CN115752491A - Path planning method, terminal and computer storage medium - Google Patents
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Abstract
The application relates to a path planning method, a terminal and a computer storage medium, wherein the path planning method comprises the following steps: determining planned paths of a plurality of vehicles according to road network undirected graph data and the position information of the plurality of vehicles; the road network undirected graph data comprises the available time of vertexes and edges in the road network undirected graph; performing conflict detection on planned paths of a plurality of vehicles; wherein the collision detection comprises safe distance collision detection; when a conflict exists between the planned paths of any two vehicles, a path constraint condition is established for the target vehicle according to conflict information; and updating the planned path of the target vehicle according to the path constraint condition, and determining the target planned paths of the plurality of vehicles. According to the method and the device, the target planning paths of a plurality of vehicles are determined based on the available time of the vertexes and the edges in the road network undirected graph, diversified vehicle dispatching requirements can be met, and the vehicle dispatching efficiency and flexibility are improved; and can avoid collision caused by safe distance conflict and simplify the road network design process.
Description
Technical Field
The present application relates to the field of path planning technologies, and in particular, to a path planning method, a terminal, and a computer storage medium.
Background
In a large warehouse operation process, in order to improve the transportation efficiency, a plurality of vehicles, such as a plurality of Automated Guided Vehicles (AGVs), need to be dispatched for transportation simultaneously or in batches. Under the condition of dispatching a plurality of vehicles, path points of a certain road section may be dense, path points of a certain road section may be sparse, and the size of a space where different road sections can walk is diversified. In the same working scene, the operation flow is various, vehicles with different geometric dimensions are often required to work cooperatively, in the process of controlling the movement of the vehicles, distance limitation among path points is generally added when a road network is designed in order to avoid collision of the vehicles with different dimensions due to safety distance collision, the method depends on the accuracy of the road network design, collision caused by the safety distance collision cannot be effectively avoided in a complex scene of vehicle scheduling, and the complexity of the road network design is increased.
In addition, when dispatching multiple batches of vehicles, the currently adopted path planning method has the following defects:
1) Carrying out global path planning on all batches of vehicles; the method has higher requirement on computing power, cannot obtain the path planning result of each batch of vehicles in expected time, and has low vehicle dispatching efficiency;
2) After waiting for the vehicles in the previous batch to travel to the target position, planning the path of the vehicles in the current batch; the method cannot flexibly schedule vehicles and cannot meet diversified vehicle scheduling requirements.
Disclosure of Invention
In view of the above technical problems, the present application provides a path planning method, a terminal, and a computer storage medium, so as to avoid collision due to a safe distance conflict, simplify a road network design process, meet diversified vehicle scheduling requirements, and improve vehicle scheduling efficiency and flexibility.
The application provides a path planning method, which comprises the following steps: s1, determining planned paths of a plurality of vehicles according to road network undirected graph data and position information of the plurality of vehicles; the road network undirected graph data comprises available time of vertexes and edges in the road network undirected graph; s2, performing conflict detection on the planned paths of the plurality of vehicles; wherein the collision detection comprises a safe distance collision detection; s3, when a conflict exists between the planned paths of any two vehicles, creating a path constraint condition for the target vehicle according to conflict information; wherein the target vehicle is two vehicles in which the conflict exists between the planned paths; s4, updating the planned path of the target vehicle according to the path constraint condition; and S5, repeatedly executing the steps S2-S4, and determining the target planned paths of the vehicles.
In one embodiment, the collision detection further comprises vertex collision detection and edge collision detection; the step S2 includes: according to a preset rule, sequentially carrying out the vertex conflict detection, the side conflict detection and the safety distance conflict detection on the planned paths of the vehicles; in step S3, according to the conflict information, a path constraint condition is created for the target vehicle, including: and when the conflict between any two vehicles is the safe distance conflict, according to the first time when the safe distance conflict occurs, the distance of each vehicle in the target vehicles at the first time is restricted to be larger than a safe distance threshold value.
