CN110763246A - Automatic driving vehicle path planning method and device, vehicle and storage medium - Google Patents
Automatic driving vehicle path planning method and device, vehicle and storage medium Download PDFInfo
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- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
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Abstract
The invention discloses a method and a device for planning a path of an automatic driving vehicle, the vehicle and a storage medium, wherein the method comprises the following steps: when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range, the lane position of the vehicle in the current road is acquired through a forward-looking camera, whether the vehicle needs to change lanes or not is determined according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road, when the vehicle needs to change lanes is determined, the vehicle is controlled to run to the target lane according to the mapping relation between the vehicle and each lane line, and the path of the vehicle running into the target intersection from the target lane is determined according to the distance between a target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined through the forward-looking camera. The method has the advantages of strong portability, low cost and high accuracy.
Description
Technical Field
The embodiment of the invention relates to the field of automatic driving, in particular to a method and a device for planning a path of an automatic driving vehicle, the vehicle and a storage medium.
Background
With the development of science and technology, the automatic driving technology becomes a hotspot in the automobile industry. Path planning is a key technology for implementing automatic driving technology.
At present, global path planning in the automatic driving technology is generally realized through a high-precision map and high-precision positioning, the high-precision map is high in precision and complete in elements, but the high-precision map has the following main defects that the ① technology is immature, the communication protocol and interface specification industry has no unified standard temporarily, the ② map-collecting cost is high, a plurality of sensors such as laser radars and cameras need to be carried on a map-collecting vehicle, the ③ map-making period is long, the updating frequency is low, the map-collecting vehicle can be updated once in three months generally, the ④ auditing period is long, the map-collecting vehicle can be used commercially after a series of processes such as map examination and application of deflection plug-in units are required after the high-precision map data are manufactured according to.
Therefore, in the current path planning mode of the automatic driving vehicle, on one hand, the transportability is poor due to the fact that the unified standard is not available temporarily, on the other hand, the cost is high due to the fact that a special map collecting vehicle is needed to collect road information, and on the other hand, the accuracy of a path planned based on a high-precision map which is not updated timely is low due to the fact that the map updating frequency is low and the auditing period is long.
Disclosure of Invention
The invention provides a method and a device for planning a path of an automatic driving vehicle, the vehicle and a storage medium, which aim to solve the technical problems of poor transportability, high cost and low accuracy of the planned path of the conventional method for planning the path of the automatic driving vehicle.
In a first aspect, an embodiment of the present invention provides a method for planning a path of an autonomous vehicle, including:
when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range, acquiring the lane position of the vehicle in the current road through a forward-looking camera;
determining whether the vehicle needs to change lanes according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road;
when the fact that the vehicle needs to change lanes is determined, controlling the vehicle to run to a target lane according to the mapping relation between the vehicle and each lane line;
and determining a path for driving from the target lane to the target intersection according to the distance between the target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera.
In the method as described above, when it is determined that the distance between the vehicle and the target intersection in the road-level navigation information acquired in advance is within the preset distance range, the method further includes:
acquiring the road-level navigation information through a vehicle-mounted navigation system; or,
and acquiring the road-level navigation information through a control device.
In the method as shown above, the acquiring, by a forward-looking camera, a lane position of the vehicle in a current road includes:
acquiring a front environment image of the vehicle through the front-view camera;
and identifying the front environment image, and determining the lane position of the vehicle in the current road.
In the method, the mapping relationship between the vehicle and the lane line is as follows: y ═ C3*x3+C2*x2+C1*x+C0Wherein, C3、C2、C1And C0The vehicle front view camera coordinate system comprises a front view camera coordinate system, a front view camera coordinate system and a vehicle, wherein the front view camera coordinate system is used for recording the position of the vehicle, the front direction of the vehicle is used for recording the position of the vehicle, and the front direction of the vehicle is used for recording the position of the vehicle.
In the method, when it is determined that the vehicle needs to change lanes, the controlling the vehicle to travel to a target lane according to the mapping relationship between the vehicle and each lane line includes:
determining the distance between each target lane line and a target position according to the mapping relation between the vehicle and two target lane lines of the target lane;
taking the average value of the sum of the distances between each target lane line and the target position as the optimal position of the vehicle in the target lane;
controlling the vehicle to travel to the optimal position.
