CN115060279B - Path planning method, path planning device, electronic equipment and computer readable medium - Google Patents
Path planning method, path planning device, electronic equipment and computer readable medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- 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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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
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Abstract
The invention discloses a path planning method, a path planning device, electronic equipment and a computer readable medium, and relates to the technical field of automatic driving. The method comprises the following steps: determining information of an obstacle between a current position of the vehicle and a destination of the vehicle; generating a grid area around a destination, and determining a first cost of each grid according to a preset first rule and information of obstacles; determining a plurality of alternative destinations around the destination, and determining a second cost for each alternative destination according to a preset second rule and the first cost of the grid; and sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets the preset condition according to the order from the second cost to the large cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle. The method can ensure the accurate stop at the station and the running safety, has less calculation amount and ensures the real-time performance of path planning.
Description
Technical Field
The present invention relates to the field of autopilot technology, and in particular, to a path planning method, apparatus, electronic device, and computer readable medium.
Background
In an automatic driving scene, an unmanned vehicle stop is a common task scene, and is particularly common in the fields of unmanned taxis and unmanned buses. In an autopilot scenario, a travel path needs to be planned for an unmanned vehicle based on environmental information. In the related art, path planning may be classified into global path planning and local path planning according to a degree of knowledge of environmental information. The global path planning needs to master all environment information, and the path planning is carried out according to all the information of the environment map; the local path planning only needs to collect the environment information in real time by the sensor, understand the environment map information, and then determine the position of the map and the local barrier distribution condition, so that the optimal path from the current node to a certain sub-target node can be selected.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a path planning method, apparatus, electronic device, and computer readable medium, which can ensure running safety while ensuring successful completion of a docking task, effectively reduce the calculation amount, and ensure real-time performance of path planning.
To achieve the above object, according to an aspect of the embodiments of the present invention, there is provided a path planning method, including:
determining information of an obstacle between a current location of a vehicle and a destination of the vehicle;
generating a grid area around the destination, and determining a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid;
determining a plurality of alternative destinations around the destination, and determining a second cost for each of the alternative destinations according to a preset second rule and the first cost of the grid;
and sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets a preset condition according to the order from the low cost to the high cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle.
Optionally, generating a mesh region around the destination includes: determining a trajectory curve between a current location of the vehicle and a destination of the vehicle; detecting whether the track curve collides with the obstacle according to the information of the obstacle; if yes, generating a grid area around the destination; if not, taking a track curve between the current position of the vehicle and the destination of the vehicle as a running path of the vehicle.
Optionally, the information of the obstacle includes position information of the obstacle;
according to a preset first rule and information of the obstacle, determining a first cost of each grid in the grid area comprises the following steps: determining, for each mesh, whether the mesh collides with the obstacle according to information of the obstacle; if yes, determining that the first cost of the grid is a preset value; if not, determining a first distance between the grid and the obstacle according to the position information of the obstacle; determining a second distance between the mesh and the destination; and determining a first cost of the grid according to the first distance and the second distance.
Optionally, determining the first cost of the grid according to the first distance and the second distance includes: determining a minimum first distance from among a plurality of first distances between the mesh and a plurality of the obstacles in the case where the number of the obstacles is plural; and determining the first cost of the grid according to the minimum first distance and the second distance.
Optionally, determining a plurality of alternative destinations around the destination includes: generating a target graph taking the destination as a center, wherein the coverage range of the target graph is heavy to that of the grid area; sampling on the target graph, and taking a sampling point as the alternative destination.
Optionally, determining the second cost of each of the alternative destinations according to a preset second rule and the first cost of the grid includes: for each alternative destination, determining a first cost of a grid in which the alternative destination is located; determining a third distance between the alternative destination and the current location of the vehicle; and determining a second cost of the alternative destination according to the first cost and the third distance.
Optionally, the method further comprises: before determining whether a trajectory curve between the candidate destination and a current position of the vehicle satisfies a preset condition, determining an invalid candidate among the plurality of candidate destinations, and screening out the invalid candidate.
Optionally, determining an invalid alternative of the plurality of alternative destinations includes: determining, for each alternative destination, whether a mesh in which the alternative destination is located collides with the obstacle; if so, determining the alternative destination as an invalid alternative.
