC) is triggered by a driver or a system, automatically controls a steering wheel after confirming that the target lane has no dangerous vehicles, and realizes a function of changing the lane to the target lane, and if vehicles on the target lane are wrongly divided into other lanes, serious traffic accidents are likely to be caused, so that the lane to which the target vehicle belongs is accurately judged, and a very important influence is brought to the improvement of the safety of the automatic driving function.
The current automatic driving system has a good processing effect on the lane division of the vehicle in front of the vehicle, but has no good processing scheme on the vehicle behind. For example, a chinese patent CN202110065925.4 discloses a method, an apparatus and a computer device for determining a leading vehicle of a vehicle, wherein the method comprises: acquiring attribute information of each vehicle in front of the target vehicle and attribute information of each lane line; inputting the attribute information of each vehicle in front of the target vehicle in driving and the attribute information of each lane line into a preset machine learning model to obtain first leading vehicle information of the target vehicle; calculating to obtain the lane information of each vehicle in front of the target vehicle according to the attribute information of each vehicle in front of the target vehicle and the attribute information of each lane line, and determining second leading vehicle information of the target vehicle according to the lane information of each vehicle in front of the target vehicle; and determining the leading vehicle of the target vehicle according to the first leading vehicle information and the second leading vehicle information. By implementing the method, the accuracy of front vehicle determination is greatly improved, and the reliability of an automatic driving system is improved. But it is mainly constrained by the following conditions:
1) the main sensors of the automatic driving vehicle are configured as a single front-view camera, a front millimeter wave radar and a rear angle radar, rear lane line information is lacked under the condition of no rear-view camera, and the system cost can be greatly improved by adding the rear-view camera;
2) if the front lane line information is used to fit the rear lane line, the performance is better when the lane is straight, but wrong rear lane line information is given when the lane is curved, so that the lane to which the target belongs is judged by mistake, as shown in fig. 3;
3) some vehicles run close to a lane line, and the sensor cannot stably identify the transverse distance of the target, so that the information of the lane to which the target belongs is judged to jump repeatedly, and the stability of the automatic driving function is influenced.
Disclosure of Invention
In order to solve the above problems, the present invention provides a lane dividing method and a storage medium for a target vehicle behind a vehicle, so as to improve the control safety of an automatic driving system and reduce the risk of collision caused by misjudgment and missed judgment of a rear vehicle.
In order to solve the technical problem, the technical scheme adopted by the invention is as follows: a lane dividing method for a target vehicle behind a vehicle comprises the following steps,
s1, constructing a curvature queue of the lane line behind the vehicle, and acquiring the information of the lane line behind the vehicle;
s2, obtaining the position information of the center of mass of the target vehicle behind the vehicle;
s3, acquiring the position relation between the target vehicle and the lane line according to the lane line information and the position information;
and S4, acquiring the line pressing amount of the target vehicle in lanes on two sides of the lane line according to the position relation, acquiring the occupation ratio of the target vehicle in each lane according to the line pressing amount, and dividing the target vehicle into corresponding lanes according to the occupation ratio.
And as optimization, the construction of the curvature queue comprises the steps of periodically collecting and storing the curvature of a lane driven by the vehicle through a front-view camera of the vehicle, after the vehicle moves for a first preset distance, averaging the stored curvatures of all the lanes, writing the curvatures into the curvature queue in a queue segment mode, sequentially arranging all the queue segments in a second preset distance of the vehicle movement to form the curvature queue, writing the newly written queue segments from the front end of the curvature queue, and kicking out the queue segments at the tail end of the curvature queue.
Preferably, the first preset distance is 1m, and the second preset distance is 100 m.
And obtaining the lane line information behind the vehicle by a least square method according to the curvature queue, wherein the lane line information comprises the curvature and the curvature change rate of the lane line.
