CN114047760B

CN114047760B - Path planning method and device, electronic equipment and automatic driving vehicle

Info

Publication number: CN114047760B
Application number: CN202111326794.7A
Authority: CN
Inventors: 梁兴亚; 刘阳; 耿涛; 彭亮
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2021-11-10
Filing date: 2021-11-10
Publication date: 2024-04-02
Anticipated expiration: 2041-11-10
Also published as: CN114047760A

Abstract

The disclosure provides a path planning method, a path planning device, electronic equipment and an automatic driving vehicle, relates to the technical field of computers, and particularly relates to the technical field of automatic driving. The implementation scheme is as follows: acquiring first position information of a first position and second position information of a second position; determining at least one first node corresponding to the first location information and at least one second node corresponding to the second location information based on the lane topology; adding virtual nodes in the lane topological graph, wherein the distance attribute of a lane corresponding to the virtual nodes is set to be 0, and the virtual nodes are respectively connected with each first node in at least one first node; and determining the shortest path from the virtual node to any one of the at least one second node based on the lane topological graph after the virtual node is added, thereby realizing the shortest path planning from multiple nodes to multiple nodes.

Description

Path planning method and device, electronic equipment and automatic driving vehicle

Technical Field

The present disclosure relates to the field of computer technology, and in particular, to the field of autopilot technology, and more particularly, to a path planning method, apparatus, electronic device, computer-readable storage medium, computer program product, and autopilot vehicle.

Background

The path planning technology is widely applied to various technical fields such as intelligent travel, automatic driving, autonomous robot actions and the like. The path planning algorithm is a core for realizing intelligent navigation, and has wide application prospect and scientific research value.

The approaches described in this section are not necessarily approaches that have been previously conceived or pursued. Unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, the problems mentioned in this section should not be considered as having been recognized in any prior art unless otherwise indicated.

Disclosure of Invention

The present disclosure provides a path planning method, apparatus, electronic device, computer-readable storage medium, computer program product, and autonomous vehicle.

According to an aspect of the present disclosure, there is provided a path planning method including: acquiring first position information of a first position and second position information of a second position; determining at least one first node corresponding to the first position information and at least one second node corresponding to the second position information based on the lane topology map, wherein each of the at least one first node and the at least one second node corresponds to one lane in the map; adding virtual nodes in the lane topological graph, wherein the distance attribute of a lane corresponding to the virtual nodes is set to be 0, and the virtual nodes are respectively connected with each first node in at least one first node; and determining a shortest path from the virtual node to any one of the at least one second node based on the lane topology after adding the virtual node.

According to another aspect of the present disclosure, there is provided a path planning apparatus including: an acquisition unit configured to acquire first position information of a first position and second position information of a second position; a first determination unit configured to determine at least one first node corresponding to the first position information and at least one second node corresponding to the second position information based on the lane topology map, wherein each of the at least one first node and the at least one second node corresponds to one lane in the map, respectively; an adding unit configured to add a virtual node in the lane topology, wherein the length of the lane corresponding to the virtual node is set to 0, and the virtual node is connected to each of the at least one first node; and a second determination unit that determines a shortest path from the virtual node to any one of the at least one second node based on the lane topology after adding the virtual node.

According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to perform the method as described above.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method as described above.

According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program, wherein the computer program, when executed by a processor, implements the method as claimed in claim.

According to another aspect of the present disclosure, there is provided an autonomous vehicle including: such as the electronic device described above.

According to one or more embodiments of the present disclosure, shortest path planning from multiple nodes to multiple nodes may be implemented.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.

Drawings

The accompanying drawings illustrate exemplary embodiments and, together with the description, serve to explain exemplary implementations of the embodiments. The illustrated embodiments are for exemplary purposes only and do not limit the scope of the claims. Throughout the drawings, identical reference numerals designate similar, but not necessarily identical, elements.

