CN112572428B - Method, apparatus, device and storage medium for controlling vehicle - Google Patents
Method, apparatus, device and storage medium for controlling vehicle Download PDFInfo
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- CN112572428B CN112572428B CN201910941197.1A CN201910941197A CN112572428B CN 112572428 B CN112572428 B CN 112572428B CN 201910941197 A CN201910941197 A CN 201910941197A CN 112572428 B CN112572428 B CN 112572428B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
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Abstract
According to the embodiment of the disclosure, a method, a device, equipment and a computer-readable storage medium for controlling a vehicle are provided, and relate to the field of automatic driving. The method comprises the following steps: in response to determining that a potential risk area exists on a planned path of a vehicle, sending instructions to a detection device onboard the vehicle to cause the detection device to exit the vehicle to obtain information associated with the potential risk area; receiving information from a detection device; determining whether the vehicle is able to safely pass through the potential risk area based on the information; and adjusting the planned path of the vehicle in response to determining that the vehicle cannot safely pass through the potential risk area. In this way, the vehicle may be enabled to avoid driving hazards due to the potential risk areas.
Description
Technical Field
Embodiments of the present disclosure relate generally to the field of computer technology, and more particularly, to methods, apparatuses, devices, and computer-readable storage media for controlling a vehicle.
Background
With the development of technology, automatic driving or smart driving has become a current hotspot. When an autonomous vehicle is driving on a road, some potential risk areas that are difficult to predict may be encountered, such as water accumulation, snow accumulation, mud pits, sand pits, or the like. Existing autonomous driving techniques have difficulty determining whether a vehicle can safely pass through these potential risk areas and thus making effective autonomous driving decisions. A hazard may be involved if the vehicle continues to travel along the previously planned route.
Disclosure of Invention
According to an example embodiment of the present disclosure, a scheme for controlling a vehicle is provided.
In a first aspect of the disclosure, a method for controlling a vehicle is provided. The method comprises the following steps: in response to determining that a potential risk area exists on the planned path of the vehicle, sending instructions to a detection device onboard the vehicle to cause the detection device to exit the vehicle to obtain information associated with the potential risk area; receiving information from a detection device; determining whether the vehicle is able to safely pass through the potential risk area based on the information; and adjusting the planned path of the vehicle in response to determining that the vehicle cannot safely pass through the potential risk area.
In a second aspect of the present disclosure, a method for controlling a vehicle is provided. The method comprises the following steps: in response to instructions received from the vehicle, controlling the detection device to exit the vehicle to obtain information associated with a potential risk area located on a planned path of the vehicle; and providing information to the vehicle for use in determining whether to adjust the planned path of the vehicle.
In a third aspect of the present disclosure, an apparatus for controlling a vehicle is provided. The device comprises: a transmitting module configured to transmit instructions to a detection device onboard the vehicle in response to determining that a potential risk area exists on a planned path of the vehicle, such that the detection device leaves the vehicle to obtain information associated with the potential risk area; a receiving module configured to receive information from a detection device; a safety determination module configured to determine whether the vehicle is able to safely pass through the potential risk area based on the information; and a path adjustment module configured to adjust a planned path of the vehicle in response to determining that the vehicle cannot safely pass through the potential risk area.
In a fourth aspect of the present disclosure, an apparatus for controlling a vehicle is provided. The device comprises: a drive-off module configured to control the detection device to exit the vehicle to obtain information associated with a potential risk area located on a planned path of the vehicle in response to instructions received from the vehicle; and a providing module configured to provide information to the vehicle for determining whether to adjust the planned path of the vehicle.
In a fifth aspect of the present disclosure, there is provided an apparatus comprising one or more processors; and storage means for storing the one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method according to the first aspect of the disclosure.
In a sixth aspect of the present disclosure, there is provided an apparatus comprising one or more processors; and storage means for storing the one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method according to the second aspect of the disclosure.
In a seventh aspect of the present disclosure, a computer readable storage medium is provided, having stored thereon a computer program, which when executed by a processor, implements a method according to the first aspect of the present disclosure.
In an eighth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements a method according to the second aspect of the present disclosure.