In one embodiment, the step S4 includes: if the times of creating the path constraint condition is 1, updating the planned path of the target vehicle according to the path constraint condition created at the 1 st time; if the times of creating the path constraint condition is N, updating the planned path of the target vehicle according to all the path constraint conditions created from the 1 st time to the Nth time; wherein N is an integer greater than 1.
In one embodiment, the step S4 includes: and determining an updated planned path of the target vehicle according to the road network undirected graph data, the position information of the target vehicle and the path constraint condition.
In one embodiment, the step S5 includes: combining the planned paths of all vehicles in the target vehicle before and after updating to determine multiple groups of planned paths of the target vehicle; wherein any set of planned paths for the target vehicle includes an updated planned path for at least one vehicle of the target vehicle.
In one embodiment, the step S5 includes: according to the cost values of the multiple groups of planned paths of the target vehicle, carrying out priority ordering on the multiple groups of planned paths of the multiple vehicles corresponding to the multiple groups of planned paths of the target vehicle; and sequentially carrying out the conflict detection on the multiple groups of planned paths of the vehicles according to the sequence of the priorities from high to low.
In one embodiment, the step S5 includes: if the new conflict exists in the path included in each group of the multiple groups of planned paths of the multiple vehicles, creating the path constraint condition for the target vehicle according to the conflict information of the group of planned paths with the highest priority of the multiple vehicles; and if the paths included in any one of the plurality of groups of planned paths of the plurality of vehicles do not have the new conflict, taking the paths included in the corresponding group as the target planned paths of the plurality of vehicles.
In one embodiment, after determining the target planned paths for the plurality of vehicles, the method includes: acquiring time information of target planned paths of the plurality of vehicles; and updating the available time of the top points and the edges in the road network undirected graph according to the time information of the target planned paths of the vehicles.
The application also provides a terminal, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of the path planning method when executing the computer program.
The present application further provides a computer storage medium storing a computer program which, when executed by a processor, implements the steps of the above-described path planning method.
According to the path planning method, the terminal and the computer storage medium, the target planning paths of a plurality of vehicles are determined based on the available time of the top points and the edges in the road network undirected graph, so that multiple batches of path planning tasks are linked in time, diversified vehicle dispatching requirements can be met, and the vehicle dispatching efficiency and flexibility are improved; in addition, in the process of determining the target planned paths of the plurality of vehicles, safety distance conflict detection is carried out on the planned paths of the plurality of vehicles, so that the collision caused by the safety distance conflict can be effectively avoided, distance limitation among path points is not required to be added when a road network is designed, and the road network design process is simplified.
Drawings
Fig. 1 is a schematic flowchart of a path planning method according to an embodiment of the present application;
fig. 2 is a schematic diagram of a road network according to an embodiment of the present application;
FIG. 3 is a diagram illustrating the effect of conflict types provided in an embodiment of the present application;
fig. 4 is a schematic view of a scenario of planned path update according to an embodiment of the present application;
fig. 5 is a schematic diagram of available time of vertices and edges in a road network undirected graph according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a terminal according to a second embodiment of the present application.
Detailed Description
The technical solution of the present application is further described in detail with reference to the drawings and specific embodiments of the specification. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, "and/or" includes any and all combinations of one or more of the associated listed items.
Fig. 1 is a schematic flowchart of a path planning method according to an embodiment of the present disclosure. As shown in fig. 1, the path planning method of the present application may include the following steps:
step S1: determining planned paths of a plurality of vehicles according to the road network undirected graph data and the position information of the plurality of vehicles; the road network undirected graph data comprises the available time of vertexes and edges in the road network undirected graph;
optionally, the position information of the plurality of vehicles includes current positions and target positions of the plurality of vehicles.