In the method as described above, when it is determined that the distance between the vehicle and the target intersection in the road-level navigation information acquired in advance is within the preset distance range, the method further includes:
acquiring the distance between the vehicle and the target intersection through a vehicle-mounted navigation system; or,
and determining the distance between the vehicle and the target intersection through a vehicle-mounted navigation system and the guideboard information acquired by the forward-looking camera.
In a second aspect, an embodiment of the present invention provides an automatic driving vehicle path planning apparatus, including:
the first acquisition module is used for acquiring the lane position of the vehicle in the current road through a forward-looking camera when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range;
the first determining module is used for determining whether the vehicle needs lane changing or not according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road;
the control module is used for controlling the vehicle to run to a target lane according to the mapping relation between the vehicle and each lane line when the fact that the vehicle needs to change lanes is determined;
and the second determining module is used for determining a path for driving from the target lane to the target intersection according to the distance between the target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera.
In a third aspect, an embodiment of the present invention further provides a vehicle, including:
one or more processors;
a memory for storing one or more programs;
the front-view camera is used for acquiring an image in front of the vehicle;
when executed by the one or more processors, cause the one or more processors to implement the method of automatically driving vehicle path planning as provided in the first aspect.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the method for planning a path of an autonomous vehicle as provided in the first aspect.
The embodiment provides a method, a device, a vehicle and a storage medium for planning a path of an automatic driving vehicle, wherein the method comprises the following steps: when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range, the lane position of the vehicle in the current road is acquired through a forward-looking camera, whether the vehicle needs to change lanes or not is determined according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road, when the vehicle needs to change lanes is determined, the vehicle is controlled to run to the target lane according to the mapping relation between the vehicle and each lane line, and the path of the vehicle running into the target intersection from the target lane is determined according to the distance between a target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined through the forward-looking camera. On one hand, the related technologies such as image acquisition and image recognition are mature technologies, the method is applicable to various vehicle platforms and has strong portability, on the other hand, the method is based on the existing sensors and controllers of the existing automatic driving vehicle in the implementation process, the hardware cost is not increased, the cost is low, on the other hand, the map updating frequency of the existing vehicle-mounted navigation system is high, and the accuracy of the path of the vehicle planned based on the map is high.
Drawings
FIG. 1 is a system architecture diagram of a method for planning a path of an autonomous vehicle according to the present invention;
FIG. 2 is a schematic flow chart diagram illustrating an embodiment of a method for planning a route of an autonomous vehicle according to the present invention;
FIG. 3 is a schematic view of the front camera coordinate system in the embodiment of FIG. 2;
FIG. 4 is a schematic diagram of a path planned using the embodiment of FIG. 2;
FIG. 5 is a schematic structural diagram of an embodiment of an automatic vehicle path planning apparatus provided by the present invention;
fig. 6 is a schematic structural diagram of a vehicle according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Fig. 1 is a system architecture diagram of the automatic driving vehicle path planning method provided by the present invention. As shown in fig. 1, the system of the automatic driving vehicle path planning method provided by this embodiment includes: a forward looking camera 11, a vehicle navigation system 12 and an autopilot controller 13. The forward-looking camera 11 and the vehicle-mounted navigation system 12 are both connected to an automatic driving Controller 13, which may be specifically connected through a Controller Area Network (CAN) bus. The front view camera 11 in the present embodiment may be provided on a front windshield of the vehicle, and more specifically, may be provided on a side of the front windshield that is located inside the vehicle. The automatic driving controller 13 may be connected to a vehicle CAN network through a CAN bus to obtain information such as a vehicle speed, a steering wheel angle, a longitudinal and lateral acceleration, a yaw rate, and the like, and send a control signal to the vehicle after a path is planned, so as to control the vehicle to allow the vehicle to travel along the planned path.
Fig. 2 is a schematic flow chart of an embodiment of a method for planning a route of an autonomous vehicle according to the present invention. The embodiment is suitable for a scenario of path planning for an autonomous vehicle. The present embodiment may be implemented by an autonomous vehicle path planning apparatus, which may be implemented by software and/or hardware, and may be integrated into a central control host or an autonomous controller of a vehicle. As shown in fig. 2, the method for planning the route of the autonomous vehicle provided by this embodiment includes the following steps:
step 201: and when the distance between the vehicle and the target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range, acquiring the lane position of the vehicle in the current road through the forward-looking camera.