FIG. 1 illustrates a schematic diagram of an exemplary system in which various methods described herein may be implemented, in accordance with an embodiment of the present disclosure;

FIG. 2 illustrates a flow chart of a path planning method according to an embodiment of the present disclosure;

fig. 3 shows a flowchart of step S204 in fig. 2;

fig. 4 shows a flow chart of a path planning method according to a further embodiment of the present disclosure;

FIG. 5 illustrates a topology diagram from a start point to an end point in a path planning method according to an embodiment of the present disclosure;

FIG. 6A illustrates a topology diagram from a start point to a waypoint in a path planning method according to an embodiment of the disclosure;

FIG. 6B illustrates a topology diagram from a pass point to a final point in a path planning method according to an embodiment of the present disclosure;

fig. 7 shows a block diagram of a path planning apparatus according to an embodiment of the present disclosure;

fig. 8 illustrates a block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one 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 of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

In the present disclosure, the use of the terms "first," "second," and the like to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of the elements, unless otherwise indicated, and such terms are merely used to distinguish one element from another. In some examples, a first element and a second element may refer to the same instance of the element, and in some cases, they may also refer to different instances based on the description of the context.

The terminology used in the description of the various illustrated examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context clearly indicates otherwise, the elements may be one or more if the number of the elements is not specifically limited. Furthermore, the term "and/or" as used in this disclosure encompasses any and all possible combinations of the listed items.

The current path planning algorithms mainly include an a star algorithm, a CH (Contraction Hierarchies) algorithm, an ant colony algorithm, and the like, and the path planning algorithms can only realize the shortest path planning from a single starting point to a single end point, but for the automatic driving field, an automatic driving vehicle needs to select not only a shortest path for passing, but also a lane in the path, and when one path corresponds to a plurality of lanes, the shortest path planning algorithm has a limitation.

The embodiment of the disclosure provides a shortest path planning method, a shortest path planning device, electronic equipment, a computer readable storage medium, a computer program product and an automatic driving vehicle, wherein the shortest path planning with multiple starting points and multiple end points can be realized by adding virtual nodes for a plurality of nodes corresponding to the starting points and starting the search of the shortest path from the virtual nodes.

Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

Fig. 1 illustrates a schematic diagram of an exemplary system 100 in which various methods and apparatus described herein may be implemented, in accordance with an embodiment of the present disclosure. Referring to fig. 1, the system 100 includes a motor vehicle 110, a server 120, and one or more communication networks 130 coupling the motor vehicle 110 to the server 120.

In an embodiment of the present disclosure, motor vehicle 110 may include a computing device in accordance with an embodiment of the present disclosure and/or be configured to perform a method in accordance with an embodiment of the present disclosure.

Server 120 may run one or more services or software applications that enable a multi-node to multi-node shortest path planning method. In some embodiments, server 120 may also provide other services or software applications that may include non-virtual environments and virtual environments. In the configuration shown in fig. 1, server 120 may include one or more components that implement the functions performed by server 120. These components may include software components, hardware components, or a combination thereof that are executable by one or more processors. A user of motor vehicle 110 may in turn utilize one or more client applications to interact with server 120 to utilize the services provided by these components. It should be appreciated that a variety of different system configurations are possible, which may differ from system 100. Accordingly, FIG. 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.

The server 120 may include one or more general purpose computers, special purpose server computers (e.g., PC (personal computer) servers, UNIX servers, mid-end servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and/or combination. The server 120 may include one or more virtual machines running a virtual operating system, or other computing architecture that involves virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain virtual storage devices of the server). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

The computing units in server 120 may run one or more operating systems including any of the operating systems described above as well as any commercially available server operating systems. Server 120 may also run any of a variety of additional server applications and/or middle tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

In some implementations, server 120 may include one or more applications to analyze and consolidate data feeds and/or event updates received from motor vehicle 110. Server 120 may also include one or more applications to display data feeds and/or real-time events via one or more display devices of motor vehicle 110.

