CN114572250A - Method for automatically driving through intersection and storage medium - Google Patents
Method for automatically driving through intersection and storage medium 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
- B60W60/0015—Planning or execution of driving tasks specially adapted for safety
- B60W60/0016—Planning or execution of driving tasks specially adapted for safety of the vehicle or its occupants
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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
- B60W30/18154—Approaching an intersection
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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
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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
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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
- B60W2552/50—Barriers
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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
- B60W2552/53—Road markings, e.g. lane marker or crosswalk
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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
- B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
- B60W2555/60—Traffic rules, e.g. speed limits or right of way
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Abstract
The invention discloses a method and a storage medium for automatically driving through an intersection, which comprises the following steps of S1, reconstructing a road environment according to road environment information of the intersection, acquiring navigation information of a vehicle, and predicting a drivable area; s2, executing a preset lane change decision according to the vehicle navigation information; s3, executing a preset longitudinal decision according to the road environment; s4, planning a driving track fitting mode of the vehicle; and S5, executing a preset track decision according to the road environment and the drivable area. The method is based on vision, radar sensors and a navigation map, reconstructs the road environment of the intersection by collecting the road environment information of the intersection, and simultaneously executes corresponding lane change decision, longitudinal decision and running track decision of the vehicle by combining a navigation path provided by the navigation map and the lane where the vehicle is located, so that the road environment of the intersection can be accurately obtained, and the vehicle can stably and safely pass through the intersection.
Description
Technical Field
The invention belongs to the technical field of automatic driving of automobiles, and particularly relates to a method for automatically driving to pass through an intersection and a storage medium.
Background
At present, the automatic driving development gradually expands to urban scenes, intersections are difficult points and key points in the urban scenes, high-precision maps cannot provide complete intersection information at the intersections, and V2X is limited in popularization and cannot serve as a dependable sensor to serve as an automatic driving control basis.
For example, chinese patent CN202111050404.8 discloses a method, a device, a vehicle and a medium for driving an intersection of automatically driven vehicles, the method includes: when the current position of the automatic driving vehicle identifies that the vehicle is positioned at the intersection, acquiring actual intersection information of the intersection from a current map; identifying vehicle information of at least one other vehicle in an area of interest in the intersection according to current vehicle information of the autonomous vehicle; predicting the subsequent running track of each other vehicle based on the actual intersection information and the vehicle information of at least one other vehicle by utilizing a pre-trained prediction model; and determining a target local path and a target driving behavior of the automatic driving vehicle according to the actual intersection information, the subsequent driving tracks of each other vehicle and the traffic information of the intersection. Therefore, the problem that safety accidents easily occur due to the fact that information such as surrounding barrier vehicles and traffic lights cannot be accurately identified is solved, the collision risk with other vehicles is reduced, and the safety and the comfort of the vehicles are improved.
Therefore, the sensor of the vehicle needs to be relied on to sense the working condition of the intersection as early as possible so as to accurately plan the path, and the vehicle can accurately and smoothly pass through the intersection.
Disclosure of Invention
In order to solve the problems, the invention provides a method for automatically driving to pass through an intersection and a storage medium, which can accurately reconstruct the road environment of the intersection, realize lane change by combining a navigation map, and stably and safely pass through the intersection according to the decision of a preset driving track and logic.
In order to solve the above technical problems, the present invention adopts a technical solution in which a method of automatically driving through an intersection includes the steps of,
s1, reconstructing a road environment according to the road environment information of the intersection, acquiring the navigation information of the vehicle, and predicting a drivable area;
s2, executing a preset lane change decision according to the vehicle navigation information;
s3, executing a preset longitudinal decision according to the road environment;
s4, planning a running track fitting mode of the vehicle;
and S5, executing a preset track decision according to the road environment and the drivable area.
As optimization, the road environment information comprises target vehicle information and/or obstacle information and/or lane line information and/or road edge information and/or guardrail information and/or traffic light information acquired by the data acquisition equipment.
Preferably, the data acquisition equipment comprises a panoramic camera and/or a radar sensor.
As optimization, the navigation information of the vehicle includes the lane where the vehicle is located and/or the navigation path of the vehicle, which are obtained through a navigation map.
As an optimization, the lane change decision includes, if the distance between the vehicle and the front intersection is less than a preset distance:
s201, if the navigation path is that the front road turns left, and the lane where the vehicle is located is a middle lane or a right lane, changing the lane to the left lane;
s202, if the navigation path is that the front road turns right, and the lane where the vehicle is located is a middle lane or a left lane, changing the lane to the right lane;
and S203, if the navigation path is that the front road goes straight and the lane where the vehicle is located is the left lane or the right lane, changing the lane to the middle lane.
