CN114047760A

CN114047760A - Path planning method and device, electronic equipment and automatic driving vehicle

Info

Publication number: CN114047760A
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: 2022-02-15
Anticipated expiration: 2041-11-10
Also published as: CN114047760B

Abstract

The disclosure provides a path planning method and device, electronic equipment and an automatic driving vehicle, and relates to the technical field of computers, in particular 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 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 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 the multiple nodes to the 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 technologies, and in particular, to a method and an apparatus for path planning, an electronic device, a computer-readable storage medium, a computer program product, and an autonomous driving vehicle.

Background

The path planning technology is widely applied to various technical fields, such as intelligent travel, automatic driving, robot autonomous action and the like. The path planning algorithm is the 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, unless otherwise indicated, the problems mentioned in this section should not be considered as having been acknowledged in any prior art.

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 topological graph, wherein each of the at least one first node and the at least one second node respectively 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 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.

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 determining unit 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 respectively corresponds to one lane in the map; the system comprises an adding unit, a judging unit and a judging unit, wherein the adding unit is configured to add a virtual node in a lane topological graph, the length of a lane corresponding to the virtual node is set to be 0, and the virtual node is respectively connected with each first node in 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 map to which the virtual node is added.

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 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 having stored thereon computer instructions for causing a computer to perform the method as described above.

According to another aspect of the disclosure, a computer program product is provided, comprising a computer program, wherein the computer program realizes the method of claim if executed by a processor.

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

According to one or more embodiments of the present disclosure, shortest path planning from a multi-node to a multi-node may be achieved.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the embodiments and, together with the description, serve to explain the exemplary implementations of the embodiments. The illustrated embodiments are for purposes of illustration only and do not limit the scope of the claims. Throughout the drawings, identical reference numbers 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, according to an embodiment of the present disclosure;

FIG. 2 shows a flow diagram 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 diagram of a path planning method according to a further embodiment of the present disclosure;

fig. 5 shows a topological structure diagram from a starting point to an end point in a path planning method according to an embodiment of the present disclosure;

fig. 6A illustrates a topological structure diagram from a starting point to a waypoint in a path planning method according to an embodiment of the present disclosure;

fig. 6B shows a topological structure diagram from a route point to an end 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 with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as 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 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, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, the timing relationship, or the importance relationship of the elements, and such terms are used only 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, based on the context, they may also refer to different instances.

The terminology used in the description of the various described 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, if the number of elements is not specifically limited, the elements may be one or more. Furthermore, the term "and/or" as used in this disclosure is intended to encompass any and all possible combinations of the listed items.

The current path planning algorithms mainly include an a star algorithm, a ch (control hierarchy) algorithm, an ant colony algorithm, and the like, which can only realize the shortest path planning from a single starting point to a single end point, but for the field of automatic driving, an automatic driving vehicle not only needs to select a road with the shortest path to pass, but also needs to further select lanes in the road, and when a road corresponds to a plurality of lanes, the shortest path planning algorithm has limitations.

The disclosed embodiments provide a shortest path planning method, apparatus, electronic device, computer-readable storage medium, computer program product, and autonomous driving vehicle, which can implement shortest path planning from multiple start points to multiple end points by adding virtual nodes to multiple nodes corresponding to the start points and starting shortest path search 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 embodiments 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 embodiments of the present disclosure, motor vehicle 110 may include a computing device and/or be configured to perform a method in accordance with embodiments 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, the 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, which may be executed 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 take advantage of the services provided by these components. It should be understood 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 involving virtualization (e.g., one or more flexible pools of logical storage that may be virtualized to maintain virtual storage for the server). In various embodiments, the 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. The 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, and the like.

In some embodiments, 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 variety of available protocols, including but not limited to TCP/IP, SNA, IPX, etc. By way of example only, one or more networks 110 may be a satellite communication 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, e.g., bluetooth, WiFi), and/or any combination of these and 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 the 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 certain embodiments, the data store used by the server 120 may be a database, such as a relational database. One or more of these databases may store, update, and retrieve data to and from the database in response to the command.

In some embodiments, one or more of the 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 regular stores supported by a file system.

