Automatic driving unloading method, device, equipment and automatic driving vehicle

Abstract

The present disclosure provides an autonomous driving unloading method, device, equipment and autonomous driving vehicle, which relates to the field of artificial intelligence technology, in particular to autonomous driving, perception and other technical fields. The specific implementation scheme is: obtaining virtual unloading information, the virtual unloading information includes N virtual unloading positions, N is a positive integer; generating a target driving path, the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions; performing autonomous driving according to the target driving path; when the autonomous driving vehicle reaches the target virtual unloading position, sensing the actual unloading position and performing autonomous driving towards the actual unloading position; performing unloading when the distance between the autonomous driving vehicle and the actual unloading position is within a preset distance range. The present disclosure can realize adaptive unloading to reduce the labor cost of unloading.

Description

Technical Field

[0001] The present disclosure relates to the fields of artificial intelligence technologies such as autonomous driving and perception, and in particular to an autonomous driving unloading method, device, equipment, and autonomous driving vehicle. Background Art

[0002] At present, cargo unloading is a very important scenario. The current method of cargo unloading is mainly for the driver to observe the actual site and control the vehicle to unload according to the observed site conditions. Summary of the Invention

[0003] The present disclosure provides an autonomous driving unloading method, apparatus, equipment, and autonomous driving vehicle.

[0004] According to one aspect of the present disclosure, there is provided an autonomous driving unloading method, which is applied to an autonomous driving vehicle, comprising:

[0005] Acquire virtual uninstallation information, where the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer;

[0006] generating a target driving path, wherein the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions;

[0007] Performing autonomous driving according to the target driving path;

[0008] When the autonomous driving vehicle reaches the target virtual unloading position, sensing the actual unloading position and autonomously driving toward the actual unloading position;

[0009] When the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range, unloading is performed.

[0010] According to another aspect of the present disclosure, an automatic driving unloading device is provided, comprising:

[0011] An acquisition module, configured to acquire virtual uninstallation information, wherein the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer;

[0012] A first generating module is configured to generate a target driving path, wherein the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions;

[0013] a first driving module, configured to perform automatic driving according to the target driving path;

[0014] a second driving module, configured to sense an actual unloading position when the autonomous driving vehicle reaches the target virtual unloading position, and to perform autonomous driving toward the actual unloading position;

[0015] The unloading module is used to unload the cargo when the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range.

[0016] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the method provided by the present disclosure.

[0020] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the method provided by the present disclosure.

[0021] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, which implements the method provided in the present disclosure when executed by a processor.

[0022] According to another aspect of the present disclosure, an autonomous driving vehicle is provided, comprising the electronic device provided by the present disclosure.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings are provided to facilitate a better understanding of the present invention and do not constitute a limitation of the present disclosure.

[0025] Figure 1 This is a flow chart of an automatic driving unloading method provided by the present disclosure;

[0026] Figure 2 This is a schematic diagram of an automatic driving unloading system provided by the present disclosure;

[0027] Figure 3 is a schematic diagram of an automatic driving unloading device provided by the present disclosure;

[0028] Figure 4 is a schematic diagram of another automatic driving unloading device provided by the present disclosure;

[0029] Figure 5 is a schematic diagram of another automatic driving unloading device provided by the present disclosure;

[0030] Figure 6 is a block diagram of an electronic device for implementing the embodiments of the present disclosure. DETAILED DESCRIPTION

[0031] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0032] See Figure 1 , Figure 1 This is a flow chart of an automatic driving unloading method provided by the present disclosure, which is applied to an automatic driving vehicle, such as Figure 1 As shown, the following steps are included:

[0033] Step S101: Acquire virtual uninstallation information, where the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer.

[0034] The virtual unloading information may be obtained by the autonomous driving vehicle receiving the virtual unloading information sent by a cloud device, a roadside device, a terminal, or other device. In some embodiments, the virtual unloading information may also be pre-configured, that is, the virtual unloading information may be obtained by the autonomous driving vehicle configuring the virtual unloading information.

