CN110119147A - Vehicle automatic driving method, device, computer equipment and storage medium - Google Patents

Abstract

The application relates to a vehicle automatic driving method, a vehicle automatic driving device, a computer device and a storage medium. The method comprises the following steps: determining a target area for the vehicle to move ahead; sending an acquisition instruction to the at least one unmanned aerial vehicle; the acquisition instruction is used for instructing the unmanned aerial vehicle to acquire environmental information of the target area; receiving the environment information sent by the at least one unmanned aerial vehicle; and determining the driving path of the automatic driving of the vehicle according to the environment information. According to the embodiment of the invention, the unmanned aerial vehicle is adopted to collect the environmental information, so that the detection area can be increased, the detection blind area can be reduced, and more and richer environmental data can be provided for the automatic driving vehicle, so that the automatic driving vehicle can perform more accurate path planning according to the collected environmental information, the safety of the automatic driving vehicle is ensured, and the application range of the automatic driving vehicle is expanded.

Description

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

technical field

The present application relates to the technical field of automatic driving, and in particular, to a method, apparatus, computer equipment and storage medium for automatic driving of vehicles.

Background technique

With the development of vehicles, autonomous driving technology has become a hot research trend. In the field of automatic driving, the ability of automatic driving system to collect information on the surrounding environment is of great significance to vehicle safety, and the information collection ability of automatic driving system is heavily dependent on the arrangement of sensors.

At present, the sensors of autonomous vehicles are basically limited to the roof or around the body, and the detection area of the sensor is a limited range centered on the location of the vehicle.

However, this arrangement still has a detection blind spot, which cannot meet the perception requirements of autonomous vehicles, and there are still some risks.

SUMMARY OF THE INVENTION

Based on this, it is necessary to provide a vehicle automatic driving method, device, computer equipment and storage medium that can meet the perception requirements of the automatic driving vehicle in view of the above technical problems.

On the one hand, an embodiment of the present invention provides a method for automatic driving of a vehicle. The vehicle is equipped with at least one unmanned aerial vehicle, and the above method includes:

Determine the target area for the vehicle to move forward;

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;

Receive environmental information sent by at least one drone;

Determine the driving path of the vehicle for automatic driving according to the environmental information.

In one embodiment, the above-mentioned determination of the target area where the vehicle moves forward includes:

Receive the target location input by the user, and determine the target area according to the preset map data and target location;

Or, the target area that receives user input.

In one of the embodiments, the above-mentioned sending of acquisition instructions to at least one unmanned aerial vehicle includes:

If the vehicle is in a driving state, send a collection instruction to at least one UAV according to the driving data of the vehicle and the target area;

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

Wherein, the collection instruction includes the flight position information of the UAV.

In one of the embodiments, the above-mentioned flight position information includes flight distances, offset angles and flight heights of at least two UAVs.

In one of the embodiments, the flight distances and offset angles of the at least two UAVs are the same, and the flight heights are different; or

The flight distance and flight height of the at least two UAVs are the same, and the offset angles are different; or

The flight heights and offset angles of the at least two UAVs are the same, and the flight distances are different.

In one embodiment, the above-mentioned sending a collection instruction to at least one UAV according to the driving data of the vehicle and the target area includes:

Calculate the horizontal distance between at least one UAV and the vehicle according to the driving data of the vehicle and the preset time constant; wherein, the driving data includes at least one of the driving speed and the driving acceleration;

Calculate the offset angle between at least one UAV and the vehicle according to the target area and the collection range of each UAV;

According to the horizontal distance and the offset angle, the acquisition command is sent to at least one UAV.

In one of the embodiments, the above-mentioned UAV has a barrier function.

In one embodiment, before determining the target area according to the preset map data and the target location, the method further includes:

Get map data from the server.

In one of the embodiments, the above-mentioned UAV includes at least one of an image acquisition device and a lidar;

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

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

If the vehicle is in a driving state, wirelessly receive environmental information sent by at least one drone;

If the vehicle is in a stopped state, control at least one drone to return to the vehicle and receive environmental information through wired or wireless means.

