CN113359724B - Vehicle intelligent driving system and method based on unmanned aerial vehicle and storage medium - Google Patents
Vehicle intelligent driving system and method based on unmanned aerial vehicle and storage medium Download PDFInfo
- Publication number
- CN113359724B CN113359724B CN202110615111.3A CN202110615111A CN113359724B CN 113359724 B CN113359724 B CN 113359724B CN 202110615111 A CN202110615111 A CN 202110615111A CN 113359724 B CN113359724 B CN 113359724B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- unit
- unmanned aerial
- information
- communication connection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000003860 storage Methods 0.000 title claims abstract description 53
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000004891 communication Methods 0.000 claims abstract description 104
- 238000013439 planning Methods 0.000 claims abstract description 31
- 238000012545 processing Methods 0.000 claims description 31
- 238000004590 computer program Methods 0.000 claims description 21
- 230000004927 fusion Effects 0.000 claims description 13
- 230000008569 process Effects 0.000 claims description 13
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical group C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 claims description 10
- 230000005540 biological transmission Effects 0.000 claims description 4
- 230000004888 barrier function Effects 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 13
- 238000010586 diagram Methods 0.000 description 10
- 238000012544 monitoring process Methods 0.000 description 6
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 230000008447 perception Effects 0.000 description 4
- 238000013135 deep learning Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000008054 signal transmission Effects 0.000 description 3
- 238000012384 transportation and delivery Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 239000013256 coordination polymer Substances 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000001141 propulsive effect Effects 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000011895 specific detection Methods 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0225—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving docking at a fixed facility, e.g. base station or loading bay
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0285—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using signals transmitted via a public communication network, e.g. GSM network
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Aviation & Aerospace Engineering (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Electromagnetism (AREA)
- Acoustics & Sound (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a vehicle intelligent driving system based on an unmanned aerial vehicle, a method and a storage medium, wherein the vehicle intelligent driving system comprises: the unmanned aerial vehicle subsystem is used for acquiring traffic information of a current road section of a vehicle; the cloud subsystem is in communication connection with the unmanned aerial vehicle subsystem and used for receiving the traffic information and acquiring traffic information of a road section near a self vehicle according to the traffic information; and the vehicle-mounted subsystem is in communication connection with the unmanned aerial vehicle subsystem and the cloud subsystem and is used for receiving the current road traffic information and the traffic information of nearby roads of the own vehicle, acquiring the driving path planning information of the own vehicle and controlling the running state of the own vehicle. According to the intelligent driving system, the unmanned aerial vehicle subsystem is used for sensing the environment, the visual field blind area of the intelligent driving vehicle is reduced, so that the safety of intelligent driving is improved, meanwhile, the cloud subsystem is combined on the basis of the unmanned aerial vehicle subsystem, the vehicle-to-outside information exchange system in the prior art can be effectively replaced, and the cost is greatly saved.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to a vehicle intelligent driving system and method based on an unmanned aerial vehicle and a storage medium.
Background
The intelligent driving and auxiliary driving technology is used as an active safety technology, so that the safety of the vehicle during running can be effectively improved, and the perception of the surrounding environment information plays an important role in an intelligent driving system. The current ways of sensing ambient information are two more: one is to sense road conditions and decide driving paths through a sensing system of a single vehicle, and for the mode, when the intelligent driving vehicle is in a congestion environment, a vehicle body sensor cannot detect road condition information of a blind area due to the shielding of other vehicles or obstacles, so that the accident is not caused by the processing of various emergency situations; the other method is to construct an information exchange system of the vehicle to the outside, data acquired by perception sensors on infrastructures such as intersection signal lamps and corner buildings are transmitted to a cloud control center of an intelligent network in a centralized mode for data processing and decision of a driving path, for the mode, the construction of the information exchange system of the vehicle to the outside needs large-scale arrangement of the sensors, and meanwhile, a large amount of manpower and material resources are needed for maintenance and repair of the sensors in the later period.
Disclosure of Invention
The invention aims to overcome the defects of the background technology, and provides an intelligent vehicle driving system and method based on an unmanned aerial vehicle, which can cover the self-vehicle perception visual field blind area and is an intelligent driving system with relatively moderate cost under the condition of ensuring the timeliness and the accuracy.
In a first aspect, an intelligent driving system for a vehicle based on an unmanned aerial vehicle is provided, which includes:
the unmanned aerial vehicle subsystem is used for acquiring traffic information of a current road section of a vehicle;
the cloud subsystem is used for acquiring traffic information of a road section near the self-vehicle according to the traffic information;
and the vehicle-mounted subsystem is in communication connection with the unmanned aerial vehicle subsystem and the cloud subsystem and is used for receiving the current road traffic information and the traffic information of nearby roads of the self-vehicle, acquiring the driving path planning information of the self-vehicle and controlling the running state of the self-vehicle.
According to a first aspect, in a first possible implementation manner of the first aspect, the vehicle-mounted subsystem includes:
the vehicle-mounted base module is in communication connection with the unmanned aerial vehicle subsystem and the cloud subsystem and is used for transmitting data information and storing the data information with the outside;
the intelligent driving module is in communication connection with the vehicle-mounted basic module and is used for acquiring the driving path planning information of the self-vehicle and controlling the running state of the self-vehicle;
the unmanned aerial vehicle releasing module is electrically connected with the vehicle-mounted basic module, comprises an unmanned aerial vehicle releasing unit and is used for controlling the releasing state of the unmanned aerial vehicle.