Specifically, the vehicle in the present embodiment is a vehicle having an automatic driving function.
The road-level navigation information in this embodiment refers to navigation information in which the navigation information is only accurate to the road name but not to the lane line. The road-level navigation information may include a start point, an end point, a road name, an intersection, and turning information corresponding to the intersection. For example, the road-level navigation information may be that the vehicle enters the G road from the F intersection after driving for 5 kilometers along the E road, and reaches the destination after driving for 3 kilometers along the G road.
The target intersection in this embodiment refers to an intersection closest to the current position of the vehicle in the road-level navigation information. In other words, the target intersection refers to an intersection into which the vehicle is going to drive.
In an implementation manner, the road-level navigation information in this embodiment may be acquired by a vehicle-mounted navigation system. In another implementation manner, the road-level navigation information in this embodiment may be acquired through the control device. Illustratively, the control device referred to herein may be a cell phone. The control device may establish a wireless or wired connection with the autonomous vehicle path planning apparatus, through which road-level navigation information is sent to the autonomous vehicle path planning apparatus.
In one implementation, the autonomous vehicle path planning apparatus may obtain a distance between the vehicle and the target intersection through a vehicle navigation system. The vehicle-mounted navigation system can realize the positioning of the vehicle, and can determine the distance between the vehicle and the target intersection according to the positioning of the vehicle and the position of the target intersection.
In another implementation, the route planning apparatus for an autonomous vehicle may determine the distance between the vehicle and the target intersection based on the guideboard information acquired by the forward-looking camera. During the driving process of the vehicle, the forward-looking camera can acquire images of the roadside signboards, and the signboards in the embodiment include distances from the intersection, for example, "2 km from the ramp". The collected images are identified, and the information of the road sign representation can be determined, namely the distance between the vehicle and the target intersection is determined.
In another implementation, the route planning apparatus for an autonomous vehicle may determine a distance between the vehicle and the target intersection based on the guideboard information acquired by the vehicle navigation system and the forward-looking camera. Because the distance between the vehicle and the target intersection determined by the vehicle-mounted navigation system and the distance between the vehicle and the target intersection determined by the forward-looking camera both have errors, in the implementation mode, the distance between the vehicle and the target intersection can be determined by combining the vehicle-mounted navigation system and the forward-looking camera, so that the accuracy of the acquired distance is improved. For example, the distance between the vehicle and the target intersection determined by the vehicle-mounted navigation system and the distance between the vehicle and the target intersection determined by the forward-looking camera may be weighted and averaged to obtain the distance between the vehicle and the target intersection.
In this embodiment, the preset distance range is determined according to empirical data. Alternatively, the predetermined distance range may be between 1 km and 1.5 km.
When the distance between the vehicle and the target intersection is determined to be within the preset distance range, the vehicle is shown to drive into the target intersection from the current road after the preset time period. In order to realize that the vehicle successfully drives into the target intersection from the current road, the vehicle is required to drive into the lane which can enter the target intersection without violating the back crossing rule from the current lane. At this time, it is necessary to acquire the lane position of the vehicle in the current road to determine whether the vehicle needs to change lanes. The lane position indicates which lane of the current road the vehicle is in.
Optionally, the automatic driving vehicle path planning apparatus may acquire an environment image in front of the vehicle through the front-view camera, identify the environment image in front, and determine a lane position of the vehicle on the current road. In this implementation, when the front environment image is recognized, the recognition may be performed by a recognition template set in advance.
One possible recognition procedure is to recognize the edge of the current road according to the recognition template and the objects on the left and right sides of the image in the front environment image, for example, when the object on the left side is the isolation zone, the left lane line of the first lane on the right side of the isolation zone may be determined, and when the object on the right side is the emergency lane, the right lane line of the nth lane on the left side of the emergency lane may be determined. After the edge of the current road is identified, the total number of lanes of the current road can be determined according to the number of lane lines. And determining the lane position of the vehicle on the current road according to the number of the left lane lines, the number of the right lane lines and the total number of the lanes of the vehicle, so as to realize lane-level positioning.
Step 202: and determining whether the vehicle needs to change lanes according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road.