Optionally, the method further comprises: if the track curves between all the alternative destinations and the current position of the vehicle do not meet the preset condition, determining a new alternative destination, and judging whether the track curve between the new alternative destination and the current position of the vehicle meets the preset condition according to the order of the second cost of the new alternative destination from small to large.
Optionally, the method further comprises: determining whether an obstacle moves or not in the process that the automatic driving vehicle runs according to the running path; if yes, the running path of the vehicle is planned again according to the information of the moved obstacle.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a path planning apparatus including:
an obstacle determination module for determining information of an obstacle between a current position of a vehicle and a destination of the vehicle;
the first calculation module is used for generating a grid area around the destination and determining a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid;
a second calculation module, configured to determine a plurality of alternative destinations around the destination, and determine a second cost of each of the alternative destinations according to a preset second rule and the first cost of the grid;
and the path determining module is used for sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets a preset condition according to the order from the low cost to the high cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle.
Optionally, the first computing module is further configured to: determining a trajectory curve between a current location of the vehicle and a destination of the vehicle; detecting whether the track curve collides with the obstacle according to the information of the obstacle; if yes, generating a grid area around the destination; if not, taking a track curve between the current position of the vehicle and the destination of the vehicle as a running path of the vehicle.
Optionally, the information of the obstacle includes position information of the obstacle;
the first computing module is further for: determining, for each mesh, whether the mesh collides with the obstacle according to information of the obstacle; if yes, determining that the first cost of the grid is a preset value; if not, determining a first distance between the grid and the obstacle according to the position information of the obstacle; determining a second distance between the mesh and the destination; and determining a first cost of the grid according to the first distance and the second distance.
Optionally, the first computing module is further configured to: determining a minimum first distance from among a plurality of first distances between the mesh and a plurality of the obstacles in the case where the number of the obstacles is plural; and determining the first cost of the grid according to the minimum first distance and the second distance.
Optionally, the second computing module is further configured to: generating a target graph taking the destination as a center, wherein the coverage range of the target graph is overlapped with the coverage range of the grid area; sampling is carried out on the target graph, and sampling points are used as the alternative destinations.
Optionally, the second computing module is further configured to: for each alternative destination, determining a first cost of a grid in which the alternative destination is located; determining a third distance between the alternative destination and the current location of the vehicle; and determining a second cost of the alternative destination according to the first cost and the third distance.
Optionally, the apparatus further comprises a screening module for: an invalid alternative of the plurality of alternative destinations is determined and screened out.
Optionally, the screening module is further configured to: determining, for each alternative destination, whether a mesh in which the alternative destination is located collides with the obstacle; if so, determining the alternative destination as an invalid alternative.
Optionally, the apparatus further comprises a retry module for: if the track curves between all the alternative destinations and the current position of the vehicle do not meet the preset condition, determining a new alternative destination, and judging whether the track curve between the new alternative destination and the current position of the vehicle meets the preset condition according to the order of the second cost of the new alternative destination from small to large.
Optionally, the retry module is further configured to: determining whether an obstacle movement occurs in the process that the automatic driving vehicle runs according to the running path; if yes, the running path of the vehicle is planned again according to the information of the moved obstacle.
To achieve the above object, according to still another aspect of an embodiment of the present invention, there is provided an electronic device including: one or more processors; and the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are enabled to realize the path planning method of the embodiment of the invention.
To achieve the above object, according to still another aspect of the embodiments of the present invention, there is provided a computer-readable medium having stored thereon a computer program which, when executed by a processor, implements a path planning method of the embodiments of the present invention.