According to the first aspect, in a second possible implementation manner of the first aspect, the drone subsystem includes:
the remote control flight module is in communication connection with the unmanned aerial vehicle launching unit and is used for controlling launching and flight states of the unmanned aerial vehicle;
the sensing module is in communication connection with the remote control flight module and comprises a sensing unit used for acquiring real-time traffic information and acquiring barrier information in the driving direction of the vehicle according to the real-time traffic information;
the unmanned aerial vehicle base module is in communication connection with the sensing module and the vehicle-mounted base module and is used for receiving and storing the barrier information and transmitting data to the outside; and the number of the first and second groups,
the remote control flight module includes: the navigation unit is used for acquiring the position information of the unmanned aerial vehicle; the flight control unit is in communication connection with the navigation unit and is used for controlling the launching and flight processes of the unmanned aerial vehicle; and the power unit is in communication connection with the flight control unit and is used for providing lift force for the unmanned aerial vehicle.
According to a third possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, the unmanned aerial vehicle base module includes:
the unmanned aerial vehicle storage unit is in communication connection with the sensing unit and used for storing the obstacle information;
and the unmanned aerial vehicle communication unit is in communication connection with the unmanned aerial vehicle storage unit and is used for transmitting data information with the outside.
According to a fourth possible implementation manner of the first aspect, in a fourth possible implementation manner of the first aspect, the vehicle-mounted base module includes:
the vehicle-mounted communication unit is in communication connection with the unmanned aerial vehicle communication unit and is used for transmitting data information with the outside;
and the vehicle-mounted storage unit is in communication connection with the vehicle-mounted communication unit and is used for storing data information.
According to the second possible implementation manner of the first aspect, in a fifth possible implementation manner of the first aspect, the smart driving module includes:
the vehicle-mounted sensing unit is used for acquiring surrounding information of the vehicle on a driving path;
the fusion unit is in communication connection with the vehicle-mounted sensing unit and is used for fusing the obtained surrounding information to obtain real-time external information of the vehicle;
the positioning unit is used for acquiring the position information of the vehicle together with the vehicle-mounted sensing unit and the fusion unit;
the prediction unit is in communication connection with the fusion unit and the positioning unit and is used for predicting external information and position information of the vehicle;
the planning unit is in communication connection with the prediction unit and the vehicle-mounted storage unit and is used for planning the driving path of the vehicle;
and the control unit is in communication connection with the planning unit and is used for controlling the running state of the self-vehicle according to the running path.
According to a second possible implementation manner of the first aspect, in a sixth possible implementation manner of the first aspect, the cloud subsystem includes:
the cloud base module comprises a cloud communication unit and a cloud storage unit in communication connection with the cloud communication unit, and the cloud communication unit is in communication connection with the vehicle-mounted communication unit and is used for transmitting data information with the outside;
and the data arbitration module is in communication connection with the cloud storage unit and is used for planning and arbitrating the obtained driving path of the self-vehicle.
According to the second possible implementation manner of the first aspect, in a seventh possible implementation manner of the first aspect, the data arbitration module includes:
the data processing unit is in communication connection with the cloud storage unit and used for processing the received data information;
the wireless message processing unit is in communication connection with the data processing unit and the cloud storage unit and is used for decoding data information received by wireless transmission;
and the danger arbitration unit is in communication connection with the data processing unit and is used for planning and arbitrating the driving path of the self vehicle.
In a second aspect, a vehicle intelligent driving method based on an unmanned aerial vehicle is provided, which includes the following steps:
acquiring traffic information of a current road section of a vehicle;
receiving the traffic information, and acquiring traffic information of a road section near the own vehicle according to the traffic information;
and receiving the current road traffic information and the traffic information of nearby roads of the own vehicle, acquiring the driving path planning information of the own vehicle, and controlling the running state of the own vehicle.
In a third aspect, a storage medium is provided, on which a computer program is stored, wherein the computer program is executed by a processor to implement the vehicle intelligent driving method.
Compared with the prior art, the system senses the environment by utilizing the unmanned aerial vehicle subsystem, reduces the visual field blind area of the intelligent driving vehicle, improves the safety of intelligent driving, and meanwhile, the cloud subsystem is combined on the basis of the unmanned aerial vehicle subsystem, so that the system can effectively replace an information exchange system of the vehicle to the outside in the prior art, and the cost is greatly saved.
Drawings
FIG. 1 is a schematic structural diagram of an intelligent driving system for a vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an onboard subsystem according to another embodiment of the present invention;
fig. 3 is a schematic structural diagram of a subsystem of an unmanned aerial vehicle according to another embodiment of the present invention;
fig. 4 is a schematic structural diagram of a cloud subsystem according to another embodiment of the present invention;
fig. 5 is a schematic flow chart of a method for intelligently driving a vehicle according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the present embodiments of the invention, examples of which are illustrated in the accompanying drawings. While the invention will be described in conjunction with the specific embodiments, it will be understood that they are not intended to limit the invention to the embodiments described. On the contrary, it is intended to cover alternatives, modifications, and equivalents as may be included within the spirit and scope of the invention as defined by the appended claims. It should be noted that the method steps described herein may be implemented by any functional block or functional arrangement, and that any functional block or functional arrangement may be implemented as a physical entity or a logical entity, or a combination of both.