As an optimization, in step S3, the positional relationship between the target vehicle and the lane line is obtained according to the lane line equation,
where x is the longitudinal position of the target vehicle's center of mass, y is the transverse position of the lane line corresponding to x, c0Is the curvature of the lane line, c1Is the rate of change of curvature of the lane line,
is the heading angle, x, of the target vehicle0Is the lateral distance of the lane line at the origin of coordinates.
As an optimization, in step S4, the pressing line amounts of the target vehicle in the lanes on both sides of the lane line are calculated according to the following equation:
correspondingly, the occupation ratio of the target vehicle in each lane is calculated according to the following formula:
in the formula, W isThe vehicle width of the target vehicle, D2 is the lateral distance between the centroid of the target vehicle and the lane line,
is the heading angle of the target vehicle.
As an optimization, when the occupancy of the target vehicle in the lane is equal to or greater than 60%, the target vehicle is classified into the lane.
As an optimization, in step S2, the position information identified by the vehicle-mounted sensor and having the center of the tail of the target vehicle as coordinates is subjected to coordinate transformation to obtain the position information of the center of mass of the target vehicle having the center of mass of the target vehicle as coordinates.
As an optimization, step S2 further includes making a short-time domain prediction of the position information of the center of mass of the target vehicle according to the lateral speed of the target vehicle.
A storage medium storing one or more programs which, when executed by a processor, perform the steps of the lane division method of a target vehicle behind a host vehicle.
Compared with the prior art, the invention has the following advantages:
the invention aims to solve the problem of inaccurate lane division of a vehicle behind the vehicle under the precondition of not adding a sensor, help the automatic driving function to better identify a target, store the curvature of a road which the vehicle runs through by designing a curvature queue, and continuously update the curvature queue in the running process of the vehicle, thereby obtaining the information of lane lines behind the vehicle which cannot be seen by the sensor originally; converting the target position information from the tail center to a target mass center, and performing short-time domain prediction on the target position according to the target transverse speed; according to the lane line information behind the vehicle, the transverse position of each lane line at the target position is obtained; and (4) calculating the line pressing quantity of the target by combining the target position and the lane line position to obtain the target ratio of each lane, so as to divide the target vehicle into corresponding lanes.
The curvature of the road where the vehicle runs is stored and used for fitting the originally unknown lane line equation behind the vehicle, so that an additional sensor is not required to be installed, and the system cost is greatly saved. The target vehicle is subjected to short time domain prediction before the lane to which the target belongs is judged, so that the lane changing behavior of the target can be judged in advance, and the system is more flexible and efficient; when the lane to which the target vehicle belongs is divided, the robustness design is made in consideration of the unstable result caused by the fact that the target vehicle is likely to press the line to run, the stability of the performance of the whole system can be improved, and the lane division of the vehicle behind the target vehicle is more accurate.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic diagram of a curvature queue according to the present invention;
FIG. 3 is a schematic illustration of a target vehicle identification location and center of mass location of the present invention;
fig. 4 is a schematic diagram of the occupation ratio of the target vehicle in each lane according to the present invention.
Detailed Description
The invention will be further explained with reference to the drawings and the embodiments.
Example (b): with reference to figures 1-4 of the drawings,
a lane dividing method for a target vehicle behind a vehicle comprises the following steps,
s1, constructing a curvature queue of the lane line behind the vehicle, and acquiring the information of the lane line behind the vehicle; the curvature queue construction method comprises the steps that the curvature of a lane driven by a vehicle is periodically collected and stored through a front-view camera of the vehicle, after the vehicle moves for a first preset distance, the stored curvature of all the lanes is averaged and written into the curvature queue in a queue segment mode, all queue segments in a second preset distance of the vehicle are sequentially arranged to form the curvature queue, and the newly written queue segments are written into the front end of the curvature queue and play out the queue segments at the tail end of the curvature queue. The first preset distance is 1m, and the second preset distance is 100 m. Specifically, when the vehicle is static, all curvature queues are clear 0, when the vehicle moves, the curvature of the lane line acquired by the front-looking camera is stored in each running period, when the accumulated movement exceeds 1m, all stored curvatures are averaged and written into the curvature queues, the oldest curvature is kicked out of the curvature queues, and the curvature queues are always kept to be formed by the longitudinal distance of 100m in the past;
after the curvature array is obtained, it can be understood that there is a series of (x, curve) point traces, and a curve can be obtained by the least square method, so that the error sum of squares between the curve and actual data is minimum, and the least square method is generally in the form of:
solving:
the equation here is:
f(x)＝c1x+c0 (8)
in the formula, c0Is curvature c1Is the rate of change of curvature.