Specifically, in the road-level navigation information, each intersection corresponds to turning information. After the lane position of the vehicle on the current road is determined, whether the vehicle needs to change lanes or not can be determined according to the lane position of the vehicle on the current road and the turning information corresponding to the target intersection. The specific process is as follows.
And if the middle lane of the vehicle in the current road is determined, wherein the middle lane refers to lanes except for the leftmost lane, the rightmost lane and the emergency lane, and the turning information corresponding to the target intersection is left-turning, determining that the vehicle needs to change lanes.
And if the vehicle is determined to be in the middle lane of the current road and the turning information corresponding to the target intersection is right turning, determining that the vehicle needs to change lanes.
And if the vehicle is determined to be in the leftmost lane except the emergency lane in the current road and the turning information corresponding to the target intersection is left-turning, determining that the vehicle does not need to change lanes.
And if the vehicle is determined to be in the leftmost lane except the emergency lane in the current road and the turning information corresponding to the target intersection is the right turn, determining that the vehicle needs to change lanes.
And if the rightmost lane of the vehicle in the current road except the emergency lane is determined and the turning information corresponding to the target intersection is left-turning, determining that the vehicle needs to change lanes.
And if the rightmost lane of the vehicle in the current road except the emergency lane is determined and the turning information corresponding to the target intersection is right turning, determining that the vehicle does not need to change lanes.
Step 203: and when the vehicle is determined to need to change lanes, controlling the vehicle to run to the target lane according to the mapping relation between the vehicle and each lane line.
Specifically, the target lane in the present embodiment refers to a lane that can enter the target intersection without violating traffic regulations.
When the vehicle is determined to need to change lanes, the vehicle can be controlled to run to the target lane according to the mapping relation between the vehicle and each lane line.
In a specific implementation, the mapping relationship between the vehicle and the lane line can be expressed by a formula: y ═ C3*x3+C2*x2+C1*x+C0. Wherein, C3、C2、C1And C0Are all preset parameters. C3Representing the variation of curvature of the lane line, C2Representing the curvature of the lane line, C1Representing the slope of the lane line, C0When x is 0, the distance between the lane line and the vehicle is represented. X represents the distance between the current position of the vehicle and the target position of the vehicle in front of the X axis in the coordinate system of the front-view camera, Y represents the distance between the lane line and the target position in the coordinate system of the front-view camera, the origin of the coordinate system of the front-view camera is the position of the front-view camera, the positive direction of the X axis is the advancing direction of the vehicle, and the positive direction of the Y axis is the direction perpendicular to the right direction of the X axis.
For each stripThe lane lines correspond to the mapping relation between the vehicles and the lane lines. In the mapping relation, C corresponding to different lane lines3、C2、C1And C0Different. C3、C2、C1And C0Are parameters predetermined from empirical data or experimentation.
Fig. 3 is a schematic diagram of the front camera coordinate system in the embodiment of fig. 2. As shown in fig. 3, the origin of the coordinate system of the front camera is the position of the front camera, the positive direction of the X-axis is the forward direction of the vehicle, and the positive direction of the Y-axis is the direction perpendicular to the right of the X-axis. During the running of the vehicle, the coarse positioning of the vehicle can be realized through the satellite 31 involved in the vehicle navigation system. X in this embodiment refers to a distance between the current position of the vehicle and a target position M of the vehicle forward in the X axis direction, and y refers to a distance between the lane line and the target position M. The value of x may also be determined from empirical data.
Based on the mapping relationship, the specific implementation process of step 203 may be: determining the distance between each target lane line and a target position according to the mapping relation between the vehicle and two target lane lines of the target lane; taking the average value of the sum of the distances between each target lane line and the target position as the optimal position of the vehicle in the target lane; and controlling the vehicle to run to the optimal position.
Based on the mapping relation and two target lane lines of the target lane, C corresponding to different target lane lines of the target lane3、C2、C1And C0In contrast, when the x value is known, the distance between the two target lane lines and the target position can be determined. As shown in fig. 3, it is assumed that the lane 3 is a target lane, and the two target lane lines are a target lane line O and a target lane line P. The distance between the target lane line O and the target position M is N, and the distance between the target lane line P and the target position M is K. And taking the average value of the distance N and the distance K as the optimal position of the vehicle in the target lane, and assuming that the optimal position is H, controlling the vehicle to run to the optimal position H by the automatic driving vehicle path planning device. The autonomous vehicle path planning device may specifically determine the control parameters based on the current operating parameters of the vehicle and the optimal position,and sending the control parameter to the CAN network of the whole vehicle.