[0035] The virtual unloading information may include all or part of the virtual unloading locations at the cargo unloading site. Each virtual unloading location may be manually set or set by a data collection vehicle. For example, a virtual unloading location may be separated from a retaining wall by a preset distance, or separated from unloaded cargo by a preset distance. This can reduce the frequency of updating the virtual unloading location. The preset distance can be set based on actual needs, such as 5 meters or 8 meters.

[0036] In this disclosure, the virtual unloading position can be understood as an auxiliary reference point position used to assist the autonomous driving vehicle in unloading. Different virtual unloading positions correspond to different unloading areas. For example: Figure 2 As shown, a row of virtual unloading positions is set at positions parallel or approximately parallel to the actual retaining wall, and the above-mentioned N virtual unloading positions can be all or part of this row of virtual unloading positions.

[0037] In addition, the distances between the N virtual unloading positions can be set according to actual needs. For example, the distances between the N virtual unloading positions can be about twice the size of the vehicle body.

[0038] It should be noted that in the present disclosure, multiple unloading operations can be performed by executing step S101 once. In some embodiments, step S101 can be executed periodically or at a fixed time, and multiple unloading operations can be performed each time it is executed.

[0039] Step S102: Generate a target driving path, where the end point of the target driving path is the target virtual unloading position among the N virtual unloading positions.

[0040] Generating the target driving path may include determining the target unloading location from the N virtual unloading locations and generating a driving path for the autonomous vehicle to the target virtual unloading location. For example, a path planning module of the autonomous vehicle may plan a route to the target virtual unloading location using the target virtual unloading location as a destination.

[0041] The target virtual unloading location may be a virtual unloading location selected from the N virtual unloading locations according to a random or sequential strategy.

[0042] Step S103: Perform automatic driving according to the target driving path.

[0043] This step may be that the autonomous driving vehicle drives to the above-mentioned target unloading position according to the above-mentioned target driving path.

[0044] Step S104: When the autonomous driving vehicle reaches the target virtual unloading position, it senses the actual unloading position and automatically drives toward the actual unloading position.

[0045] This step may be that when the autonomous driving vehicle reaches the target virtual unloading position, the autonomous driving vehicle continues to drive autonomously, senses the actual unloading position through sensors on the vehicle during the autonomous driving process, and drives autonomously towards the actual unloading position.

[0046] The actual unloading location is the location where the autonomous vehicle unloads its cargo. This location can be dynamically sensed by radar or visual sensors behind the autonomous vehicle. Alternatively, the actual unloading location can be the boundary of the unloaded cargo, a retaining wall, or a location where the cargo is lower within the unloaded cargo area.

[0047] Step S105: Unloading is performed when the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range.

[0048] The above-mentioned preset distance range can be set according to information such as cargo type or vehicle type. For example, if the cargo is coal or soil, the above-mentioned preset distance range can be a distance range of 0.5 meters or 0.6 meters, etc. For large cargo, the above-mentioned preset distance range can be a distance range of 0.5 meters, 0.8 meters or 1 meter, etc.

[0049] The distance between the above-mentioned autonomous driving vehicle and the actual unloading position may be within the preset distance range, that is, the distance between the autonomous driving vehicle and the actual unloading position is less than or equal to the boundary value of the preset distance range, that is, the autonomous driving vehicle enters the above-mentioned preset distance range.

[0050] The above-mentioned unloading may be that the speed of the autonomous driving vehicle drops to a preset threshold and automatically stops to unload.

[0051] In the present disclosure, each step in the above method is performed by the above-mentioned autonomous driving vehicle, which can be a large truck, a medium-sized truck or a small truck, etc., and the cargo of the autonomous driving vehicle can be coal, soil, garbage, articles and other goods.