In one embodiment, the above-mentioned determination of the driving path of the vehicle for automatic driving according to the environmental information includes:

Identify path information and obstacle information from the environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and road obstacle information;

The driving path is determined according to the path information and obstacle information.

In one of the embodiments, after identifying the path information and the obstacle information from the environment information, the method further includes:

Compare path information and obstacle information identified from environmental information with preset map data;

Correct the driving route according to the comparison result.

In one embodiment, the method further includes:

Start the first drone in the standby state to collect the environmental information;

The second drone that controls the working state returns to the vehicle.

In one of the embodiments, after the second drone in the control working state returns to the vehicle, the method further includes:

At least one of firmware upgrade and charging is performed on the second drone returning to the vehicle.

In another aspect, an embodiment of the present invention also provides a vehicle automatic driving device, the device comprising:

The target area determination module is used to determine the target area where the vehicle moves forward;

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

an environmental information receiving module for receiving environmental information sent by at least one drone;

The driving path determination module is used for determining the driving path of the automatic driving of the vehicle according to the environmental information.

In one embodiment, the above-mentioned target area determination module includes:

The first target area determination submodule is used to receive the target location input by the user, and determine the target area according to the preset map data and the target location;

The second target area determination sub-module is configured to receive the target area input by the user.

In one embodiment, the above-mentioned acquisition instruction sending module includes:

The first collection instruction sending sub-module is used to send a collection instruction to at least one UAV according to the driving data of the vehicle and the target area if the vehicle is in a driving state;

The second collection instruction sending sub-module is used to send a collection instruction to at least one UAV according to the target area if the vehicle is in a stopped state;

Wherein, the collection instruction includes the flight position information of the UAV.

In one of the embodiments, the above-mentioned flight position information includes flight distances, offset angles and flight heights of at least two UAVs.

In one of the embodiments, the flight distances and offset angles of the at least two UAVs are the same, and the flight heights are different; or

The flight distance and flight height of the above at least two UAVs are the same, and the offset angles are different; or

The flight heights and offset angles of the above at least two UAVs are the same, and the flight distances are different.

In one embodiment, the above-mentioned first acquisition instruction sending submodule includes:

a horizontal distance calculation unit, configured to calculate the horizontal distance between at least one UAV and the vehicle according to the 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;

The offset angle calculation unit is used to calculate the offset angle between at least one UAV and the vehicle according to the target area and the collection range of each UAV;

The acquisition instruction sending unit is used for sending acquisition instructions to at least one UAV according to the horizontal distance and the offset angle.

In one of the embodiments, the above-mentioned UAV has a barrier function.

In one embodiment, the device further includes:

The map data acquisition module is used to acquire map data from the server.

In one of the embodiments, the above-mentioned UAV includes at least one of an image acquisition device and a lidar;

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

In one embodiment, the above-mentioned environmental information receiving module includes:

a first environmental information receiving sub-module, configured to wirelessly receive environmental information sent by at least one drone if the vehicle is in a driving state;

The second environment information receiving sub-module is configured to control at least one drone to return to the vehicle if the vehicle is in a stopped state, and receive the environment information in a wired or wireless manner.

In one embodiment, the driving path determination module includes:

a path obstacle identification sub-module, used for identifying path information and obstacle information from environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and road obstacle information;

The driving path determination sub-module is used to determine the driving path according to the path information and obstacle information.

In one embodiment, the device further includes:

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

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

In one embodiment, the device further includes:

an unmanned aerial vehicle startup module, used for starting the first unmanned aerial vehicle in the standby state to collect the environmental information;

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

In one embodiment, the above-mentioned device further includes:

The charging module is adjusted to perform at least one operation of firmware upgrade and charging on the second drone returning to the vehicle.

In another aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

In another aspect, an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the steps of the above method.