In a ninth aspect of the present disclosure, a computer program product is provided. The computer program product comprises instructions which, when executed by a processor, implement the method according to the first or second aspect.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential 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 apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
FIG. 1 illustrates a schematic diagram of an example environment in which embodiments of the present disclosure can be implemented;
FIG. 2 shows a flow diagram of a process for controlling a vehicle according to one embodiment of the present disclosure;
FIG. 3 shows a flow diagram of a process of determining whether a potential risk area can be safely passed in accordance with an embodiment of the present disclosure;
FIG. 4 shows a flow diagram of a process for controlling a vehicle according to another embodiment of the present disclosure; (ii) a
FIG. 5 shows a schematic block diagram of an apparatus for controlling a vehicle according to one embodiment of the present disclosure;
FIG. 6 shows a schematic block diagram of an apparatus for controlling a vehicle according to another embodiment of the present disclosure; and
FIG. 7 illustrates a block diagram of a computing device capable of implementing various embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
In describing embodiments of the present disclosure, the terms "include" and its derivatives should be interpreted as being inclusive, i.e., "including but not limited to. The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
As discussed above, smart vehicles need to have the ability to sense traffic direction signals. The current vehicle can determine the command gesture of the traffic police through image recognition technology such as gesture recognition, or can recognize the sound and semantic meaning of the traffic through voice recognition and natural language processing. However, such a scheme has a large limitation, for example, in a traffic jam environment, image information of a traffic police may not be received due to a front vehicle blocking the image sensing apparatus. Alternatively, in a noisy traffic environment, it is difficult for a vehicle to extract the voice information of a traffic police from the voice information containing a large amount of background noise.
According to an embodiment of the present disclosure, a solution for controlling a vehicle is presented. In this approach, upon determining that a potential risk area exists on the planned path of the vehicle, instructions are sent to a detection device onboard the vehicle to cause the detection device to exit the vehicle to obtain information associated with the potential risk area. Information is then received from the detection device and a determination is made as to whether the vehicle can safely pass through the potential risk area based on the information. When it is determined that the vehicle cannot safely pass through the potential risk area, the planned path of the vehicle is adjusted. According to another aspect of the present disclosure, a solution for controlling a vehicle is also presented. In this approach, in response to instructions received from the vehicle, the vehicle is exited to obtain information associated with a potential risk area located on the planned path of the vehicle and the information is provided to the vehicle for use in determining whether to adjust the planned path of the vehicle. In this way, vehicles can be enabled to safely pass through or bypass the potential risk areas, and dangers caused by the potential risk areas are avoided.
Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings.
Fig. 1 illustrates a schematic diagram of an example environment 100 in which various embodiments of the present disclosure can be implemented. Some typical objects are schematically shown in this example environment 100, including vehicles 105 traveling on a roadway 102. In the example of FIG. 1, the vehicle 105 may be any type of vehicle that may carry people and/or things and be moved by a powered system such as an engine, including but not limited to a car, truck, bus, electric vehicle, motorcycle, recreational vehicle, train, and the like. One or more vehicles 105 in the environment 100 may be vehicles with some autopilot capability, such vehicles also referred to as unmanned vehicles.
In the example of fig. 1, vehicle 105 is traveling on road 102 following planned path 115. As shown in fig. 1, there is a potential risk area 120, such as a water-catchment area, a snow-covered area, a mud pit area, or a sand pit area, on the planned path 115 of the vehicle 105. Such risk potential areas 120 may make it difficult for the vehicle 105 to follow the planned route 115.
The vehicle 105 may be communicatively coupled to a first computing device 135. Although shown as a separate entity, the first computing device 135 may be embedded in the vehicle 105. The first computing device 135 can also be an entity external to the vehicle 105 and can communicate with the vehicle 105 via a wireless network. The first computing device 135 may be implemented as one or more computing devices containing at least a processor, memory, and other components typically found in a general purpose computer to implement computing, storage, communication, control, and like functions.