One embodiment of the above invention has the following advantages or benefits:
generating a grid area around a vehicle destination, and determining a first cost of each grid in the grid area according to information of an obstacle between the current position of the vehicle and the destination and a preset first rule; the first price is used for indicating the feasibility of the grid, and the smaller the first price is, the higher the feasibility is, the safer the running is, so that the safe area and the dangerous area in the grid area can be determined; then determining a plurality of alternative destinations around the destination, and determining a second cost of each alternative destination according to a preset second rule and the first cost of the grid; and judging whether the track curve between the alternative destination and the current position of the vehicle meets the preset condition or not in sequence according to the order from small to large of the second cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle, so that the running safety can be ensured while the accurate stop at the station is ensured, the calculated amount is less, and the real-time performance of path planning is ensured.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 schematically illustrates a flow chart of a path planning method of an embodiment of the present invention;
FIG. 2 shows a schematic diagram of a grid area in a path planning method of an embodiment of the present invention;
FIG. 3 shows a schematic diagram of an alternative destination in a path planning method of an embodiment of the present invention;
FIG. 4 schematically shows a flow chart of a path planning method of another embodiment of the invention;
fig. 5 schematically shows a schematic structural diagram of a path planning apparatus according to an embodiment of the present invention;
fig. 6 schematically shows a structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 schematically shows a flowchart of a path planning method according to an embodiment of the present invention, where the path planning method according to the embodiment of the present invention may be applied to an on-board control unit of a vehicle, or may be applied to a server, and the server may issue a travel path of the vehicle to the vehicle after determining the travel path. As shown in fig. 1, the method includes:
step 101: information of an obstacle between a current location of a vehicle and a destination of the vehicle is determined.
In this embodiment, the destination of the vehicle may be determined according to a specific scenario, for example, the parking passenger task may obtain the task end point (i.e., the destination) on the map, and issue the task end point to the vehicle through the cloud. The current position of the vehicle may be obtained from positioning information of an in-vehicle integrated navigation module previously provided on the vehicle. The information of the obstacle may be acquired by an in-vehicle sensor such as a mono/binocular camera, a fisheye camera, a millimeter wave radar, an ultrasonic radar, a laser radar, or the like. The obstacle may include, for example, a pedestrian, an object on a road surface, a construction section, a bumpy road surface, or the like, and the present invention is not limited thereto. Information of the obstacle may include, but is not limited to: the location of the obstacle, the status of the obstacle (e.g., stationary or moving), the type of obstacle (e.g., pedestrian, object, construction road segment, etc.). The information of the obstacle can also be obtained from the map, for example, if a construction road section exists on the road section where the destination is located, the information of the construction road section can be obtained through marking information on the map. The vehicle in the embodiment of the invention may be an automatic driving vehicle (also called an unmanned vehicle), such as an unmanned taxi, an unmanned bus, etc., and the invention is not limited herein.
Step 102: generating a grid area around the destination, and determining a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid.
Wherein the mesh area generated around the destination may be a positive direction, a rectangle, a circle, or the like, and the present invention is not limited thereto. As an example, as shown in fig. 2, the grid area is square, and the grid within the grid area is also square. In the embodiment of the invention, the size of the grid area and the size of the grid can be flexibly set according to the vehicle parameters, the scene task and the environment of the destination, and the method is not limited. As an example, in a parking guest scenario, the side length of the grid may be set to 0.5 meters to compromise both the speed of the vehicle and the driving safety. After the grid area is generated, an obstacle between the current position of the vehicle and the destination may be marked within the grid area.
After the grid area is generated, a first cost is calculated for each grid within the grid area, the first cost being used to indicate the feasibility of the grid, the lower the cost, the higher the feasibility, the more suitable the vehicle will be to run. If the grid collides with an obstacle, the risk of the grid is determined, and the first price of the grid is set to a preset value, such as infinity. When judging whether the grid collides with the obstacle, the obstacle can be converted into a rectangle (the obstacle completely falls into the rectangle), then whether the grid and the rectangle have an overlapping part is determined according to the hyperplane segmentation theorem, and if the grid and the rectangle have an overlapping part, the grid collides with the obstacle is determined.
For a mesh that does not collide with an obstacle, its first cost may be determined according to the following procedure:
determining a first distance between the grid and the obstacle according to the position information of the obstacle;
determining a second distance between the mesh and the destination;
and determining a first cost of the grid according to the first distance and the second distance.
Wherein the first distance of the mesh from the obstacle may be a distance between a center of the mesh and a center of the obstacle. The smaller the first distance, the more dangerous the vehicle will travel on the grid. The second distance between the mesh and the destination may be the distance between the center of the mesh and the destination, the smaller the second distance, the more efficient. After determining the first distance and the second distance, a first cost of the grid may be calculated according to a pre-set cost function.
As an example, the preset cost function may be represented by the following formula (1):
cost_net＝obstacle_distance-target_distance(1)
where cost_net represents the first cost of the grid, object_distance represents the first distance, and target_distance represents the second distance.