As an optimization, the longitudinal decision comprises,
s301, if the road environment of the intersection is non-passable, planning deceleration according to the distance between the vehicle and the stop line, and stopping before the stop line;
s302, if the road environment at the intersection is passable and no front vehicle is in front of the vehicle, the vehicle longitudinally runs according to the set vehicle speed;
and S303, if the road environment at the intersection is passable and a front vehicle is in front of the vehicle, the vehicle runs along with the front vehicle.
In step S4, the driving trajectory of the host vehicle includes a following driving trajectory, a following line driving trajectory, and a predicted forward trajectory.
As an optimization, in step S5, the trajectory decision includes,
if there is no front vehicle right in front of the vehicle and,
s501, after the vehicle enters the intersection and before the lane line of the target lane is not recognized, the running track of the vehicle is a front predicted track;
s502, after the vehicle enters the intersection and the lane line of the target lane is identified again, switching the running track of the vehicle from the front predicted track to the following line running track;
s503, if the track curve of the front predicted track or the following line driving track in the S501 and the S502 is outside the cut-off range of the driving area, determining an offset according to the cut-off range of the driving area and carrying out interpolation transition to obtain a final driving track;
if there is a preceding vehicle directly in front of the vehicle, the traveling locus of the vehicle is a following traveling locus.
As an optimization, the prediction of the forward predicted trajectory comprises,
s5011, if the navigation path is a right turn/left turn, predicting according to the road environment;
and S5012, if the navigation path is straight, predicting according to the historical driving track of the vehicle.
Based on the above method, the present invention also provides a storage medium storing one or more programs which, when executed by a processor, perform the steps of the method for automatically driving through an intersection.
Compared with the prior art, the invention has the following advantages:
the method for the automatic driving assistance system to cross the intersection based on the vision, the radar sensor and the navigation map collects the road environment information of the intersection through each sensor, wherein the road environment information comprises target vehicle information, obstacle information, lane line information, road edge information, guardrail information, traffic light information and the like, the information is fused to reconstruct the road environment of the intersection, and meanwhile, corresponding lane changing decision, longitudinal decision and running track decision of the vehicle are executed by combining a navigation path and the lane of the vehicle provided by the navigation map, so that the road environment of the intersection can be accurately obtained, and the intersection can be stably and safely passed.
Drawings
Fig. 1 is a schematic view of the working process of the present invention.
Detailed Description
The invention will be further explained with reference to the drawings and the embodiments.
Example (b): with reference to figure 1 of the drawings,
a method of automatically driving through an intersection, comprising the steps of,
and S1, reconstructing the road environment according to the road environment information of the intersection, acquiring the navigation information of the vehicle, and predicting the drivable area. The road environment information comprises target vehicle information and/or obstacle information and/or lane line information and/or road edge information and/or guardrail information and/or traffic light information acquired by data acquisition equipment. The data acquisition equipment comprises a panoramic camera and/or a radar sensor. The navigation information of the vehicle comprises a lane where the vehicle is located and/or a navigation path of the vehicle, which are acquired through a navigation map.
Specifically, the panoramic camera is a monocular non-fisheye camera, is distributed on the front side, the rear side and two sides of the vehicle body, can reach the recognition range of 150m farthest, is mainly used for recognizing lane lines, target classification and guardrails and road edges, and can recognize intersection traffic lights.
The panoramic camera is a fisheye camera, is distributed on the front side, the rear side and two sides of the vehicle body, and is positioned towards the ground so as to compensate a visual blind area of the panoramic camera, and the identification range is 0-10 m.
The radar sensors are millimeter wave radars which are distributed on the front side, the rear side and two sides of the vehicle body, and can identify guardrails and targets.
The navigation map provides navigation path information including intersection distance, crossing driving direction (left turn, right turn, straight going) and vehicle target lane information before crossing after a driver sets a destination.
The environmental reconstruction of the road environment comprises,
(1) and receiving the information of the targets, the obstacles, the lane lines, the road edges and the guardrails output by the panoramic camera, the panoramic camera and the millimeter wave radar, fusing, restoring the road environment of the intersection, and outputting a lane line equation where the vehicle is located, target information, left and right road edges/guardrail coefficients, traffic light information of the vehicle and the like.
(2) And calculating the position of the current lane.