[0052] In this disclosure, the autonomous vehicle first performs autonomous driving based on a target virtual unloading location. Upon reaching the target virtual unloading location, the vehicle senses the actual unloading location and, if the distance to the actual unloading location is within a preset range, unloading is performed. This allows the autonomous vehicle to sense the actual unloading location based on the virtual unloading location, thus enabling adaptive unloading and reducing labor costs.

[0053] In one embodiment, the virtual unloading information further includes N reversing directions corresponding to the N virtual unloading positions;

[0054] The target driving path includes a reverse driving path, and the reverse direction of the reverse driving path is the target reverse direction corresponding to the target virtual unloading position, and the end position of the reverse driving path is the end position of the target driving path.

[0055] The N reversing directions are respectively set for the N virtual unloading positions.

[0056] In this embodiment, the above-mentioned reversing driving path can be generated based on the target reversing direction corresponding to the target virtual unloading position. In this way, since the vehicle is in a reversing state when it reaches the target virtual unloading position, the vehicle can directly unload when it drives near the actual unloading position, thereby improving the unloading efficiency.

[0057] In another embodiment, the target driving path further includes a forward driving path, the end position of the forward driving path is the starting position of the reverse driving path, and the end position of the forward driving path is determined based on the target virtual position.

[0058] The above-mentioned forward driving path can be a forward driving path that enables the vehicle to quickly reach the target virtual unloading position, for example: Figure 2 As shown, the target driving path includes a forward driving path 201 and a reverse driving path 202 .

[0059] The end position of the forward driving path may be determined based on the target virtual position, so as to enable the vehicle to reverse and reach the target virtual unloading position.

[0060] In this embodiment, since the target driving path also includes a forward driving path, and the end position of the forward driving path is determined based on the target virtual position, the vehicle can reach the target virtual unloading position as quickly as possible, thereby saving unloading time and reducing vehicle power consumption.

[0061] It should be noted that in the present disclosure, in an embodiment where the target driving path includes a reverse driving path, the target driving path is not limited to also including a forward driving path. For example, when the vehicle is located to the right of the target virtual position, the autonomous driving vehicle can directly reverse to the target virtual position, and there is no need to set a forward driving path.

[0062] It should be noted that, in the present disclosure, the virtual unloading information is not limited to include the above-mentioned N reversing directions. For example, the autonomous driving vehicle determines the reversing direction to reach the target virtual position according to the pre-configured retaining wall position, and thus determines the target driving path based on the reversing direction rule.

[0063] In one embodiment, when N is a positive integer greater than 1:

[0064] The target virtual unloading position is a virtual unloading position randomly selected from the N virtual unloading positions; or

[0065] The target virtual unloading location is a virtual unloading location selected from the N virtual unloading locations according to reference information, where the reference information is used to indicate at least one of the following:

[0066] The number of times a vehicle passes each of the M1 virtual unloading locations within a preset time;

[0067] The distances between M2 virtual unloading locations and the cargo;

[0068] The M1 virtual unloading positions are part or all of the N virtual unloading positions, and M1 is a positive integer less than or equal to N;

[0069] The M2 virtual unloading positions are part or all of the N virtual unloading positions, and M2 is a positive integer less than or equal to N.

[0070] In this embodiment, in some implementations, the target virtual unloading location may be randomly selected from N virtual unloading locations.

[0071] The aforementioned reference information may be reference information received by the autonomous vehicle from a cloud device, roadside equipment, or terminal. In some embodiments, some or all of the aforementioned reference information may also be information collected or sensed by the autonomous vehicle, such as the distance between the target virtual unloading location and the cargo, as sensed or collected by the autonomous vehicle during unloading.

[0072] The virtual unloading position selected from the N virtual unloading positions based on the reference information may be the virtual unloading position with the least number of passing vehicles among the N virtual unloading positions. The unloading area corresponding to the virtual unloading position with fewer passing vehicles may have less cargo unloaded. By selecting this virtual unloading position, the cargo unloaded in the unloading area can be as balanced as possible.