In the above-mentioned vehicle automatic driving method, device, computer equipment and storage medium, the vehicle is equipped with at least one unmanned aerial vehicle, and the automatic driving vehicle first determines the target area of the vehicle; then sends a collection instruction to the at least one unmanned aerial vehicle; and then receives at least one The environmental information sent by the drone; and the driving path of the vehicle's automatic driving is determined according to the environmental information. Through the embodiment of the present invention, the use of unmanned aerial vehicles to collect environmental information can increase the detection area, reduce the detection blind area, and provide more and richer environmental data for the automatic driving vehicle, so that the automatic driving vehicle can perform the operation according to the collected environmental information. More accurate path planning ensures the safety of autonomous vehicles and expands the application scope of autonomous vehicles.

Description of drawings

FIG. 1a is one of the application environment diagrams of the vehicle automatic driving method in one embodiment;

Fig. 1b is the second application environment diagram of the vehicle automatic driving method in one embodiment;

FIG. 2 is a schematic flowchart of steps of a vehicle automatic driving method in one embodiment;

3 is a schematic flowchart of a step of sending a collection instruction to at least one unmanned aerial vehicle in one embodiment;

Figure 4a is one of the schematic diagrams of the relative position between the drone and the vehicle in one embodiment;

Fig. 4b is the second schematic diagram of the relative position between the drone and the vehicle in one embodiment;

5 is a schematic flowchart of steps of determining a driving path for automatic driving of a vehicle according to environmental information in one embodiment;

6 is a schematic flowchart of the interaction between a vehicle and a drone in one embodiment;

FIG. 7 is a structural block diagram of a vehicle automatic driving apparatus in one embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

The vehicle automatic driving method provided in this application can be applied to the application environment shown in Fig. 1a and Fig. 1b. Among them, the vehicle has an autopilot system that can communicate with at least one drone and perform path planning. UAVs include image acquisition equipment, lidar and other information acquisition equipment. The embodiment of the present invention does not limit the vehicle and the UAV in detail, and can be set according to the actual situation.

Referring to FIG. 2 , a method for automatic driving of a vehicle provided by an embodiment of the present invention is shown, and the method is applied to the vehicle in FIG. 1 a and FIG. 1 b as an example for description. The vehicle carries at least one drone, and the method includes:

Step 101: Determine the target area where the vehicle moves forward.

In this embodiment, before the vehicle performs automatic driving, a target area where the vehicle moves forward needs to be determined. Optionally, determine the direction, length, width, area, etc. of the target area. 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, and a desert. The embodiment of the present invention does not limit the target area in detail, and can be set according to the actual situation.

Only by determining the target area for the vehicle to travel, can the collection area of environmental information be determined, and further, the driving path can be planned according to the environmental information.

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.

In this embodiment, after determining the target area where the vehicle moves forward, a collection instruction is sent to the UAV. If the vehicle is equipped with one UAV, a collection instruction is sent to the UAV; if the vehicle is equipped with multiple UAVs, a collection instruction is sent to at least one UAV. This embodiment of the present invention does not limit this in detail, and may be set according to actual conditions.

After receiving the collection instruction, the UAV collects the 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 environment information is not limited in detail in the embodiment of the present invention, and can be set according to actual situation information.

Due to the high height of the UAV, the detection area can be increased, the detection blind spot can be reduced, and more and richer environmental data can be provided for the autonomous driving vehicle, so that the autonomous driving vehicle can perform more accurate path planning according to the collected environmental information. .

Step 103: Receive environmental information sent by at least one drone.

In this embodiment, after collecting the 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 wirelessly received. If the vehicle is in a stopped state, control at least one drone to return to the vehicle and receive environmental information through wired or wireless means. Understandably, the more the number of UAVs, the more environmental information collected, and the more environmental information the vehicle needs to receive. Receiving environmental information through wired means is not limited by bandwidth, and improves the efficiency of environmental information. transfer speed. The embodiments of the present invention are not limited in detail, and may be set according to actual conditions.

