WO2020238347A1 - 无人机搭乘路线处理方法、装置、设备及可读存储介质 - Google Patents

无人机搭乘路线处理方法、装置、设备及可读存储介质 Download PDF

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Publication number
WO2020238347A1
WO2020238347A1 PCT/CN2020/080154 CN2020080154W WO2020238347A1 WO 2020238347 A1 WO2020238347 A1 WO 2020238347A1 CN 2020080154 W CN2020080154 W CN 2020080154W WO 2020238347 A1 WO2020238347 A1 WO 2020238347A1
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WIPO (PCT)
Prior art keywords
candidate
boarding
route
vehicle
point
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PCT/CN2020/080154
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English (en)
French (fr)
Inventor
王凯斌
Original Assignee
北京京东尚科信息技术有限公司
北京京东世纪贸易有限公司
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Application filed by 北京京东尚科信息技术有限公司, 北京京东世纪贸易有限公司 filed Critical 北京京东尚科信息技术有限公司
Priority to JP2021563657A priority Critical patent/JP7271718B2/ja
Priority to EP20812904.9A priority patent/EP3951547A4/en
Publication of WO2020238347A1 publication Critical patent/WO2020238347A1/zh
Priority to US17/516,385 priority patent/US20220057814A1/en

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    • 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
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • 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
    • G05D1/0005—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots with arrangements to save energy
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C39/00—Aircraft not otherwise provided for
    • B64C39/02—Aircraft not otherwise provided for characterised by special use
    • B64C39/024—Aircraft not otherwise provided for characterised by special use of the remote controlled vehicle type, i.e. RPV
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • 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
    • G05D1/12—Target-seeking control
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
    • G08G1/207—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles with respect to certain areas, e.g. forbidden or allowed areas with possible alerting when inside or outside boundaries
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/003—Flight plan management
    • G08G5/0034—Assembly of a flight plan
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0043—Traffic management of multiple aircrafts from the ground
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/006—Navigation or guidance aids for a single aircraft in accordance with predefined flight zones, e.g. to avoid prohibited zones
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2201/00—UAVs characterised by their flight controls
    • B64U2201/10—UAVs characterised by their flight controls autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U80/00—Transport or storage specially adapted for UAVs
    • B64U80/80—Transport or storage specially adapted for UAVs by vehicles
    • B64U80/86—Land vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping

Definitions

  • the embodiments of the present application relate to the technical field of drones, and in particular, to a method, device, equipment, and readable storage medium for processing drone riding routes.
  • drones have begun to be used in the logistics field. At present, drones rely on their own power to transport packages and fly from the starting point to the destination according to the established flight route.
  • the embodiments of the application provide a method, device, equipment, and readable storage medium for processing drone riding routes to solve the problem of the limited battery capacity of drones in the prior art and the short distance that drones fly on their own power. problem.
  • One aspect of the embodiments of the present application is to provide a method for processing drone riding routes, including:
  • the candidate vehicles are determined
  • the drone is controlled to board at least one of the candidate boarding vehicles.
  • Another aspect of the embodiments of the present application is to provide a UAV boarding route processing device, including:
  • the vehicle selection module is used to determine candidate vehicles for boarding according to the autonomous flight route of the drone from the flight starting point to the flight end point;
  • the boarding route calculation module is used to determine the boarding flight route of the UAV according to the current position of each candidate boarding vehicle;
  • the boarding control module is configured to control the UAV to board at least one of the candidate boarding vehicles according to the boarding flight route.
  • Another aspect of the embodiments of the present application is to provide a UAV boarding route processing device, including:
  • a memory a processor, and a computer program stored on the memory and running on the processor,
  • Another aspect of the embodiments of the present application is to provide a computer-readable storage medium storing a computer program
  • the method, device, equipment, and readable storage medium for processing drone boarding routes determine candidate boarding vehicles according to the autonomous flight path of the drone from the flight starting point to the flight destination; The current position is used to determine the flight route of the drone; according to the flight route, the drone is controlled to take at least one of the candidate boarding vehicles from the flight starting point to the flight end point, achieving During the travel from the starting point of the flight to the end of the flight, the UAV greatly reduces the distance and time of the UAV flying on its own power by taking at least one vehicle, which greatly saves the UAV's power consumption and extends the UAV's transportation distance. .