[0073] The virtual unloading position selected from the N virtual unloading positions based on the reference information may be a virtual unloading position that is farthest from the cargo among the N virtual unloading positions, so that the cargo unloaded in the unloading area can be as balanced as possible.

[0074] The virtual unloading position selected from the N virtual unloading positions based on the reference information can be the virtual unloading position selected from the N virtual unloading positions with the least number of passing vehicles and the farthest distance from the cargo, so that the cargo unloaded in the unloading area can be as balanced as possible.

[0075] In this embodiment, since the target virtual unloading position is selected from the N virtual unloading positions based on the reference information, the unloading position can be selected flexibly and reasonably to improve the unloading effect of the unloading position.

[0076] In some embodiments, the reference information may further include unloading time information for some or all of the N virtual unloading locations. This unloading time information may include the time at which a vehicle most recently passed by a virtual unloading location. Based on this unloading time information, a virtual unloading location with a longer time to pass can be selected to avoid congestion caused by multiple autonomous vehicles unloading at the same virtual unloading location.

[0077] In one embodiment, the rear of the autonomous driving vehicle is provided with an activation radar and a millimeter-wave radar. Step S104 in the above embodiments includes:

[0078] When the autonomous driving vehicle reaches the target virtual unloading position, transmitting a lidar signal through the activation radar and sending a millimeter-wave radar signal through the millimeter-wave radar;

[0079] receiving a laser echo signal of the laser radar signal and a millimeter wave echo signal of the millimeter wave radar signal;

[0080] sensing an actual unloading position based on the laser radar signal, the laser echo signal, the millimeter wave radar signal, and the millimeter wave echo signal, and automatically driving toward the actual unloading position;

[0081] The actual unloading position is a retaining wall position or a boundary position of the unloaded goods.

[0082] The above-mentioned sensing of the actual unloading position based on the laser radar signal, the laser echo signal, the millimeter-wave radar signal, and the millimeter-wave echo signal may be achieved by fusing the sensing of the actual unloading position based on the laser radar signal, the laser echo signal, the millimeter-wave radar signal, and the millimeter-wave echo signal. For example, a first actual unloading position sensed based on the laser radar signal and the laser echo signal and a second actual unloading position sensed based on the millimeter-wave radar signal and the millimeter-wave echo signal are weighted together to obtain the final actual unloading position.

[0083] In this embodiment, the actual unloading position is sensed based on the laser radar signal, laser echo signal, millimeter wave radar signal and millimeter wave echo signal. In this way, the accuracy of sensing the actual unloading position can be improved by using different radar signals for sensing.

[0084] It should be noted that, in some embodiments, laser radar signals and laser echo signals may be used to sense the actual unloading position, or millimeter wave radar signals and millimeter wave echo signals may be used to sense the actual unloading position.

[0085] In one embodiment, the method further comprises the following steps:

[0086] Recording the parking location of the autonomous vehicle for unloading;

[0087] calculating a distance between the parking position and the target virtual unloading position;

[0088] When the distance between the parking position and the target virtual unloading position is less than a preset distance threshold, the parking position is sent to the target device, and the parking position is used by the target device to update the target virtual unloading position.

[0089] The parking position for the above-mentioned autonomous driving vehicle to unload cargo is the parking position of the autonomous driving vehicle when unloading cargo.

[0090] The target device may be a device used to generate the N virtual unloading locations, such as a cloud device, a roadside device, or a terminal.

[0091] The above-mentioned preset distance threshold can be set according to actual needs, for example: 1 meter, 2 meters, etc.

[0092] In this embodiment, the parking position can be sent to the target device so that the target device can update the virtual unloading position in time to avoid the problem of the virtual unloading position overlapping with the unloaded cargo position causing the vehicle to collide with the unloaded cargo.

[0093] In one embodiment, the method further comprises the following steps:

[0094] monitoring a vehicle state of the autonomous driving vehicle from a starting position of the target driving path to a parking position for unloading cargo, the vehicle state comprising at least one of a bumpy state and a cargo state;

[0095] Based on the vehicle state, cargo loading information is generated, where the cargo loading information is used to indicate the amount of cargo loaded when the autonomous driving vehicle subsequently passes through the target virtual unloading position for unloading.