In addition, during the travel of the vehicle, the optimal position of the vehicle is determined based on the mapping relationship between the vehicle and each lane line, and the vehicle is controlled to travel to the optimal position. During a vehicle lane change, the optimal position is the position in the target lane. During the driving of the vehicle along the same lane, the optimal position is the position in the current lane.
Step 204: and determining a path for driving from the target lane to the target intersection according to the distance between the target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera.
Specifically, the target guideboard corresponding to the target intersection refers to a guideboard in which a distance from the target intersection is within a preset range or indicated information is associated with the target intersection. The distance between the target guideboard corresponding to the target intersection and the target intersection can be acquired from road-level navigation information or acquired from a navigation map of a vehicle-mounted navigation system.
The distance between the vehicle and the target intersection can be determined by the forward looking camera. The specific process can be as follows: the target crossing is firstly identified through the image collected by the forward-looking camera, and then the distance between the vehicle and the target crossing is determined. In one implementation, the forward-looking camera may be a camera capable of determining object distance, e.g., a depth camera. In another implementation, a laser radar is integrated into the forward-looking camera to determine the distance between the vehicle and the target intersection according to the point cloud data.
After the vehicle travels to the target lane, it is necessary to determine when the vehicle has made a turn to enter the target intersection. In this embodiment, a route from the target lane to the target intersection is determined according to the distance between the target guideboard and the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera. The path from the target lane to the target intersection may include a time point of the entry from the target lane to the target intersection. For example, if the distance between the target road sign and the target intersection is 5 meters and the distance between the vehicle and the target intersection is 50 meters, the determined path is to make a turn within a length of 5 meters and enter the target intersection after the vehicle travels 45 meters on the target lane, or the determined path is to make a turn and enter the target intersection after a time point determined according to 5 meters after the vehicle travels 45 meters on the target lane.
The above process is described below as a specific example. Fig. 4 is a schematic diagram of a path planned using the embodiment of fig. 2. As shown in fig. 4, the road-level navigation information is from a starting point a to travel along the R-way-turn right to the D-way-travel along the T-way-to the end point B. The vehicle will pass three guideboards along the way and the intersection C. After starting from the starting point a, the vehicle travels along the R road. During the driving of the vehicle, the distance of the vehicle from the target intersection D is determined. When the distance between the vehicle and the target intersection D is determined to be within the preset distance range, the distance between the vehicle and the target intersection is within the preset distance range when the vehicle is at the U point. At the moment, the lane position of the vehicle on the current road R is acquired as a left lane through the front-view camera. And the turning information corresponding to the target intersection D is a right turn. It is determined that the vehicle needs to change lanes. Thereafter, step 203 and step 204 are executed to control the vehicle to enter the T-way from the target intersection D.
The method for planning the path of the automatic driving vehicle provided by the embodiment comprises the following steps: when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range, the lane position of the vehicle in the current road is acquired through a forward-looking camera, whether the vehicle needs to change lanes or not is determined according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road, when the vehicle needs to change lanes is determined, the vehicle is controlled to run to the target lane according to the mapping relation between the vehicle and each lane line, and the path of the vehicle running into the target intersection from the target lane is determined according to the distance between a target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined through the forward-looking camera. On one hand, the related technologies such as image acquisition and image recognition are mature technologies, the method is applicable to various vehicle platforms and has strong portability, on the other hand, the method is based on the existing sensors and controllers of the existing automatic driving vehicle in the implementation process, the hardware cost is not increased, the cost is low, on the other hand, the map updating frequency of the existing vehicle-mounted navigation system is high, and the accuracy of the path of the vehicle planned based on the map is high.
Fig. 5 is a schematic structural diagram of an embodiment of the automatic driving vehicle path planning apparatus provided by the present invention. As shown in fig. 5, the automatic driving vehicle path planning apparatus provided in this embodiment includes: a first obtaining module 51, a first determining module 52, a control module 53 and a second determining module 54.
The first obtaining module 51 is configured to obtain a lane position of the vehicle on the current road through the forward-looking camera when it is determined that the distance between the vehicle and the target intersection in the pre-obtained road-level navigation information is within a preset distance range.