Network 130 may be any type of network known to those skilled in the art that may support data communications using any of a number of available protocols, including but not limited to TCP/IP, SNA, IPX, etc. By way of example only, the one or more networks 110 may be a satellite communications network, a Local Area Network (LAN), an ethernet-based network, a token ring, a Wide Area Network (WAN), the internet, a virtual network, a Virtual Private Network (VPN), an intranet, an extranet, a Public Switched Telephone Network (PSTN), an infrared network, a wireless network (including, for example, bluetooth, wiFi), and/or any combination of these with other networks.

The system 100 may also include one or more databases 150. In some embodiments, these databases may be used to store data and other information. For example, one or more of databases 150 may be used to store information such as audio files and video files. The data store 150 may reside in various locations. For example, the data store used by the server 120 may be local to the server 120, or may be remote from the server 120 and may communicate with the server 120 via a network-based or dedicated connection. The data store 150 may be of different types. In some embodiments, the data store used by server 120 may be a database, such as a relational database. One or more of these databases may store, update, and retrieve the databases and data from the databases in response to the commands.

In some embodiments, one or more of databases 150 may also be used by applications to store application data. The databases used by the application may be different types of databases, such as key value stores, object stores, or conventional stores supported by the file system.

Motor vehicle 110 may include a sensor 111 for sensing the surrounding environment. The sensors 111 may include one or more of the following: visual cameras, infrared cameras, ultrasonic sensors, millimeter wave radar, and laser radar (LiDAR). Different sensors may provide different detection accuracy and range. The camera may be mounted in front of, behind or other locations on the vehicle. The vision cameras can capture the conditions inside and outside the vehicle in real time and present them to the driver and/or passengers. In addition, by analyzing the captured images of the visual camera, information such as traffic light indication, intersection situation, other vehicle running state, etc. can be acquired. The infrared camera can capture objects under night vision. The ultrasonic sensor can be arranged around the vehicle and is used for measuring the distance between an object outside the vehicle and the vehicle by utilizing the characteristics of strong ultrasonic directivity and the like. The millimeter wave radar may be installed in front of, behind, or other locations of the vehicle for measuring the distance of an object outside the vehicle from the vehicle using the characteristics of electromagnetic waves. Lidar may be mounted in front of, behind, or other locations on the vehicle for detecting object edges, shape information for object identification and tracking. The radar apparatus may also measure a change in the speed of the vehicle and the moving object due to the doppler effect.

Motor vehicle 110 may also include a communication device 112. The communication device 112 may include a satellite positioning module capable of receiving satellite positioning signals (e.g., beidou, GPS, GLONASS, and GALILEO) from satellites 141 and generating location information based on these signals. The communication device 112 may also include a module for communicating with the mobile communication base station 142, and the mobile communication network may implement any suitable communication technology, such as the current or evolving wireless communication technology (e.g., 5G technology) such as GSM/GPRS, CDMA, LTE. The communication device 112 may also have a Vehicle-to-Everything (V2X) module configured to enable, for example, vehicle-to-Vehicle (V2V) communication with other vehicles 143 and Vehicle-to-Infrastructure (V2I) communication with Infrastructure 144. In addition, the communication device 112 may also have a module configured to communicate with a user terminal 145 (including but not limited to a smart phone, tablet computer, or wearable device such as a watch), for example, by using a wireless local area network or bluetooth of the IEEE802.11 standard. With the communication device 112, the motor vehicle 110 can also access the server 120 via the network 130.

Motor vehicle 110 may also include a control device 113. The control device 113 may include a processor, such as a Central Processing Unit (CPU) or a Graphics Processing Unit (GPU), or other special purpose processor, etc., in communication with various types of computer readable storage devices or mediums. The control device 113 may include an autopilot system for automatically controlling various actuators in the vehicle. The autopilot system is configured to control a powertrain, steering system, braking system, etc. of a motor vehicle 110 (not shown) via a plurality of actuators in response to inputs from a plurality of sensors 111 or other input devices to control acceleration, steering, and braking, respectively, without human intervention or limited human intervention. Part of the processing functions of the control device 113 may be implemented by cloud computing. For example, some of the processing may be performed using an onboard processor while other processing may be performed using cloud computing resources. The control device 113 may be configured to perform a method according to the present disclosure. Furthermore, the control means 113 may be implemented as one example of a computing device on the motor vehicle side (client) according to the present disclosure.

The system 100 of fig. 1 may be configured and operated in various ways to enable application of the various methods and apparatus described in accordance with the present disclosure. In some embodiments, motor vehicle 110 may be an autonomous vehicle.

FIG. 2 illustrates a flow chart of a path planning method according to an embodiment of the present disclosure; referring to fig. 2, the present embodiment provides a path planning method 200, which includes steps S201 to S204.

Step S201, acquiring first location information of a first location and second location information of a second location.

Step S202, determining at least one first node corresponding to the first position information and at least one second node corresponding to the second position information based on the lane topological graph, wherein each of the at least one first node and the at least one second node corresponds to one lane in the map.

In step S203, virtual nodes are added to the lane topology, where the distance attribute of the lane corresponding to the virtual node is set to 0, and the virtual nodes are respectively connected to each of the at least one first node.

Step S204, determining the shortest path from the virtual node to any one of the at least one second node based on the lane topology after adding the virtual node.

The path planning method provided by the embodiment can realize the shortest path planning between the plurality of first nodes corresponding to the first position and the plurality of nodes corresponding to the second position, reduces the calculated amount and is beneficial to realizing the shortest path planning of the unmanned vehicle.

Taking a path from a start point to an end point as an example, the first position may be the start point of the path, the first position information may be the coordinates of the start point, the second position information may be the end point of the path, and the second position information may be the coordinates of the end point.

The lane topological graph can be a lane-level topological graph, the lane topological graph comprises a plurality of nodes, each node represents one lane in the map, and information such as the length of the lane, the coordinates of a starting point and a finishing point and the like is recorded. In addition, the lane topology is also provided with a connecting line representing a connecting attribute, and the connecting line can be used for connecting two nodes and representing that two corresponding lanes are connected, namely, the connecting line can pass from one lane to the other lane.

It will be appreciated that taking the first location as an example, the first location information represents a start point coordinate, which may correspond to one or more lanes, and in the lane topology, the first location information may correspond to one or more first nodes, and likewise, the second location information may correspond to one or more second nodes in the lane topology. The shortest path from the first location to the second location is the shortest path between any one of the first nodes and any one of the second nodes.

In step S203, a virtual node may be added to the lane topology, where the virtual node is also a node in the lane topology, and the virtual node is connected to all the first nodes through connection lines, that is, the virtual node is connected to each first node.

The distance attribute of the virtual node may be set to 0. In some embodiments, the distance attribute of the lane corresponding to the virtual node may represent the length of the lane corresponding to the virtual node, that is, the length of the lane may be set to 0. Still alternatively, the distance attribute may be further expressed as a distance between the virtual node and each of the at least one first node, i.e. the distance from the virtual node to each of all the first nodes is 0. By setting the distance attribute, the virtual nodes can be associated with all the first nodes, the calculation of the subsequent shortest path is convenient, and the result of the calculation of the shortest path is not influenced.

In step S204, the lane topology after adding the virtual node may be used as a basis of the shortest path planning, the virtual node is set as a start point of the path, searching is started from the virtual node, and since the virtual node is connected to all the first nodes, each first node may be used as a next-stage searching node of the virtual node.

And the searched path among the virtual node, the first node, the other nodes and the second node is the shortest path from the first position to the second position.

Further, the shortest path may be transmitted to a terminal of the autonomous vehicle for execution.

Fig. 3 shows a flowchart of step S204 in fig. 2; referring to fig. 3, determining a shortest path from a virtual node to any one of at least one second node includes step S301 and step S302.

Step S301, a virtual node is used as a searching starting point, and the next node in the lane topological graph is determined to be used as a current searching node based on a shortest path solving algorithm.

In step S302, in response to determining that the current search node is any one of the at least one second node, the current shortest path is acquired as the shortest path.

The shortest path solving algorithm may be a shortest path solving algorithm capable of realizing a single node to a single node, which is common in the related art. For example, the shortest path solving algorithm includes: the embodiment converts the multi-node-to-multi-node shortest path solving into a single node-to-single node computing mode by using an A star algorithm, a CH algorithm or an ant colony algorithm, so that multi-node-to-multi-node shortest path planning can be realized by using the common algorithms.

Taking the shortest path solving algorithm as an example, taking the virtual node as a searching starting point, and then searching nodes in the lane topological graph in sequence, it can be understood that the current searching node is the node with the shortest path from the virtual node, which is currently searched, and the current searching node also changes along with the increase of the searching time, if the current searching node is any one second node, the searching can be ended, and the searched second node is taken as the end point of the path, so that the calculation of the one-to-many shortest path from the single virtual node to a plurality of second nodes can be realized by utilizing the shortest path solving algorithm from the single node to the single node.

Fig. 4 shows a flow chart of a path planning method according to a further embodiment of the present disclosure; referring to fig. 4, the present embodiment further provides a path planning method 400, which includes steps S401 to S405.

Step S401, generating a lane topology map based on the map, wherein the lane topology map includes a plurality of nodes for respectively representing a plurality of lanes and connecting lines for representing a connection relationship between the lanes.

Step S402, acquiring first location information of a first location and second location information of a second location.

Step S403, determining at least one first node corresponding to the first location information and at least one second node corresponding to the second location information based on the lane topology map, wherein each of the at least one first node and the at least one second node corresponds to one lane in the map, respectively.

In step S404, a virtual node is added to the lane topology, where a distance attribute of a lane corresponding to the virtual node is set to 0, and the virtual node is connected to each of the at least one first node.

Step S405, determining a shortest path from the virtual node to any one of the at least one second node based on the lane topology after adding the virtual node.

The map may be a high-definition map, and can distinguish roads, lanes, and the like. All lanes in the map can be used as nodes respectively, and the connected lanes are used as connecting lines between two nodes, so that the connection attribute between the nodes is represented, and whether the lanes can pass through or not can be shown from the topological graph.

Steps S402 to S405 are the same as steps S201 to S204 in the above embodiments, and specific reference may be made to the above embodiments, which are not repeated.

By the method provided by the embodiment, the lane topological graph can be generated by means of the map, and a basis is provided for calculating the shortest path.

FIG. 5 illustrates a topology diagram from a start point to an end point in a path planning method according to an embodiment of the present disclosure; referring to fig. 5, a partial lane topology is shown, dots in the diagram represent nodes, and connection lines with arrows represent interconnections between nodes.

In this embodiment, after the first position information and the second position information are acquired, nodes corresponding to the first position information and the second position information may be found in the lane topological graph, where the first position information corresponds to four first nodes 502a, 502b, 502c, and 502d, and the second position information corresponds to four second nodes 505a, 505b, 505c, and 505d.

Then, a virtual node 501 is added to the plurality of first nodes (502 a, 502b, 502c and 502 d), the distance attribute of the virtual node 501 is 0, and the virtual node is connected with the four first nodes (502 a, 502b, 502c and 502 d) through connecting lines respectively.

Then, the virtual node 501 is taken as a searching starting point, and the nodes closest to the virtual node 501 start to be searched one by one, and since the virtual node 501 is connected with four first nodes (505 a, 505b, 505c and 505 d), the next-stage node on the shortest path searched by the virtual node 501 is necessarily one of the four first nodes, such as the first node 502a in the figure, by taking the virtual node 501 as a searching starting point.

