Vehicle automatic driving method, device, computer equipment and storage medium

Abstract

The present application relates to a method, apparatus, computer equipment and storage medium for automatic vehicle driving. The method comprises: determining a target area for the vehicle to move forward; sending a collection instruction to the at least one drone; the collection instruction is used to instruct the drone to collect environmental information of the target area; receiving the environmental information sent by the at least one drone; and determining the driving path of the automatic vehicle driving based on the environmental information. Through the embodiments of the present invention, the use of drones to collect environmental information can increase the detection area, reduce detection blind spots, and provide more and richer environmental data for the automatic driving vehicle, so that the automatic driving vehicle can perform more accurate path planning based on the collected environmental information, thereby ensuring the safety of the automatic driving vehicle and expanding the application scope of the automatic driving vehicle.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a method, apparatus, computer equipment, and storage medium for autonomous driving of a vehicle. Background Art

[0002] With the development of vehicles, autonomous driving technology has become a hot research trend. In the field of autonomous driving, the ability of autonomous driving systems to collect information about the surrounding environment is crucial to vehicle safety, and this information collection capability of autonomous driving systems is heavily dependent on the layout of sensors.

[0003] At present, the sensors of autonomous vehicles are basically limited to the roof or around the body of the vehicle, and the detection area of ​​the sensors is within a limited range centered on the vehicle's location.

[0004] However, this arrangement still has detection blind spots, cannot meet the perception requirements of autonomous vehicles, and still poses some risks. Summary of the Invention

[0005] Based on this, it is necessary to provide a vehicle autonomous driving method, device, computer equipment and storage medium that can meet the perception requirements of autonomous driving vehicles in response to the above technical problems.

[0006] In one aspect, an embodiment of the present invention provides a method for autonomous driving of a vehicle, wherein the vehicle is equipped with at least one drone, the method comprising:

[0007] Determine the target area for the vehicle to move forward;

[0008] Sending a collection instruction to at least one UAV; the collection instruction is used to instruct the UAV to collect environmental information of the target area;

[0009] receiving environmental information sent by at least one drone;

[0010] Determine the vehicle's autonomous driving path based on environmental information.

[0011] In one embodiment, determining the target area for the vehicle to move forward includes:

[0012] Receive the target location input by the user and determine the target area based on the preset map data and the target location;

[0013] Or, the target area to receive user input.

[0014] In one embodiment, the sending of a collection instruction to at least one drone includes:

[0015] If the vehicle is in a driving state, a collection instruction is sent to at least one UAV based on the vehicle's driving data and the target area;

[0016] If the vehicle is in a stopped state, a collection instruction is sent to at least one UAV according to the target area;

[0017] Among them, the collection instructions include the flight position information of the UAV.

[0018] In one embodiment, the flight position information includes the flight distance, offset angle, and flight altitude of at least two UAVs.

[0019] In one embodiment, the at least two UAVs have the same flight distance and offset angle but different flight altitudes; or

[0020] The at least two UAVs have the same flight distance and flight altitude but different offset angles; or

[0021] The at least two UAVs have the same flight altitude and offset angle, but different flight distances.

[0022] In one embodiment, the sending of a collection instruction to at least one drone based on the vehicle's driving data and the target area includes:

[0023] Calculating a horizontal distance between at least one UAV and the vehicle based on driving data of the vehicle and a preset time constant; wherein the driving data includes at least one of a driving speed and a driving acceleration;

[0024] Calculate the offset angle between at least one UAV and the vehicle based on the target area and the collection range of each UAV;

[0025] According to the horizontal distance and the offset angle, a collection instruction is sent to at least one UAV.

[0026] In one embodiment, the drone has a barrier function.

[0027] In one embodiment, before determining the target area based on the preset map data and the target location, the method further includes:

[0028] Get map data from the server.

[0029] In one embodiment, the drone includes at least one of an image acquisition device and a laser radar;

[0030] The above-mentioned environmental information includes at least one of image data and point cloud data of the target area.