Optionally, the apparatus further comprises a second obtaining module. The second acquisition module is used for acquiring road-level navigation information through the vehicle-mounted navigation system; or the second acquisition module is used for acquiring the road-level navigation information through the control equipment.
Optionally, the apparatus further comprises a third obtaining module. The third acquisition module is used for acquiring the distance between the vehicle and the target intersection through the vehicle-mounted navigation system; or the third acquisition module is used for determining the distance between the vehicle and the target intersection through the guideboard information acquired by the vehicle-mounted navigation system and the forward-looking camera.
Optionally, in terms of acquiring the lane position of the vehicle in the current road through the forward-looking camera, the first acquiring module 51 is specifically configured to: acquiring a front environment image of the vehicle through a front-view camera; and recognizing the front environment image and determining the lane position of the vehicle in the current road.
The first determining module 52 is configured to determine whether the vehicle needs to change lanes according to the turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle on the current road.
And the control module 53 is used for controlling the vehicle to run to the target lane according to the mapping relation between the vehicle and each lane line when the vehicle is determined to need to change lanes.
In one implementation, the mapping relationship between the vehicle and the lane line is:
y＝C3*x3+C2*x2+C1*x+C0
wherein, C3、C2、C1And C0The forward direction of the X axis is the forward direction of the vehicle, and the forward direction of the Y axis is the direction perpendicular to the X axis.
Based on the mapping relationship, the control module 53 is specifically configured to: determining the distance between each target lane line and a target position according to the mapping relation between the vehicle and two target lane lines of the target lane; taking the average value of the sum of the distances between each target lane line and the target position as the optimal position of the vehicle in the target lane; and controlling the vehicle to run to the optimal position.
And a second determining module 54, configured to determine a path from the target lane to the target intersection according to the distance between the target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera.
The automatic driving vehicle path planning device provided by the embodiment of the invention can execute the automatic driving vehicle path planning method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Fig. 6 is a schematic structural diagram of a vehicle according to the present invention. As shown in fig. 6, the vehicle includes a processor 70 and memory 71, and further includes a front-view camera 72 for capturing images in front of the vehicle. The number of processors 70 in the vehicle may be one or more, and one processor 70 is taken as an example in fig. 6; the processor 70 and memory 71 of the vehicle may be connected by a bus or other means, as exemplified by the bus connection in fig. 6.
The memory 71 serves as a computer-readable storage medium for storing software programs, computer-executable programs, and modules, such as program instructions and modules corresponding to the automatic driving vehicle path planning method in the embodiment of the present invention (for example, the first obtaining module 51, the first determining module 52, the control module 53, and the second determining module 54 in the automatic driving vehicle path planning apparatus). The processor 70 executes various functional applications and data processing of the vehicle by running software programs, instructions and modules stored in the memory 71, that is, implements the above-described automated driving vehicle path planning method.
The memory 71 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the vehicle, and the like. Further, the memory 71 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 71 may further include memory located remotely from the processor 70, which may be connected to the vehicle over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The present invention also provides a storage medium containing computer-executable instructions which, when executed by a computer processor, perform a method of route planning for an autonomous vehicle, the method comprising:
when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range, acquiring the lane position of the vehicle in the current road through a forward-looking camera;
determining whether the vehicle needs to change lanes according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road;
when the fact that the vehicle needs to change lanes is determined, controlling the vehicle to run to a target lane according to the mapping relation between the vehicle and each lane line;
and determining a path for driving from the target lane to the target intersection according to the distance between the target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera.
Of course, the storage medium containing the computer-executable instructions provided by the embodiments of the present invention is not limited to the method operations described above, and may also perform related operations in the method for planning a route of an autonomous vehicle provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the automatic vehicle path planning apparatus, the units and modules included in the automatic vehicle path planning apparatus are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for planning a path for an autonomous vehicle, comprising:
when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range, acquiring the lane position of the vehicle in the current road through a forward-looking camera;
determining whether the vehicle needs to change lanes according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road;
when the fact that the vehicle needs to change lanes is determined, controlling the vehicle to run to a target lane according to the mapping relation between the vehicle and each lane line;
and determining a path for driving from the target lane to the target intersection according to the distance between the target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera.