  • FIG. 1 is a flowchart of a method for processing a drone boarding route provided by Embodiment 1 of the application;
  • FIG. 2 is a flowchart of a method for processing a drone boarding route provided in the second embodiment of the application
  • FIG. 3 is a schematic diagram of a drone boarding route provided in Embodiment 2 of this application.
  • FIG. 4 is a schematic structural diagram of a UAV boarding route processing device provided in Embodiment 3 of the application;
  • FIG. 5 is a schematic structural diagram of a UAV boarding route processing device provided in Embodiment 5 of the application.
  • Geo-fencing is a new application of LBS (Location Based Service), which uses a virtual fence to enclose a virtual geographic boundary.
  • LBS Location Based Service
  • the mobile terminal can receive automatic notification and warning information.
  • POI is the abbreviation of "Point of Interest", also known as “point of interest”.
  • a POI can be a house, a shop, a mailbox, a bus stop, etc.
  • Directed line segment Refers to the line segment that specifies the direction.
  • the direction of a directed line segment is the direction from one point to another point. At this time, the two end points of the directed line segment are in order. We call the previous point the starting point of the directed line segment, and the other point is called the end point of the directed line segment.
  • FIG. 1 is a flowchart of a method for processing a UAV boarding route provided in Embodiment 1 of the application.
  • the embodiments of the present application address the problem that the battery capacity of the drone in the prior art is limited and the distance that the drone travels on its own power is relatively short, and provides a method for processing the route taken by the drone.
  • the method in this embodiment is applied to a UAV boarding route processing device.
  • the UAV boarding route processing device may be a UAV, a UAV control device, or it may be used for flight control and management of the UAV In other embodiments, the method can also be applied to other devices.
  • a drone boarding route processing device is used as an example for schematic illustration. As shown in Figure 1, the specific steps of the method are as follows:
  • Step S101 According to the autonomous flight route of the drone from the flight start point to the flight end point, a candidate vehicle for boarding is determined.
  • This embodiment can be applied to the itinerary of the drone to transport the goods or the return itinerary after running the goods to the destination.
  • the starting point of the flight is the take-off location of the drone, and the end of the flight is the destination of the drone.
  • the starting point and ending point of the flight can be expressed in POI.
  • the starting point of the flight may be the starting point POI determined according to the latitude and longitude of the location before the drone takes off
  • the ending point of the flight may be the ending point POI determined according to the latitude and longitude of the drone site corresponding to the delivery address of the drone transported items.
  • the area within the specified width on both sides of the autonomous flight route of the drone can be taken as the specific geographic area according to the autonomous flight route of the drone, so as to determine the geography corresponding to this autonomous flight route.
  • fence and further from vehicles whose driving route is at least partly within the geo-fence, a vehicle whose driving speed meets a preset condition is selected as a candidate to board the vehicle.
  • the designated width can be calculated according to the autonomous flight route this time, or the designated width can be set by a technician according to actual application scenarios, which is not specifically limited in this embodiment.
  • the specified width may be a preset scale parameter multiplied by the length of the autonomous flight route, where the preset scale parameter may be set by a technician according to actual application scenarios, which is not specifically limited in this embodiment.
  • the preset condition that the driving speed meets is used to restrict the driving speed of the vehicle from being too fast or too slow, which can be set by a technician according to actual application scenarios and empirical values, which is not specifically limited in this embodiment.
  • the flight starting point, the flight end point and the autonomous flight route can also be displayed on the electronic map.
  • Step S102 Determine the flight route of the drone based on the current position of each candidate boarding vehicle.