In an alternative embodiment of the present invention, a weight coefficient corresponding to the first distance and/or the second distance may be set when calculating the first cost of the grid, as shown in the following formula (2):
cost_net＝k_obstacle*obstacle_distance-k_target*target_distance(2)
Where k_obstacle represents a weight coefficient corresponding to a first distance and k_target represents a weight coefficient corresponding to a second distance. Since the units of the obstacle_distance and the target_distance are the same, k_obstacle=k_target=1 may be set by default to indicate that the weights of the obstacle and the target are the same, and then the adjustment is performed according to the specific details of the task, for example, k_obstacle may be reduced when the safety is desired to be ensured as much as possible, and k_target may be reduced when the endpoint is desired to be reached as soon as possible.
Step 103: a plurality of alternative destinations are determined around the destination, and a second cost for each of the alternative destinations is determined according to a preset second rule and the first cost of the grid.
Wherein the alternative destination may be determined according to the following procedure:
generating a target graph taking the destination as a center, wherein the coverage range of the target graph is overlapped with the coverage range of the grid area;
sampling is carried out on the target graph, and sampling points are used as the alternative destinations.
The target graph centered on the destination may fall entirely or partially within the grid region. The target pattern may be circular, square, rectangular, etc., and the invention is not limited in this regard. In an alternative embodiment, as shown in fig. 3, a circle may be generated with the side of the mesh as a radius centered on the destination (assuming the side of the mesh is r). After a circle centered on the destination is generated, the circle may be uniformly sampled with the sampling points as alternative destinations.
Step 104: and sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets a preset condition according to the order from the low cost to the high cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle.
The preset conditions may include, but are not limited to, a minimum turning radius of the vehicle.
In an alternative embodiment, the alternative destinations may be ordered in a second cost-effective order, and then a loop of the following process is performed according to the order until the travel path of the vehicle is determined or all the alternative destinations are traversed:
generating a trajectory curve between the current position of the vehicle and the alternative destination using a cubic polynomial, a penta-order polynomial, or a hepta-order polynomial;
judging whether the track curve meets preset conditions or not;
if the track curve meets the preset condition, taking the track curve as a running path of the vehicle;
if not, the next alternative destination is judged.
In an alternative embodiment, a track curve of the current position of the vehicle and the alternative destination may also be generated according to the Reed-Shepps curve, and if the track curve can be successfully generated, the track curve is determined to be the running path of the vehicle.
According to the path planning method, a grid area is generated around a vehicle destination, and the first cost of each grid in the grid area is determined according to the information of the obstacle between the current position of the vehicle and the destination and a preset first rule; the first price is used for indicating the feasibility of the grid, and the smaller the first price is, the higher the feasibility is, the safer the running is, so that the safe area and the dangerous area in the grid area can be determined; then determining a plurality of alternative destinations around the destination, and determining a second cost of each alternative destination according to a preset second rule and the first cost of the grid; and judging whether the track curve between the alternative destination and the current position of the vehicle meets the preset condition or not in sequence according to the order from small to large of the second cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle, so that the running safety can be ensured while the accurate stop at the station is ensured, the calculated amount is less, and the real-time performance of path planning is ensured.
The path planning method of the embodiment of the invention can determine the triggering mode according to different triggering conditions or triggering modes, for example, according to specific sensor configuration and task scenes, and can plan the path for the vehicle according to the method when the triggering conditions are met. As an example, path planning may be triggered by the following two ways: after updating the state of the environment nearby a destination, triggering a path planning task, which is commonly found in a guest receiving task with complex environment; another task for path planning is triggered for a fixed period, such as running a local path planning task every 100 milliseconds, and is often used in a scenario where the update frequencies of multiple sensors are inconsistent.
Fig. 4 schematically shows a flow chart of a path planning method according to another embodiment of the invention, as shown in fig. 4, the method comprising:
step 401: determining information of an obstacle between a current location of a vehicle and a destination of the vehicle;
step 402: determining a trajectory curve between a current location of the vehicle and a destination of the vehicle;
step 403: detecting whether the track curve collides with the obstacle according to the information of the obstacle;
step 404: if not, taking the track curve as a running path of the vehicle;
step 405: if yes, generating a grid area around the destination, and determining a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid;
step 406: determining a plurality of alternative destinations around the destination, and determining a second cost for each of the alternative destinations according to a preset second rule and the first cost of the grid;
step 407: and sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets a preset condition according to the order from the low cost to the high cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle.