[0031] In one embodiment, the receiving of environmental information sent by at least one drone includes:

[0032] If the vehicle is in a driving state, it receives environmental information sent by at least one drone via wireless means;

[0033] If the vehicle is in a stopped state, at least one UAV is controlled to return to the vehicle and receive environmental information via wired or wireless means.

[0034] In one embodiment, determining the driving path of the vehicle for autonomous driving based on environmental information includes:

[0035] Identifying path information and obstacle information from environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and roadblock information;

[0036] Determine the driving path based on path information and obstacle information.

[0037] In one embodiment, after identifying the path information and obstacle information from the environmental information, the method further includes:

[0038] Comparing the path information and obstacle information identified from the environmental information with the preset map data;

[0039] The driving path is corrected according to the comparison results.

[0040] In one embodiment, the method further comprises:

[0041] Starting a first UAV in a standby state to collect the environmental information;

[0042] Control the second UAV in the working state to return to the vehicle.

[0043] In one embodiment, after the second UAV in the control working state returns to the vehicle, the method further includes:

[0044] Perform at least one of firmware upgrade and charging on the second drone that has returned to the vehicle.

[0045] In another aspect, an embodiment of the present invention further provides an automatic driving device for a vehicle, the device comprising:

[0046] A target area determination module is used to determine the target area for the vehicle to move forward;

[0047] A collection instruction sending module is used to send a collection instruction to at least one UAV; the collection instruction is used to instruct the UAV to collect environmental information of the target area;

[0048] An environmental information receiving module, configured to receive environmental information sent by at least one UAV;

[0049] The driving path determination module is used to determine the driving path of the vehicle's automatic driving based on environmental information.

[0050] In one embodiment, the target area determination module includes:

[0051] A first target area determination submodule is configured to receive a target location input by a user and determine a target area based on preset map data and the target location;

[0052] The second target area determination submodule is configured to receive a target area input by a user.

[0053] In one embodiment, the acquisition instruction sending module includes:

[0054] a first acquisition instruction sending submodule, configured to send an acquisition instruction to at least one UAV based on the vehicle's driving data and the target area if the vehicle is in a driving state;

[0055] a second acquisition instruction sending submodule, configured to send an acquisition instruction to at least one UAV according to a target area if the vehicle is in a stopped state;

[0056] Among them, the collection instructions include the flight position information of the UAV.

[0057] In one embodiment, the flight position information includes the flight distance, offset angle, and flight altitude of at least two UAVs.

[0058] In one embodiment, the at least two UAVs have the same flight distance and offset angle but different flight altitudes; or

[0059] The flight distance and altitude of at least two of the above drones are the same, but the deviation angles are different; or

[0060] The at least two UAVs have the same flight altitude and offset angle but different flight distances.

[0061] In one embodiment, the first acquisition instruction sending submodule includes:

[0062] a horizontal distance calculation unit, configured to calculate the horizontal distance between at least one UAV and the vehicle based on the vehicle's driving data and a preset time constant; wherein the driving data includes at least one of a driving speed and a driving acceleration;

[0063] an offset angle calculation unit, configured to calculate an offset angle between at least one UAV and the vehicle based on the target area and the acquisition range of each UAV;

[0064] The acquisition instruction sending unit is used to send an acquisition instruction to at least one UAV according to the horizontal distance and the offset angle.

[0065] In one embodiment, the drone has a barrier function.

[0066] In one embodiment, the apparatus further comprises:

[0067] The map data acquisition module is used to obtain map data from the server.

[0068] In one embodiment, the drone includes at least one of an image acquisition device and a laser radar;

[0069] The above-mentioned environmental information includes at least one of image data and point cloud data of the target area.

[0070] In one embodiment, the environment information receiving module includes:

[0071] a first environmental information receiving submodule, configured to wirelessly receive environmental information sent by at least one drone when the vehicle is in a driving state;

[0072] The second environmental information receiving submodule is used to control at least one UAV to return to the vehicle if the vehicle is in a stopped state, and receive environmental information via wired or wireless means.