  • the flight route of the drone can be determined.
  • the location of the geofence corresponding to the secondary autonomous flight route is used as the corresponding final departure point, and a candidate flight route is generated for each candidate boarding vehicle.
  • the drone takes only one vehicle, and the candidate boarding vehicle waits for the drone to board at its current location. After the drone has boarded the vehicle, the vehicle then travels along the driving route.
  • the first boarding point on the travel route of each candidate boarding vehicle may be the location on the travel route that is closest to the flight starting point of the drone; place these candidate boarding vehicles Leaving the location of the geo-fence corresponding to this autonomous flight route is used as the corresponding final departure point, and a candidate flight route is generated for each candidate boarding vehicle.
  • the drone takes only one vehicle, and the drone and the candidate boarding vehicle go to the first boarding point at the same time. If the drone arrives at the first boarding point first, the drone waits for the candidate boarding vehicle to arrive; The boarding vehicle arrives at the first boarding point first, and the candidate boarding vehicle waits for the drone to arrive. The drone gets on the vehicle at the first boarding point, and after the drone gets on the vehicle, the vehicle then travels along the driving route.
  • the candidate boarding vehicles After the candidate boarding vehicles are determined, calculate the candidate first boarding point and candidate final departure point on the travel route of each candidate boarding vehicle based on the current position of each candidate boarding vehicle; and according to the candidate first boarding point on the travel route of each candidate boarding vehicle
  • the boarding point and the candidate final departure point are used to calculate the candidate drone transfer route; further based on the candidate first boarding point, the candidate drone transfer route, and the driving of each candidate vehicle
  • the candidate final departure point on the route generates at least one candidate flight route; then, an optimal route is selected from the at least one candidate flight route as the flight route for the drone.
  • the drone can take one or more vehicles.
  • the candidate boarding vehicles After the candidate boarding vehicles are determined, calculate the candidate first boarding point and candidate final departure point on the travel route of each candidate boarding vehicle based on the current position, driving route and driving speed of each candidate boarding vehicle; The candidate first boarding point and the candidate final departure point on the driving route are used to calculate the candidate drone transfer route; further based on the candidate first boarding point and the candidate drone transfer route on the driving route of each candidate boarding vehicle, and The candidate final departure point on the driving route of each candidate boarding vehicle is generated to generate at least one candidate boarding flight route; then, an optimal route is selected from the at least one candidate boarding flight route as the flying route of the drone.
  • the UAV can take one or more vehicles.
  • This embodiment combines the travel route and speed of the candidate boarding vehicle to determine the UAV’s flight route, which can arrange the UAV’s flight more reasonably. Taking the flight route allows the drone to take the vehicle as much as possible, reducing the distance and time that the drone needs to fly with its own power.
  • Step S103 Control the drone to board at least one candidate boarding vehicle according to the boarding flight route.
  • control the drone After determining the flight route of the drone, control the drone to follow the flight route and take one or more candidate vehicles from the starting point of the flight to the end of the flight, so that the drone can take the vehicle to complete the trip.
  • the candidate boarding vehicle is determined according to the autonomous flight route of the drone from the flight starting point to the flight destination; the current location of each candidate boarding vehicle is used to determine the flying route of the drone;
  • the man-machine takes at least one candidate vehicle to travel from the starting point of the flight to the end of the flight.
  • the UAV can greatly reduce the distance and time of the UAV flying on its own power by boarding at least one vehicle. It greatly saves the power consumption of the drone and extends the distance of the drone.
  • FIG. 2 is a flowchart of a method for processing a drone boarding route provided in Embodiment 2 of the application
  • FIG. 3 is a schematic diagram of a drone boarding route provided in Embodiment 2 of this application.
  • the determination of the candidate boarding vehicle according to the autonomous flight route of the drone from the flight starting point to the flight end includes: according to the autonomous flight route of the drone from the flight starting point to the flight end Calculate the geo-fence corresponding to the autonomous flight route; obtain the vehicles whose current driving route is at least part of the geo-fence as the initial candidate vehicle; select the vehicles whose driving speed meets the preset conditions from the initial candidate vehicles as the candidate boarding vehicles.