Steps 401, 405-407 are the same as those in the embodiment shown in fig. 1, and the present invention is not repeated here.
For steps 402-403, a trajectory curve between the current location of the vehicle and the destination may be generated using a cubic polynomial, a penta-order polynomial, or a hepta-order polynomial. Then, the gesture of the vehicle on the track curve can be predicted, whether the vehicle runs on the track curve and collides with the obstacle or not is determined according to the gesture of the vehicle on the track curve and the information of the obstacle, and if yes, the track curve collides with the obstacle is determined. When determining whether the vehicle runs on the track curve and collides with the obstacle, whether the vehicle overlaps with the coverage of the obstacle or not can be determined according to whether the coverage of the vehicle under the pose is overlapped with the coverage of the obstacle or not, and if so, the vehicle is determined to run on the track curve and collide with the obstacle. If the track curve does not collide with the obstacle, the track curve can be used as a running path of the vehicle, so that the following steps are omitted, the calculated amount is effectively reduced, and the running safety can be ensured while the parking task is completed.
In an alternative embodiment, before determining whether the trajectory profile between the alternative destination and the current location of the vehicle meets a preset condition, the path planning method further comprises: an invalid alternative of the plurality of alternative destinations is determined and screened out. Wherein determining an invalid alternative of the plurality of alternative destinations may include:
determining, for each alternative destination, whether a mesh in which the alternative destination is located collides with the obstacle; namely, determining whether the first price of the grid where the alternative destination is located is a preset value;
if so, determining the alternative destination as an invalid alternative.
According to the method and the device for preventing the vehicle from collision, the planned driving path and the obstacle can be prevented from collision by screening out invalid alternatives in the alternative destination, and the driving safety of the vehicle is guaranteed.
In an alternative embodiment, the path planning method further comprises: and if the track curves between all the alternative destinations and the current position of the vehicle do not meet the preset conditions, determining a new alternative destination, and judging whether the track curve between the new alternative destination and the current position of the vehicle meets the preset conditions or not. For example, a new target pattern may be generated centered on the destination, and sampling is performed on the new target pattern to obtain a new alternative destination. Taking fig. 3 as an example, a new circle may be generated with the destination as the center and 2r as the radius, and a new alternative destination may be sampled on the new circle. After determining the new alternative destinations, calculating second costs of each new alternative destination, and then sequentially judging whether the track curve between the new alternative destination and the current position of the vehicle meets a preset condition according to the order of the second costs from small to large until the track curve meeting the preset condition is determined, wherein the track curve meeting the preset condition is used as the running path of the vehicle.
In an alternative embodiment, the path planning method further comprises: determining whether an obstacle moves or not in the process that the automatic driving vehicle runs according to the running path; if yes, the driving path of the vehicle is re-planned according to the information of the moved obstacle, namely, steps 101-104 or steps 401-407 are re-executed. Wherein the condition of the obstacle movement includes one or more of: the obstacle moves from the first grid to the second grid, the obstacle moves from inside the grid area to outside the grid area, and the new obstacle moves from outside the grid area to inside the grid area. In the path planning method of the embodiment, whether the obstacle movement occurs is detected in real time in the running process of the automobile, and if the obstacle movement occurs, the running path of the automobile is planned again, so that the automobile can be safely driven to a destination.
Fig. 5 schematically illustrates a schematic structural diagram of a path planning apparatus 500 according to an embodiment of the present invention, and as shown in fig. 5, the path planning apparatus 500 includes:
an obstacle determination module 501 for determining information of an obstacle between a current position of a vehicle and a destination of the vehicle;
a first calculation module 502, configured to generate a grid area around the destination, and determine a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid;
A second calculation module 503, configured to determine a plurality of alternative destinations around the destination, and determine a second cost of each of the alternative destinations according to a preset second rule and the first cost of the grid;
and the path determining module 504 is configured to determine, according to the order of the second cost from smaller to larger, whether a trajectory curve between the candidate destination and the current position of the vehicle meets a preset condition, and if yes, take the trajectory curve as a running path of the vehicle.