Step 104: Determine the driving path of the vehicle for automatic driving according to the environmental information.

In this embodiment, after receiving the environmental information, the vehicle identifies information such as paths and obstacles from the environmental information, and then plans the driving path of the vehicle, such as the direction, speed, and avoidance methods of automatic driving according to the path and obstacle information.

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

Specifically, the UAV can collect the image data of the target area through the image acquisition device. After the vehicle receives the image data of the target area, the image recognition technology can be used to identify the path and obstacle information from the image data. The UAV can also collect the point cloud data of the target area through lidar. After the vehicle receives the point cloud data of the target area, it can model according to the point cloud data, so as to identify the path and obstacles in the built model. information. It is understandable that when there are many information collection devices set on the UAV, different environmental information can be collected, and different identification methods can be adopted for different environmental information. The embodiment of the present invention does not limit the identification mode in detail, and may be set according to the actual situation.

To sum up, in the embodiment of the present invention, the vehicle is equipped with at least one UAV, and the autonomous vehicle first determines the target area where the vehicle moves forward; then sends a collection instruction to the at least one UAV; and then receives the at least one UAV to send and determine the driving path of the vehicle for automatic driving according to the environmental information. Through the embodiment of the present invention, the use of unmanned aerial vehicles to collect environmental information can increase the detection area, reduce the detection blind area, and provide more and richer environmental data for the automatic driving vehicle, so that the automatic driving vehicle can perform the operation according to the collected environmental information. More accurate path planning ensures the safety of autonomous vehicles and expands the application scope of autonomous vehicles.

In another embodiment, the present embodiment relates to an optional process of the step of determining the target area where the vehicle moves forward. On the basis of the above-mentioned embodiment shown in FIG. 2 , the above-mentioned step 102 may specifically include the following methods:

Manner 1: Receive the target location input by the user, and determine the target area according to the preset map data and the target location. For example, if the vehicle is at point A, and the user inputs the target location as point B in the preset map, the vehicle can determine the target area as the area from point A to point B according to the preset map data.

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

The second method is to receive the target area input by the user. Specifically, when there is no preset map data in the vehicle, the user can directly input the target area. For example, the input target area is an area 10 kilometers long and 1 kilometer wide in the northeast direction, or the input target area is an area with a radius of 5 kilometers centered on the vehicle. The embodiment of the present invention does not limit the determination method of the target area in detail, and may be set according to the actual situation.

To sum up, in this embodiment of the present invention, the target area is determined by receiving the target location input by the user, determining the target area according to the preset map data and the target location, and receiving the target area input by the user. The function of determining the target area can be realized in both cases that there is preset map data in the vehicle and there is no preset map data, which makes the application scenarios of autonomous vehicles more extensive.

In another embodiment, as shown in FIG. 3 , this embodiment relates to an optional process of the step of sending a collection instruction to at least one UAV. On the basis of the above-mentioned embodiment shown in FIG. 2 , the above-mentioned step 102 may specifically include the following steps:

Step 201, if the vehicle is in a driving state, send a collection instruction to at least one UAV according to the driving data of the vehicle and the target area; wherein the collection instruction further includes the flight position information of the UAV.

In this embodiment, if the vehicle is in a driving state, when sending a collection instruction to the UAV, it is necessary to first determine the flight position information of the UAV according to the driving data of the vehicle and the target area, and then send the flight position information to the UAV. .

Determining the flight position of the UAV may specifically include the following steps:

Step 2011: Calculate the horizontal distance between at least one UAV and the vehicle according to the driving data of the vehicle and a preset time constant; wherein the driving data includes at least one of driving speed and driving acceleration.

In this embodiment, driving data including driving speed and driving acceleration can be collected when the vehicle is driving, and the horizontal distance between the drone and the vehicle can be obtained by calculating according to the driving data and preset constants. For example, if the driving speed is m and the preset time constant is t, the horizontal distance L=m*n can be calculated.