In one embodiment, determining planned paths of a plurality of vehicles according to road network undirected graph data and position information of the plurality of vehicles comprises:
respectively determining a path set from each current position to each target position of each vehicle in the plurality of vehicles according to the road network undirected graph data and the position information of the plurality of vehicles;
and respectively selecting a path with the lowest cost from the path set of each vehicle in the plurality of vehicles as a planned path of each vehicle in the plurality of vehicles.
Optionally, a Space-Time a (STA) algorithm is used to select, according to the road network undirected graph data and the location information of the multiple vehicles, a path with the lowest cost from the current location to the target location of each vehicle among the multiple vehicles as a planned path of each vehicle.
As shown in fig. 2, modeling is performed according to the size of the real physical world, the black part represents an area which cannot be driven, the white part represents an area which can be driven, a road network is extracted from the white area and is designed into an undirected graph form, and vertexes with different serial numbers and edges formed by different vertexes are obtained; optionally, after the planned path of each vehicle is determined, each vehicle will travel along the planned path according to the time beat; if the planned path of the A vehicle is as follows: 1-2-3, when t =0s, the vehicle a moves from the vertex 1 to the vertex 2 along the side formed by the vertices 1 and 2 after 1 st time beat, for example, 5s, i.e., when t =5s, the vehicle a reaches the vertex 2 in the road network, and moves from the vertex 2 to the vertex 3 along the side formed by the vertices 2 and 3 after 2 nd time beat, i.e., when t =10s, the vehicle a reaches the vertex 3 in the road network; the time beat is a preset value, and each vehicle can adjust the speed according to the distance between adjacent vertexes in the planned path so as to move from the current vertex to the next adjacent vertex along the planned path through one time beat. Further, the vehicles are labeled in an equal proportion in fig. 2 according to the sizes of the vehicles, so that the collision detection process and/or the path planning result of the planned path of the vehicles can be displayed in a simulation mode.
Step S2: performing conflict detection on planned paths of a plurality of vehicles; wherein the collision detection comprises safety distance collision detection;
optionally, the collision detection further includes vertex collision detection and edge collision detection;
in one embodiment, the collision detection of the planned paths of the plurality of vehicles in step S2 includes:
and according to a preset rule, sequentially carrying out vertex collision detection, side collision detection and safety distance collision detection on the planned paths of the plurality of vehicles.
Optionally, the preset rule includes:
performing vertex conflict detection on the planned paths of the plurality of vehicles;
performing side collision detection on the planned paths of a plurality of vehicles after vertex collision does not exist or exists between the planned paths of any two vehicles and the vertex collision is eliminated;
and after side conflict does not exist or exists between the planned paths of any two vehicles and the side conflict is eliminated, safety distance conflict detection is carried out on the planned paths of the multiple vehicles.
Optionally, before the safety distance collision detection is performed on the planned paths of the plurality of vehicles, the method includes:
acquiring sizes of a plurality of vehicles;
wherein the vehicle dimension is the maximum inner diameter of the vehicle outer contour.
Optionally, the vehicle is an AGV.
And step S3: when a conflict exists between the planned paths of any two vehicles, establishing a path constraint condition for a target vehicle according to conflict information, wherein the target vehicle is two vehicles with conflicts between the planned paths;
optionally, the conflict information includes the vehicle, time, location and conflict type where the conflict occurs; wherein the conflict types include vertex conflicts, edge conflicts, and safety distance conflicts.
In one embodiment, the step S3 of creating the path constraint condition for the target vehicle according to the conflict information includes:
when the conflict existing between the planned paths of any two vehicles is a safety distance conflict, according to the first time when the safety distance conflict occurs, the distance of each vehicle in the target vehicles at the first time is restricted to be larger than a safety distance threshold value;
when the conflict between the planned paths of any two vehicles is a peak conflict, according to the peak where the conflict occurs and the second time, each vehicle in the constraint target vehicle reaches the corresponding peak when the second time is different;
and when the conflict between the planned paths of any two vehicles is side conflict, according to the side where the conflict occurs and the third time, restraining each vehicle in the target vehicles to pass through the corresponding side when the third time is different.