[0096] The above-mentioned bumpy state may indicate the degree of bumping of the above-mentioned autonomous driving vehicle from the above-mentioned starting position to the parking position for unloading.

[0097] The above-mentioned cargo status can indicate the cargo falling situation of the above-mentioned autonomous driving vehicle from the above-mentioned starting position to the parking position for unloading. For example, some roads may be bumpy during driving, causing the vehicle to fall during driving. For example, some roads in open-pit mines may be bumpy, so the coal or soil loaded by the autonomous driving vehicle may fall.

[0098] The above-mentioned bumpy state and cargo state can be monitored by sensors installed on the autonomous driving vehicle, for example: monitoring the cargo state through a visual sensor and monitoring the bumpy state through a motion sensor.

[0099] The above-mentioned generation of cargo loading information based on the vehicle state may be that, when the bumpy state indicates that the road is severely bumpy, the cargo loading is reduced on the basis of the cargo loading standard to avoid cargo falling due to overloading, and / or, when the bumpy state indicates that the road is not bumpy, a small amount of cargo is added on the basis of the cargo loading standard to improve unloading efficiency; or, when the cargo state indicates that there is a risk of cargo falling during driving, the cargo loading is reduced on the basis of the cargo standard loading to avoid cargo falling, and / or, when the cargo state indicates that there is no cargo falling during driving, the cargo is loaded according to the cargo loading standard; or, alternatively, when the bumpy state indicates that the road is severely bumpy and the cargo state indicates that there is a risk of cargo falling during driving, the cargo loading is reduced on the basis of the cargo loading standard.

[0100] In this embodiment, since cargo loading information is generated based on the vehicle status, the cargo loading effect of the vehicle can be improved when the autonomous driving vehicle subsequently passes through the target virtual unloading position to unload cargo, thereby improving unloading efficiency or reducing cargo falling.

[0101] In the present disclosure, since the autonomous driving vehicle can perceive the actual unloading position based on the virtual unloading position, adaptive unloading can be achieved to reduce the labor cost of unloading.

[0102] See Figure 3 , Figure 3 This invention provides an automatic driving unloading device. Figure 3 As shown, the automatic driving unloading device 300 includes:

[0103] An acquisition module 301 is configured to acquire virtual uninstallation information, where the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer.

[0104] A first generating module 302 is configured to generate a target driving path, wherein the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions;

[0105] A first driving module 303, configured to perform automatic driving according to the target driving path;

[0106] A second driving module 304 is configured to sense an actual unloading position when the autonomous driving vehicle reaches the target virtual unloading position, and to perform autonomous driving toward the actual unloading position;

[0107] The unloading module 305 is used to unload the cargo when the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range.

[0108] In one embodiment, the virtual unloading information further includes N reversing directions corresponding to the N virtual unloading positions;

[0109] The target driving path includes a reverse driving path, and the reverse direction of the reverse driving path is the target reverse direction corresponding to the target virtual unloading position, and the end position of the reverse driving path is the end position of the target driving path.

[0110] In one embodiment, the target driving path further includes a forward driving path, the end position of the forward driving path is the starting position of the reverse driving path, and the end position of the forward driving path is determined based on the target virtual position.

[0111] In one embodiment, when N is a positive integer greater than 1:

[0112] The target virtual unloading position is a virtual unloading position randomly selected from the N virtual unloading positions; or

[0113] The target virtual unloading location is a virtual unloading location selected from the N virtual unloading locations according to reference information, where the reference information is used to indicate at least one of the following:

[0114] The number of times a vehicle passes each of the M1 virtual unloading locations within a preset time;

[0115] The distances between M2 virtual unloading locations and the cargo;

[0116] The M1 virtual unloading positions are part or all of the N virtual unloading positions, and M1 is a positive integer less than or equal to N;

[0117] The M2 virtual unloading positions are part or all of the N virtual unloading positions, and M2 is a positive integer less than or equal to N.