[0073] In one embodiment, the driving path determination module includes:

[0074] A path obstacle identification submodule is used to identify path information and obstacle information from environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and roadblock information;

[0075] The driving path determination submodule is used to determine the driving path based on the path information and obstacle information.

[0076] In one embodiment, the apparatus further comprises:

[0077] a comparison module for comparing the path information and obstacle information identified from the environmental information with the preset map data;

[0078] The driving path correction module is used to correct the driving path according to the comparison result.

[0079] In one embodiment, the apparatus further comprises:

[0080] A UAV starting module, configured to start a first UAV in a standby state to collect the environmental information;

[0081] The drone recall module is used to control the second drone in working state to return to the vehicle.

[0082] In one embodiment, the apparatus further comprises:

[0083] The charging module is adjusted to perform at least one of firmware upgrade and charging on the second UAV returned to the vehicle.

[0084] On the other hand, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0085] On the other hand, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when executed by a processor.

[0086] In the aforementioned autonomous vehicle method, apparatus, computer device, and storage medium, a vehicle is equipped with at least one drone. The autonomous vehicle first determines a target area for the vehicle's forward movement; then sends a collection instruction to the at least one drone; subsequently receives environmental information from the at least one drone; and determines a path for the autonomous vehicle based on the environmental information. By using drones to collect environmental information in embodiments of the present invention, the detection area can be expanded, blind spots can be reduced, and more abundant environmental data can be provided to the autonomous vehicle. This allows the autonomous vehicle to perform more accurate path planning based on the collected environmental information, thereby ensuring the safety of the autonomous vehicle and expanding its scope of application. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1a This is one of the application environment diagrams of the vehicle automatic driving method in one embodiment;

[0088] Figure 1b This is a second diagram of an application environment of the method for automatic vehicle driving in one embodiment;

[0089] Figure 2 A schematic diagram of a process flow of a method for automatic vehicle driving according to an embodiment;

[0090] Figure 3 A schematic diagram of a flow chart of steps for sending a collection instruction to at least one drone in one embodiment;

[0091] Figure 4a FIG1 is a schematic diagram of the relative positions of a drone and a vehicle in one embodiment;

[0092] Figure 4b This is a second schematic diagram of the relative positions between the drone and the vehicle in one embodiment;

[0093] Figure 5 A schematic diagram of a flow chart of steps for determining a driving path for automatic driving of a vehicle based on environmental information in one embodiment;

[0094] Figure 6 1 is a schematic diagram of the process of interaction between a vehicle and a drone in one embodiment;

[0095] Figure 7 This is a structural block diagram of a vehicle automatic driving device in one embodiment. DETAILED DESCRIPTION

[0096] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0097] The vehicle automatic driving method provided in this application can be applied to Figure 1a and Figure 1b In the application environment shown, the vehicle has an autonomous driving system that can communicate with at least one drone and perform path planning. The drone includes image acquisition equipment, lidar, and other information collection devices. The embodiments of the present invention do not specifically limit the vehicle and drone, and can be configured according to actual circumstances.

[0098] Reference Figure 2 , shows a vehicle automatic driving method provided by an embodiment of the present invention, and the method is applied to Figure 1a and Figure 1b The vehicle in FIG. 1 is used as an example. The vehicle carries at least one drone, and the method includes:

[0099] Step 101: Determine a target area for the vehicle to travel.

[0100] In this embodiment, before the vehicle performs autonomous driving, it is necessary to determine a target area for the vehicle's forward travel. Optionally, the direction, length, width, area, etc. of the target area are determined. Optionally, the target area is determined to be at least one of a highway, an urban road, a closed park, a mountainous area, a grassland, or a desert. This embodiment of the present invention does not impose specific limitations on the target area and may be set based on actual circumstances.

[0101] Only by determining the target area for the vehicle to move forward can we determine the area for collecting environmental information, and further plan the driving route based on the environmental information.

[0102] Step 102: Send a collection instruction to at least one UAV; the collection instruction is used to instruct the UAV to collect environmental information of the target area.