In order that those skilled in the art will better understand the present invention, the following detailed description of the invention is provided in conjunction with the accompanying drawings and the detailed description of the invention.
Note that: the example to be described next is only a specific example, and does not limit the embodiments of the present invention necessarily to the following specific steps, values, conditions, data, orders, and the like. Those skilled in the art can, upon reading this specification, utilize the concepts of the present invention to construct more embodiments than those specifically described herein.
Referring to fig. 1, an embodiment of the present invention provides an intelligent vehicle driving system 100 based on an unmanned aerial vehicle, including:
the unmanned aerial vehicle subsystem 110 is used for acquiring traffic information of a current road section of a vehicle;
the cloud subsystem 120 is used for acquiring traffic information of a road section near the self-vehicle according to the traffic information;
and the vehicle-mounted subsystem 130 is in communication connection with the unmanned aerial vehicle subsystem 110 and the cloud subsystem 120, and is configured to receive traffic information of a current road section and traffic information of a nearby road section of the own vehicle, acquire planning information of a driving path of the own vehicle, and control an operating state of the own vehicle.
Specifically, in this embodiment, by setting the unmanned aerial vehicle subsystem 110, the cloud end subsystem 120 and the vehicle-mounted subsystem 130, the unmanned aerial vehicle subsystem 110 may obtain complete traffic information of a current road section in real time, and wirelessly transmit the complete traffic information of the current road section to the vehicle-mounted subsystem 130 and the cloud end subsystem 120, so as to make up a self-vehicle perception view blind area; the cloud subsystem 120 may convert the complete traffic information transmitted by the unmanned aerial vehicle subsystem 110 of another vehicle into complete traffic information of a nearby road segment, and provide support for path planning; the vehicle-mounted subsystem 130 may generate a driving path according to the complete traffic information transmitted by the unmanned aerial vehicle subsystem 110 and the complete traffic information of the nearby road segment acquired by the cloud subsystem 120, and control the motion state of the current vehicle in combination with the driving state thereof, and plan the driving path according to the actual road condition of each road segment, thereby improving the accuracy of planning the driving path and the safety of intelligent driving.
The vehicle intelligent driving system 100 based on the unmanned aerial vehicle effectively solves the problems that in the prior art, a sensing system of a single vehicle is adopted for sensing and deciding the driving road condition, when the intelligent driving vehicle is in a congestion environment, a vehicle body sensor cannot detect the road condition information of a blind area due to the shielding of other vehicles or obstacles, and is not beneficial to the processing of various emergency situations, and the problem that in the prior art, the maintenance cost of the sensors is high in the later period due to the adoption of an information exchange system of a building vehicle to the outside.
Optionally, as shown in fig. 2, in another embodiment of the present invention, the vehicle-mounted subsystem 130 includes:
the vehicle-mounted base module 131 is in communication connection with the unmanned aerial vehicle subsystem 110 and the cloud subsystem 120, and is used for transmitting data information and storing data information with the outside;
the intelligent driving module 132 is in communication connection with the vehicle-mounted basic module 131 and is used for acquiring the traveling path planning information of the vehicle and controlling the running state of the vehicle;
unmanned aerial vehicle puts in module 133, with on-vehicle basic module 131 electricity is connected, puts in unit 1331 including unmanned aerial vehicle for control unmanned aerial vehicle's the state of puting in.
Specifically, in this embodiment, the intelligent driving module 132 is configured to control an automatic running state of the current vehicle; the vehicle-mounted base module 131 is used for transmitting data with the outside, storing the data and providing power; and the unmanned aerial vehicle launching module 133 is used for launching and recovering the unmanned aerial vehicle.
Optionally, as shown in fig. 3, in a further embodiment of the present invention, the drone subsystem 110 includes: the remote control flight module 111 is in communication connection with the unmanned aerial vehicle launching unit 1331 and is used for controlling launching and flight states of the unmanned aerial vehicle;
the sensing module 112 is in communication connection with the remote control flight module 111, and includes a sensing unit 1121, configured to acquire real-time traffic information and acquire obstacle information in a driving direction of the vehicle according to the real-time traffic information;
and the unmanned aerial vehicle base module 113 is in communication connection with the sensing module 112 and the vehicle-mounted base module 131, and is used for receiving and storing the obstacle information and transmitting data with the outside. Specifically, in this embodiment, the base module 113 of the unmanned aerial vehicle is configured to transmit data with the outside, store the data, and provide a power supply; the remote control flight module 111 is used for controlling the flight state of the current unmanned aerial vehicle; the sensing module 112 is configured to obtain surrounding information on a current road segment and provide obstacle information for a following vehicle. Furthermore, in this embodiment, the remote control flight module 111 includes: the navigation unit 1111 is used for acquiring the position information of the unmanned aerial vehicle; a flight control unit 1112, communicatively connected to the navigation unit 1111, and configured to control the launch and flight process of the unmanned aerial vehicle; and a power unit 1113, which is in communication connection with the flight control unit 1112 and is used for providing lift force for the unmanned aerial vehicle.