Next, the node 503 and the node 504 may be sequentially determined, and finally, one second node 505c is searched, that is, a path from the virtual node 501 to the second node 505c through the first node 502a, the node 503, and the node 504 sequentially is the shortest path.

And, since the distance attribute of the virtual node 501 is 0, the shortest path passing through the first node 502a, the node 503, the node 504 and the second node 505c in order after the virtual node is removed can be transmitted to the autonomous vehicle as the travel path of the autonomous vehicle.

It will be appreciated that in the above embodiments, the path is planned with the first location as the start point and the second location as the end point, and in some embodiments, the shortest path may be searched reversely with the first location as the end point and the second location as the start point.

Further, in some embodiments, at least one path point may be set between the start point and the end point, so as to adapt to more path planning requirements. At this time, the second position may be a path position between the first position and the third position.

It will be understood that, if a route point is set as an example, a first shortest path may be calculated by using a start point as a first position and a route point as a second position, then a second shortest path may be calculated by using a route point as the first position and an end point as the second position, and a path formed by combining the first shortest path and the second shortest path is a planned target path.

It will be understood that if N route points are included, N is a natural number, where the N route points may divide the start point to the end point into n+1 routes, the start point of each route may be used as a first position, the end point of each route may be used as a second position, and steps S201 to S204 are performed, so that n+1 shortest paths may be obtained, and the shortest paths may be connected to obtain a shortest path from the start point to the end point through the N route points.

FIG. 6A illustrates a topology diagram from a start point to a waypoint in a path planning method according to an embodiment of the disclosure; FIG. 6B illustrates a topology diagram from a pass point to a final point in a path planning method according to an embodiment of the present disclosure; referring to fig. 6A and 6B, in this embodiment, taking an example of having one passing point, in fig. 6A, a start point and a passing point may be first acquired as a first position and a second position, and nodes corresponding to first position information and second position information may be found in a lane topology, where the first position information corresponds to four first nodes 602a, 602B, 602c and 602d, and the second position information corresponds to four second nodes 605a, 605B, 605c and 605d.

Then, a virtual node 601 is set for the four first nodes (602 a, 602b, 602c and 602 d), and then the shortest path to any one of the second nodes (605 a, 605b, 605c or 605 d) is calculated using the virtual node 601 as a search start point, that is, the first shortest path sequentially passing through the first node 602a, the node 603, the node 604 to the second node 605 c.

Then referring to fig. 6B, the route point and the end point are acquired as a first position and a second position, respectively, and nodes corresponding to the first position information corresponding to four first nodes 605a, 605B, 605c, and 605d and the second position information corresponding to four second nodes 609a, 609B, 609c, and 609d are found in the lane topology.

Then, a virtual node 606 is set for the four first nodes (605 a, 605b, 605c and 605 d), and then the shortest path to any one of the second nodes (609 a, 609b, 609c or 609 d), that is, the second shortest path to the second node 609c through the first node 605b, the node 607, the node 608 in order, is calculated using the virtual node 606 as a search start point.

The first shortest path and the second shortest path are then combined as a result of the overall path planning. It will be appreciated that although the end point of the first leg is the second node 605c in fig. 6A and the start point of the second leg is the first node 605B in fig. 6B, since both nodes correspond to the same waypoint coordinates, the connection from the first shortest path to the second shortest path can be achieved by switching lanes, i.e. from the lane corresponding to the node 605c to the lane corresponding to the node 605B.

Of course, fig. 5, 6A and 6B are only examples, only the nodes (e.g., nodes 603 and 604 in fig. 5, nodes 603 and 605 in fig. 6A, and nodes 607 and 608 in fig. 6B) through which the shortest path passes are shown, not all the nodes are shown, and the number of nodes and passing points in the graph may be set according to actual situations, which is not limited.

Fig. 7 shows a block diagram of a path planning apparatus according to an embodiment of the present disclosure; referring to fig. 7, the present embodiment provides a path planning apparatus 700, including:

an acquisition unit 701 configured to acquire first position information of a first position and second position information of a second position.