As shown in fig. 3 (a), the vehicle 1 and the vehicle 2 are expected to reach the same vertex in the road network at the same time, i.e. the vehicle 1 and the vehicle 2 are expected to reach the same vertex at the same time or the same time t of reaching the vertex at the time 1 Generating vertex conflict, restricting the beat of the vehicles 1 and 2 at the time or at the moment t 1 Not reaching the same vertex at the same time to solve the vertex conflict; as shown in fig. 3 (b), 3 cars and 4 cars are expected to pass through the same edge of the road network to reach the vertex of the opponent at the same time beat, that is, 3 cars and 4 cars are expected to reach the vertex of the opponent at the same time beat or the same time t of reaching the vertex of the opponent 2 If an edge collision occurs, then the 3 and 4 vehicles are constrained to beat at that time or at time t 2 Not passing through the same edge at the same time to solve the edge conflict; as shown in fig. 3 (c), vehicles 5 and 6 with different sizes will reach from vertex 2 to vertex 3 and from vertex 1 to vertex 2 in the road network respectively at the same time beat, and the distance between vertex 2 and vertex 3 is smaller than the safety distance threshold, so vehicles 5 and 6 reach the same time t of vertex 3 and vertex 2 respectively at the time beat or the same time t 3 Generating a safety distance conflict, then restricting the time beat or the time t 3 The distance between the 5-vehicle and the 6-vehicle is larger than a safety distance threshold value so as to solve the safety distance conflict; optionally, the safe distance threshold = the sum of the sizes of the vehicles in the target vehicle/2, such as (5 vehicle size +6 vehicle size)/2.
And step S4: updating the planned path of the target vehicle according to the path constraint condition;
in one embodiment, step S4 includes:
if the times of creating the path constraint condition is 1, updating the planned path of the target vehicle according to the path constraint condition created at the 1 st time;
if the times of creating the path constraint conditions are N, updating the planned path of the target vehicle according to all the path constraint conditions created from the 1 st time to the Nth time;
wherein N is an integer greater than 1.
In one embodiment, step S4 includes:
and determining the updated planned path of the target vehicle according to the road network undirected graph data, the position information of the target vehicle and the path constraint condition.
In one embodiment, determining an updated planned path of a target vehicle according to road network undirected graph data, position information of the target vehicle and path constraint conditions comprises:
respectively determining a path set from each current position to each target position of each vehicle in the target vehicles according to the road network undirected graph data, the position information of the target vehicles and the path constraint conditions;
and respectively selecting the path with the lowest cost from the path set of each vehicle in the target vehicles as the updated planned path of each vehicle in the target vehicles.
Optionally, a route with the lowest cost from the current position to the target position of each vehicle in the target vehicles is respectively selected as the updated planned route of each vehicle in the target vehicles by using an STA algorithm according to the road network undirected graph data, the position information of the target vehicles and the route constraint conditions.
Step S5: and (5) repeatedly executing the steps S2-S4 to determine the target planning paths of the plurality of vehicles.
In one embodiment, step S5 includes:
combining the planned paths of all vehicles in the target vehicle before and after updating to determine multiple groups of planned paths of the target vehicle;
wherein any group of planned paths of the target vehicles comprises the updated planned path of at least one vehicle in the target vehicles.
In one embodiment, step S5 includes:
according to the cost values of the multiple groups of planned paths of the target vehicle, carrying out priority sequencing on the multiple groups of planned paths of the multiple vehicles corresponding to the multiple groups of planned paths of the target vehicle;
and sequentially carrying out collision detection on the multiple groups of planned paths of the vehicles according to the sequence of the priorities from high to low.
Illustratively, the planned paths of 2 vehicles in 5 vehicles are updated to obtain multiple groups of planned paths of the 2 vehicles, and the multiple groups of planned paths of the 2 vehicles are combined with the planned paths of other 3 vehicles respectively, so that multiple groups of planned paths of 5 vehicles corresponding to the multiple groups of planned paths of the 2 vehicles can be obtained.