[0103] In this embodiment, after determining the target area for the vehicle's forward movement, a collection instruction is sent to the drone. If the vehicle is equipped with a single drone, the collection instruction is sent to that drone; if the vehicle is equipped with multiple drones, the collection instruction is sent to at least one drone. This embodiment of the present invention does not impose specific limitations on this, and may be configured based on actual circumstances.

[0104] After receiving the collection instruction, the drone collects environmental information of the target area according to the collection instruction. For example, the collected environmental information may include at least one of path information, vehicles, pedestrians, mountains, trees, and rivers. The embodiments of the present invention do not specifically limit the environmental information and can be set according to actual circumstances.

[0105] Due to the high altitude of drones, they can expand the detection area and reduce detection blind spots, providing more and richer environmental data for autonomous vehicles, so that autonomous vehicles can make more accurate path planning based on the collected environmental information.

[0106] Step 103: Receive environmental information sent by at least one UAV.

[0107] In this embodiment, after collecting environmental information, the drone sends the environmental information to the vehicle, and the vehicle receives the environmental information sent by the drone. Specifically, if the vehicle is in a driving state, the environmental information sent by at least one drone is received wirelessly. If the vehicle is in a stopped state, at least one drone is controlled to return to the vehicle and receive the environmental information via a wired or wireless method. It can be understood that the more drones there are, the more environmental information is collected, and the more environmental information the vehicle needs to receive. Receiving environmental information via a wired method is not limited by bandwidth and increases the transmission speed of environmental information. The embodiments of the present invention are not limited in detail and can be set according to actual conditions.

[0108] Step 104: Determine the driving path of the vehicle for automatic driving based on the environmental information.

[0109] In this embodiment, after receiving environmental information, the vehicle identifies information such as paths and obstacles from the environmental information, and then plans the direction, speed, avoidance method, and other driving paths of the vehicle's automatic driving based on the path and obstacle information.

[0110] Optionally, the UAV includes at least one of an image acquisition device and a lidar; and the environmental information includes at least one of image data and point cloud data of the target area.

[0111] Specifically, the drone can collect image data of the target area through image acquisition equipment. After receiving the image data of the target area, the vehicle can use image recognition technology to identify path and obstacle information from the image data. The drone can also collect point cloud data of the target area through lidar. After receiving the point cloud data of the target area, the vehicle can build a model based on the point cloud data, thereby identifying path and obstacle information in the built model. It is understandable that when a large number of information acquisition devices are installed on the drone, different environmental information can be collected, and different identification methods can be used for different environmental information. The embodiment of the present invention does not set any detailed restrictions on the identification method, and it can be set according to actual conditions.

[0112] In summary, in an embodiment of the present invention, a vehicle is equipped with at least one drone. The autonomous vehicle first determines a target area for the vehicle to travel to; then sends a collection instruction to the at least one drone; subsequently receives environmental information sent by the at least one drone; and determines the autonomous vehicle's driving path based on the environmental information. By using drones to collect environmental information in this embodiment of the present invention, the detection area can be expanded, blind spots can be reduced, and more abundant environmental data can be provided to the autonomous vehicle. This allows the autonomous vehicle to perform more accurate path planning based on the collected environmental information, thereby ensuring the safety of the autonomous vehicle and expanding its application range.

[0113] In another embodiment, this embodiment relates to an optional process of determining the target area for the vehicle to move forward. Figure 2 Based on the embodiment shown, the above step 102 may specifically include the following methods:

[0114] Method 1: Receive a target location input by the user and determine a target area based on the preset map data and the target location. For example, if the vehicle is at point A and the user enters point B as the target location on the preset map, the vehicle can determine the target area as the area between points A and B based on the preset map data.

[0115] Optionally, before determining the target area according to the preset map data and the target location, the method may further include: obtaining map data from a server. After obtaining the map data from the server, the vehicle may determine the target area according to the map data.

[0116] Method 2: Receive user-entered target area. Specifically, if the vehicle does not have pre-installed map data, the user can directly enter the target area. For example, the target area may be entered as an area 10 kilometers long and 1 kilometer wide in the northeast direction, or as an area with a radius of 5 kilometers centered on the vehicle. This embodiment of the present invention does not specifically limit the method for determining the target area, and it can be set according to actual circumstances.