Specifically, in this embodiment, the navigation unit 1112 is configured to obtain the current position information of the unmanned aerial vehicle, and mainly includes, for example, a gyroscope, the gyroscope is used for sensing a flight attitude, an accelerometer, a geomagnetic sensor, and an air pressure sensor, the air pressure sensor is used for coarse hovering height control and an ultrasonic sensor, the ultrasonic sensor is used for precise low altitude height control or obstacle avoidance, a position sensing unit, and an optical flow sensor, the optical flow sensor is used for precise hovering horizontal position determination, the position sensing unit, and a GPS module, and the GPS module is used for coarse horizontal position height positioning; the flight control unit 1111 is used for controlling the whole flight process of the unmanned aerial vehicle such as take-off, air flight, task execution, return recovery and the like, comprises an onboard computer and servo actuation equipment, and mainly realizes three main functions of unmanned aerial vehicle attitude stabilization and control, unmanned aerial vehicle task equipment management and emergency control; the power unit 1113 is used for providing lift for the unmanned aerial vehicle, mainly contains the motor, the motor is used for converting the electric energy into mechanical energy, electricity (for example electronic governor), its main effect is exactly to fly the control signal of control panel, change into the size of electric current to the rotational speed of control motor, the screw, its main effect is to turn into propulsive force or lift with motor rotation power.
Furthermore, in this embodiment, the unmanned aerial vehicle base module 113 includes: an unmanned aerial vehicle storage unit 1131, communicatively connected to the sensing unit 1121, and configured to store the obstacle information; the unmanned aerial vehicle communication unit 1132 is in communication connection with the unmanned aerial vehicle storage unit 1131 and is used for transmitting data information with the outside, and the unmanned aerial vehicle communication unit 1132 can also comprise an unmanned aerial vehicle power supply unit which is used for supplying power to the unmanned aerial vehicle; in an embodiment of the present invention, the unmanned aerial vehicle storage unit 1131 is configured to store data, and may store data in a current driving process of a vehicle, for example, ambient environment and obstacle information of the vehicle within a period of time may be stored in the unmanned aerial vehicle storage unit 1131, so as to be conveniently used as a tachograph for subsequent viewing and calling, the unmanned aerial vehicle communication unit 1132 is configured to perform data or signal transmission with the outside, and the ambient environment and obstacle information of the vehicle may be directly transmitted to the vehicle-mounted subsystem 130 through the unmanned aerial vehicle communication unit 1132.
In the unmanned aerial vehicle subsystem 110, a sensor is arranged to sense surrounding environment elements, raw data is acquired and is transmitted to the sensing unit 1121 and the navigation unit 1112, the navigation unit 1112 receives raw data of the sensor (for example, IMU, GPS, and the like), generates position information of a current unmanned aerial vehicle through an algorithm (for example, UKF algorithm, and the like), and transmits the position information to the sensing unit 1121 and the flight control unit 1111, the sensing unit 1121 receives position information and sensor data of the current unmanned aerial vehicle, generates an obstacle list (for example, information including position, speed, acceleration, size, and the like of an obstacle) through an algorithm (for example, deep learning, and the like), and transmits the obstacle list information to the unmanned aerial vehicle storage unit 1131, the unmanned aerial vehicle storage unit 1131 receives the obstacle information, transmits the obstacle list to the unmanned aerial vehicle communication unit 1132, and transmits a predicted heading to the flight control unit 1111; the flight control unit 1111 receives the predicted course and the current position information of the unmanned aerial vehicle, generates the direction and the size of the lift force through an algorithm (such as a PID algorithm), transmits the information of the direction and the size of the lift force to the power unit 1113, the power unit 1113 receives the information of the direction and the size of the lift force and controls the rotating speed of each blade to control the flight of the unmanned aerial vehicle, and the power unit of the unmanned aerial vehicle receives the wireless power supply of the power unit of the unmanned aerial vehicle in the vehicle-mounted subsystem 130.
Optionally, in another embodiment of the present invention, the vehicle-mounted base module 131 includes: the vehicle-mounted communication unit 1311 is in communication connection with the unmanned aerial vehicle communication unit 1132 and is used for transmitting data information with the outside; and the vehicle-mounted storage unit 1312 is in communication connection with the vehicle-mounted communication unit 1311 and is used for storing data information. The vehicle-mounted base module 131 can further include a vehicle-mounted power supply unit, which is used for supplying power to a vehicle-mounted electronic control unit, a vehicle sensor and the unmanned aerial vehicle power supply unit, and has a wireless charging function for the unmanned aerial vehicle, so that the cruising ability of the unmanned aerial vehicle is enhanced; the on-board storage unit 1312 is used for storing data, and storing and retrieving data during the driving process of the current vehicle, for example, a planned driving route may be stored in the storage unit, and the intelligent driving module may directly read the driving route and control the driving of the current vehicle, and may also store information such as an actual driving route of the vehicle and a driving state quantity during the driving process in the on-board storage unit 1312, so as to facilitate subsequent viewing and recall; the vehicle communication unit 1311 is configured to transmit data with the outside, and perform data or signal transmission with the outside, the planned driving path may be transmitted to the intelligent driving module 132 through the vehicle communication unit 1311, and the intelligent driving module 132 controls the current vehicle to run according to the driving path.