[0118] In one embodiment, the rear of the autonomous driving vehicle is provided with an activation radar and a millimeter-wave radar, and the second driving module 304 is configured to:

[0119] When the autonomous driving vehicle reaches the target virtual unloading position, transmitting a lidar signal through the activation radar and sending a millimeter-wave radar signal through the millimeter-wave radar;

[0120] receiving a laser echo signal of the laser radar signal and a millimeter wave echo signal of the millimeter wave radar signal;

[0121] sensing an actual unloading position based on the laser radar signal, the laser echo signal, the millimeter wave radar signal, and the millimeter wave echo signal, and automatically driving toward the actual unloading position;

[0122] The actual unloading position is a retaining wall position or a boundary position of the unloaded goods.

[0123] In one embodiment, Figure 4 Shown, including:

[0124] An acquisition module 401 is configured to acquire virtual uninstallation information, wherein the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer.

[0125] A first generating module 402 is configured to generate a target driving path, wherein the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions;

[0126] A first driving module 403, configured to perform automatic driving according to the target driving path;

[0127] A second driving module 404 is configured to sense an actual unloading position when the autonomous driving vehicle reaches the target virtual unloading position, and to perform autonomous driving toward the actual unloading position;

[0128] The unloading module 405 is configured to unload the cargo when the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range;

[0129] a recording module 406 for recording the parking location of the autonomous driving vehicle for unloading;

[0130] a calculation module 407, configured to calculate a distance between the parking position and the target virtual unloading position;

[0131] The sending module 408 is configured to send the parking position to a target device when the distance between the parking position and the target virtual unloading position is less than a preset distance threshold, and the parking position is used by the target device to update the target virtual unloading position.

[0132] In one embodiment, Figure 5 Shown, including:

[0133] An acquisition module 501 is configured to acquire virtual uninstallation information, where the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer.

[0134] A first generating module 502 is configured to generate a target driving path, wherein the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions;

[0135] A first driving module 503, configured to perform automatic driving according to the target driving path;

[0136] A second driving module 504 is configured to sense an actual unloading position when the autonomous driving vehicle reaches the target virtual unloading position, and to perform autonomous driving toward the actual unloading position;

[0137] The unloading module 505 is configured to unload the cargo when the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range;

[0138] a monitoring module 506 for monitoring a vehicle state of the autonomous driving vehicle from a starting position of the target driving path to a parking position for unloading cargo, wherein the vehicle state includes at least one of a bumpy state and a cargo state;

[0139] The second generating module 507 is used to generate cargo loading information based on the vehicle state, where the cargo loading information is used to indicate the amount of cargo loaded when the autonomous driving vehicle subsequently passes through the target virtual unloading position for unloading.

[0140] The automatic driving unloading device provided in the present disclosure can realize each process implemented by the automatic driving unloading method provided in the present disclosure and achieve the same technical effect. To avoid repetition, it will not be described here.

[0141] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, a computer program product and an autonomous driving vehicle.

[0142] The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the radar message sending method provided in the present disclosure.

[0143] The above-mentioned readable storage medium stores computer instructions, wherein the computer instructions are used to enable the computer to execute the radar message sending method provided by the present disclosure.

[0144] The above-mentioned computer program product includes a computer program, and when the computer program is executed by a processor, it implements the radar message sending method provided by the present disclosure.

[0145] The above-mentioned autonomous driving vehicle includes the above-mentioned electronic equipment.