The preset time constant is a time constant determined according to the transmission speed of the environmental information and the path planning time. The horizontal distance between the UAV and the vehicle calculated according to the preset time constant and the driving data can meet the requirements of the path planning time during the driving process of the vehicle, and avoid the environmental information collected by the UAV being too close to the vehicle or If it is too far, the planned path will be deviated when the vehicle is driving automatically.

Step 2012: Calculate the offset angle between at least one UAV and the vehicle according to the target area and the collection range of each UAV.

In this embodiment, the offset angle between the UAV and the vehicle is calculated, so that the collection range of the UAV can better cover the target area where the vehicle is traveling. If the vehicle is equipped with multiple drones, the offset angles formed by the multiple drones and the vehicle are calculated, as shown in Figure 4a and Figure 4b, so that the collection area of environmental information is longer or the area is larger, so as to realize The coverage rate of the target area is higher, which in turn makes the path planned by the vehicle based on the environmental information more accurate.

Step 2013: Send a collection instruction to at least one UAV according to the horizontal distance and the offset angle.

In this embodiment, after determining the horizontal distance and offset angle between at least one UAV and the vehicle, the vehicle sends a collection instruction to each UAV respectively, and the collection instruction includes the horizontal distance and offset angle determined above, that is, including The flight position information of the drone. After receiving the collection instruction including the flight position information, the UAV determines the flight position according to the collection instruction, so as to collect environmental information at the flight position. Multiple UAVs collect environmental information according to the flight position information contained in the collection instruction, then a UAV formation can be formed, so that the collection range of multiple UAVs can be combined, and the coverage rate of the target area is higher.

Optionally, the flight position information includes flight distances, offset angles and flight heights of the at least two drones. Among them, the following situations are included: at least two UAVs have the same flight distance and offset angle, and different flight heights. The acquisition range is small, but the accuracy is higher. Or, at least two UAVs have the same flight distance and flight height, and different offset angles. For example, if two drones are on the left and right in front of the vehicle, the acquisition range of the two drones can be spliced to expand the acquisition range. Or, at least two UAVs have the same flight height and offset angle, and different flight distances. The UAV with a long flight distance can extend the acquisition range further.

Optionally, the above-mentioned UAV has a barrier function. The flight height range of the UAV can be preset, for example, the flight height of the UAV is preset to be 4 meters to 5 meters above the ground. In the case of encountering obstacles within this height range, the drone can evade itself according to the barrier function. For example, there are street signs, trees, etc. within a preset height range, and the drone can avoid it by itself, without the need for vehicle control. The UAV has a barrier function, which makes the flying position of the UAV very flexible in a small range, avoiding damage to the UAV caused by obstacles.

Step 202, if the vehicle is in a stopped state, send a collection instruction to at least one UAV according to the target area.

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, refer to the above step 2011, which will not be repeated here.

To sum up, in the embodiment of the present invention, the flight position information of the UAV is determined according to the vehicle state and the target area, and the flight position information is sent to the UAV, so that the UAV can collect environmental information according to the flight position information. Through the embodiments of the present invention, regardless of whether the vehicle is in a running state or in a stopped state, the UAV can better collect environmental information, meet the needs of automatic driving of the vehicle, and enable the automatic driving vehicle to be applied to more scenarios. Expanding the range of applications for autonomous vehicles.

In another embodiment, as shown in FIG. 5 , this embodiment relates to an optional process of the step of determining a driving path for automatic driving of the vehicle according to environmental information. On the basis of the above embodiment shown in FIG. 2 , step 104 may specifically include the following steps:

Step 301, identifying path information and obstacle information from the environmental information; wherein the obstacle information includes at least one of traffic information, pedestrian information, and road obstacle information.

In this embodiment, the unmanned aerial vehicle includes image collection equipment and information collection equipment such as laser radar, and the collected environmental information includes image data, point cloud data, and the like. Image recognition technology can be used to identify path information and obstacle information from image data; it can also be modeled based on point cloud data, and path information and obstacle information can be identified from the model. The obstacle information includes traffic information, pedestrian information, road block information, and the like. This embodiment of the present invention does not limit this in detail, and may be set according to actual conditions.