Furthermore, in this embodiment, the intelligent driving module 132 includes: an in-vehicle sensing unit 1321 for obtaining surrounding information of the own vehicle on the travel path; the fusion unit 1322 is in communication connection with the vehicle-mounted sensing unit 1321, and is used for fusing the obtained surrounding information to obtain real-time external information of the vehicle; a positioning unit 1323, communicatively connected to the vehicle sensing unit 1321 and the fusion unit 1322, for obtaining the position information of the vehicle; a prediction unit 1324 communicatively connected to the fusion unit 1322 and the positioning unit 1323, and configured to predict external information and position information of the vehicle; a planning unit 1325, communicatively connected to the prediction unit 1324 and the vehicle-mounted storage unit 1312, for planning a traveling path of the vehicle; and a control unit 1326, communicatively connected to the planning unit 1325, for controlling the operation state of the vehicle according to the driving route.
Specifically, the vehicle-mounted sensing unit 1321 is configured to acquire surrounding information of the current vehicle, and may be a small number of cameras and radars that are disposed around a vehicle body to acquire a basic state of the vehicle around the vehicle during traveling, such as whether there is an obstacle in a track direction; the fusion unit 1322 is configured to fuse the peripheral information of the current vehicle to obtain real-time external information of the current vehicle; the positioning unit 1323 is configured to acquire pose information of the current vehicle, and may be a combination of a set of inertial navigation system and a GPS positioning system; the prediction unit 1324 is configured to predict real-time external information of the current vehicle and pose information of the current vehicle, and reduce disturbance caused by a detection error; the planning unit 1325 is configured to plan an instant path of the current vehicle according to the real-time external information, and plan the current path of the current vehicle based on the acquired external information, that is, the current driving strategy of the current vehicle, for example, when there is an obstacle in front of the driving path, the speed of the vehicle may be reduced to avoid a traffic accident; the control unit 1326 is configured to control the running state of the current vehicle according to the immediate path and the driving path, and control the running state of the current vehicle according to the driving path and the immediate path, so as to ensure that the current vehicle runs on the optimal driving path and ensure the running safety of the current vehicle.
In other embodiments of the present invention, the vehicle-mounted subsystem 130 may further include a vehicle status monitoring module, configured to monitor a current functional status of the vehicle, and specifically, the vehicle status monitoring module includes: the driver monitoring system unit is used for monitoring the state of people in the vehicle; the vehicle system monitoring unit is used for monitoring the functional state of each module of the vehicle-mounted system, and reminding a driver and recording abnormal events when the function of one or more modules is abnormal; the driving event detection unit is used for detecting a driving event on a driving path, wherein a specific detection mode can be known through a sensing device of a vehicle, can also be known through other vehicles or external equipment and then is transmitted to the current vehicle through a cloud system, and meanwhile, when the driving event is detected, dynamic information of the area within a certain time (for example, one hour) before and after the driving event occurs is obtained, so that a system log is formed, data support is provided for subsequent driving path planning, the system log can be stored, and the system log is uploaded to the cloud system in an idle time (for example, charging or idling), so that the data support is improved for subsequent automatic driving function development, improvement and verification; and the communication function detection unit is used for detecting the communication state between the vehicle-mounted system and the outside and whether the vehicle-mounted system can normally communicate with the cloud subsystem.
In the vehicle-mounted system, sensors are arranged to sense surrounding environment elements, raw data are acquired and transmitted to the vehicle-mounted sensing unit 1321 and the positioning unit 1323, the vehicle-mounted sensing unit 1321 generates an obstacle list (for example, information including position, speed, acceleration, size and the like of an obstacle) through an algorithm (for example, deep learning and the like) and transmits obstacle list information to the positioning unit 1323 and the fusion unit 1322, the positioning unit 1323 receives the sensor raw data and the obstacle list information, generates a current vehicle body position through an algorithm (for example, SLAM and the like), and transmits the position data to the fusion unit 1322 and the prediction unit 1324, the fusion unit 1322 receives the obstacle list and the current vehicle body position, generates a fused obstacle list through an algorithm (for example, KM algorithm and the like), transmits the obstacle data to the prediction unit 1324, the prediction unit 1324 receives the current vehicle body position and the obstacle list, generates an obstacle and a trajectory of the current and next 5 seconds after the current vehicle body position and the obstacle list, transmits the trajectory information to the prediction unit 1326, and the prediction unit 1312 transmits the vehicle body position and trajectory information to the prediction unit 1326 through an algorithm (for example, and a PID control unit, and the prediction unit, the vehicle-mounted storage unit 1312 receives the predicted obstacle list, the predicted vehicle body position and the road condition information of surrounding blocks, stores the predicted vehicle body position and the road condition information of the surrounding blocks into a cache, transmits the road condition information of the surrounding blocks to the planning unit 1325, transmits all data to the cloud communication unit 1211 and the unmanned aerial vehicle communication unit 1132 of the cloud subsystem 120 through the vehicle-mounted communication unit 1311, supplies power to the unmanned aerial vehicle delivery unit through the vehicle-mounted power supply unit, and the unmanned aerial vehicle delivery unit 1331 is responsible for wireless power supply for the unmanned aerial vehicle besides being responsible for delivery of the unmanned aerial vehicle.
Optionally, as shown in fig. 4, in another embodiment of the present invention, the cloud subsystem 120 includes: the cloud base module 121 comprises a cloud communication unit 1211 and a cloud storage unit 1212 connected in communication with the cloud communication unit 1211, wherein the cloud communication unit 1211 is connected in communication with the vehicle-mounted communication unit 1311 and is used for transmitting data information with the outside; the data arbitration module 122 is connected in communication with the cloud storage unit 1212, and is configured to arbitrate the obtained driving route planning of the vehicle. In other embodiments of the present invention, the cloud base module 121 may further include a cloud power unit, configured to supply power to a cloud server.