  • the flight route of the drone is calculated based on the current position, travel route, and travel speed of each candidate boarding vehicle. It can be implemented in the following ways: according to the current position, driving route and driving speed of each candidate boarding vehicle, calculate the candidate first boarding point and candidate final departure point on the driving route of each candidate boarding vehicle; according to the driving of each candidate boarding vehicle The candidate first boarding point and candidate final departure point on the route are used to calculate the candidate drone transfer route; according to the candidate first boarding point and candidate last departure point on the driving route of each candidate boarding vehicle, and the candidate drone transfer Take the route, generate at least one candidate flight route. As shown in Figure 2, the specific steps of the method are as follows:
  • Step S201 Calculate the geofence corresponding to the autonomous flight route according to the autonomous flight route of the drone from the flight starting point to the flight destination.
  • the area within the specified width on both sides of the autonomous flight route of the drone can be regarded as the specific geographic area, so as to determine the geo-fence corresponding to the autonomous flight route this time. For example, if the specified width is 2km, the geofence corresponding to the autonomous flight route is the area within 2km on both sides of the autonomous flight route.
  • the virtual boundary of the geofence may include: a curve (or straight line) parallel to the autonomous flight path of the drone and separated by a specified width from the autonomous flight path, the vertical line of the autonomous flight path at the starting point of the flight, and the autonomous flight path at the end of the flight The boundary line enclosed by the vertical line at the
  • the designated width can be calculated according to the autonomous flight route this time, or the designated width can be set by a technician according to actual application scenarios, which is not specifically limited in this embodiment.
  • the specified width may be a preset scale parameter multiplied by the length of the autonomous flight route, where the preset scale parameter may be set by a technician according to actual application scenarios, which is not specifically limited in this embodiment.
  • the designated width can be one-half of the length of the autonomous flight path of the drone.
  • Step S202 Select a vehicle whose driving route is at least partially within the geofence as an initial candidate vehicle.
  • the driving route of the vehicle refers to the driving route of the vehicle from the current location to the destination location.
  • the current location of the vehicle and the destination location may be latitude and longitude values, or may be POI information determined by latitude and longitude values.
  • the driving route of the vehicle from the current position to the destination position may be calculated according to the current position and the destination position of the vehicle.
  • the current point POI and the destination POI of the vehicle can be generated according to the longitude and latitude of the current position of the vehicle and the longitude and latitude of the destination, and then the driving route of the vehicle from the current point POI to the destination POI can be calculated.
  • the current location, destination location, and driving route of each vehicle may be displayed on the electronic map.
  • the driving route of the vehicle if the driving route of the vehicle is not within the geofence at all, it means that the driving route of the vehicle deviates far from the autonomous flight route of the drone, and these vehicles will not be the target of the drone.
  • Step S203 From the initial candidate vehicles, a vehicle whose driving speed meets a preset condition is selected as a candidate for boarding.
  • the preset condition that the vehicle's traveling speed meets at least includes: the average traveling speed of the vehicle is greater than the first speed threshold.
  • the first speed threshold can be set by a technician according to actual needs, and this embodiment is not specifically limited here.
  • selecting a vehicle whose driving speed meets a preset condition from the initial candidate vehicles, as a candidate vehicle for boarding may also include:
  • the second speed threshold is the product of the preset ratio value and the average flight speed of the drone.
  • the preset ratio value can be set by a technician according to actual application scenarios and experience, and this implementation is not specifically limited here.
  • calculating the driving direction of the initial candidate vehicle in the geo-fenced area, the straight-line distance of the area, and the actual distance of the area can be implemented in the following ways:
  • the driving direction of the initial candidate vehicle in the geofence area is from the direction start point to the direction end point; the straight line distance of the area is the straight line length from the direction start point to the direction end point; the actual distance of the area is The actual travel length of the initial candidate vehicle along the travel route from the start of the direction to the end of the direction.