Step 302: Determine the driving path according to the path information and the obstacle information.

In this embodiment, after the path information and obstacle information are determined, an avoidance path, an avoidance direction, etc. may be determined according to the obstacle information, and then an accurate driving path may be determined according to the path information.

Further, the route information and obstacle information identified from the environmental information can also be compared with the preset map data; the driving route can be corrected according to the comparison result.

Specifically, if map data is preset in the vehicle, the path information and obstacle information identified from the environmental information can also be compared with the map data to determine the difference between the identified path information and the path information in the map data. . Then, the identified path information and obstacle information are combined with the path information in the map data, so as to correct the previously planned driving path and make the driving path more accurate.

To sum up, in the embodiment of the present invention, the path information and obstacle information are identified from the environmental information, the driving path is determined according to the path information and the obstacle information, and the path information and obstacle information identified from the environmental information are compared with the preset ones. The map data is compared, and the driving route is corrected according to the comparison result. In the embodiment of the present invention, if the vehicle does not have preset map data, the path can be planned only according to the collected environmental information; if the vehicle has preset map data, the driving path can be corrected in combination with the map data, so that the driving path planned by the autonomous driving vehicle can be adjusted. The path is more precise, which further enables the autonomous vehicle to be applied to a wider range of scenarios and expands the application scope of the autonomous vehicle.

In another embodiment, as shown in FIG. 6 , this embodiment involves an optional process for the interaction between the vehicle and the UAV. On the basis of the embodiment shown in FIG. 2 above, the following steps may also be included:

Step 401: Start the first drone in the standby state to collect the environmental information.

In this embodiment, a variety of monitoring devices may be provided on the UAV, so as to realize fault monitoring, power monitoring, temperature monitoring, and the like. The embodiment of the present invention does not limit the monitoring device in detail, and may be set according to the actual situation.

The drone sends the monitored drone status data to the vehicle, the vehicle receives the drone status data, and then determines the drone status according to the drone status data, and then controls the drone according to the drone status. For example, the vehicle obtains the power of multiple drones, determines the corresponding drone state according to the power of each drone, and then controls the drone according to the drone state. The state of the drone may include at least one of a standby state and a working state. The embodiment of the present invention does not limit the state of the drone in detail, and may be set according to actual conditions.

After determining the state of the drone, start the first drone in the standby state, so that the first drone starts to work and collect environmental information. The first drone may be a single drone or a plurality of drones. This embodiment of the present invention does not limit this in detail, and may be set according to actual conditions.

Step 402, controlling the second drone in the working state to return to the vehicle.

In this embodiment, while the first drone in the standby state is activated, the second drone in the working state can be controlled to return to the vehicle. The second drone may be one drone or multiple drones. This embodiment of the present invention does not limit this in detail, and may be set according to actual conditions.

It can be seen that starting the drone in the standby state and controlling the drone in the working state to return to the vehicle can make multiple drones work seamlessly at all times, thereby prolonging the collection time of environmental information, thereby extending the travel time of the vehicle.

Step 403 , perform at least one operation of firmware upgrade and charging on the second drone returning to the vehicle.

In this embodiment, for the drone returning to the vehicle, the firmware of the drone can be upgraded; the drone can also be charged so that the drone can work better; the parts of the drone can also be replaced . This embodiment of the present invention does not limit this in detail, and may be set according to actual conditions.

To sum up, in the embodiment of the present invention, the first drone in the standby state is activated to collect the environmental information; the second drone in the working state is controlled to return to the vehicle; Firmware upgrade, charging and other operations. Through the embodiment of the present invention, the vehicle can control the UAV according to the state data of the UAV, so that multiple UAVs can work seamlessly at all times, which can not only protect the UAVs, but also keep the UAVs in good working condition. It can also prolong the collection time of environmental information, thereby prolonging the driving time of the vehicle and improving the competitiveness of autonomous driving vehicles.

It should be understood that although the steps in the flowcharts of FIGS. 1-6 are shown in sequence according to the arrows, these steps are not necessarily executed in the sequence shown by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in FIGS. 1-6 may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed and completed at the same time, but may be executed at different times. These sub-steps or stages The order of execution of the steps is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of sub-steps or stages of other steps.

In one embodiment, as shown in FIG. 7 , a vehicle automatic driving device includes:

The target area determination module 501 is used to determine the target area where the vehicle moves forward;

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

an environmental information receiving module 503, configured to receive environmental information sent by at least one drone;

The driving path determination module 504 is configured to determine the driving path of the automatic driving of the vehicle according to the environmental information.

In one embodiment, the above-mentioned target area determination module includes:

The first target area determination submodule is used to receive the target location input by the user, and determine the target area according to the preset map data and the target location;

The second target area determination sub-module is configured to receive the target area input by the user.

In one embodiment, the above-mentioned acquisition instruction sending module includes:

The first collection instruction sending sub-module is used for sending a collection instruction to at least one UAV according to the driving data of the vehicle and the target area if the vehicle is in a driving state;

The second collection instruction sending sub-module is used to send a collection instruction to at least one UAV according to the target area if the vehicle is in a stopped state;

Wherein, the collection instruction includes the flight position information of the UAV.

In one of the embodiments, the above-mentioned flight position information includes flight distances, offset angles and flight heights of at least two UAVs.

In one of the embodiments, the flight distances and offset angles of the at least two UAVs are the same, and the flight heights are different; or

The flight distance and flight height of the above at least two UAVs are the same, and the offset angles are different; or

The flight heights and offset angles of the above at least two UAVs are the same, and the flight distances are different.

In one embodiment, the above-mentioned first acquisition instruction sending submodule includes:

a horizontal distance calculation unit, configured to calculate the horizontal distance between at least one UAV and the vehicle according to the 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;

The offset angle calculation unit is used to calculate the offset angle between at least one UAV and the vehicle according to the target area and the collection range of each UAV;

The acquisition instruction sending unit is used for sending acquisition instructions to at least one UAV according to the horizontal distance and the offset angle.

In one of the embodiments, the above-mentioned UAV has a barrier function.

In one embodiment, the device further includes:

The map data acquisition module is used to acquire map data from the server.

In one of the embodiments, the above-mentioned UAV includes at least one of an image acquisition device and a lidar;

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

In one embodiment, the above-mentioned environmental information receiving module includes:

a first environmental information receiving sub-module, configured to wirelessly receive environmental information sent by at least one drone if the vehicle is in a driving state;

The second environment information receiving sub-module is configured to control at least one drone to return to the vehicle if the vehicle is in a stopped state, and receive the environment information in a wired or wireless manner.

In one embodiment, the driving path determination module includes:

A path obstacle identification submodule, used for identifying path information and obstacle information from environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and road obstacle information;

The driving path determination sub-module is used to determine the driving path according to the path information and obstacle information.

In one embodiment, the device further includes:

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

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

In one embodiment, the device further includes:

an unmanned aerial vehicle startup module, used for starting the first unmanned aerial vehicle in the standby state to collect the environmental information;

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

In one embodiment, the above-mentioned device further includes:

The charging module is adjusted to perform at least one operation of firmware upgrade and charging on the second drone returning to the vehicle.

For specific limitations on the vehicle automatic driving device, reference may be made to the above limitations on the vehicle automatic driving method, which will not be repeated here. Each module in the above-mentioned vehicle automatic driving device may be implemented in whole or in part by software, hardware and combinations thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

In one embodiment, a computer device is provided, including a memory and a processor, a computer program is stored in the memory, and the processor implements the following steps when executing the computer program:

Determine the target area for the vehicle to move forward;

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;

Receive environmental information sent by at least one drone;

Determine the driving path of the vehicle for automatic driving according to the environmental information.

In one embodiment, a computer-readable storage medium is provided on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

Determine the target area for the vehicle to move forward;

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;

Receive environmental information sent by at least one drone;

Determine the driving path of the vehicle for automatic driving according to the environmental information.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage In the medium, when the computer program is executed, it may include the processes of the above-mentioned method embodiments. Wherein, any reference to memory, storage, database or other medium used in the various embodiments provided in this application may include non-volatile and/or volatile memory. Nonvolatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may 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 chain Road (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, all It is considered to be the range described in this specification.

The above-mentioned embodiments only represent several embodiments of the present application, and the descriptions thereof are specific and detailed, but should not be construed as a limitation on the scope of the invention patent. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the scope of protection of the patent of the present application shall be subject to the appended claims.

Claims (12)

1. A vehicle automatic driving method, wherein the vehicle is equipped with at least one unmanned aerial vehicle, and the method comprises: Determine the target area for the vehicle to move forward; Send a collection instruction to the at least one UAV; the collection instruction is used to instruct the UAV to collect the environmental information of the target area; receiving the environmental information sent by the at least one drone; The driving path of the vehicle for automatic driving is determined according to the environmental information. 2. The method according to claim 1, wherein the determining the target area where the vehicle moves forward comprises: Receive the target location input by the user, and determine the target area according to the preset map data and the target location; Or, the target area that receives user input. 3. method according to claim 2, is characterized in that, described sending acquisition instruction to described at least one unmanned aerial vehicle, comprises: If the vehicle is in a driving state, sending a collection instruction to the at least one UAV according to the driving data of the vehicle and the target area; If the vehicle is in a stopped state, sending a collection instruction to the at least one UAV according to the target area; Wherein, the collection instruction includes the flight position information of the UAV. 4 . The method according to claim 3 , wherein the flight position information includes flight distances, offset angles and flight heights of at least two UAVs. 5 . 5. The method according to claim 4, wherein the flight distance and offset angle of the at least two UAVs are the same, and the flight heights are different; or The flight distance and flight height of the at least two UAVs are the same, and the offset angles are different; or The flight heights and offset angles of the at least two UAVs are the same, and the flight distances are different. 6 . The method according to claim 2 , wherein before the target area is determined according to the preset map data and the target location, the method further comprises: 6 . Obtain the map data from the server. 7. The method according to any one of claims 1-6, wherein the UAV comprises at least one of an image acquisition device and a lidar; The environmental information includes at least one of image data and point cloud data of the target area. 8. The method according to claim 1, wherein the receiving the environmental information sent by the at least one UAV comprises: If the vehicle is in a driving state, wirelessly receive the environmental information sent by the at least one drone; If the vehicle is in a stopped state, the at least one UAV is controlled to return to the vehicle, and the environmental information is received in a wired or wireless manner. 9 . The method according to claim 1 , wherein the determining the driving path of the automatic driving of the vehicle according to the environmental information comprises: 10 . Identify path information and obstacle information from the environmental information; wherein the obstacle information includes at least one of driving information, pedestrian information, and road obstacle information; The driving path is determined according to the path information and the obstacle information. 10. The method of claim 1, wherein the method further comprises: Start the first drone in the standby state to collect the environmental information; The second drone that controls the working state returns to the vehicle. 11. The method according to claim 10, wherein after the second drone in the control working state returns to the vehicle, the method further comprises: At least one of firmware upgrade and charging is performed on the second drone returning to the vehicle. 12. A vehicle automatic driving device, characterized in that the device comprises: The target area determination module is used to determine the target area where the vehicle moves forward; a collection instruction sending module, configured to send a collection instruction to the at least one UAV; the collection instruction is used to instruct the UAV to collect the environmental information of the target area; an environmental information receiving module, configured to receive the environmental information sent by the at least one drone; A driving path determination module, configured to determine a driving path for automatic driving of the vehicle according to the environmental information.