2. The method according to claim 1, wherein when it is determined that the distance between the vehicle and the target intersection in the pre-acquired road-level navigation information is within a preset distance range, the method further comprises, before acquiring the lane position of the vehicle in the current road by a forward-looking camera:
acquiring the road-level navigation information through a vehicle-mounted navigation system; or,
and acquiring the road-level navigation information through a control device.
3. The method of claim 1 or 2, wherein the obtaining of the lane position of the vehicle in the current road by a forward looking camera comprises:
acquiring a front environment image of the vehicle through the front-view camera;
and identifying the front environment image, and determining the lane position of the vehicle in the current road.
4. The method according to claim 1 or 2, wherein the mapping relationship between the vehicle and the lane line is: y ═ C3*x3+C2*x2+C1*x+C0Wherein, C3、C2、C1And C0The vehicle front view camera coordinate system comprises a front view camera coordinate system, a front view camera coordinate system and a vehicle, wherein the front view camera coordinate system is used for recording the position of the vehicle, the front direction of the vehicle is used for recording the position of the vehicle, and the front direction of the vehicle is used for recording the position of the vehicle.
5. The method according to claim 4, wherein when it is determined that the vehicle needs to change lanes, controlling the vehicle to travel to a target lane according to a mapping relationship of the vehicle to each lane line includes:
determining the distance between each target lane line and a target position according to the mapping relation between the vehicle and two target lane lines of the target lane;
taking the average value of the sum of the distances between each target lane line and the target position as the optimal position of the vehicle in the target lane;
controlling the vehicle to travel to the optimal position.
6. The method according to claim 1 or 2, wherein when it is determined that the distance between the vehicle and the target intersection in the pre-acquired road-level navigation information is within a preset distance range, the method further comprises, before acquiring the lane position of the vehicle in the current road by a forward-looking camera:
acquiring the distance between the vehicle and the target intersection through a vehicle-mounted navigation system; or,
and determining the distance between the vehicle and the target intersection through a vehicle-mounted navigation system and the guideboard information acquired by the forward-looking camera.
7. An autonomous vehicle path planning apparatus, comprising:
the first acquisition module is used for acquiring the lane position of the vehicle in the current road through a forward-looking camera when the distance between the vehicle and a target intersection in the pre-acquired road-level navigation information is determined to be within a preset distance range;
the first determining module is used for determining whether the vehicle needs lane changing or not according to turning information corresponding to the target intersection in the road-level navigation information and the lane position of the vehicle in the current road;
the control module is used for controlling the vehicle to run to a target lane according to the mapping relation between the vehicle and each lane line when the fact that the vehicle needs to change lanes is determined;
and the second determining module is used for determining a path for driving from the target lane to the target intersection according to the distance between the target guideboard corresponding to the target intersection and the distance between the vehicle and the target intersection determined by the forward-looking camera.
8. The apparatus of claim 7, further comprising a second acquisition module;
the second acquisition module is used for acquiring the road-level navigation information through a vehicle-mounted navigation system; or,
and the second acquisition module is used for acquiring the road-level navigation information through control equipment.
9. A vehicle, characterized in that the vehicle comprises:
one or more processors;
a memory for storing one or more programs;
the front-view camera is used for acquiring an image in front of the vehicle;
when executed by the one or more processors, cause the one or more processors to implement the autonomous vehicle path planning method of any of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method for path planning for an autonomous vehicle according to any of claims 1 to 6.
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| CN114394111B (en) * | 2021-12-29 | 2023-08-29 | 阿波罗智联(北京)科技有限公司 | Lane changing method for automatic driving vehicle |
| CN114394111A (en) * | 2021-12-29 | 2022-04-26 | 阿波罗智联(北京)科技有限公司 | Lane changing method for autonomous vehicle |
| CN114518122A (en) * | 2022-02-18 | 2022-05-20 | 腾讯科技（深圳）有限公司 | Driving navigation method, driving navigation device, computer equipment, storage medium and computer program product |
| CN114987541A (en) * | 2022-05-30 | 2022-09-02 | 中国第一汽车股份有限公司 | Vehicle control method, vehicle control device, storage medium, processor, and electronic device |
| CN115402321A (en) * | 2022-09-30 | 2022-11-29 | 重庆长安汽车股份有限公司 | Lane change strategy determination method, system, electronic equipment and storage medium |
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