According to embodiments of the present disclosure, the vehicle 105 may be equipped with a detection device 110. When it is determined that a risk potential area 120 is present on planned path 115, first computing device 135 may send instructions to second computing device 140 coupled with detection device 110 to cause detection device 110 to exit vehicle 105 to probe for risk potential area 120 to obtain information related to risk potential area 120, such as a maximum depth of a water accumulation area. The second computing device 140 may provide information about the potential risk area 120 to the first computing device 135 to cause the first computing device 135 to confirm whether the planned path 115 of the vehicle 105 needs to be adjusted.
A process of controlling a vehicle according to an embodiment of the present disclosure will be described below with reference to fig. 2 to 3. FIG. 2 shows a flow diagram of a method 200 for vehicle localization according to an embodiment of the present disclosure. The method 200 may be performed, for example, by the first computing device 135 shown in fig. 1.
As shown in fig. 2, at block 202, the first computing device 135 determines that a potential risk area 120 exists on the planned path 115 of the vehicle 105. In some embodiments, the potential risk area 120 may include at least one of: a water accumulation area; snow accumulation areas; a mud pit area; or a sandpit area. These potential risk areas 120 may make safe passage of the vehicle 105 difficult.
In some embodiments, the first computing device 135 may determine that the potential risk area 120 is present on the planned path 115 based on environmental information acquired by sensing devices on the installed vehicle 105. In some embodiments, the sensing device may include an image sensor. The first computing device 135 may acquire images associated with the planned path 115 of the vehicle 105 and determine that the potential risk area 120 exists on the planned path 115 based on the images. For example, the first computing device 135 may determine whether there is a water-pooling region in the image using a machine learning method. It should be appreciated that first computing device 135 may utilize any suitable sensing devices and identification techniques to identify potential risk area 120, and this disclosure is not intended to be limiting in any way.
At block 204, the first computing device 135 sends instructions to the detection device 110 loaded by the vehicle 105 to cause the detection device 110 to exit the vehicle 105 to obtain information associated with the potential risk area 120. In some embodiments, vehicle 105 mounts detection device 110, for example, in the vehicle chassis, where detection device 110 may be detached from the vehicle chassis and exit vehicle 105 to obtain information related to potential risk area 120. In some embodiments, the detection device 110 may be, for example, a robot or cart loaded with various sensing devices that can follow a route specified by the vehicle 105 or autonomously determine a route to gather information associated with the potential risk area 120.
In some embodiments, first computing device 135 may also determine the location of potential risk area 120. For example, the first computing device 135 may determine the location of the risk region 120 based on image localization techniques and include the location information in instructions sent to the detection device 110 to cause the detection device to obtain information associated with the potential risk region located at the location.
In some embodiments, the information may indicate at least one of: maximum depth of potential risk area 120; or the size of the risk potential area 120. For example, when the potential risk area 120 is a water accumulation area, the information may indicate a maximum depth of the water accumulation area, a size of the water accumulation area, or a water quality (e.g., PH value) of the water accumulation area, or the like. As another example, when the risk potential area 120 is a snow area, the information may indicate a maximum depth of the snow area or a size of the snow area, or the like. As yet another example, when the potential risk area 120 is a mud pit area, the information may indicate a maximum depth of the mud pit area, a size of the mud pit area, or a consistency of the mud pit area, etc. As yet another example, when the potential risk area 120 is a bunker area, the information may indicate a maximum depth of the bunker area, a size of the bunker area, or a degree of slippage of the bunker area, or the like.
At block 206, the first computing device 135 receives information from the detection device 110. In some embodiments, the first computing device 135 may receive such information in real-time from the detection device 110 via wireless communication. In some embodiments, the first computing device 135 may also receive information collected by the detection device 110 via wired or wireless means after the detection device 110 is reloaded into the vehicle 105.
At block 208, the first computing device 135 determines whether the vehicle 105 is able to safely pass through the potential risk area 120 based on the information. The specific process of block 208 will be described below with reference to fig. 3, which illustrates a schematic diagram of a process of determining whether a vehicle 105 can safely pass through a potential risk area 120 in accordance with an embodiment of the present disclosure.
As shown in fig. 3, at block 302, first computing device 135 may determine a security metric based on the information, where the security metric indicates a degree of security of risk potential area 120. For example, when potential risk area 120 is a water-logging area, first computing device 135 may compare the maximum depth of the water-logging area to a depth threshold to determine a security metric. For example, the depth threshold may be determined based on some parameter of the vehicle 105. For example, when the vehicle 105 is a fuel-powered vehicle, the safety metric may be set to 0 if the maximum depth of the water-laden area is greater than the ground clearance of the vehicle's exhaust ports, indicating that the vehicle 105 cannot safely pass through the potentially hazardous area. As another example, when the maximum depth of the stagnant area is less than the ground clearance of the vehicle exhaust, for example, but the difference is less than a predetermined value, the safety metric may be set to 1, for example, to indicate that the risk of the potential risk area 120 is greater. As yet another example, when the maximum depth of the waterlogged area is less than the ground clearance of the vehicle exhaust, for example, but the difference is greater than a predetermined value, the safety metric may be set to 2, for example, to indicate that the risk potential area 120 is less dangerous.
At block 304, the first computing device 135 may determine whether the security metric is above a predetermined security threshold. In some embodiments, the safety threshold may be dynamically set based on characteristics of the vehicle 105 and/or environmental information. For example, the safety threshold may be set to a lower value when the vehicle 105 is performing better off-road. Conversely, when the vehicle 105 is performing poorly off-road, the safety threshold may be set to a higher value.
When it is determined at block 304 that the safety metric is above the predetermined safety threshold, the method may proceed to block 306, i.e., the first computing device 135 may determine that the vehicle 105 is able to safely pass through the potential risk area 120. For example, the safety threshold may be set to 1, and when the safety metric is 2, the first computing device 135 may determine that the vehicle 105 is able to safely pass through the potential risk area 120. Conversely, when it is determined at block 304 that the safety metric is less than or equal to the predetermined safety threshold, the method may proceed to block 308, i.e., the first computing device 135 may determine that the vehicle 105 is unable to safely pass through the risk potential area 120. For example, the safety threshold may be set to 1, and when the safety metric is 0 or 1, the first computing device 135 may determine that the vehicle 105 is unable to safely pass through the risk potential area 120.
With continued reference to fig. 2, in response to determining at block 208 that the vehicle 105 cannot safely pass through the potential risk area 120, the method 200 proceeds to block 210 where the first computing device 135 adjusts the planned path 115 of the vehicle 105.
In some embodiments, the first computing device 135 may determine the boundary 125 of the potential risk area 120 based on the information received from the detection device 110 and re-determine the planned path 130 of the vehicle 105 based on the boundary 125 to cause the vehicle 105 to bypass the potential risk area 120. For example, taking fig. 1 as an example, the detection device 110 may acquire information about the boundary 125 of the risk area 120, for example, by a loaded image detection device. The first computing device 135, in determining the new planned path 130 of the vehicle 105, may identify the area associated with the boundary 125 as a static obstacle so that the boundary 125 is avoided in the decision making process for new path planning. For example, a new planned path may be determined as path 130 that causes vehicle 105 to bypass potential risk area 120, thereby avoiding a potential driving risk.
In some embodiments, the first computing device 135 may also cause the vehicle 105 to stop traveling along the planned path 110 and provide a warning regarding a request to manually drive the vehicle 105 to bypass the potential risk area 120. For example, the first computing device 135 may issue a voice, video, image, etc. warning requesting a security officer or a potential driver to maneuver the vehicle 105 to bypass the potential risk area 120 to avoid a potential driving risk.
Based on the method described above, it is possible to enable a vehicle to accurately determine whether a potential risk area can be driven through and to re-determine a traffic route when it is determined that the potential risk area cannot be driven through, thereby avoiding a driving risk that may exist.
According to another aspect of the present disclosure, a method for controlling a vehicle is also provided. Fig. 4 shows a flow diagram of a method 400 for controlling a vehicle according to another embodiment of the present disclosure. The method 400 may be performed, for example, by the second computing device 140 shown in fig. 1.
As shown in fig. 4, at block 402, the second computing device 140 receives an instruction from the vehicle 105. For example, as described with reference to block 204, the second computing device 140 may receive the instructions from the first computing device 135 via wired or wireless means.
At block 404, the second computing device 140 controls the detection device 110 to exit the vehicle 105 to obtain information associated with the potential risk area 120 located on the planned path 115 of the vehicle 105. In some embodiments, the potential risk area 120 may include at least one of: a water accumulation area; snow accumulation areas; a mud pit area; or a sandpit area. These potential risk areas 120 may make it difficult for the vehicle 105 to safely pass through. In some embodiments, the detection device 110 may be equipped with one or more measurement devices, such as a depth measurement device, an image capture device, a water quality detection device, a viscosity detection device, a sand friction detection device, and the like.
In some embodiments, the second computing device 140 may control the detection device 110 to travel along a predetermined route to gather information associated with the potential risk area. For example, the second computing device 140 may control the detection device 110 to traverse the wading area following the planned path 115 of the vehicle 105 to obtain information related to the wading area.
In some embodiments, the information may indicate at least one of: maximum depth of potential risk area 120; or the size of the risk potential area 120. For example, when the potential risk area 120 is a water accumulation area, the information may indicate a maximum depth of the water accumulation area, a size of the water accumulation area, or a water quality (e.g., PH value) of the water accumulation area, or the like. As another example, when potential risk area 120 is a snow area, the information may indicate a maximum depth of the snow area or a size of the snow area, or the like. As yet another example, when the potential risk area 120 is a mud pit area, the information may indicate a maximum depth of the mud pit area, a size of the mud pit area, or a consistency of the mud pit area, etc. As yet another example, when the potential risk area 120 is a bunker area, the information may indicate a maximum depth of the bunker area, a size of the bunker area, or a degree of slippage of the bunker area, or the like.
At block 406, the second computing device 140 provides information to the vehicle 105 for use in determining whether to adjust the planned path 115 of the vehicle 105. In some embodiments, the second computing device 140 may provide this information in real-time from the first computing device 135 via wireless communication. In some embodiments, the second computing device 140 may also provide the information collected by the detection device 110 to the first computing device 135 via wired or wireless means after the detection device 110 is reloaded into the vehicle 105. The process of determining whether to adjust planned path 115 has been described above with reference to fig. 2 and will not be described in detail herein.
Based on the methods described herein, it may be accurately determined whether a vehicle may safely pass through a potential risk area, thereby reducing the potential driving risk of the vehicle.
Fig. 5 shows a schematic block diagram of an apparatus 500 for controlling a vehicle according to an embodiment of the present disclosure. The apparatus 500 may be included in the first computing device 135 of fig. 1 or implemented as the first computing device 135. As shown in fig. 5, the apparatus 500 includes a transmitting module 510 configured to transmit an instruction to a detection device onboard the vehicle to cause the detection device to exit the vehicle to obtain information associated with a potential risk area in response to determining that the potential risk area exists on a planned path of the vehicle. The apparatus 500 further comprises a receiving module 520 configured to receive information from the detection device. Additionally, the apparatus 500 further includes a security determination module 530 configured to determine whether the vehicle is able to safely pass through the potential risk area based on the information. Additionally, the apparatus 500 includes a path adjustment module 540 configured to adjust the planned path of the vehicle in response to determining that the vehicle cannot safely pass through the potential risk area.
In some embodiments, the apparatus 500 further comprises: an image acquisition module configured to acquire an image associated with a planned path of a vehicle; and a risk potential region determination module configured to determine a risk potential region on the planned path based on the image.
In some embodiments, wherein the sending module 510 comprises: a location determination module configured to determine a location of a potential risk area; and an instruction sending module configured to send an instruction to the detection device to cause the detection device to acquire information associated with the risk potential area located at the location.
In some embodiments, wherein the potential risk area comprises at least one of: a water accumulation area; snow accumulation areas; a mud pit area; or a sandpit area.
In some embodiments, wherein the information indicates at least one of: maximum depth of the potential risk area; or the size of the potential risk area.
In some embodiments, wherein the security determination module 530 comprises: a security metric determination module configured to determine a security metric based on the information, the security metric indicating a degree of security of the potential risk area; and a safe-passage determination module configured to determine that the vehicle is safe to pass through the potentially risky area in response to the safety metric being above a predetermined safety threshold.
In some embodiments, wherein the path adjustment module 540 comprises: a boundary determination module configured to determine a boundary of a potential risk area based on the information; and a path re-determination module configured to re-determine a planned path of the vehicle based on the boundary such that the vehicle bypasses the potential risk area.
In some embodiments, wherein the path adjustment module 540 comprises: a stop-go module configured to cause a vehicle to stop traveling along a planned path; and a warning module configured to provide a warning regarding a request to manually drive the vehicle to bypass the potential risk area.
Fig. 6 shows a schematic block diagram of an apparatus 600 for controlling a vehicle according to an embodiment of the present disclosure. The apparatus 600 may be included in the second computing device 140 of fig. 1 or implemented as the second computing device 140. As shown in fig. 6, the apparatus 600 includes a drive-away module 610 configured to control a detection device to exit a vehicle to obtain information associated with a potential risk area located on a planned path of the vehicle in response to an instruction received from the vehicle. Furthermore, the apparatus 600 further comprises a providing module 620 configured to provide information to the vehicle for determining whether to adjust the planned path of the vehicle.
In some embodiments, the drive-off module 610 further comprises: a location acquisition module configured to acquire a location of the potential risk area from the instruction; and an information acquisition module configured to control the detection device to exit the vehicle based on the location to acquire information associated with the potential risk area.
In some embodiments, wherein the potential risk area comprises at least one of: a water accumulation area; snow accumulation areas; a mud pit area; or a sandpit area.
In some embodiments, wherein the information indicates at least one of: maximum depth of the potential risk area; or the size of the potential risk area.
Fig. 7 illustrates a schematic block diagram of an example device 700 that may be used to implement embodiments of the present disclosure. Device 700 can be used to implement first computing device 135 and/or second computing device 140 of fig. 1. As shown, device 700 includes a Central Processing Unit (CPU) 701 that may perform various appropriate actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM) 702 or computer program instructions loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 707 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processing unit 701 performs the various methods and processes described above, such as the process 300. For example, in some embodiments, method 200 and/or method 400 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of a computer program may be loaded onto and/or installed onto device 700 via ROM 702 and/or communications unit 709. When the computer program is loaded into RAM 703 and executed by CPU 701, one or more steps of method 200 and/or method 400 described above may be performed. Alternatively, in other embodiments, CPU 701 may be configured to perform method 200 and/or method 400 by any other suitable means (e.g., by way of firmware).
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a load programmable logic device (CPLD), and the like.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Further, while operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (16)
1. A method for controlling a vehicle, comprising:
acquiring an image associated with a planned path of a vehicle;
identifying, based on the image, a potential risk area of at least one of the following categories present on the planned path: water accumulation area, snow accumulation area, mud pit area or sand pit area;
in response to determining that the risk potential area exists, sending instructions to a detection device onboard the vehicle to cause the detection device to exit the vehicle to obtain information associated with the category for the risk potential area, wherein the information indicates at least: a maximum depth of the risk potential zone and a size of the risk potential zone;
receiving the information from the detection device;
determining whether the vehicle can safely pass through the potential risk area based on the information; and
adjusting the planned path of the vehicle in response to determining that the vehicle cannot safely pass through the potential risk area.
2. The method of claim 1, wherein sending instructions to the vehicle-mounted detection device comprises:
determining a location of the potential risk area; and
sending instructions to the detection device to cause the detection device to obtain information associated with the risk potential area located at the location.
3. The method of claim 1, wherein determining whether the vehicle can pass through the potential risk area based on the information comprises:
determining a security metric based on the information, the security metric indicating a degree of security of the potential risk area; and
determining that the vehicle is safe to pass through the potential risk area in response to the safety metric being above a predetermined safety threshold.
4. The method of claim 1, wherein adjusting the planned path of the vehicle comprises:
determining a boundary of the potential risk area based on the information; and
re-determining the planned path of the vehicle based on the boundary such that the vehicle bypasses the potential risk area.