According to the path planning device, a grid area is generated around a vehicle destination, and the first cost of each grid in the grid area is determined according to the information of the obstacle between the current position of the vehicle and the destination and a preset first rule; the first price is used for indicating the feasibility of the grid, and the smaller the first price is, the higher the feasibility is, the safer the running is, so that the safe area and the dangerous area in the grid area can be determined; then determining a plurality of alternative destinations around the destination, and determining a second cost of each alternative destination according to a preset second rule and the first cost of the grid; and judging whether the track curve between the alternative destination and the current position of the vehicle meets the preset condition or not in sequence according to the order from small to large of the second cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle, so that the running safety can be ensured while the accurate stop at the station is ensured, the calculated amount is less, and the real-time performance of path planning is ensured.
Optionally, the first computing module is further configured to: determining a trajectory curve between a current location of the vehicle and a destination of the vehicle; detecting whether the track curve collides with the obstacle according to the information of the obstacle; if so, a grid area is generated around the destination.
Optionally, the information of the obstacle includes position information of the obstacle;
the first computing module is further for: determining, for each mesh, a second distance between the mesh and the destination; determining a first distance between the grid and the obstacle according to the position information of the obstacle; and determining a first cost of the grid according to the first distance and the second distance.
Optionally, the first computing module is further configured to: determining a minimum first distance from among a plurality of first distances between the mesh and a plurality of the obstacles in the case where the number of the obstacles is plural; and determining the first cost of the grid according to the minimum first distance and the second distance.
Optionally, the second computing module is further configured to: generating a target graph taking the destination as a center, wherein the coverage range of the target graph is overlapped with the coverage range of the grid area; sampling is carried out on the target graph, and sampling points are used as the alternative destinations.
Optionally, the second computing module is further configured to: for each alternative destination, determining a first cost of a grid in which the alternative destination is located; determining a third distance between the alternative destination and the current location of the vehicle; and determining a second cost of the alternative destination according to the first cost and the third distance.
Optionally, the apparatus further comprises a screening module for: an invalid alternative of the plurality of alternative destinations is determined and screened out.
Optionally, the screening module is further configured to: determining, for each alternative destination, whether a mesh in which the alternative destination is located collides with the obstacle; if so, determining the alternative destination as an invalid alternative.
Optionally, the apparatus further comprises a retry module for: if the track curves between all the alternative destinations and the current position of the vehicle do not meet the preset condition, determining a new alternative destination, and judging whether the track curve between the new alternative destination and the current position of the vehicle meets the preset condition according to the order of the second cost of the new alternative destination from small to large.
Optionally, the retry module is further configured to: determining whether an obstacle movement occurs in the process that the automatic driving vehicle runs according to the running path; if yes, the running path of the vehicle is planned again according to the information of the moved obstacle.
The device can execute the method provided by the embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. Technical details not described in detail in this embodiment may be found in the methods provided in the embodiments of the present invention.
The embodiment of the invention also provides an electronic device, as shown in fig. 6, comprising one or more processors 601, a communication interface 602, a storage device 603 and a communication bus 604, wherein the processors 601, the communication interface 602, the storage device 603 are in communication with each other via the communication bus 604,
a storage device 603 for storing one or more programs;
the processor 601 is configured to execute the program stored in the storage device 603, thereby implementing the following steps:
determining information of an obstacle between a current location of a vehicle and a destination of the vehicle;
generating a grid area around the destination, and determining a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid;
Determining a plurality of alternative destinations around the destination, and determining a second cost for each of the alternative destinations according to a preset second rule and the first cost of the grid;
and sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets a preset condition according to the order from the low cost to the high cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle.
The communication bus mentioned by the above electronic device may be a peripheral component interconnect standard (Peripheral Component Interconnect, abbreviated as PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated as EISA) bus, or the like. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The communication interface is used for communication between the electronic device and other devices.
The storage device may include a random access memory device (Random Access Memory, RAM) or a non-volatile memory device (non-volatile memory), such as at least one magnetic disk storage device. Alternatively, the storage device may be at least one storage device located remotely from the aforementioned processor.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processing, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
In yet another embodiment of the present invention, a computer readable storage medium is provided, in which instructions are stored, which when run on a computer, cause the computer to perform the path planning method according to any one of the above embodiments.
In a further embodiment of the present invention, a computer program product comprising instructions which, when run on a computer, causes the computer to perform the path planning method according to any of the above embodiments is also provided.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present invention, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.