And (4) estimating the current lane (left lane, middle lane and right lane) according to the number of lanes at the current position provided by the navigation map and the transverse distance between the left/right guardrails/road edges and the vehicle.
(3) Travelable area FreeStace prediction
And updating the three-order curve of the FreePasce in the travelable area in real time according to the longitudinal distance between the target and the obstacle and the three-order equation curves of the guardrail and the road edge.
And S2, executing a preset lane change decision according to the vehicle navigation information. The lane change decision comprises the following steps that if the distance between the vehicle and the front intersection is less than 100m (can be calibrated according to actual requirements):
s201, if the navigation map makes a left turn on a front road and the vehicle is located in a middle lane or a right lane, triggering a lane changing function to the left lane;
s202, if the navigation map makes a right turn on the road ahead and the vehicle is in a middle lane or a left lane, triggering a lane changing function to the right lane;
s203, if the navigation map shows that the front road goes straight and the vehicle is in the left lane or the left lane, triggering a lane changing function to the middle lane;
and under other working conditions which are not S201-S203, the vehicle does not trigger lane change.
And S3, executing preset longitudinal decision according to the road environment. The longitudinal decision-making comprises the steps of,
s301, if the road environment of the intersection is non-passable, planning deceleration according to the distance between the vehicle and the stop line, and stopping before the stop line;
s302, if the road environment at the intersection is passable and no front vehicle is in front of the vehicle, the vehicle longitudinally runs according to the set vehicle speed;
and S303, if the road environment at the intersection is passable and a front vehicle is in front of the vehicle, the vehicle runs along with the front vehicle.
Specifically, after the target lane in S2 is reached, the longitudinal motion of the vehicle is determined based on the traffic light information of the current lane output by the environment reconstruction.
(1) If the traffic light is red light or yellow light, the vehicle plans deceleration according to the distance from the vehicle to the intersection stop line so as to ensure that the vehicle stops before the intersection stop line.
(2) If the traffic light is green and the lane has no front vehicles, the vehicle longitudinally runs according to the set speed.
(3) If the traffic light is green and the lane has a front vehicle, the vehicle runs along with the front vehicle.
And S4, planning a running track fitting mode of the vehicle. The driving track of the vehicle comprises a following driving track, a following line driving track and a front predicted track. Wherein the content of the first and second substances,
(1) and fitting the following driving track.
And (5) fitting the historical track of the target in the past TBD periods according to the horizontal and vertical coordinates of the same TrackID target.
(2) And (5) fitting a line following driving track.
When the lane lines on the two sides exist, the lane centering track coefficient is calculated according to the following rule:
centering track coefficients A0, A1, A2 and A3 are respectively half of the sum of left and right lane line coefficients A0, A1, A2 and A3; the length of the centering track is the maximum length of the lane lines on two sides.
(3) And fitting the front predicted track.
And fitting a third-order curve according to the historical driving track points of the vehicle and predicting the driving track in the future TBD period.
And S5, executing a preset track decision according to the road environment and the drivable area. The trajectory decision comprises a decision to take a trajectory,
if there is no front vehicle right in front of the vehicle and,
s501, after the vehicle enters the intersection and before the lane line of the target lane is not recognized, the running track of the vehicle is a front predicted track; the prediction of the forward predicted trajectory may include,
s5011, if the navigation path is a right turn/left turn, predicting according to the road environment;
and S5012, if the navigation path is straight, predicting according to the historical driving track of the vehicle.
S502, after the vehicle enters the intersection and the lane line of the target lane is identified again, switching the running track of the vehicle from the front predicted track to the following line running track;
and S503, if the track curve of the front predicted track or the following line driving track in the S501 and the S502 is out of the cut-off range of the driving area, determining an offset according to the cut-off range of the driving area and carrying out interpolation transition to obtain a final driving track.
In particular, the method comprises the following steps of,
(1) after the green light passes through the intersection stop line and before the lane line of the target lane is not identified, predicting a front track:
A. if the vehicle needs to turn right/left according to the navigation map and no vehicle exists in the lane before the stop line, predicting a front driving track according to a road edge/guardrail curve on the right side of the vehicle;
B. if the vehicle needs to go straight according to the navigation map and no vehicle exists in the lane before the stop line, predicting a front running track according to the historical running track of the vehicle;
C. if there is a front vehicle in the lane before the stop line, the vehicle follows the track of the front vehicle;
(2) after the green light passes through the intersection stop line, the lane line of the target lane is re-identified in the driving process of the vehicle, and the driving track of the vehicle is switched from the predicted driving track to the driving track following the central line of the target lane;
(3) if the two generated trajectory curves are outside the FreeScae cut-off range, determining the offset according to the FreeScae cut-off range to ensure that the driving trajectory of the vehicle is a reliable driving trajectory, and performing interpolation transition on the 'centering driving trajectory A0' according to the 'transverse offset' to obtain a final driving curve.