The first determining unit 702 is configured to determine at least one first node corresponding to the first location information and at least one second node corresponding to the second location information based on the lane topology map, wherein each of the at least one first node and the at least one second node corresponds to one lane in the map, respectively.

An adding unit 703 configured to add a virtual node in the lane topology, wherein the length of the lane corresponding to the virtual node is set to 0, and the virtual node is connected to each of the at least one first node, respectively.

The second determining unit 704 is configured to determine a shortest path from the virtual node to any one of the at least one second node based on the lane topology after adding the virtual node.

In some embodiments, the second determining unit 704 is further configured to determine, based on the shortest path solving algorithm, a next node in the lane topology as a current searching node with the virtual node as a searching start point; and in response to determining that the current search node is any one of the at least one second node, acquiring the current shortest path as the shortest path.

In some embodiments, the shortest path solving algorithm comprises: an a star algorithm, a CH algorithm or an ant colony algorithm.

In some embodiments, the second location is a pathway location between the first location and the third location.

In some embodiments, the distance attribute of the lane corresponding to the virtual node is a length of the lane corresponding to the virtual node or a distance between the lane corresponding to the virtual node and each of the plurality of first nodes.

In some embodiments, the path planning apparatus further comprises: and a generation unit configured to generate a lane topology map based on the map, wherein the lane topology map includes a plurality of nodes for respectively representing a plurality of lanes and connecting lines for representing a connection relationship between the lanes.

According to embodiments of the present disclosure, there is also provided an electronic device, a readable storage medium, a computer program product and an autonomous vehicle.

According to another aspect of the disclosure, there is further provided an edge computing device, optionally, the edge computing device may further include a communication component, and the electronic device may be integrally integrated with the communication component or may be separately provided. The electronic device may acquire data of the road side sensing device (such as a road side camera), for example, pictures and videos, so as to perform image video processing and data calculation, and then transmit the processing and calculation results to the cloud control platform via the communication component.

Optionally, the edge computing device may also be a roadside computing unit (Road Side Computing Unit, RSCU). Optionally, the electronic device may also have a perceived data acquiring function and a communication function, for example, an AI camera, and the electronic device may directly perform image video processing and data calculation based on the acquired perceived data, and then transmit the processing and calculation results to the cloud control platform.

Optionally, the cloud control platform performs processing at the cloud end to perform image video processing and data calculation, and the cloud control platform may also be referred to as a vehicle-road collaborative management platform, a V2X platform, a cloud computing platform, a central system, a cloud server, and the like.

Fig. 8 illustrates a block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure. With reference to fig. 8, a block diagram of an electronic device 800 that may be a server or a client of the present disclosure, which is an example of a hardware device that may be applied to aspects of the present disclosure, will now be described. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 8, the electronic device 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM803, various programs and data required for the operation of the electronic device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to the bus 804.

Various components in electronic device 800 are connected to I/O interface 805, including: an input unit 806, an output unit 807, a storage unit 808, and a communication unit 809. The input unit 806 may be any type of device capable of inputting information to the electronic device 800, the input unit 806 may receive input numeric or character information and generate key signal inputs related to user settings and/or function control of the electronic device, and may include, but is not limited to, a mouse, a keyboard, a touch screen, a trackpad, a trackball, a joystick, a microphone, and/or a remote control. The output unit 807 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers. The storage unit 808 may include, but is not limited to, magnetic disks, optical disks. The communication unit 809 allows the electronic device 800 to exchange information/data with other devices over computer networks, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth (TM) devices, 802.11 devices, wiFi devices, wiMax devices, cellular communication devices, and/or the like.

The computing unit 801 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 801 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The calculation unit 801 performs the respective methods and processes described above, for example, a path planning method. For example, in some embodiments, the path planning method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 800 via the ROM 802 and/or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the path planning method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the path planning method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

According to another aspect of the present disclosure, there is also provided an autonomous vehicle including the electronic apparatus of the above-described embodiment of the present disclosure.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.

Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it is to be understood that the foregoing methods, systems, and apparatus are merely exemplary embodiments or examples, and that the scope of the present invention is not limited by these embodiments or examples but only by the claims following the grant and their equivalents. Various elements of the embodiments or examples may be omitted or replaced with equivalent elements thereof. Furthermore, the steps may be performed in a different order than described in the present disclosure. Further, various elements of the embodiments or examples may be combined in various ways. It is important that as technology evolves, many of the elements described herein may be replaced by equivalent elements that appear after the disclosure.

Claims

1. A path planning method, comprising:

acquiring first position information of a first position and second position information of a second position;

determining at least one first node corresponding to the first position information and at least one second node corresponding to the second position information based on a lane topology map, wherein each of the at least one first node and the at least one second node corresponds to one lane in a map;

adding a virtual node in the lane topological graph, wherein the distance attribute of a lane corresponding to the virtual node is set to 0, and the virtual node is respectively connected with each first node in the at least one first node; and

determining a shortest path from the virtual node to any one of the at least one second node based on the lane topology after adding the virtual node.

2. The path planning method of claim 1, wherein the determining a shortest path from the virtual node to any of the at least one second node comprises:

determining the next node in the lane topological graph as a current searching node based on a shortest path solving algorithm by taking the virtual node as a searching starting point; and

And in response to determining that the current search node is any one of the at least one second node, acquiring a current shortest path as the shortest path.

3. The path planning method according to claim 2, wherein,

the shortest path solving algorithm comprises the following steps: an a star algorithm, a CH algorithm or an ant colony algorithm.

4. A path planning method according to any one of claims 1 to 3, wherein the second location is a pathway location between the first and third locations.

5. A path planning method according to any one of claims 1 to 3, the distance attribute of the lane to which the virtual node corresponds being the length of the lane to which the virtual node corresponds or the distance between the lane to which the virtual node corresponds and each of the at least one first node.

6. A path planning method according to any one of claims 1-3, further comprising:

the lane topological graph is generated based on a map, wherein the lane topological graph comprises a plurality of nodes used for respectively representing a plurality of lanes and connecting lines used for representing the connection relation among the lanes.

7. A path planning apparatus comprising:

An acquisition unit configured to acquire first position information of a first position and second position information of a second position;

a first determination unit configured to determine at least one first node corresponding to the first position information and at least one second node corresponding to the second position information based on a lane topology map, wherein each of the at least one first node and the at least one second node corresponds to one lane in a map, respectively;

an adding unit configured to add a virtual node in the lane topology map, wherein the length of a lane corresponding to the virtual node is set to 0, and the virtual node is respectively connected with each first node in the at least one first node; and

and a second determination unit configured to determine a shortest path from the virtual node to any one of the at least one second node based on the lane topology after adding the virtual node.

8. The path planning apparatus according to claim 7, wherein the second determination unit is further configured to determine a next node in the lane topology as a current search node based on a shortest path solving algorithm with the virtual node as a search start point; and in response to determining that the current search node is any one of the at least one second node, acquiring a current shortest path as the shortest path.

9. The path planning apparatus according to claim 8, wherein,

10. A path planning apparatus according to any one of claims 7 to 9, wherein the second location is a pathway location between the first and third locations.

11. The path planning apparatus according to any one of claims 7 to 9, the distance attribute of the lane to which the virtual node corresponds being a length of the lane to which the virtual node corresponds or a distance between the lane to which the virtual node corresponds to each of the at least one first node.

12. The path planning apparatus according to any one of claims 7-9, further comprising:

and a generation unit configured to generate the lane topology based on a map, wherein the lane topology includes a plurality of nodes for respectively representing a plurality of lanes and connecting lines for representing a connection relationship between the lanes.

13. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the method comprises the steps of

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.

14. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-6.

15. An autonomous vehicle comprising: the electronic device of claim 13.