  • the direction starting point is the starting point of a part of the route within the geofence of the initial candidate vehicle; the direction end point is the ending point of the part of the route within the geofence of the initial candidate vehicle.
  • the starting point of the direction of the initial candidate vehicle in the geofence is: the current position of the initial candidate vehicle; If the current position is not in the geofence, the starting point of the initial candidate vehicle in the geofence is: the initial candidate vehicle travels along the driving route and enters the first point of the geofence.
  • the direction end point of the initial candidate vehicle in the geofence is: the destination location of the initial candidate vehicle; If the destination location is not within the geofence, the direction end point of the initial candidate vehicle in the geofence is: the initial candidate vehicle travels along the driving route and leaves the last point before the geofence.
  • the actual distance of the initial candidate vehicle in the geofence area divided by the average driving speed can be calculated to obtain the estimated travel time of the initial candidate vehicle within the geofence.
  • the linear distance of the initial candidate vehicle in the geofence area is divided by the estimated travel time to calculate the linear speed of the initial candidate vehicle in the geofence.
  • the autonomous flight direction of the drone from the starting point to the ending point can be determined; combined with the driving direction of the initial candidate vehicle in the geo-fenced area, the regional linear velocity and the The velocity component in the autonomous flight direction of the drone.
  • the autonomous flight direction of the drone is direction (EF) ⁇ ;
  • an initial candidate vehicle is in the geofence’s direction starting point and direction ending point Respectively A and B, the direction of the linear velocity of the initial candidate vehicle in the geofence area is (AB) ⁇ , and the component of the linear velocity of the initial candidate vehicle in the geofence in the direction (EF) ⁇ can be calculated , Get the velocity component of the regional linear velocity of the initial candidate vehicle in the autonomous flight direction of the UAV.
  • a vehicle with a speed component greater than the second speed threshold may be used as a candidate to board the vehicle.
  • Step S204 Calculate the candidate first boarding point and candidate final departure point on the traveling route of each candidate boarding vehicle based on the current position, driving route, and traveling speed of each candidate boarding vehicle.
  • the candidate first boarding point refers to the location point where the UAV directly flies to a vehicle from the flight starting point for the first boarding of this flight.
  • the candidate final departure point refers to the point where the UAV flies away from the current vehicle and directly flies to the end of the flight.
  • the candidate first boarding point on the travel route of each candidate boarding vehicle is calculated according to the current location, travel route, and travel speed of each candidate boarding vehicle, which can be specifically implemented in the following manner:
  • each candidate boarding vehicle calculates the candidate boarding point on the driving route of each candidate boarding vehicle. While the drone flies from the flight starting point to the candidate boarding point, each candidate boarding vehicle travels to the corresponding Candidates for boarding points. If there are multiple candidate boarding points on the route of a candidate boarding vehicle, calculate the UAV boarding and turning time corresponding to the multiple candidate boarding points, and use the candidate boarding point with the shortest UAV boarding and turning time as The candidate first boarding point on the route of the candidate boarding vehicle.
  • the UAV boarding-to-fly time refers to the time required for the UAV to fly from the flight starting point to the candidate boarding point.
  • the flight time of the drone from the starting point of flight to a certain point on the driving route of a certain candidate boarding vehicle is tn1
  • the candidate boarding vehicle travels from the current location to the location point.
  • the flight time of the drone from the starting point of flight to a certain point on the driving route of a candidate vehicle can be calculated by dividing the flying distance of the drone to the certain point by the average flying speed of the drone get.
  • the travel time of the candidate boarding vehicle from the current position to a certain location point can be obtained by dividing the distance of the candidate boarding vehicle from the current location to a certain location point by the average traveling speed of the candidate boarding vehicle.
  • a unique number is assigned to all the candidate boarding vehicles, the physical fence can be displayed on the electronic map, and the driving route of the candidate boarding vehicles in the physical fence can be displayed, and the candidate The unique number of the boarding vehicle marks the driving route.