Motor vehicle 110 may include sensors 111 for sensing the surrounding environment. The sensors 111 may include one or more of the following sensors: visual cameras, infrared cameras, ultrasonic sensors, millimeter wave radar, and laser radar (LiDAR). Different sensors may provide different detection accuracies and ranges. The camera may be mounted in front of, behind, or otherwise on the vehicle. The visual camera may capture conditions inside and outside the vehicle in real time and present to the driver and/or passengers. In addition, by analyzing the picture captured by the visual camera, information such as traffic light indication, intersection situation, other vehicle running state, and the like can be acquired. The infrared camera can capture objects under night vision conditions. The ultrasonic sensors can be arranged around the vehicle and used for measuring the distance between an object outside the vehicle and the vehicle by utilizing the characteristics of strong ultrasonic directionality and the like. The millimeter wave radar may be installed in front of, behind, or other positions of the vehicle for measuring the distance of an object outside the vehicle from the vehicle using the characteristics of electromagnetic waves. The lidar may be mounted in front of, behind, or otherwise of the vehicle for detecting object edges, shape information, and thus object identification and tracking. The radar apparatus can also measure a speed variation 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 the satellites 141 and generating position information based on these signals. The communication device 112 may also include modules to communicate with a mobile communication base station 142, and the mobile communication network may implement any suitable communication technology, such as current or evolving wireless communication technologies (e.g., 5G technologies) like GSM/GPRS, CDMA, LTE, etc. The communication device 112 may also have a Vehicle-to-Vehicle (V2X) networking or Vehicle-to-Vehicle (V2X) module configured to enable, for example, Vehicle-to-Vehicle (V2V) communication with other vehicles 143 and Vehicle-to-Infrastructure (V2I) communication with the Infrastructure 144. Further, the communication device 112 may also have a module configured to communicate with a user terminal 145 (including but not limited to a smartphone, tablet, or wearable device such as a watch), for example, via wireless local area network using IEEE802.11 standards or bluetooth. Motor vehicle 110 may also access server 120 via network 130 using communication device 112.

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 media. 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, and 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 realized by cloud computing. For example, some processing may be performed using an onboard processor while other processing may be performed using the computing resources in the cloud. The control device 113 may be configured to perform a method according to the present disclosure. Furthermore, the control apparatus 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 shows a flow diagram 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.

In step S201, first position information of a first position and second position information of a second position are acquired.

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

Step S203, adding a virtual node in the lane topological graph, wherein the distance attribute of the lane corresponding to the virtual node is set to be 0, and the virtual node is respectively connected with each first node in the at least one first node.

And step S204, 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.

The path planning method provided by the embodiment can realize the shortest path planning from the plurality of first nodes corresponding to the first position to 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 distance from the starting point to the ending point as an example, the first position may be a starting point of the distance, the first position information may be coordinates of the starting point, the second position information may be an ending point of the distance, and the second position information may be coordinates of the ending point.

The lane topological graph can be a topological graph at a lane level, and 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, coordinates of a starting point and an ending point and the like is recorded. In addition, the lane topological graph also has a connecting line representing a connection attribute, and the connecting line can be used for connecting two nodes and representing that the two corresponding lanes are connected, namely the two corresponding lanes can pass from one lane to the other lane.

It is understood that, taking the first position as an example, the first position information represents a start coordinate, which may correspond to one or more lanes, and in the lane topology map, the first position information may correspond to one or more first nodes, and similarly, the second position information may also correspond to one or more second nodes in the lane topology map. The shortest path from the first position to the second position is the shortest path from any one first node to any one second node.

In step S203, a virtual node may be added to the lane topology map, where the virtual node is also a node in the lane topology map, 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 also be represented as a distance between the virtual node and each of the at least one first node, that is, the distance between the virtual node and each of all the first nodes is 0. By setting the distance attribute, the virtual node can be associated with all the first nodes, so that the calculation of the subsequent shortest path is facilitated, and the calculation result of the shortest path is not influenced.

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

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

Further, the shortest path may be sent 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 the shortest path from the virtual node to any one of the at least one second node includes steps S301 and S302.

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

Step S302, in response to determining that the current search node is any one of the at least one second node, obtaining a current shortest path as a shortest path.

The shortest path solving algorithm may be a common shortest path solving algorithm capable of realizing a single node to a single node in the related art. For example, the shortest path solving algorithm includes: the present embodiment converts the multi-node shortest path solution into a single-node-to-single-node calculation mode, so that the common algorithms can be used to implement the multi-node to multi-node shortest path planning.