In one embodiment, step S5 includes:
if the paths included in each group of the multiple groups of planned paths of the multiple vehicles have new conflicts, creating a path constraint condition for the target vehicle according to the conflict information of the group of planned paths with the highest priority of the multiple vehicles;
and if the paths included in any one of the plurality of groups of planned paths of the plurality of vehicles do not have new conflicts, taking the paths included in the corresponding group as the target planned paths of the plurality of vehicles.
As shown in fig. 4, the current position of the vehicle 1 is the vertex 2, and the target position thereof is the vertex 4;2, the current position of the vehicle is a vertex 4, and the target position of the vehicle is a vertex 2; the black areas are not drivable and the white areas are drivable. Obtaining a planned path of 1 vehicle according to the road network undirected graph data and the position information of the two vehicles: 2-3-4; the planned path of the 2 vehicles is as follows: 4-3-2; obviously, at time 1, beat 1, car and car 2 have point conflicts at vertex 3;
create path constraint 1: when the beats of the 1 st vehicle and the 2 nd vehicle are different, the 1 st vehicle and the 2 nd vehicle reach the vertex 3, the planned paths of the 1 st vehicle and the 2 nd vehicle are updated according to the constraint condition 1 (the 1 st vehicle: 2-3-4, the 2 nd vehicle: 4-3-2), and 2 groups of planned paths are obtained: 1, vehicle: 2-2-3-4, 2 cars: 4-3-2, the cost value for the set of planned paths being 5 x beats of time; 1, vehicle: 2-3-4, 2 cars: 4-4-3-2, the cost value for the set of planned paths is also 5 x beats; obviously, the 2 sets of planned paths have edge conflicts in the 2 nd time beat;
because the cost values of the 2 groups of planned paths are equal, any group of planned paths is updated continuously; if the 1 st group of planned paths (1 vehicle: 2-2-3-4 and 2 vehicles: 4-3-2) are selected, a path constraint condition 2 is created: and (3) the 1 st vehicle and the 2 nd vehicle pass through the edge formed by the vertex 2 and the vertex 3 at different time beats at the 2 nd time, and the 1 st group of planned paths are updated according to the path constraint condition 1 and the path constraint condition 2 to obtain 2 groups of planned paths: 1, vehicle: 2-2-2-3-4, 2 cars: 4-3-2, the cost value for the set of planned paths being 6 x beats of time; 1, vehicle: 2-2-3-4, 2 cars: 4-3-1-3-2, the cost value for the set of planned paths being 7 x beats of time; according to the size of the cost value, firstly carrying out collision detection on a group of planned paths with low cost values (1 vehicle: 2-2-2-3-4 and 2 vehicles: 4-3-2), and finding that the 1 vehicle and the 2 vehicle have point collision at the top 2 in the 2 nd time beat; and then carrying out conflict detection on a group of planned paths with high cost values (1 vehicle: 2-2-3-4 and 2 vehicles: 4-3-1-3-2), finding that no new conflict exists in the group of planned paths, and taking the paths included in the group as target planned paths of the 1 vehicle and the 2 vehicles.
In one embodiment, after determining the target planned paths for the plurality of vehicles, the method includes:
acquiring time information of target planning paths of a plurality of vehicles;
and updating the available time of the top points and the edges in the road network undirected graph according to the time information of the target planned paths of the vehicles.
The time information of the target planned paths of the vehicles comprises time for determining the target planned paths of the vehicles, time beats of running of the vehicles along the target planned paths, and time for reaching each node on the target planned paths and passing each edge.