[0117] To summarize, in the embodiments of the present invention, the target area is determined by receiving a target location input by a user and determining the target area based on preset map data and the target location, and receiving a target area input by a user. This function of determining the target area can be implemented in both cases where there is preset map data in the vehicle and where there is no preset map data, thereby making the application scenarios of autonomous driving vehicles more extensive.

[0118] In another embodiment, Figure 3 As shown, this embodiment involves an optional process of sending a collection instruction step to at least one drone. Figure 2 Based on the embodiment shown, the above step 102 may specifically include the following steps:

[0119] Step 201: If the vehicle is in a driving state, a collection instruction is sent to at least one UAV based on the vehicle's driving data and the target area; wherein the collection instruction also includes the flight position information of the UAV.

[0120] In this embodiment, if the vehicle is in motion, when sending a collection instruction to the drone, it is necessary to first determine the flight position information of the drone based on the vehicle's driving data and the target area, and then send the flight position information to the drone.

[0121] Determining the flight location of a drone can specifically include the following steps:

[0122] Step 2011: Calculate the horizontal distance between at least one UAV and the vehicle based on the vehicle's driving data and a preset time constant; wherein the driving data includes at least one of a driving speed and a driving acceleration.

[0123] In this embodiment, the vehicle can collect driving data, including speed and acceleration, while driving. Based on this driving data and preset constants, the horizontal distance between the drone and the vehicle can be calculated. For example, if the driving speed is m and the preset time constant is t, the horizontal distance L can be calculated as m*n.

[0124] The preset time constant is determined based on the transmission speed of environmental information and the path planning time. The horizontal distance between the drone and the vehicle calculated using this preset time constant and driving data can meet the path planning time requirements during vehicle driving, preventing the drone from collecting environmental information too close or too far from the vehicle, which could cause deviations in the planned path during autonomous driving.

[0125] Step 2012: Calculate the offset angle between at least one UAV and the vehicle based on the target area and the acquisition range of each UAV.

[0126] In this embodiment, the offset angle between the UAV and the vehicle is calculated so that the UAV's collection range can better cover the target area where the vehicle is moving. If the vehicle is equipped with multiple UAVs, the offset angles formed by the multiple UAVs and the vehicle are calculated. Figure 4a and Figure 4b , so that the collection area of ​​environmental information is longer or larger, thereby achieving higher coverage of the target area, and making the path planned by the vehicle based on environmental information more accurate.

[0127] Step 2013: Send a collection instruction to at least one UAV based on the horizontal distance and the offset angle.

[0128] In this embodiment, after determining the horizontal distance and offset angle between at least one drone and the vehicle, the vehicle sends a collection instruction to each drone. The collection instruction includes the determined horizontal distance and offset angle, that is, the drone's flight position information. Upon receiving the collection instruction including the flight position information, the drone determines its flight position based on the collection instruction and then collects environmental information at that flight position. Multiple drones can form a drone formation by collecting environmental information based on the flight position information contained in the collection instructions, combining their collection ranges to achieve higher coverage of the target area.

[0129] Optionally, the flight position information includes the flight distance, offset angle, and altitude of at least two drones. This includes the following situations: if the at least two drones have the same flight distance and offset angle but different flight altitudes, the drone with the higher altitude will have a larger acquisition range but slightly lower accuracy, while the drone with the lower altitude will have a smaller acquisition range but higher accuracy. Alternatively, the at least two drones may have the same flight distance and altitude but different offset angles. For example, if two drones are in front of a vehicle, one to the left and one to the right, the acquisition ranges of the two drones can be combined to expand the acquisition range. Alternatively, if the at least two drones have the same flight altitude and offset angle but different flight distances, the drone with the longer flight distance can extend the acquisition range further.

[0130] Optionally, the drone has a barrier function. A preset flight altitude range can be set for the drone, for example, 4 to 5 meters above the ground. If an obstacle is encountered within this altitude range, the drone can use the barrier function to automatically avoid it. For example, if there are road signs or trees within the preset altitude range, the drone can avoid them without requiring vehicle control. The barrier function allows the drone to be highly flexible in its flight position within a small range, preventing damage to the drone caused by obstacles.