S2, obtaining the position information of the center of mass of the target vehicle behind the vehicle; the position information which is recognized by the vehicle-mounted sensor and takes the tail center of the target vehicle as the coordinate is converted into the position information which takes the center of mass of the target vehicle as the coordinate to obtain the center of mass of the target vehicle. And performing short-time domain prediction on the position information of the center of mass of the target vehicle according to the transverse speed of the target vehicle. Specifically, the target position identified by the sensor is generally the tail center of the target, and needs to be converted into the target centroid position:
d1: the lateral distance to which the target is identified;
d2: the target centroid position lateral distance;
l1: longitudinal distance to target identification;
l2: a target centroid position longitudinal distance;
l: a target vehicle length;
w: a target vehicle width;
and (3) leading: a target course angle;
D2＝D1+L*sin(Heading)/2；
L2＝L1+L*cos(Heading)/2；
d 'short time domain prediction'2＝D2+speed*time。
S3, acquiring the position relation between the target vehicle and the lane line according to the lane line information and the position information; obtaining the position relation between the target vehicle and the lane line according to a lane line equation which is as follows,
where x is the longitudinal position of the target vehicle's center of mass, y is the transverse position of the lane line corresponding to x, c0Is the curvature of the lane line, c1Is the rate of change of curvature of the lane line,
is the heading angle, x, of the target vehicle0Is the lateral distance of the lane line at the origin of coordinates.
And S4, acquiring the line pressing amount of the target vehicle in lanes on two sides of the lane line according to the position relation, acquiring the occupation ratio of the target vehicle in each lane according to the line pressing amount, and dividing the target vehicle into corresponding lanes according to the occupation ratio. The line pressing amount of the target vehicle in the lanes on the two sides of the lane line is calculated according to the following formula:
correspondingly, the occupation ratio of the target vehicle in each lane is calculated according to the following formula:
wherein W is the vehicle width of the target vehicle, D2 is the transverse distance between the centroid of the target vehicle and the lane line,
is the heading angle of the target vehicle.
When a target line is pressed to run, the situation that the division of a target lane is unstable easily occurs, so that the target jumps back and forth between two lanes, and therefore, the lane proportion of the target needs to be subjected to anti-jumping redundancy protection: only if the percentage of the target vehicle in the lane is above 60% will the target be classified on that lane.
A storage medium storing one or more programs which, when executed by a processor, perform the steps of the lane division method of a target vehicle behind a host vehicle.
The invention aims to solve the problem of inaccurate lane division of a vehicle behind the vehicle under the precondition of not adding a sensor, help the automatic driving function to better identify a target, store the curvature of a road which the vehicle runs through by designing a curvature queue, and continuously update the curvature queue in the running process of the vehicle, thereby obtaining the information of lane lines behind the vehicle which cannot be seen by the sensor originally; converting the target position information from the tail center to a target mass center, and performing short-time domain prediction on the target position according to the target transverse speed; according to the lane line information behind the vehicle, the transverse position of each lane line at the target position is obtained; and (4) calculating the line pressing quantity of the target by combining the target position and the lane line position to obtain the target ratio of each lane, so as to divide the target vehicle into corresponding lanes.