[0146] In the technical solutions disclosed herein, the acquisition, storage, and application of user personal information involved comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0147] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. 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 assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are provided as examples only and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0148] like Figure 6 As shown, the device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the device 600 can also be stored in the RAM 603. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0149] Various components in device 600 are connected to I / O interface 605, including an input unit 606, such as a keyboard, mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a magnetic disk, optical disk, etc.; and a communication unit 609, such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows device 600 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0150] Computing unit 601 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Computing unit 601 performs the various methods and processes described above, such as the autonomous unloading method. For example, in some embodiments, the autonomous unloading method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by computing unit 601, one or more steps of the autonomous unloading method described above can be performed. Alternatively, in other embodiments, computing unit 601 can be configured to perform the autonomous unloading method by any other suitable means (e.g., via firmware).

[0151] Various embodiments of the systems and techniques described 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), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes 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.

[0152] The program code for implementing the method of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0153] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can 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.

[0154] To provide interaction with a user, the systems and techniques described herein 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 the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the 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 can be received in any form (including acoustic input, voice input, or tactile input).

[0155] The systems and techniques described herein can be implemented in a computing system that includes back-end 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 front-end components (e.g., a user computer having 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 back-end components, middleware components, 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 a local area network (LAN), a wide area network (WAN), and the Internet.

[0156] A computer system may include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The client-server relationship arises through computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, a server in a distributed system, or a server integrated with a blockchain.

[0157] According to another aspect of the present disclosure, an autonomous driving vehicle is provided, comprising the electronic device provided by the present disclosure.

[0158] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved. This is not limited herein.

[0159] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. An autonomous driving unloading method, applied to an autonomous driving vehicle, comprising: Acquire virtual uninstallation information, where the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer; generating a target driving path, wherein the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions; Performing autonomous driving according to the target driving path; When the autonomous driving vehicle reaches the target virtual unloading location, sensing an actual unloading location and autonomously driving toward the actual unloading location, the actual unloading location including a boundary location of the unloaded cargo; Unloading the cargo when the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range; Recording the parking location of the autonomous vehicle for unloading; calculating a distance between the parking position and the target virtual unloading position; When the distance between the parking position and the target virtual unloading position is less than a preset distance threshold, the parking position is sent to the target device, and the parking position is used by the target device to update the target virtual unloading position.

2. The method according to claim 1, wherein The virtual unloading information also includes N reversing directions corresponding to the N virtual unloading positions; The target driving path includes a reverse driving path, and the reverse direction of the reverse driving path is the target reverse direction corresponding to the target virtual unloading position, and the end position of the reverse driving path is the end position of the target driving path.

3. The method according to claim 2, wherein: The target driving path also includes a forward driving path, the end position of the forward driving path is the starting position of the reverse driving path, and the end position of the forward driving path is determined according to the target virtual position.

4. The method according to any one of claims 1 to 3, wherein When N is a positive integer greater than 1: The target virtual unloading position is a virtual unloading position randomly selected from the N virtual unloading positions; or The target virtual unloading location is a virtual unloading location selected from the N virtual unloading locations according to reference information, where the reference information is used to indicate at least one of the following: The number of times a vehicle passes each of the M1 virtual unloading locations within a preset time; The distances between M2 virtual unloading locations and the cargo; The M1 virtual unloading positions are part or all of the N virtual unloading positions, and M1 is a positive integer less than or equal to N; The M2 virtual unloading positions are part or all of the N virtual unloading positions, and M2 is a positive integer less than or equal to N.

5. The method according to any one of claims 1 to 3, wherein The tail of the autonomous driving vehicle is provided with an activation radar and a millimeter wave radar. When the autonomous driving vehicle reaches the target virtual unloading position, the autonomous driving vehicle senses the actual unloading position and automatically drives toward the actual unloading position, including: When the autonomous driving vehicle reaches the target virtual unloading position, transmitting a lidar signal through the activation radar and sending a millimeter-wave radar signal through the millimeter-wave radar; receiving a laser echo signal of the laser radar signal and a millimeter wave echo signal of the millimeter wave radar signal; Based on the laser radar signal, the laser echo signal, the millimeter wave radar signal and the millimeter wave echo signal, the actual unloading position is sensed, and automatic driving is performed toward the actual unloading position.