As shown in fig. 5, when each vertex and each edge in the road network are not on the target planned path, the initial available time of each vertex and each edge is [ (0, inf) ], where inf represents infinity, that is, each vertex and each edge are available at any time from 0 to infinity;
if t =0s, determining the target planned path of the first batch of vehicles as: 1, vehicle: 3-2-0-7, wherein the time beat is 1s; then at t =0s, 1 slot is located at vertex 3, and vertex 3 is not available at t =0 s; at t =1s, 1 car will pass edge 3- >2 to vertex 2, and vertex 2, edge 3- >2 is not available at t = 1s; at t =2s, 1 car will pass edge 2- >0 to vertex 0, and vertex 0, edge 2- >0 are not available at t =2 s; at t =3s, 1 car will pass side 0- >7 to vertex 7, and vertex 7 and side 0- >7 are not available at t =3 s;
according to the time information of the target planning path of the first batch of vehicles, respectively updating the available time of the top points and the edges in the road network undirected graph as follows:
vertex 3: [ (1, inf) ] edge 3- >2: [ (0, 0), (2, inf) ]
Vertex 2: [ (0, 0), (2, inf) ] edge 2: [ (0, 1), (3, inf) ]
Vertex 0: [ (0, 1), (3, inf) ] edge 0- >7: [ (0, 2), (4, inf) ]
Vertex 7: [ (0, 2), (4, inf) ]
If t =5s, determining that the target planned path of the second batch of vehicles is: 2, vehicle: 5-0-2, the time beat is 1s, then 2 vehicles are located at vertex 5 when t =5s, and vertex 5 is not available when t =5 s; at t =6s, vertex 0 would be reached via edge 5- >0, and vertex 0 and edge 5- >0 would not be available at t =6 s; at t =7s, vertex 2 would be reached through edge 0- >2, and vertex 2 and edge 0- >2 would not be available at t =7 s.
According to the time information of the target planned paths of the vehicles of the first batch and the second batch, the available time of the top points and the edges in the network undirected graph is updated in an accumulated mode:
vertex 5: [ (0, 4), (6, inf) ] edge 5: [ (0, 1), (3, 5), (7, inf) ]
Vertex 0: [ (0, 1), (3, 5), (7, inf) ] side 0- >2: [ (0, 0), (2, 6), (8, inf) ]
Vertex 2: [ (0, 0), (2, 6), (8, inf) ] edge 0- >7: [ (0, 2), (4, inf) ]
Vertex 7: [ (0, 2), (4, inf) ] side 3- >2: [ (0, 0), (2, inf) ]
Vertex 3: [ (1, inf) ] edge 2- >0: [ (0, 1), (3, inf) ]
Where, (0, 0) denotes t =0s.
According to the path planning method provided by the embodiment of the application, the target planning paths of a plurality of vehicles are determined based on the available time of the top points and the edges in the road network undirected graph, so that multiple batches of path planning tasks are linked in time, diversified vehicle dispatching requirements can be met, and the vehicle dispatching efficiency and flexibility are improved; in addition, in the process of determining the target planned paths of the plurality of vehicles, safety distance conflict detection is carried out on the planned paths of the plurality of vehicles, so that the collision caused by the safety distance conflict can be effectively avoided, the distance limit among path points is not required to be added when a road network is designed, and the road network design process is simplified.
Fig. 6 is a schematic structural diagram of a terminal provided in this application. The terminal of the application includes: a processor 110, a memory 111, and a computer program 112 stored in the memory 111 and operable on the processor 110. The steps in the above-described embodiments of the path planning method are implemented when the processor 110 executes the computer program 112.
The terminal may include, but is not limited to, a processor 110, a memory 111. Those skilled in the art will appreciate that fig. 6 is merely an example of a terminal and is not intended to be limiting and may include more or fewer components than those shown, or some of the components may be combined, or different components, e.g., the terminal may also include input-output devices, network access devices, buses, etc.
The Processor 110 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 111 may be an internal storage unit of the terminal, such as a hard disk or a memory of the terminal. The memory 111 may also be an external storage device of the terminal, such as a plug-in hard disk provided on the terminal, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 111 may also include both an internal storage unit and an external storage device of the terminal. The memory 111 is used for storing computer programs and other programs and data required by the terminal. The memory 111 may also be used to temporarily store data that has been output or is to be output.