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

Fig. 4 shows a flow diagram 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 topological graph based on the 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 between the lanes.

Step S402, first position information of the first position and second position information of the second position are acquired.

Step S403, 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, where each of the at least one first node and the at least one second node corresponds to a lane in the map.

Step S404, adding a virtual node in the lane topological graph, wherein the distance attribute of the lane corresponding to the virtual node is set to be 0, and the virtual node is respectively connected with each first node in the at least one first node.

Step S405, 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.

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

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

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

Fig. 5 shows a topological structure diagram from a starting 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, wherein dots represent nodes and connecting lines with arrows represent the interconnection between the nodes.

In this embodiment, after acquiring the first position information and the second position information, nodes corresponding to the first position information and the second position information may be found in the lane topology map, 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 505 d.

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

Then, the virtual node 501 is used as a search starting point, and the nodes closest to the virtual node 501 are searched one by one, because the virtual node 501 is connected with four first nodes (505a, 505b, 505c and 505d), and the next-level 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 using the virtual node 501 as the search starting point.

Then, the node 503 and the node 504 may be determined in turn, and finally a second node 505c is searched, i.e. the path from the virtual node 501 to the second node 505c via the first node 502a, the node 503, and the node 504 in turn is the shortest path.

And since the virtual node 501 distance attribute is 0, the shortest path, from which the virtual node is removed, sequentially passing through the first node 502a, the node 503, the node 504, and the second node 505c may be sent to the autonomous vehicle as a driving path of the autonomous vehicle.

It is to be understood that, in the above embodiments, the route is planned with the first position as the starting point and the second position as the ending point, and in some embodiments, the shortest route may also be reversely searched with the first position as the ending point and the second position as the starting point.

Further, in some embodiments, at least one path point may be set between the starting point and the ending point, so that more path planning requirements may be met. At this time, the second position may be a route position between the first position and the third position.

It can be understood that, for example, if one route point is set, the starting point may be used as the first position, the route point may be used as the second position, the first shortest path is calculated, then the route point may be used as the first position, the end point may be used as the second position, the second shortest path is calculated, and the route obtained by combining the first shortest path and the second shortest path is the planned destination route.

It can be understood that if N route points are included, where N is a natural number, the N route points may divide the starting point to the end point into N +1 routes, and may use the starting point of each route as a first position and the end point of each route as a second position, and execute steps S201 to S204, so as to obtain N +1 shortest paths, and the shortest paths may be connected to obtain the shortest path from the starting point to the end point via the N route points.

Fig. 6A illustrates a topological structure diagram from a starting point to a waypoint in a path planning method according to an embodiment of the present disclosure; fig. 6B shows a topological structure diagram from a route point to an end point in a path planning method according to an embodiment of the present disclosure; referring to fig. 6A and 6B, in the present embodiment, taking an example of having one passing point, in fig. 6A, a starting point and a passing point may be first obtained as a first position and a second position, and nodes corresponding to first position information and second position information may be found in the 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 605 d.

Then, a virtual node 601 is set for four first nodes (602a, 602b, 602c, and 602d), and then, with the virtual node 601 as a search starting point, a shortest path to any one of the second nodes (605a, 605b, 605c, or 605d) is calculated, that is, a first shortest path to the second node 605c via the first node 602a, the node 603, and the node 604 in this order.

Then, referring to fig. 6B, the approach point and the end point are acquired as a first position and a second position, respectively, and nodes corresponding to first position information corresponding to four

first nodes

605a, 605B, 605c, and 605d and second position information corresponding to four

second nodes

609a, 609B, 609c, and 609d are found in the lane topology map.

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

The first shortest path and the second shortest path are then combined as a result of the overall path plan. It is understood that although the end point of the first route is the second node 605c in fig. 6A, and the start point of the second route is the first node 605B in fig. 6B, since the two nodes both correspond to the same passing point coordinate, the connection from the first shortest path to the second shortest path can be realized by switching lanes, that is, by switching from the lane corresponding to the node 605c to the lane corresponding to the node 605B.

Of course, fig. 5, fig. 6A and fig. 6B are only examples, and only show nodes through which the shortest path passes (for example,

nodes

603 and 604 in fig. 5, nodes 603 and 605 in fig. 6A, and

nodes

607 and 608 in fig. 6B), not all nodes are shown, and the number of nodes and via points in the figures may be set according to actual situations, and is not limited herein.

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.

A first determining unit 702 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 respectively corresponds to one lane in the map.

An adding unit 703 configured to add a virtual node to the lane topology map, 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.

A second determining unit 704 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 map after the virtual node is added.

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

In some embodiments, the shortest path solving algorithm comprises: the A star algorithm, the CH algorithm, or the 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 includes: the vehicle lane topological graph generating unit is configured to generate a lane topological graph 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 between the lanes.

There is also provided, in accordance with an embodiment of the present disclosure, an electronic device, a readable storage medium, a computer program product, and an autonomous vehicle.

According to another aspect of the present disclosure, an edge computing device is further provided, and optionally, the edge computing device may further include a communication component and the like in addition to the electronic device, and the electronic device may be integrated with the communication component or may be separately disposed. The electronic device can acquire data, such as pictures and videos, of the roadside sensing device (such as a roadside camera), so that image video processing and data calculation are performed, and then processing and calculation results are transmitted to the cloud control platform through the communication component.

Optionally, the edge Computing device may also be a Road Side Computing Unit (RSCU). Optionally, the electronic device itself may also have a perception data acquisition 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 perception 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 cooperative 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. Referring to fig. 8, a block diagram of a structure of an electronic device 800, which 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 device is 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 phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples 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 apparatus 800 can also be stored. The calculation 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 bus 804.

A number of components in the electronic device 800 are connected to the 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, and the input unit 806 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device, and may include, but is not limited to, a mouse, a keyboard, a touch screen, a track pad, a track ball, a joystick, a microphone, and/or a remote controller. Output unit 807 can be any type of device capable of presenting information and can include, but is not limited to, a display, speakers, a video/audio output terminal, a vibrator, and/or a printer. The storage unit 808 may include, but is not limited to, a magnetic disk, an optical disk. The communication unit 809 allows the electronic device 800 to exchange information/data with other devices via a computer network, 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.

Computing unit 801 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and the like. The calculation unit 801 performs the respective methods and processes described above, such as the path planning method. For example, in some embodiments, the path planning method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and/or installed onto the electronic device 800 via the ROM 802 and/or the communication unit 809. When loaded into RAM803 and executed by the computing unit 801, a computer program may perform one or more steps of the path planning method described above. 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 circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a 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 that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes 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 codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. 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. A 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 a pointing device (e.g., a mouse or a 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 can 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, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end 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 back-end, 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 clients and servers. A client and server are generally 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 with a combined blockchain.

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

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be performed in parallel, sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.

Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it is to be understood that the above-described 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 as issued and their equivalents. Various elements in the embodiments or examples may be omitted or may be replaced with equivalents thereof. Further, the steps may be performed in an order different from that described in the present disclosure. Further, various elements in 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 with equivalent elements that appear after the present 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 respectively 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 be 0, and the virtual node is respectively connected with each first node in the at least one first node; and

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.

2. The path planning method according to claim 1, wherein the determining a shortest path from the virtual node to any one 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

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

3. The path planning method according to claim 1 or 2,

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

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

5. The path planning method according to any one of claims 1 to 4, wherein 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 at least one first node.

6. The path planning method according to any one of claims 1-5, further comprising:

generating the lane topological graph 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 between the lanes.

7. A path planner, comprising:

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

a first determining 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 respectively corresponds to one lane in a map;

the adding unit is configured to add a virtual node in the lane topological graph, wherein the length of a lane corresponding to the virtual node is set to be 0, and the virtual node is respectively connected with each first node in the at least one first node; 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 map after the virtual node is added.

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

9. The path planning apparatus according to claim 7 or 8,

10. The path planner according to any of the claims 7-9, wherein the second position is a pathway position between the first position and a third position.

11. The path planner according to any one of claims 7-10, wherein 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 at least one first node.

12. The path planner according to any of the claims 7-11, further comprising:

a generating unit configured to generate the lane topological graph based on a map, wherein the lane topological graph includes a plurality of nodes for respectively representing a plurality of lanes and connecting lines for representing connection relationships 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 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 having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-6.

15. A computer program product comprising a computer program, wherein the computer program realizes the method of any one of claims 1-6 when executed by a processor.

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