Specifically, in this embodiment, the cloud storage unit 1212 is configured to store data, for example, the ambient environment and obstacle information of the vehicle in a period of time may be stored in the storage unit, so as to be conveniently used as arbitration data and deep learning training data for subsequent viewing and invoking; the cloud communication unit 1211 is configured to perform data or signal transmission with the outside, and the cloud communication unit 1211 may directly upload the information about the surroundings and the obstacles of the vehicle to the cloud subsystem 120, and may also transmit the information about the surroundings and the obstacles of other intelligent driving vehicles to the own vehicle to perform path planning.
Wherein, the data arbitration module 122 further comprises: the data processing unit 1221 is connected to the cloud storage unit 1212 in a communication manner, and is configured to process the received data information; the wireless message processing unit 1222, which is communicatively connected to the data processing unit 1221 and the cloud storage unit 1212, and is configured to decode data information received by wireless transmission; and a danger arbitration unit 1223, which is connected to the data processing unit 1221 in a communication manner, and is used for arbitrating the planning of the driving path of the vehicle.
Specifically, in this embodiment, the data processing unit 1221 is configured to process the received environment and obstacle information; the wireless message processing unit 1222 is used for decoding the message received by wireless transmission, transmitting the message to the storage unit, adding code data and transmitting the data to the vehicle-mounted system; the danger arbitration unit 1223 arbitrates data obtained by data processing according to the surrounding environment and obstacle information of the plurality of intelligent driving vehicles, and can find and avoid dangers in advance.
In the cloud subsystem 120, data (for example, a list of obstacles detected by the vehicle, a pose of the vehicle, a position of the drone, a list of obstacles detected by the drone, etc.) transmitted by the vehicle communication unit 1311 in the vehicle-mounted subsystem 130 is received by the cloud communication unit 1211 and sent to the cloud storage unit 1212; the data transmitted by the cloud storage unit 1212 (i.e., the data related to the other vehicles) is received and sent to the vehicle-mounted communication unit 1311 in the vehicle-mounted subsystem 130, the cloud storage unit 1212 receives the data sent by the cloud communication unit 1211 and the data processing unit 1221 and sends the data to the wireless message processing unit 1222, the wireless message processing unit 1222 processes the received data into processable data and sends the processable data to the data processing unit 1221, the data processing unit 1221 processes (for example, screens, globalizes, and the like) the received vehicle data and sends the processed data to the cloud storage unit 1212 and the hazard arbitration unit 1223, and the hazard arbitration unit 1223 receives the vehicle data of the multiple vehicles, arbitrates the vehicle data, and sends an arbitration result to the data processing unit 1221.
As shown in fig. 5, a method for intelligent driving of a vehicle based on an unmanned aerial vehicle includes the following steps:
acquiring traffic information of a current road section of a vehicle;
receiving the traffic information, and acquiring traffic information of a road section near the own vehicle according to the traffic information;
and receiving the current road traffic information and the traffic information of nearby roads of the own vehicle, acquiring the driving path planning information of the own vehicle, and controlling the running state of the own vehicle.
The present invention realizes all or part of the processes of the above methods, and can also be implemented by a computer program instructing related hardware, where the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above method embodiments can be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution media, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, in accordance with legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunications signals.
Based on the same inventive concept, an embodiment of the present application further provides an electronic device, which includes a memory and a processor, where the memory stores a computer program running on the processor, and the processor executes the computer program to implement all or part of the method steps in the method.
The processor may be a Central Processing Unit (CP U), or may be other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (fpga) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center of the computer device and the various interfaces and lines connecting the various parts of the overall computer device.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the computer device by executing or executing the computer programs and/or modules stored in the memory, as well as by invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (e.g., a sound playing function, an image playing function, etc.); the storage data area may store data (e.g., audio data, video data, etc.) created according to the use of the cellular phone. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a flash memory Card (flash Card), at least one magnetic disk storage device, a flash memory device, or other volatile solid state storage device.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, server, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), servers, and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart 1 flow or flows and/or block 1 block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows of FIG. 1 and/or block diagram block or blocks of FIG. 1.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart 1 flow or flows and/or block 1 block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. The utility model provides a vehicle intelligence driving system based on unmanned aerial vehicle which characterized in that includes:
the unmanned aerial vehicle subsystem is used for acquiring traffic information of a current road section of a vehicle and acquiring position information of an unmanned aerial vehicle;
the cloud subsystem is used for acquiring traffic information of a road section near the self-vehicle according to the traffic information;
the vehicle-mounted subsystem is in communication connection with the unmanned aerial vehicle subsystem and the cloud subsystem and is used for receiving traffic information of a current road section and traffic information of a nearby road section of the self-vehicle, acquiring planning information of a driving path of the self-vehicle and controlling the running state of the self-vehicle;
the on-board subsystem includes:
the vehicle-mounted base module is in communication connection with the unmanned aerial vehicle subsystem and the cloud subsystem and is used for transmitting data information and storing the data information with the outside;
the intelligent driving module is in communication connection with the vehicle-mounted basic module and is used for acquiring the driving path planning information of the self-vehicle and controlling the running state of the self-vehicle;
the unmanned aerial vehicle releasing module is electrically connected with the vehicle-mounted basic module, comprises an unmanned aerial vehicle releasing unit and is used for controlling the releasing state of the unmanned aerial vehicle.