The present application further provides a computer storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the steps in the above-mentioned path planning method embodiment are implemented.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
As used herein, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, including not only those elements listed, but also other elements not expressly listed.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method of path planning, comprising:
s1, determining planned paths of a plurality of vehicles according to road network undirected graph data and position information of the plurality of vehicles; the road network undirected graph data comprises available time of vertexes and edges in the road network undirected graph;
s2, performing conflict detection on the planned paths of the plurality of vehicles; wherein the collision detection comprises a safe distance collision detection;
s3, when a conflict exists between the planned paths of any two vehicles, creating a path constraint condition for the target vehicle according to conflict information; wherein the target vehicle is two vehicles between which the conflict exists between the planned paths;
s4, updating the planned path of the target vehicle according to the path constraint condition;
and S5, repeatedly executing the steps S2-S4, and determining the target planned paths of the vehicles.
2. The path planning method of claim 1 wherein said collision detection further comprises vertex collision detection and edge collision detection;
the step S2 includes:
according to a preset rule, sequentially carrying out the vertex conflict detection, the side conflict detection and the safety distance conflict detection on the planned paths of the vehicles;
in step S3, according to the collision information, a path constraint condition is created for the target vehicle, including:
and when the conflict existing between any two vehicles is the safe distance conflict, according to the first time when the safe distance conflict occurs, restricting the distance of each vehicle in the target vehicles at the first time to be larger than a safe distance threshold value.
3. The path planning method according to claim 1, wherein the step S4 includes:
if the times of creating the path constraint condition is 1, updating the planned path of the target vehicle according to the path constraint condition created at the 1 st time;
if the times of creating the path constraint condition is N, updating the planned path of the target vehicle according to all the path constraint conditions created from the 1 st time to the Nth time;
wherein N is an integer greater than 1.
4. A path planning method according to claim 1 or 3, wherein said step S4 comprises:
and determining an updated planned path of the target vehicle according to the road network undirected graph data, the position information of the target vehicle and the path constraint condition.
5. The path planning method according to claim 1, wherein the step S5 includes:
combining the planned paths of all vehicles in the target vehicle before and after updating to determine multiple groups of planned paths of the target vehicle;
wherein any set of planned paths for the target vehicle includes an updated planned path for at least one vehicle of the target vehicle.
6. The path planning method according to claim 5, wherein the step S5 comprises:
according to the cost values of the multiple groups of planned paths of the target vehicle, carrying out priority ordering on the multiple groups of planned paths of the multiple vehicles corresponding to the multiple groups of planned paths of the target vehicle;
and sequentially carrying out the conflict detection on the multiple groups of planned paths of the vehicles according to the sequence from high priority to low priority.
7. The path planning method according to claim 6, wherein the step S5 includes:
if the new conflict exists in the path included in each of the multiple groups of planned paths of the multiple vehicles, creating the path constraint condition for the target vehicle according to the conflict information of the group of planned paths with the highest priority of the multiple vehicles;
and if the new conflict does not exist in the paths included in any one of the multiple groups of planned paths of the multiple vehicles, taking the paths included in the corresponding group as the target planned paths of the multiple vehicles.
8. The path planning method of claim 1, after determining the target planned paths for the plurality of vehicles, comprising:
acquiring time information of target planned paths of the plurality of vehicles;
and updating the available time of the top points and the edges in the road network undirected graph according to the time information of the target planned paths of the vehicles.
9. A terminal, characterized in that the terminal comprises a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the path planning method according to any one of claims 1 to 8 when executing the computer program.
10. A computer storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the path planning method according to any one of claims 1 to 8.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211297385.3A CN115752491A (en) | 2022-10-21 | 2022-10-21 | Path planning method, terminal and computer storage medium |
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