6. The method according to any one of claims 1 to 3, further comprising: monitoring a vehicle state of the autonomous driving vehicle from a starting position of the target driving path to a parking position for unloading cargo, the vehicle state comprising at least one of a bumpy state and a cargo state; Based on the vehicle state, cargo loading information is generated, where the cargo loading information is used to indicate the amount of cargo loaded when the autonomous driving vehicle subsequently passes through the target virtual unloading position for unloading.

7. An automatic driving unloading device comprising: An acquisition module, configured to acquire virtual uninstallation information, wherein the virtual uninstallation information includes N virtual uninstallation locations, where N is a positive integer; A first generating module is configured to generate a target driving path, wherein the end position of the target driving path is the target virtual unloading position among the N virtual unloading positions; a first driving module, configured to perform automatic driving according to the target driving path; a second driving module, configured to sense an actual unloading position when the autonomous driving vehicle reaches the target virtual unloading position, and autonomously drive toward the actual unloading position, wherein the actual unloading position includes a boundary position of the unloaded cargo; an unloading module, configured to unload cargo when the distance between the autonomous driving vehicle and the actual unloading location is within a preset distance range; a recording module, configured to record the parking location of the autonomous driving vehicle for unloading; a calculation module, configured to calculate a distance between the parking position and the target virtual unloading position; The sending module is used to send the parking position to the target device when the distance between the parking position and the target virtual unloading position is less than a preset distance threshold, and the parking position is used by the target device to update the target virtual unloading position.

8. The device according to claim 7, wherein The virtual unloading information also includes N reversing directions corresponding to the N virtual unloading positions; The target driving path includes a reverse driving path, and the reverse direction of the reverse driving path is the target reverse direction corresponding to the target virtual unloading position, and the end position of the reverse driving path is the end position of the target driving path.

9. The device according to claim 8, wherein The target driving path also includes a forward driving path, the end position of the forward driving path is the starting position of the reverse driving path, and the end position of the forward driving path is determined according to the target virtual position.

10. The device according to any one of claims 7 to 9, wherein When N is a positive integer greater than 1: The target virtual unloading position is a virtual unloading position randomly selected from the N virtual unloading positions; or The target virtual unloading location is a virtual unloading location selected from the N virtual unloading locations according to reference information, where the reference information is used to indicate at least one of the following: The number of times a vehicle passes each of the M1 virtual unloading locations within a preset time; The distances between M2 virtual unloading locations and the cargo; The M1 virtual unloading positions are part or all of the N virtual unloading positions, and M1 is a positive integer less than or equal to N; The M2 virtual unloading positions are part or all of the N virtual unloading positions, and M2 is a positive integer less than or equal to N.

11. The device according to any one of claims 7 to 9, wherein The tail of the autonomous driving vehicle is provided with an activation radar and a millimeter-wave radar, and the second driving module is used to: When the autonomous driving vehicle reaches the target virtual unloading position, transmitting a lidar signal through the activation radar and sending a millimeter-wave radar signal through the millimeter-wave radar; receiving a laser echo signal of the laser radar signal and a millimeter wave echo signal of the millimeter wave radar signal; Based on the laser radar signal, the laser echo signal, the millimeter wave radar signal and the millimeter wave echo signal, the actual unloading position is sensed, and automatic driving is performed toward the actual unloading position.

12. The apparatus according to any one of claims 7 to 9, further comprising: a monitoring module, configured to monitor a vehicle state of the autonomous driving vehicle from a starting position of the target driving path to a parking position for unloading cargo, wherein the vehicle state includes at least one of a bumpy state and a cargo state; The second generating module is used to generate cargo loading information based on the vehicle state, and the cargo loading information is used to indicate: the amount of cargo loaded by the autonomous driving vehicle when it subsequently passes through the target virtual unloading position for unloading.

13. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

14. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

15. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

16. An autonomous driving vehicle comprising the electronic device according to claim 13.

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