  • the candidate boarding points are also filtered, which specifically includes: excluding not on autonomous flight routes
  • the candidate boarding points in the corresponding geo-fence are excluded from the candidate boarding points located at locations where the drone cannot be boarded.
  • the drone after determining the candidate boarding point on the driving route of each candidate boarding vehicle, if there are multiple candidate boarding points for the drone and a certain candidate boarding vehicle, select the drone to fly from the flight starting point to the candidate boarding point The candidate first boarding point with the shortest flight time of is used as the candidate first boarding point of the candidate vehicle.
  • the candidate first boarding point on the driving route of each candidate boarding vehicle may be displayed on the electronic map and marked with the unique number of the candidate boarding vehicle.
  • the candidate final departure point on the driving route of each candidate boarding vehicle is calculated, which can be implemented in the following ways:
  • the point closest to the end of the flight among the road sections where the drone is allowed to fly away on the driving route of each candidate boarding vehicle is taken as the candidate final departure point.
  • each candidate boarding vehicle can be looped, and the closest point to the end point of the drone flight in the driving route of each candidate boarding vehicle is set as the candidate on the driving route of each candidate boarding vehicle. Finally fly away from the point.
  • the candidate first boarding point on the driving route of each candidate boarding vehicle may be displayed on the electronic map and marked with the unique number of the candidate boarding vehicle.
  • the average flight speed of the drone can be derived from historical data based on current weather conditions (including sunny, rain, snow, fog, wind speed, etc.). Flight speed.
  • Step S205 Calculate the candidate drone transfer route based on the candidate first boarding point and the candidate final departure point on the travel route of each candidate boarding vehicle.
  • the UAV can ride on one or more vehicles when traveling from the starting point of the flight to the end of the flight.
  • the number of vehicles on board In the process of driving from the starting point of the flight to the end of the flight, if the number of vehicles on board is larger, the variable will be greater in the middle (for example, the vehicle is driving too fast or too slow, etc.).
  • the number of vehicles that the drone takes usually does not exceed the preset number during the journey from the starting point to the end of the flight.
  • the preset number of rides can be set by a technician according to actual application scenarios and experience, and this embodiment does not specifically limit it here.
  • the preset number of rides can be 3, and at this time, 2 candidate drone transfer routes can be calculated.
  • the candidate drone transfer route is calculated according to the candidate first boarding point and the candidate final departure point on the driving route of each candidate boarding vehicle, which can be implemented in the following ways:
  • the first candidate transfer route corresponding to the candidate first boarding point refers to:
  • the candidate first boarding point corresponds to the first midway departure point on the driving route, and the flight route to the first midway boarding point on the driving route of a candidate transfer object; each candidate boarding on the driving route that contains the candidate final departure point Vehicles are used as candidate transfer objects.
  • the second candidate transfer route corresponding to each first candidate transfer route is calculated.
  • the second candidate transfer route corresponding to the first candidate transfer route refers to:
  • the first midway boarding point of the transfer route corresponds to the second midway departure point on the travel route and the flight route to the second midway boarding point on the travel route of a candidate transfer object.
  • each candidate boarding vehicle of the candidate first boarding point may be included in the circular traveling route, and the first candidate transfer route corresponding to each candidate first boarding point. Then, each candidate boarding vehicle (including the candidate boarding vehicle whose travel route does not contain the candidate first boarding point) is looped, and the second candidate transfer route corresponding to the first candidate transfer route is calculated.
  • the process of determining the first halfway departure point and the first halfway boarding point of the first candidate transfer route is the same as calculating the second candidate transfer route corresponding to each first candidate transfer route.
  • the process of determining the second halfway departure point and the second halfway boarding point of the second candidate transfer route is the same, which can be implemented in the following ways:
  • the starting point of the directed line segment is the first movement point
  • the corresponding vehicle is the first vehicle that the drone will fly away.