Claims (11)
1. A method of path planning, comprising:
determining information of an obstacle between a current location of a vehicle and a destination of the vehicle;
generating a grid area around the destination, and determining a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid;
determining a plurality of alternative destinations around the destination, and determining a second cost for each of the alternative destinations according to a preset second rule and the first cost of the grid;
sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets a preset condition according to the order from the low cost to the high cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle;
Wherein determining a plurality of alternative destinations around the destination comprises:
generating a target graph taking the destination as a center, wherein the coverage range of the target graph is overlapped with the coverage range of the grid area;
sampling is carried out on the target graph, and sampling points are used as the alternative destinations;
determining a second cost of each alternative destination according to a preset second rule and the first cost of the grid, including:
for each alternative destination, determining a first cost of a grid in which the alternative destination is located;
determining a third distance between the alternative destination and the current location of the vehicle;
and determining a second cost of the alternative destination according to the first cost and the third distance.
2. The method of claim 1, wherein generating a mesh region around the destination comprises:
determining a trajectory curve between a current location of the vehicle and a destination of the vehicle;
detecting whether the track curve collides with the obstacle according to the information of the obstacle;
if yes, generating a grid area around the destination;
If not, taking a track curve between the current position of the vehicle and the destination of the vehicle as a running path of the vehicle.
3. The method of claim 1, wherein the information of the obstacle comprises position information of the obstacle;
according to a preset first rule and information of the obstacle, determining a first cost of each grid in the grid area comprises the following steps:
determining, for each mesh, whether the mesh collides with the obstacle according to information of the obstacle;
if yes, determining that the first cost of the grid is a preset value;
if not, determining a first distance between the grid and the obstacle according to the position information of the obstacle; determining a second distance between the mesh and the destination; and determining a first cost of the grid according to the first distance and the second distance.
4. A method according to claim 3, wherein determining the first cost of the grid from the first distance and the second distance comprises:
determining a minimum first distance from among a plurality of first distances between the mesh and a plurality of the obstacles in the case where the number of the obstacles is plural;
And determining the first cost of the grid according to the minimum first distance and the second distance.
5. The method according to claim 1, wherein the method further comprises:
before determining whether a trajectory curve between the candidate destination and a current position of the vehicle satisfies a preset condition, determining an invalid candidate among the plurality of candidate destinations, and screening out the invalid candidate.
6. The method of claim 5, wherein determining an invalid alternative of the plurality of alternative destinations comprises:
determining, for each alternative destination, whether a mesh in which the alternative destination is located collides with the obstacle;
if so, determining the alternative destination as an invalid alternative.
7. The method according to any one of claims 1-6, further comprising:
if the track curves between all the alternative destinations and the current position of the vehicle do not meet the preset condition, determining a new alternative destination, and judging whether the track curve between the new alternative destination and the current position of the vehicle meets the preset condition according to the order of the second cost of the new alternative destination from small to large.
8. The method of claim 7, wherein the method further comprises:
determining whether an obstacle movement occurs during the running of the vehicle according to the running path;
if yes, the running path of the vehicle is planned again according to the information of the moved obstacle.
9. A path planning apparatus for performing the path planning method according to any one of claims 1 to 8, the path planning apparatus comprising:
an obstacle determination module for determining information of an obstacle between a current position of a vehicle and a destination of the vehicle;
the first calculation module is used for generating a grid area around the destination and determining a first cost of each grid in the grid area according to a preset first rule and information of the obstacle; wherein the first price is used to indicate the feasibility of the grid;
a second calculation module, configured to determine a plurality of alternative destinations around the destination, and determine a second cost of each of the alternative destinations according to a preset second rule and the first cost of the grid;
and the path determining module is used for sequentially judging whether the track curve between the alternative destination and the current position of the vehicle meets a preset condition according to the order from the low cost to the high cost until the track curve meeting the preset condition is determined, and taking the track curve meeting the preset condition as the running path of the vehicle.
10. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-8.
11. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-8.
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| CN202210640790.4A CN115060279B (en) | 2022-06-08 | 2022-06-08 | Path planning method, path planning device, electronic equipment and computer readable medium |
| PCT/CN2022/117365 WO2023236378A1 (en) | 2022-06-08 | 2022-09-06 | Path planning method and apparatus, and electronic device and computer-readable medium |
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