[0131] Step 202: If the vehicle is in a stopped state, a collection instruction is sent to at least one UAV according to the target area.

[0132] In this embodiment, if the vehicle is in a stopped state, the flight position information of the UAV is determined according to the target area and the collection range of each UAV. For details, please refer to the above step 2011 and will not be repeated here.

[0133] In summary, in this embodiment of the present invention, the drone's flight position information is determined based on the vehicle's state and target area, and this flight position information is transmitted to the drone, allowing the drone to collect environmental information based on the flight position information. This embodiment of the present invention allows the drone to effectively collect environmental information, regardless of whether the vehicle is in motion or stationary, meeting the requirements for autonomous driving. This allows autonomous vehicles to be applied in more scenarios and expands their scope of application.

[0134] In another embodiment, Figure 5 As shown, this embodiment involves an optional process of determining the driving path of the vehicle automatic driving based on environmental information. Figure 2 Based on the embodiment shown, step 104 may specifically include the following steps:

[0135] Step 301 : Identify path information and obstacle information from environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and roadblock information.

[0136] In this embodiment, the drone includes information acquisition equipment such as image acquisition devices and lidar. The collected environmental information includes image data, point cloud data, and other information. Image recognition technology can be used to identify path information and obstacle information from the image data. Alternatively, modeling can be performed based on the point cloud data to identify path information and obstacle information from the model. Obstacle information includes driving information, pedestrian information, roadblock information, and so on. This embodiment of the present invention does not impose specific limitations on this, and configuration can be performed based on actual circumstances.

[0137] Step 302: Determine the driving path based on the path information and obstacle information.

[0138] In this embodiment, after the path information and obstacle information are determined, the avoidance path, avoidance direction, etc. can be determined based on the obstacle information, and then the accurate driving path can be determined based on the path information.

[0139] Furthermore, the path information and obstacle information identified from the environmental information may be compared with the preset map data; and the driving path may be corrected based on the comparison result.

[0140] Specifically, if map data is pre-installed in the vehicle, the path and obstacle information identified from the environmental information can be compared with the map data to determine the differences between the identified path and the path information in the map data. The identified path and obstacle information can then be combined with the path information in the map data to correct the previously planned driving path, making the driving path more accurate.

[0141] In summary, in embodiments of the present invention, path information and obstacle information are identified from environmental information, a driving path is determined based on the path and obstacle information, the path and obstacle information identified from the environmental information are compared with pre-set map data, and the driving path is corrected based on the comparison results. Through embodiments of the present invention, if the vehicle does not have pre-set map data, the path can be planned based solely on the collected environmental information; if the vehicle has pre-set map data, the driving path can be corrected in conjunction with the map data, making the driving path planned by the autonomous vehicle more accurate, further enabling the application of autonomous vehicles in a wider range of scenarios and expanding the scope of their application.

[0142] In another embodiment, Figure 6 As shown, this embodiment involves an optional process of interaction between a vehicle and a drone. Figure 2 Based on the embodiment shown, the following steps may also be included:

[0143] Step 401: Start a first UAV in a standby state to collect the environmental information.

[0144] In this embodiment, a variety of monitoring devices can be installed on the drone to achieve fault monitoring, power monitoring, temperature monitoring, etc. The embodiment of the present invention does not limit the monitoring device in detail, and it can be installed according to actual conditions.

[0145] The drone transmits monitored drone status data to the vehicle. The vehicle receives the drone status data, determines the drone's status based on the drone status data, and then controls the drone accordingly. For example, a vehicle can obtain the battery levels of multiple drones, determine the corresponding drone status based on the battery levels of each drone, and then control the drones based on the drone status. A drone status can include at least one of a standby state and an active state. This embodiment of the present invention does not specifically limit the drone status and can be set based on actual circumstances.

[0146] After determining the status of the drone, the first drone in the standby state is activated to start working and collect environmental information. The first drone can be a single drone or multiple drones. This embodiment of the present invention does not impose any specific restrictions on this, and can be set according to actual circumstances.

[0147] Step 402: Control the second UAV in the working state to return to the vehicle.

[0148] In this embodiment, while the first drone in standby mode is activated, a second drone in active mode can be controlled to return to the vehicle. The second drone can be a single drone or multiple drones. This embodiment of the present invention does not impose any specific restrictions on this, and can be configured based on actual circumstances.

[0149] It can be seen that starting the drone in standby state and controlling the drone in working state to return to the vehicle can enable multiple drones to work seamlessly at all times, thereby extending the time for collecting environmental information and thus extending the vehicle's driving time.

[0150] Step 403: Perform at least one of firmware upgrade and charging on the second UAV that has returned to the vehicle.

[0151] In this embodiment, for a drone that returns to the vehicle, the drone's firmware can be upgraded; the drone can also be charged so that it can function better; and parts of the drone can also be replaced. This embodiment of the present invention does not limit this in detail and can be configured according to actual circumstances.

[0152] In summary, in this embodiment of the present invention, a first drone in standby mode is activated to collect environmental information; a second drone in active mode is controlled to return to the vehicle; and firmware upgrades and charging are performed on the second drone that has returned to the vehicle. Through this embodiment of the present invention, the vehicle can control drones based on their status data, enabling multiple drones to operate seamlessly at all times. This not only protects the drones and keeps them in optimal working condition, but also extends the time it takes to collect environmental information, thereby extending the vehicle's driving time and improving the competitiveness of autonomous vehicles.

[0153] It should be understood that although the various steps in the flowcharts of Figures 1-6 are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in Figures 1-6 may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0154] In one embodiment, Figure 7 As shown, a vehicle automatic driving device, the device comprising:

[0155] A target area determination module 501 is used to determine a target area for the vehicle to move forward;

[0156] The collection instruction sending module 502 is used to send a collection instruction to at least one UAV; the collection instruction is used to instruct the UAV to collect environmental information of the target area;

[0157] An environmental information receiving module 503 is configured to receive environmental information sent by at least one UAV;

[0158] The driving path determination module 504 is used to determine the driving path of the vehicle for automatic driving based on environmental information.

[0159] In one embodiment, the target area determination module includes:

[0160] A first target area determination submodule is configured to receive a target location input by a user and determine a target area based on preset map data and the target location;

[0161] The second target area determination submodule is configured to receive a target area input by a user.

[0162] In one embodiment, the acquisition instruction sending module includes:

[0163] a first acquisition instruction sending submodule, configured to send an acquisition instruction to at least one UAV based on the vehicle's driving data and the target area if the vehicle is in a driving state;

[0164] a second acquisition instruction sending submodule, configured to send an acquisition instruction to at least one UAV according to a target area if the vehicle is in a stopped state;

[0165] Among them, the collection instructions include the flight position information of the UAV.

[0166] In one embodiment, the flight position information includes the flight distance, offset angle, and flight altitude of at least two UAVs.

[0167] In one embodiment, the at least two UAVs have the same flight distance and offset angle but different flight altitudes; or

[0168] The flight distance and altitude of at least two of the above drones are the same, but the deviation angles are different; or

[0169] The at least two UAVs have the same flight altitude and offset angle but different flight distances.

[0170] In one embodiment, the first acquisition instruction sending submodule includes:

[0171] a horizontal distance calculation unit, configured to calculate the horizontal distance between at least one UAV and the vehicle based on the vehicle's driving data and a preset time constant; wherein the driving data includes at least one of a driving speed and a driving acceleration;

[0172] an offset angle calculation unit, configured to calculate an offset angle between at least one UAV and the vehicle based on the target area and the acquisition range of each UAV;

[0173] The acquisition instruction sending unit is used to send an acquisition instruction to at least one UAV according to the horizontal distance and the offset angle.

[0174] In one embodiment, the drone has a barrier function.

[0175] In one embodiment, the apparatus further comprises:

[0176] The map data acquisition module is used to obtain map data from the server.

[0177] In one embodiment, the drone includes at least one of an image acquisition device and a laser radar;

[0178] The above-mentioned environmental information includes at least one of image data and point cloud data of the target area.

[0179] In one embodiment, the environment information receiving module includes:

[0180] a first environmental information receiving submodule, configured to wirelessly receive environmental information sent by at least one drone when the vehicle is in a driving state;

[0181] The second environmental information receiving submodule is used to control at least one UAV to return to the vehicle if the vehicle is in a stopped state, and receive environmental information via wired or wireless means.

[0182] In one embodiment, the driving path determination module includes:

[0183] A path obstacle identification submodule is used to identify path information and obstacle information from environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and roadblock information;

[0184] The driving path determination submodule is used to determine the driving path based on the path information and obstacle information.

[0185] In one embodiment, the apparatus further comprises:

[0186] a comparison module for comparing the path information and obstacle information identified from the environmental information with the preset map data;

[0187] The driving path correction module is used to correct the driving path according to the comparison result.

[0188] In one embodiment, the apparatus further comprises:

[0189] A UAV starting module, configured to start a first UAV in a standby state to collect the environmental information;

[0190] The drone recall module is used to control the second drone in working state to return to the vehicle.

[0191] In one embodiment, the apparatus further comprises:

[0192] The charging module is adjusted to perform at least one of firmware upgrade and charging on the second UAV returned to the vehicle.

[0193] The specific definition of the vehicle autonomous driving device can be found in the definition of the vehicle autonomous driving method above, and will not be repeated here. The various modules in the above-mentioned vehicle autonomous driving device can be implemented in whole or in part through software, hardware, or a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of the above modules.

[0194] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0195] Determine the target area for the vehicle to move forward;

[0196] Sending a collection instruction to at least one UAV; the collection instruction is used to instruct the UAV to collect environmental information of the target area;

[0197] receiving environmental information sent by at least one drone;

[0198] Determine the vehicle's autonomous driving path based on environmental information.

[0199] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0200] Determine the target area for the vehicle to move forward;

[0201] Sending a collection instruction to at least one UAV; the collection instruction is used to instruct the UAV to collect environmental information of the target area;

[0202] receiving environmental information sent by at least one drone;

[0203] Determine the vehicle's autonomous driving path based on environmental information.

[0204] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0205] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0206] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for automatic vehicle driving, characterized in that: The vehicle carries at least one drone, and the method comprises: Receiving a target location input by a user, and determining a target area for the vehicle to travel to based on preset map data and the target location; When the vehicle is in a driving state, a horizontal distance between at least one of the UAVs and the vehicle is calculated based on driving data of the vehicle and a preset time constant, wherein the driving data includes at least one of driving speed and driving acceleration; an offset angle between at least one of the UAVs and the vehicle is calculated based on the target area and the collection range of each of the UAVs; and a collection instruction is sent to at least one of the UAVs based on the horizontal distance and the offset angle, wherein the collection instruction includes the horizontal distance and the offset angle; When the vehicle is in a stopped state, sending the collection instruction to at least one of the drones according to the target area and the collection range of each of the drones; After receiving the collection instruction, at least one of the drones collects environmental information of the target area according to the collection instruction, wherein the environmental information includes at least one of path information, vehicles, pedestrians, mountains, trees, and rivers; receiving the environmental information sent by the at least one UAV; determining a path and obstacle information based on the environmental information, and planning a direction, speed, and avoidance method for the automatic driving of the vehicle based on the path and obstacle information; The path information and obstacle information identified from the environmental information are compared with the preset map data, and the direction, speed and avoidance method of the vehicle's automatic driving are corrected according to the comparison result.

2. The method according to claim 1, characterized in that The calculating the horizontal distance between at least one UAV and the vehicle based on the vehicle's driving data and a preset time constant includes: The driving speed is m, the preset time constant is t, and the horizontal distance between at least one UAV and the vehicle is L=m*t; wherein the preset time constant is a constant determined according to the transmission speed of environmental information and the path planning time.

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