Based on the above method, the present invention also provides a storage medium storing one or more programs which, when executed by a processor, perform the steps of the method for automatically driving through an intersection.
The method for the automatic driving assistance system to cross the intersection based on the vision, the radar sensor and the navigation map collects the road environment information of the intersection through each sensor, wherein the road environment information comprises target vehicle information, obstacle information, lane line information, road edge information, guardrail information, traffic light information and the like, the information is fused to reconstruct the road environment of the intersection, and meanwhile, corresponding lane changing decision, longitudinal decision and running track decision of the vehicle are executed by combining a navigation path and the lane of the vehicle provided by the navigation map, so that the road environment of the intersection can be accurately obtained, and the intersection can be stably and safely passed.
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 method of automatically driving through an intersection, comprising the steps of,
s1, reconstructing a road environment according to the road environment information of the intersection, acquiring the navigation information of the vehicle, and predicting a drivable area;
s2, executing a preset lane change decision according to the vehicle navigation information to enable the vehicle to change lanes to a specified lane;
s3, executing a preset longitudinal decision according to the road environment, and enabling the vehicle to pass through the intersection or stop in front of the stop line or stop behind the front vehicle;
s4, planning a running track fitting mode of the vehicle;
and S5, executing a preset track decision according to the road environment and the drivable area, and passing through the intersection.
2. The method of claim 1, wherein the road environment information comprises target vehicle information and/or obstacle information and/or lane line information and/or road edge information and/or guardrail information and/or traffic light information acquired by a data acquisition device.
3. The method of claim 2, wherein the data acquisition device comprises a panoramic camera and/or a radar sensor.
4. The method of claim 2, wherein the navigation information of the host vehicle comprises a lane in which the host vehicle is located and/or a navigation path of the host vehicle obtained from a navigation map.
5. The method of claim 4, wherein the lane-change decision comprises, if the distance between the vehicle and the intersection ahead is less than a predetermined distance:
s201, if the navigation path is that the front road turns left and the lane where the vehicle is located is a middle lane or a right lane, changing the lane to the left lane;
s202, if the navigation path is that the front road turns right, and the lane where the vehicle is located is a middle lane or a left lane, changing the lane to the right lane;
and S203, if the navigation path is that the front road goes straight and the lane where the vehicle is located is the left lane or the right lane, changing the lane to the middle lane.
6. The automated method of driving through an intersection according to claim 4, wherein the longitudinal decision comprises,
s301, if the road environment of the intersection is non-passable, planning deceleration according to the distance between the vehicle and the stop line, and stopping before the stop line;
s302, if the road environment at the intersection is passable and no front vehicle is in front of the vehicle, the vehicle longitudinally runs according to the set vehicle speed;
and S303, if the road environment at the intersection is passable and a front vehicle is arranged right ahead of the vehicle, the vehicle runs along with the front vehicle.
7. The method of claim 4, wherein in step S4, the driving path of the vehicle includes a following driving path, and a predicted path ahead.
8. The method of automatically driving through an intersection according to claim 4, wherein in step S5, the trajectory decision comprises,
if there is no front vehicle right in front of the vehicle and,
s501, after the vehicle enters the intersection and before the lane line of the target lane is not recognized, the running track of the vehicle is a front predicted track;
s502, after the vehicle enters the intersection and the lane line of the target lane is identified again, switching the running track of the vehicle from the front predicted track to the following line running track;
s503, if the track curve of the front predicted track or the following line driving track in the S501 and the S502 is outside the cut-off range of the driving area, determining an offset according to the cut-off range of the driving area and carrying out interpolation transition to obtain a final driving track;
if there is a preceding vehicle directly in front of the vehicle, the traveling locus of the vehicle is a following traveling locus.
9. The method of automatically driving through an intersection according to claim 8, wherein the prediction of the forward predicted trajectory comprises,
s5011, if the navigation path is a right turn/left turn, predicting according to the road environment;
and S5012, if the navigation path is straight, predicting according to the historical driving track of the vehicle.
10. A storage medium storing one or more programs which, when executed by a processor, perform the steps of the method of automatically driving through an intersection as recited in any of claims 1-9.
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