  • the end of the directed line segment is the second moving point, and the corresponding vehicle is the second vehicle that the drone will transfer to.
  • the first vehicle is the vehicle currently boarded by the drone, and the second vehicle is another vehicle that can be used as a transfer object.
  • directed line segments meet the following conditions: the drone flies away from the first vehicle from the starting point of the directed line segment, and flies along the directed line segment. After time T, it reaches the end of the directed line segment. At this time, the second vehicle just drives to At the end of the directed line segment, the drone can take the second vehicle.
  • the starting point and the end point of a directed line segment can be used as a midway departure point and a midway boarding point, and the directed line segment can be used as a candidate transfer route.
  • T is the preset duration, which can be calculated according to the average flying speed of the drone, the average driving speed of the second vehicle, and the driving route of the second vehicle by using methods in the prior art, which will not be repeated in this embodiment .
  • the first moment can start from the moment the drone gets on the first vehicle, that is, the initial state of the starting point of the directed line segment is that the drone just got on the first vehicle.
  • the location of a vehicle According to the average driving speed of the first vehicle and the second vehicle, simulate the changes of the two directed line segments in the future, and select the directed line segment with the shortest length and all the directed line segments in the geofence, as the drone from The transfer route of the first vehicle to the second vehicle.
  • the starting point and the end point of the directed line segment are respectively used as the departure point and the midway boarding point.
  • the directed line segment is the first candidate transfer route corresponding to the candidate first boarding point where the drone takes the first vehicle.
  • the directed line segment corresponds to the first candidate transfer route for the drone to transfer to the first vehicle Second candidate transfer route.
  • Step S206 Generate at least one candidate flight route based on the candidate first boarding point and candidate final departure point on the travel route of each candidate boarding vehicle, and the candidate drone transfer route.
  • the candidate first boarding point and the candidate final departure point on the travel route of each candidate boarding vehicle calculated according to the above steps, and the candidate drone transfer route are combined into at least one candidate boarding flight route.
  • the candidate first boarding point, the first candidate transfer route corresponding to each candidate first boarding point, the second candidate transfer route corresponding to each first candidate transfer route, and the candidate final departure point calculated according to the above steps can be combined Make at least one candidate flight route.
  • the candidate flight route may not include the first candidate transfer route or the second candidate transfer route.
  • E and F represent the flight start and end points of the drone, respectively.
  • Route AB represents the travel route of the candidate boarding vehicle car1 in the geofence
  • route CD represents the location of the candidate boarding vehicle Car2 in the geofence.
  • Driving route I is the candidate first boarding point on the route of the candidate boarding vehicle car1
  • L is the candidate final departure point on the traveling route of the candidate boarding vehicle car1
  • M is the candidate first boarding point on the traveling route of the candidate boarding vehicle Car2
  • H It is the candidate final departure point on the route of the candidate boarding vehicle Car2.
  • a directed line segment (JK) ⁇ is the first candidate transfer route corresponding to the candidate first boarding point I on the route of car1.
  • the candidate flight routes for drones include at least:
  • Candidate flight route 1 (it can be represented by "EI-JK-HF”): the drone flies in the direction of EI from the starting point E.
  • EI-JK-HF the drone flies in the direction of EI from the starting point E.
  • car1 just arrives at point I, and the drone rides on car1 .
  • point J the UAV flies away from car1
  • JK the direction of JK to point K
  • car2 just arrives at point K.
  • the UAV transfers to car2 at point K.
  • point H the UAV flies away from car2 and heads to the end point F along the HF direction.
  • Candidate flight route 2 (it can be represented by "EI-LF"): the drone flies in the direction of EI from the flight starting point E. When the drone reaches point I, car1 just reaches point I, and the drone rides on car1. When car1 arrives at point L, the UAV flies away from car1 and heads to the end point F along LF.