5. The method of claim 1, wherein adjusting the planned path of the vehicle comprises:
causing the vehicle to stop traveling along the planned path; and
providing a warning regarding a request to manually drive the vehicle to bypass the potential risk area.
6. A method for controlling a vehicle, comprising:
in response to instructions received from a vehicle, controlling a detection device to exit the vehicle to obtain information associated with a potential risk area located on a planned path of the vehicle in at least one of the following categories: -a water-catchment area, a snow-catchment area, a mud pit area or a sand pit area, and the information is associated with the category; and
providing the information to the vehicle for determining whether to adjust the planned path of the vehicle,
wherein the information at least indicates: the maximum depth of the risk potential area and the size of the risk potential area,
wherein exiting the vehicle comprises:
obtaining a location of the risk potential area from the instruction; and
controlling the detection device to exit the vehicle based on the location to obtain the information associated with the potential risk area.
7. An apparatus for controlling a vehicle, comprising:
an image acquisition module configured to acquire an image associated with a planned path of a vehicle;
a risk potential region identification module configured to identify, based on the image, a risk potential region on the planned path where at least one of the following categories exists: water accumulation area, snow accumulation area, mud pit area or sand pit area;
a transmitting module configured to transmit instructions to a detection device onboard the vehicle to cause the detection device to exit the vehicle to obtain information associated with the category for the risk potential area in response to determining that the risk potential area exists, wherein the information indicates at least: a maximum depth of the risk potential region and a size of the risk potential region;
a receiving module configured to receive the information from the detection device;
a safety determination module configured to determine whether the vehicle is able to safely pass through the potential risk area based on the information; and
a path adjustment module configured to adjust the planned path of the vehicle in response to determining that the vehicle cannot safely pass through the potential risk area.
8. The apparatus of claim 7, wherein the sending module comprises:
a location determination module configured to determine a location of the potential risk area; and
an instruction sending module configured to send an instruction to the detection device to cause the detection device to acquire information associated with the risk potential area located at the location.
9. The apparatus of claim 7, wherein the security determination module comprises:
a security metric determination module configured to determine a security metric based on the information, the security metric indicating a degree of security of the potential risk area; and
a safety pass determination module configured to determine that the vehicle is able to safely pass through the potential risk area in response to the safety metric being above a predetermined safety threshold.
10. The apparatus of claim 7, wherein the path adjustment module comprises:
a boundary determination module configured to determine a boundary of the potential risk area based on the information; and
a path re-determination module configured to re-determine the planned path of the vehicle based on the boundary such that the vehicle bypasses the potential risk area.
11. The apparatus of claim 7, wherein the path adjustment module comprises:
a stop-driving module configured to cause the vehicle to stop driving along the planned path; and
a warning module configured to provide a warning regarding a request to manually drive the vehicle to bypass the potential risk area.
12. An apparatus for controlling a vehicle, comprising:
a drive-off module configured to control a detection device to exit a vehicle to obtain information associated with a potentially risky area located on a planned path of the vehicle in at least one of the following categories, in response to an instruction received from the vehicle: -a water accumulation area, a snow accumulation area, a mud pit area or a sand pit area, and the information is associated with the category; and
a providing module configured to provide the information to the vehicle for determining whether to adjust the planned path of the vehicle,
wherein the information at least indicates: the maximum depth of the risk potential area and the size of the risk potential area,
wherein said drive-off module further comprises:
a location acquisition module configured to acquire a location of the potential risk area from the instructions; and
an information acquisition module configured to control the detection device to exit the vehicle based on the location to acquire the information associated with the potential risk area.
13. An electronic device, the electronic device comprising:
one or more processors; and
memory storing one or more programs that, when executed by the one or more processors, cause the electronic device to implement the method of any of claims 1-5.
14. An electronic device, the electronic device comprising:
one or more processors; and
memory storing one or more programs that, when executed by the one or more processors, cause the electronic device to implement the method of claim 6.
15. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
16. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to claim 6.
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| CN201910941197.1A CN112572428B (en) | 2019-09-30 | 2019-09-30 | Method, apparatus, device and storage medium for controlling vehicle |
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| CN112572428A (en) | 2021-03-30 |
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