The curvature of the road where the vehicle runs is stored and used for fitting the originally unknown lane line equation behind the vehicle, so that an additional sensor is not required to be installed, and the system cost is greatly saved. The target vehicle is subjected to short time domain prediction before the lane to which the target belongs is judged, so that the lane changing behavior of the target can be judged in advance, and the system is more flexible and efficient; when the lanes to which the target vehicles belong are divided, the robustness design is made in consideration of the unstable result caused by possible line pressing driving of the targets, the stability of the performance of the whole system can be improved, and lane division of the vehicles behind is more accurate.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and not for limiting the technical solutions, and those skilled in the art should understand that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all that should be covered by the claims of the present invention.
Claims (10)
1. A lane division method for a target vehicle behind a vehicle is characterized by comprising the following steps,
s1, constructing a curvature queue of the lane line behind the vehicle, and acquiring the information of the lane line behind the vehicle;
s2, obtaining the position information of the center of mass of the target vehicle behind the vehicle;
s3, acquiring the position relation between the target vehicle and the lane line according to the lane line information and the position information;
and S4, acquiring the line pressing amount of the target vehicle in lanes on two sides of the lane line according to the position relation, acquiring the occupation ratio of the target vehicle in each lane according to the line pressing amount, and dividing the target vehicle into corresponding lanes according to the occupation ratio.
2. The method for dividing lanes of a rear target vehicle according to claim 1, wherein the constructing of the curvature queue includes periodically collecting and storing the lane curvature traveled by the vehicle through a forward-looking camera of the vehicle, averaging all the stored lane curvatures after the vehicle moves for a first preset distance, writing the average into the curvature queue in a queue segment manner, sequentially arranging all the queue segments in a second preset distance of the vehicle movement to form the curvature queue, writing the newly written queue segment from the front end of the curvature queue, and kicking out the queue segment at the tail end of the curvature queue.
3. The lane division method of a rear target vehicle according to claim 2, wherein the first preset distance is 1m and the second preset distance is 100 m.
4. The method as claimed in claim 1, wherein the lane marking information behind the vehicle is obtained by a least square method based on the curvature queue, and the lane marking information includes curvature and curvature change rate of the lane marking.
5. The lane division method of a rear target vehicle according to claim 4, wherein in step S3, the positional relationship between the target vehicle and the lane line is obtained according to a lane line equation,
where x is the longitudinal position of the target vehicle's center of mass, y is the transverse position of the lane line corresponding to x, c0Is the curvature of the lane line, c1Is the rate of change of curvature of the lane line,
is the heading angle, x, of the target vehicle0Is the lateral distance of the lane line at the origin of coordinates.
6. The lane division method of a rear target vehicle according to claim 1, wherein in step S4, the pressing amount of the target vehicle in the lanes on both sides of the lane line is calculated according to the following formula:
correspondingly, the occupation ratio of the target vehicle in each lane is calculated according to the following formula:
wherein W is the vehicle width of the target vehicle, D2 is the transverse distance between the centroid of the target vehicle and the lane line,
is the heading angle of the target vehicle.
7. The lane division method of a rear target vehicle according to claim 1, wherein the target vehicle is divided into the lane when a proportion of the target vehicle in the lane is 60% or more.
8. The method for dividing lanes of a rear target vehicle as claimed in claim 1, wherein in step S2, the position information identified by the vehicle-mounted sensor and using the center of the tail of the target vehicle as the coordinate is transformed into the position information of the center of mass of the target vehicle obtained using the center of mass of the target vehicle as the coordinate.
9. The method for dividing the lane of a rear target vehicle according to claim 1, wherein the step S2 further comprises making a short-time domain prediction of the position information of the center of mass of the target vehicle according to the lateral velocity of the target vehicle.
10. A storage medium, characterized in that the storage medium stores one or more programs which, when executed by a processor, perform the steps of the lane division method of the target vehicle behind the own vehicle as claimed in any one of claims 1 to 9.
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