2. The drone-based vehicle smart driving system of claim 1, wherein the drone subsystem includes:
the remote control flight module is in communication connection with the unmanned aerial vehicle launching unit and is used for controlling launching and flight states of the unmanned aerial vehicle;
the sensing module is in communication connection with the remote control flight module and comprises a sensing unit used for acquiring real-time traffic information and acquiring barrier information in the driving direction of the vehicle according to the real-time traffic information;
the unmanned aerial vehicle basic module is in communication connection with the sensing module and the vehicle-mounted basic module and is used for receiving and storing the obstacle information and transmitting data with the outside;
wherein, the remote control flight module includes: the navigation unit is used for acquiring the position information of the unmanned aerial vehicle; the flight control unit is in communication connection with the navigation unit and is used for controlling the launching and flight processes of the unmanned aerial vehicle; and the power unit is in communication connection with the flight control unit and is used for providing lift force for the unmanned aerial vehicle.
3. The drone-based vehicle smart driving system of claim 2, wherein the drone base module includes:
the unmanned aerial vehicle storage unit is in communication connection with the sensing unit and is used for storing the obstacle information;
and the unmanned aerial vehicle communication unit is in communication connection with the unmanned aerial vehicle storage unit and is used for transmitting data information with the outside.
4. The drone-based vehicle smart driving system of claim 3, wherein the on-board base module includes:
the vehicle-mounted communication unit is in communication connection with the unmanned aerial vehicle communication unit and is used for transmitting data information with the outside;
and the vehicle-mounted storage unit is in communication connection with the vehicle-mounted communication unit and is used for storing data information.
5. The drone-based vehicle smart driving system of claim 4, wherein the smart driving module comprises:
the vehicle-mounted sensing unit is used for acquiring surrounding information of the vehicle on a driving path;
the fusion unit is in communication connection with the vehicle-mounted sensing unit and is used for fusing the obtained surrounding information to obtain real-time external information of the vehicle;
the positioning unit is in communication connection with the vehicle-mounted sensing unit and the fusion unit and is used for acquiring position information of the vehicle;
the prediction unit is in communication connection with the fusion unit and the positioning unit and is used for predicting external information and position information of the vehicle;
the planning unit is in communication connection with the prediction unit and the vehicle-mounted storage unit and is used for planning the driving path of the vehicle;
and the control unit is in communication connection with the planning unit and is used for controlling the running state of the self-vehicle according to the running path.
6. The drone-based vehicle smart driving system of claim 4, wherein the cloud subsystem comprises:
the cloud base module comprises a cloud communication unit and a cloud storage unit in communication connection with the cloud communication unit, and the cloud communication unit is in communication connection with the vehicle-mounted communication unit and is used for transmitting data information with the outside;
and the data arbitration module is in communication connection with the cloud storage unit and is used for planning and arbitrating the obtained driving path of the self-vehicle.
7. The drone-based vehicle smart driving system of claim 6, wherein the data arbitration module comprises:
the data processing unit is in communication connection with the cloud storage unit and used for processing the received data information;
the wireless message processing unit is in communication connection with the data processing unit and the cloud storage unit and is used for decoding data information received by wireless transmission;
and the danger arbitration unit is in communication connection with the data processing unit and is used for arbitrating the planning of the driving path of the self vehicle.
8. An intelligent vehicle driving method based on an unmanned aerial vehicle is characterized by comprising the following steps:
acquiring traffic information of a current road section of a vehicle;
receiving the traffic information, and acquiring traffic information of a road section near the own vehicle according to the traffic information;
and receiving the current road traffic information and the traffic information of nearby roads of the own vehicle, acquiring the driving path planning information of the own vehicle, and controlling the running state of the own vehicle.
9. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle intelligent driving method of claim 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110615111.3A CN113359724B (en) | 2021-06-02 | 2021-06-02 | Vehicle intelligent driving system and method based on unmanned aerial vehicle and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110615111.3A CN113359724B (en) | 2021-06-02 | 2021-06-02 | Vehicle intelligent driving system and method based on unmanned aerial vehicle and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113359724A CN113359724A (en) | 2021-09-07 |
| CN113359724B true CN113359724B (en) | 2023-02-24 |
Family
ID=77531323
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110615111.3A Active CN113359724B (en) | 2021-06-02 | 2021-06-02 | Vehicle intelligent driving system and method based on unmanned aerial vehicle and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113359724B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114783184A (en) * | 2022-04-19 | 2022-07-22 | 江苏大学 | Beyond-the-horizon sensing system based on information fusion of vehicle, road and unmanned aerial vehicle |
| CN115240450A (en) * | 2022-07-13 | 2022-10-25 | 购旺工业(赣州)有限公司 | Intelligent traffic data acquisition equipment and method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106340197A (en) * | 2016-08-31 | 2017-01-18 | 北京万集科技股份有限公司 | Auxiliary cooperative vehicle infrastructure driving system and method |
| CN107038885A (en) * | 2017-05-23 | 2017-08-11 | 奇瑞汽车股份有限公司 | Traffic reminding method and device |
| CN207540559U (en) * | 2017-12-05 | 2018-06-26 | 北京长城华冠汽车技术开发有限公司 | The unmanned plane road conditions prospecting device of vehicle and the road conditions shared system for vehicle group |
| CN109927660A (en) * | 2019-03-11 | 2019-06-25 | 汉腾汽车有限公司 | A kind of vehicle drive assist system based on unmanned plane |
| CN111256713A (en) * | 2020-03-20 | 2020-06-09 | 东风汽车集团有限公司 | Auxiliary method and auxiliary system for automatic driving of vehicle |
| CN112817307A (en) * | 2020-12-30 | 2021-05-18 | 广州大学 | Vehicle auxiliary driving system and method based on unmanned aerial vehicle road perception |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11006263B2 (en) * | 2016-07-07 | 2021-05-11 | Ford Global Technologies, Llc | Vehicle-integrated drone |
| CN109101013A (en) * | 2018-07-17 | 2018-12-28 | 知豆电动汽车有限公司 | A kind of electric car low speed automated driving system and method |
| KR20200017582A (en) * | 2018-07-26 | 2020-02-19 | 현대자동차주식회사 | System and method for assisting autonomous driving of vehicle using drone |
| KR20210026918A (en) * | 2019-09-02 | 2021-03-10 | 현대자동차주식회사 | Navigation system and method using drone |
| CN111489564A (en) * | 2020-04-23 | 2020-08-04 | 新石器慧通（北京）科技有限公司 | Driving method, device and system of unmanned vehicle |
| CN112258840A (en) * | 2020-10-23 | 2021-01-22 | 北京百度网讯科技有限公司 | Image acquisition control method, device, equipment and storage medium |
-
2021
- 2021-06-02 CN CN202110615111.3A patent/CN113359724B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106340197A (en) * | 2016-08-31 | 2017-01-18 | 北京万集科技股份有限公司 | Auxiliary cooperative vehicle infrastructure driving system and method |
| CN107038885A (en) * | 2017-05-23 | 2017-08-11 | 奇瑞汽车股份有限公司 | Traffic reminding method and device |
| CN207540559U (en) * | 2017-12-05 | 2018-06-26 | 北京长城华冠汽车技术开发有限公司 | The unmanned plane road conditions prospecting device of vehicle and the road conditions shared system for vehicle group |
| CN109927660A (en) * | 2019-03-11 | 2019-06-25 | 汉腾汽车有限公司 | A kind of vehicle drive assist system based on unmanned plane |
| CN111256713A (en) * | 2020-03-20 | 2020-06-09 | 东风汽车集团有限公司 | Auxiliary method and auxiliary system for automatic driving of vehicle |
| CN112817307A (en) * | 2020-12-30 | 2021-05-18 | 广州大学 | Vehicle auxiliary driving system and method based on unmanned aerial vehicle road perception |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113359724A (en) | 2021-09-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11157008B2 (en) | Autonomous vehicle routing using annotated maps | |
| CN107624155B (en) | Autonomous navigation system | |
| US20190146508A1 (en) | Dynamic vehicle routing using annotated maps and profiles | |
| US20180061242A1 (en) | Hybrid trip planning for autonomous vehicles | |
| CN110928284A (en) | Method, apparatus, medium, and system for assisting control of automatic driving of vehicle | |
| CN112714729A (en) | Vehicle path planning method and vehicle path planning device | |
| CN113359724B (en) | Vehicle intelligent driving system and method based on unmanned aerial vehicle and storage medium | |
| CN110928286A (en) | Method, apparatus, medium, and system for controlling automatic driving of vehicle | |
| CN110606070B (en) | Intelligent driving vehicle and braking method thereof, vehicle-mounted equipment and storage medium | |
| US11886187B1 (en) | Planner system recovery for autonomous vehicles | |
| US10836405B2 (en) | Continual planning and metareasoning for controlling an autonomous vehicle | |
| CN113479195A (en) | Method for automatic valet parking and system for carrying out said method | |
| CN110562269A (en) | Method for processing fault of intelligent driving vehicle, vehicle-mounted equipment and storage medium | |
| CN113859265A (en) | Reminding method and device in driving process | |
| CN112513951A (en) | Scene file acquisition method and device | |
| CN112654547A (en) | Driving reminding method, device and system | |
| US11904899B2 (en) | Limp home mode for an autonomous vehicle using a secondary autonomous sensor system | |
| CN115334109A (en) | System architecture, transmission method, vehicle, medium and chip for traffic signal identification | |
| EP4074562A1 (en) | Control system and control method for intelligent connected vehicle | |
| CN114691346A (en) | Configuration method and equipment of computing power resources | |
| US11801870B2 (en) | System for guiding an autonomous vehicle by a towing taxi | |
| CN112639910B (en) | Method and device for observing traffic elements | |
| US20240053742A1 (en) | Systems and methods for controlling a vehicle by teleoperation based on a speed limiter | |
| JP7444295B2 (en) | Processing equipment, processing method, processing program, processing system | |
| US20230398834A1 (en) | Emergency Heating System for Electric Vehicle (EV) Running out of Power |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20220124 Address after: 430000 No. n3010, 3rd floor, R & D building, building n, Artificial Intelligence Science Park, Wuhan Economic and Technological Development Zone, Hubei Province Applicant after: Lantu Automobile Technology Co.,Ltd. Address before: 430056 No. 1 Dongfeng Avenue, Wuhan economic and Technological Development Zone, Hubei, Wuhan Applicant before: Dongfeng Motor Corp. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |