Obstacle processing method and device for automatic driving scene, equipment and medium

Abstract

The invention discloses an obstacle processing method and device for an automatic driving scene, equipment and a storage medium. The method comprises the steps of obtaining first spatial data of a to-be-processed obstacle; segmenting the first spatial data based on a set standard length to obtain second spatial data respectively corresponding to at least two sub-to-be-processed obstacles; and determining an axis alignment bounding box of the to-be-processed obstacle according to the second spatial data. By utilizing the method, the projected obstacle reduces the space lost in the form of an axisymmetric bounding box at the place with larger curvature of the road, so that a lot of passable space is saved, and the passing efficiency is improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of autonomous driving technology, and in particular to an obstacle handling method, device, equipment and medium for an autonomous driving scenario. Background Art

[0002] Autonomous driving is usually planned in the Frenet coordinate system. Obstacles in the Cartesian system need to be projected into the Frenet system. Obstacles are usually represented in the Frenet system using an axis-aligned bounding box (aabox). This method is relatively conservative and will lose some relatively safe space, but it is relatively resource-saving.

[0003] In the Frenet system, the projected obstacles are more severely curved where the road curvature is larger. Therefore, obstacles with larger curvatures lose more space in the aabox form, which wastes a lot of traversable space for path planning, may cause planning failure and stagnation, and reduce traffic efficiency. Summary of the invention

[0004] The embodiment of the present invention provides an obstacle processing method, device, equipment and storage medium for an autonomous driving scene, wherein the projected obstacle reduces the space lost in the form of an axisymmetric bounding box in places where the road curvature is large, saves a lot of traversable space, and improves the traffic efficiency.

[0005] In a first aspect, an embodiment of the present invention provides an obstacle handling method for an autonomous driving scenario, comprising:

[0006] Acquire first spatial data of obstacles to be processed;

[0007] The first spatial data is divided based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed respectively;

[0008] An axis-aligned bounding box of the obstacle to be processed is determined according to the second spatial data.

[0009] In a second aspect, an embodiment of the present invention further provides an obstacle handling device for an autonomous driving scenario, the device comprising:

[0010] A data acquisition module, used to acquire first spatial data of obstacles to be processed;

[0011] A data segmentation module, configured to segment the first spatial data based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed;

[0012] A determination module determines an axis-aligned bounding box of the obstacle to be processed according to the second spatial data.

[0013] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0014] one or more processors;

[0015] a storage device for storing one or more programs,

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the obstacle handling method for the autonomous driving scenario provided by the embodiment of the present disclosure.

[0017] In a fourth aspect, the embodiments of the present disclosure also provide a storage medium containing computer executable instructions, which, when executed by a computer processor, are used to execute an obstacle handling method for an autonomous driving scenario provided by the embodiments of the present disclosure.

[0018] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the obstacle handling method for the autonomous driving scenario provided by the embodiment of the first aspect above.

[0019] The present invention discloses an obstacle processing method, device, equipment and storage medium for an autonomous driving scene, including: obtaining first spatial data of an obstacle to be processed; dividing the first spatial data based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed; and determining an axis-aligned bounding box of the obstacle to be processed according to the second spatial data. Using this method: the projected obstacle reduces the space lost in the form of an axisymmetric bounding box in places with large road curvature, saves a lot of traversable space, and improves traffic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0021] Figure 1 A flowchart of an obstacle handling method for an autonomous driving scenario provided by an embodiment of the present disclosure;

[0022] Figure 2 A schematic diagram of the structure of an obstacle handling device for an autonomous driving scenario provided by an embodiment of the present disclosure;

[0023] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0025] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0026] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0027] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0028] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0029] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0030] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0031] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0032] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0033] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0034] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0035] Figure 1 A flowchart of obstacle handling in an autonomous driving scenario provided in an embodiment of the present disclosure is applicable to providing a solution to the problem that more space is lost in the form of an AAbox when an obstacle with a larger degree of road curvature occurs. The method can be executed by an obstacle handling device in an autonomous driving scenario, which can be implemented in the form of software and / or hardware, and optionally, by an electronic device, which can be a mobile terminal, a PC, a server, etc.

[0036] like Figure 1 As shown, an obstacle handling method for an autonomous driving scenario provided by an embodiment of the present disclosure may specifically include the following steps:

[0037] S110: Acquire first spatial data of obstacles to be processed.

[0038] In an embodiment, the obstacle to be processed may be an obstacle that needs data processing for path planning. The first spatial data may be spatial coordinate data of the obstacle to be processed in a Cartesian coordinate system and in a corresponding Frenet system.

[0039] Specifically, first spatial data of the obstacle to be processed is obtained.

[0040] On the basis of the above embodiment, before obtaining the first spatial data of the obstacle to be processed, the method further includes:

[0041] Filter out obstacles to be processed that are located behind the current vehicle; filter out obstacles to be processed that are decided to be ignored; filter out virtual obstacles to be processed; filter out obstacles to be processed that are located at the navigation end point.

[0042] In this embodiment, the current vehicle may be the currently autonomous driving vehicle. By setting an obstacle filter, obstacles to be processed located behind the current vehicle, obstacles to be processed that are decided to be ignored, virtual obstacles to be processed, and obstacles to be processed located at the navigation end point are filtered out. Relevant static obstacles in the gate scene and other obstacles that need to be filtered according to business customization can also be filtered out.

[0043] S120: Slice the first spatial data based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed.

[0044] In this embodiment, the set standard length may be a preset length, which may be set to the current vehicle length or the current vehicle length multiplied by a proportional coefficient. It is not specifically limited in this embodiment and is set according to actual conditions. The sub-obstacle to be processed may be data obtained by virtual segmentation of the spatial data of the obstacle to be processed. The second spatial data may be the spatial coordinate data of the sub-obstacle to be processed in the Cartesian coordinate system and the corresponding spatial coordinate data in the Frenet system.

[0045] Specifically, the value of the long side in the first spatial data is divided by the set standard length and rounded up as the number of divisions. The first spatial data of the obstacle to be processed is evenly divided along the long side according to the number of divisions to obtain at least two sub-obstacles to be processed and obtain the second spatial data corresponding to the sub-obstacles to be processed.

[0046] Based on the above embodiment, before the obstacles to be processed are segmented based on the set standard length, the method further includes:

[0047] a1) determining whether the area enclosed by each point in the first spatial data is greater than or equal to a set threshold;

[0048] b1) if the area enclosed by the points in the first spatial data is smaller than a set threshold, the axis-aligned bounding box corresponding to the first spatial data is used as the axis-aligned bounding box of the obstacle to be processed;

[0049] c1) if the area enclosed by the points in the first spatial data is greater than or equal to a set threshold, determining whether the first spatial data satisfies a basic condition that the obstacle to be processed is a vehicle; the basic condition at least includes: the number of corner points included in the first spatial data is a set value;

[0050] d1) if the first spatial data does not satisfy the basic condition that the obstacle to be processed is a vehicle, using the axis-aligned bounding box corresponding to the first spatial data as the axis-aligned bounding box of the obstacle to be processed;

[0051] e1) If the first spatial data meets the basic condition that the obstacle to be processed is a vehicle, the first spatial data is segmented based on a set standard length.

[0052] In this embodiment, the set threshold value may be a preset threshold value, which may be set to the projection area of ​​a large vehicle, which is not specifically limited in this embodiment and is set according to actual conditions. The set value may be a preset threshold value, which may be set to 4, which is not specifically limited in this embodiment and is set according to actual conditions.

[0053] The specific steps of using the axis-aligned bounding box corresponding to the first spatial data as the axis-aligned bounding box of the obstacle to be processed are the same as the steps of using the axis-aligned bounding box corresponding to the second spatial data as the axis-aligned bounding box of the obstacle to be processed, specifically: determining the initial sub-axis-aligned bounding box corresponding to the first spatial data, and obtaining the speed of the obstacle to be processed; if the speed is greater than the first set threshold and less than the second set threshold, updating the initial sub-axis-aligned bounding box; if the speed is equal to the first set threshold or greater than the second set threshold, updating the initial sub-axis-aligned bounding box, and outputting the first sub-axis-aligned bounding box; if the shape of the obstacle to be processed is a set shape, the front and back of the first sub-axis-aligned bounding box are extended by a set length; if the shape of the obstacle to be processed is not a set shape, the first sub-axis-aligned bounding box is not expanded, and the second sub-axis-aligned bounding box is output; if part of the position of the obstacle to be processed is located after the position of the current vehicle, the part located after the position of the current vehicle is deleted, and the third sub-axis-aligned bounding box is output.

[0054] Specifically, determine whether the area enclosed by each point in the first spatial data is greater than or equal to a set threshold; if the area enclosed by each point in the first spatial data is less than the set threshold, use the axis-aligned bounding box corresponding to the first spatial data as the axis-aligned bounding box of the obstacle to be processed; if the area enclosed by each point in the first spatial data is greater than or equal to the set threshold, determine whether the first spatial data meets the basic condition that the obstacle to be processed is a vehicle; the basic condition at least includes: the number of corner points contained in the first spatial data is a set value; if the first spatial data does not meet the basic condition that the obstacle to be processed is a vehicle, use the axis-aligned bounding box corresponding to the first spatial data as the axis-aligned bounding box of the obstacle to be processed; if the first spatial data meets the basic condition that the obstacle to be processed is a vehicle, segment the first spatial data based on the set standard length.

[0055] On the basis of the above embodiment, dividing the first spatial data based on the set standard length to obtain at least two sub-obstacles to be processed corresponding to the second spatial data respectively may include the following steps:

[0056] a2) dividing the value of the long side in the first spatial data by the set standard length and rounding up to an integer, which is used as the number of divisions.

[0057] b2) Evenly dividing the first spatial data of the obstacle to be processed along the long side according to the number of divisions to obtain at least two sub-obstacles to be processed and acquiring second spatial data corresponding to the sub-obstacles to be processed.

[0058] In this embodiment, the long sides are the two longer sides among the four sides formed by the four corner points in the spatial data.

[0059] Specifically, the value of the long side in the first spatial data is divided by the set standard length and rounded up as the number of divisions. The first spatial data of the obstacle to be processed is evenly divided along the long side according to the number of divisions to obtain at least two sub-obstacles to be processed and obtain the second spatial data corresponding to the sub-obstacles to be processed.

[0060] S130. Determine an axis-aligned bounding box of the obstacle to be processed according to the second spatial data.

[0061] In this embodiment, the axisymmetric bounding box is a technical term related to computer graphics and collision detection, and its full name is "Axis-Aligned Bounding Box". In two-dimensional space, AABB can be defined as a rectangle whose sides are parallel to the coordinate axes. In two-dimensional space, AABB is defined by the minimum and maximum coordinate points of the rectangle, which correspond to the minimum and maximum values ​​of the rectangle on the x-axis and y-axis, respectively. The construction method of the axisymmetric bounding box is the default constructor: create an axis-aligned bounding box with zero length and width at the origin; or create an AABB by giving a center point, length and width; or create it by giving a vertex and a vertex diagonal to it.

[0062] Specifically, an axis-aligned bounding box is constructed for each second spatial data to obtain a sub-axis-aligned bounding box, and each sub-axis-aligned bounding box corresponding to each second spatial data is used as the axis-aligned bounding box of the obstacle to be processed.

[0063] Based on the above embodiment, determining the axis-aligned bounding box of the obstacle to be processed according to the second spatial data may include the following steps:

[0064] a3) constructing an axis-aligned bounding box for each second spatial data to obtain a sub-axis-aligned bounding box.

[0065] b3) using each sub-axis-aligned bounding box corresponding to each second spatial data as the axis-aligned bounding box of the obstacle to be processed.

[0066] In this embodiment, a sub-axis aligned bounding box may be constructed for each second spatial data.

[0067] Specifically, an axis-aligned bounding box is constructed for each second spatial data to obtain a sub-axis-aligned bounding box, and each sub-axis-aligned bounding box corresponding to each second spatial data is used as the axis-aligned bounding box of the obstacle to be processed.

[0068] On the basis of the above embodiment, constructing an axis-aligned bounding box for each second spatial data to obtain a sub-axis-aligned bounding box specifically comprises the following steps:

[0069] a31) Determine an initial sub-axis aligned bounding box corresponding to the second spatial data.

[0070] a32) Get the speed of the obstacle to be processed.

[0071] a33) If the speed is greater than the first set threshold and less than the second set threshold, the initial sub-axis aligned bounding box is updated; if the speed is equal to the first set threshold or greater than the second set threshold, the initial sub-axis aligned bounding box is updated and the first sub-axis aligned bounding box is output.

[0072] Specifically, the first set threshold and the second set threshold may be preset thresholds, the first set threshold may be set to 0, and the second set value may be a low speed value, which may be set to 15. There is no specific limitation in the embodiment and the setting is performed according to actual conditions.

[0073] Specifically, if the speed is greater than the first set threshold and less than the second set threshold, the initial sub-axis-aligned bounding box is updated; if the speed is equal to the first set threshold or greater than the second set threshold, the initial sub-axis-aligned bounding box is updated and the first sub-axis-aligned bounding box is output. The updating method is: customize the preview time, deduce each point of the input axis-aligned bounding box based on the prediction line, obtain the position of the point after the preview time, combine the original point and the deduced point to construct the convex hull, obtain four points in the new aabox form, and update the axis-aligned bounding box.

[0074] a34) If the shape of the obstacle to be processed is the set shape, the front and back of the first sub-axis aligned bounding box are expanded by the set length; if the shape of the obstacle to be processed is not the set shape, the first sub-axis aligned bounding box is not expanded, and the second sub-axis aligned bounding box is output.

[0075] a35) If part of the position of the obstacle to be processed is behind the position of the current vehicle, the part behind the position of the current vehicle is deleted and the third sub-axis aligned bounding box is output.

[0076] In this embodiment, the set shape may be a bicycle, a car, or a traffic barrier, etc. The set length may be a preset length, which is set according to actual conditions.

[0077] Specifically, if the shape of the obstacle to be processed is a set shape, the first sub-axis aligned bounding box is expanded by a set length in front and behind. If the shape of the obstacle to be processed is not a set shape, the first sub-axis aligned bounding box is not expanded, and the second sub-axis aligned bounding box is output. If part of the position of the obstacle to be processed is behind the position of the current vehicle, the part behind the position of the current vehicle is deleted, and the third sub-axis aligned bounding box is output.

[0078] For example, if the shape of the obstacle is judged to be a bicycle, it will extend 0.5 meters in the front and 0.5 meters in the rear. If the shape of the obstacle is judged to be a car, it will extend 1.0 meters in the front and 1.0 meters in the rear. If the shape of the obstacle is judged to be a traffic barrier, it will extend 1.0 meters in the front and 5.0 meters in the rear.

[0079] The present invention discloses an obstacle processing method for an autonomous driving scene, comprising: obtaining first spatial data of an obstacle to be processed; dividing the first spatial data based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed; and determining an axis-aligned bounding box of the obstacle to be processed according to the second spatial data. Using this method: the projected obstacle reduces the space lost in the form of an axisymmetric bounding box in places where the road curvature is large, saving a lot of traversable space and improving the traffic efficiency.

[0080] Figure 2 The present invention also provides a schematic diagram of the structure of an obstacle handling device for an autonomous driving scenario. Figure 2 As shown, the device includes: a data acquisition module 210, a data segmentation module 220 and a determination module 230.

[0081] The data acquisition module 210 is used to acquire first spatial data of the obstacle to be processed;

[0082] A data segmentation module 220 is used to segment the first spatial data based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed;

[0083] The determination module 230 determines an axis-aligned bounding box of the obstacle to be processed according to the second spatial data.

[0084] The technical solution provided by the embodiment of the present disclosure reduces the space lost in the form of an axisymmetric bounding box by projecting obstacles in areas with large road curvature, saves a lot of traversable space, and improves traffic efficiency.

[0085] Furthermore, the data segmentation module 220 can be used to:

[0086] The value of the long side in the first spatial data is divided by the set standard length and rounded up to an integer as the number of divisions;

[0087] The first spatial data of the obstacle to be processed is evenly divided along the long side according to the number of divisions to obtain at least two sub-obstacles to be processed and the second spatial data corresponding to the sub-obstacles to be processed are acquired.

[0088] Furthermore, the determination module 230 may be used to:

[0089] constructing an axis-aligned bounding box for each of the second spatial data to obtain a sub-axis-aligned bounding box;

[0090] Each sub-axis-aligned bounding box corresponding to each second spatial data is used as the axis-aligned bounding box of the obstacle to be processed.

[0091] Furthermore, the determination module 230 may be used to:

[0092] Determine an initial sub-axis aligned bounding box corresponding to the second spatial data;

[0093] Obtaining the speed of the obstacle to be processed;

[0094] If the speed is greater than the first set threshold and less than the second set threshold, the initial sub-axis aligned bounding box is updated; if the speed is equal to the first set threshold or greater than the second set threshold, the initial sub-axis aligned bounding box is updated and a first sub-axis aligned bounding box is output;

[0095] If the shape of the obstacle to be processed is a set shape, the front and back of the first sub-axis-aligned bounding box are expanded by a set length; if the shape of the obstacle to be processed is not a set shape, the first sub-axis-aligned bounding box is not expanded, and a second sub-axis-aligned bounding box is output;

[0096] If a portion of the position of the obstacle to be processed is located behind the position of the current vehicle, the portion of the position behind the position of the current vehicle is deleted, and a third sub-axis aligned bounding box is output.

[0097] The device may also include:

[0098] Filtering out the obstacles to be processed that are located behind the current vehicle;

[0099] Filter out the obstacles to be processed that are decided to be ignored;

[0100] Filter out the virtual obstacles to be processed;

[0101] The obstacles to be processed located at the navigation end point are filtered out.

[0102] The device also includes:

[0103] Determining whether the area enclosed by each point in the first spatial data is greater than or equal to a set threshold;

[0104] If the area enclosed by each point in the first spatial data is smaller than a set threshold, the axis-aligned bounding box corresponding to the first spatial data is used as the axis-aligned bounding box of the obstacle to be processed;

[0105] If the area enclosed by each point in the first spatial data is greater than or equal to a set threshold, it is determined whether the first spatial data satisfies a basic condition that the obstacle to be processed is a vehicle; the basic condition at least includes: the number of corner points included in the first spatial data is a set value;

[0106] If the first spatial data does not satisfy the basic condition that the obstacle to be processed is a vehicle, using the axis-aligned bounding box corresponding to the first spatial data as the axis-aligned bounding box of the obstacle to be processed;

[0107] If the first spatial data meets the basic condition that the obstacle to be processed is a vehicle, the first spatial data is segmented based on a set standard length.

[0108] The above device can execute the methods provided by all the above embodiments of the present invention, and has the corresponding functional modules and beneficial effects of executing the above methods. For technical details not described in detail in this embodiment, please refer to the methods provided by all the above embodiments of the present invention.

[0109] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is given. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0110] like Figure 3As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0111] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0112] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the obstacle handling method of the autonomous driving scenario.

[0113] In some embodiments, the obstacle handling method for the autonomous driving scenario may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the obstacle handling method for the autonomous driving scenario described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the obstacle handling method for the autonomous driving scenario in any other appropriate manner (e.g., by means of firmware).

[0114] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0116] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the 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, voice input, or tactile input).

[0118] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0119] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0120] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0121] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An obstacle handling method for an autonomous driving scenario, characterized in that: include: Acquire first spatial data of obstacles to be processed; The first spatial data is divided based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed respectively; An axis-aligned bounding box of the obstacle to be processed is determined according to the second spatial data.

2. The method according to claim 1, characterized in that The first spatial data is divided based on the set standard length to obtain at least two sub-obstacles to be processed corresponding to the second spatial data respectively, including: The value of the long side in the first spatial data is divided by the set standard length and rounded up to an integer as the number of divisions; The first spatial data of the obstacle to be processed is evenly divided along the long side according to the number of divisions to obtain at least two sub-obstacles to be processed and the second spatial data corresponding to the sub-obstacles to be processed are acquired.

3. The method according to claim 2, characterized in that Before dividing the obstacle to be processed based on the set standard length, the method further includes: Determining whether the area enclosed by each point in the first spatial data is greater than or equal to a set threshold; If the area enclosed by each point in the first spatial data is smaller than a set threshold, the axis-aligned bounding box corresponding to the first spatial data is used as the axis-aligned bounding box of the obstacle to be processed; If the area enclosed by each point in the first spatial data is greater than or equal to a set threshold, it is determined whether the first spatial data satisfies a basic condition that the obstacle to be processed is a vehicle; the basic condition at least includes: the number of corner points included in the first spatial data is a set value; If the first spatial data does not satisfy the basic condition that the obstacle to be processed is a vehicle, using the axis-aligned bounding box corresponding to the first spatial data as the axis-aligned bounding box of the obstacle to be processed; If the first spatial data meets the basic condition that the obstacle to be processed is a vehicle, the first spatial data is segmented based on a set standard length.

4. The method according to claim 1, characterized in that: The step of determining the axis-aligned bounding box of the obstacle to be processed according to the second spatial data includes: constructing an axis-aligned bounding box for each of the second spatial data to obtain a sub-axis-aligned bounding box; Each sub-axis-aligned bounding box corresponding to each second spatial data is used as the axis-aligned bounding box of the obstacle to be processed.

5. The method according to claim 4, characterized in that: The step of constructing an axis-aligned bounding box for each of the second spatial data to obtain a sub-axis-aligned bounding box includes: Determine an initial sub-axis aligned bounding box corresponding to the second spatial data; Obtaining the speed of the obstacle to be processed; If the speed is greater than the first set threshold and less than the second set threshold, the initial sub-axis aligned bounding box is updated; if the speed is equal to the first set threshold or greater than the second set threshold, the initial sub-axis aligned bounding box is updated and a first sub-axis aligned bounding box is output; If the shape of the obstacle to be processed is a set shape, the front and back of the first sub-axis-aligned bounding box are expanded by a set length; if the shape of the obstacle to be processed is not a set shape, the first sub-axis-aligned bounding box is not expanded, and a second sub-axis-aligned bounding box is output; If a portion of the position of the obstacle to be processed is located behind the position of the current vehicle, the portion of the position behind the position of the current vehicle is deleted, and a third sub-axis aligned bounding box is output.

6. The method according to claim 1, characterized in that: Before obtaining the first spatial data of the obstacle to be processed, the following steps are included: Filtering out the obstacles to be processed that are located behind the current vehicle; Filter out the obstacles to be processed that are decided to be ignored; Filter out the virtual obstacles to be processed; The obstacles to be processed located at the navigation end point are filtered out.

7. An obstacle handling device for an autonomous driving scenario, characterized in that: include: A data acquisition module, used to acquire first spatial data of obstacles to be processed; A data segmentation module, configured to segment the first spatial data based on a set standard length to obtain second spatial data corresponding to at least two sub-obstacles to be processed; A determination module determines an axis-aligned bounding box of the obstacle to be processed according to the second spatial data.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the obstacle handling method for the autonomous driving scenario described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the obstacle handling method for the autonomous driving scenario described in any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the obstacle handling method for the autonomous driving scenario according to any one of claims 1 to 6.

Images