  • Candidate flight route 3 (it can be represented by "EM-HF”): the drone flies along the EM direction from the flight starting point E. When the drone reaches point M, car2 just arrives at point M, and the drone rides on car2. When car2 arrives at point H, the drone flies away from car2 and heads to the end point F in the direction of LF.
  • EM-HF EM-HF
  • Step S207 Select one route from at least one candidate flight route as the flight route of the drone.
  • the candidate drone after generating at least one candidate flight route based on the candidate first boarding point and the candidate final departure point on the travel route of each candidate boarding vehicle, and the candidate drone transfer route, from at least one candidate boarding route One route is selected as the flight route of the drone.
  • the total travel time of at least one candidate flight route is calculated according to the average flight speed of the drone and the average travel speed of each candidate boarding vehicle; candidate flight routes whose total travel time is greater than the limited flight duration are excluded.
  • the total travel time of the candidate flight route includes the sum of the flight time of the drone and the time the drone takes the vehicle. It can be based on the candidate flight route, the average flight speed of the drone, and the vehicle's The average driving speed is calculated.
  • the limited flight duration can be calculated as follows:
  • Calculate the remaining time between the current time and the estimated time of arrival of the drone at the end of the flight obtain the maximum total time from the starting point of the drone to the end of the flight; use the minimum of the remaining time and the maximum total time as the drone The time limit for the flight from the starting point to the ending point.
  • the maximum total time for the drone to reach the end of the flight from the starting point of the flight this time can be set by the technician according to the requirements of the subsequent flight mission of the drone, and this embodiment is not specifically limited here.
  • Z is the final index value based on the candidate flight route
  • X is the total travel time of the candidate flight route
  • Y is the flight distance or flight time of the drone in the candidate flight route
  • the flight route of the drone can be displayed on the electronic map.
  • Step S208 Control the drone to take at least one candidate boarding vehicle to drive from the starting point of the flight to the end of the flight according to the flying route.
  • control the drone After determining the flight route of the drone, control the drone to follow the flight route and take one or more candidate vehicles from the starting point of the flight to the end of the flight, so that the drone can take the vehicle to complete the trip.
  • the driving speed and location of the next target vehicle that the drone will ride on are obtained in real time. Based on the average flight speed and location, update the location of the boarding point where the drone takes the target vehicle, and control the UAV to board the target vehicle based on the updated location of the boarding point.
  • the current position of the drone is taken as the new flight starting point, and the method provided in this embodiment is adopted.
  • the straight line from the current position to the end of the flight is used as the new autonomous flight route of the drone, the geofence is updated according to the new autonomous flight route, and the flight route of the drone is recalculated.
  • the candidate boarding vehicle is determined according to the autonomous flight route of the drone from the flight starting point to the flying destination; according to the current position, driving route and driving speed of each candidate boarding vehicle, the flying route of the drone is calculated; According to the flight route, the drone is controlled to take at least one candidate boarding vehicle to travel from the starting point to the end of the flight. During the period from the starting point to the end of the flight, the drone can greatly reduce the drone's dependence on itself by taking at least one vehicle. The distance and time of powered flight greatly saves the power consumption of the drone and extends the transportation distance of the drone.
  • FIG. 4 is a schematic structural diagram of a UAV boarding route processing device provided in Embodiment 3 of the application.
  • the UAV boarding route processing device provided in the embodiment of the present application can execute the processing flow provided in the embodiment of the UAV boarding route processing method embodiment.
  • the UAV boarding route processing device 40 includes a vehicle selection module 401, a boarding route calculation module 402, and a boarding control module 403.
  • the vehicle selection module 401 is configured to determine the candidate vehicle for boarding according to the autonomous flight route of the drone from the flight start point to the flight end point.
  • the boarding route calculation module 402 is used to determine the flying route of the drone according to the current location of each candidate boarding vehicle.
  • the boarding control module 403 is used to control the UAV to board at least one candidate boarding vehicle from the starting point of the flight to the end of the flight according to the flying route.
  • the device provided in the embodiment of the present application may be specifically used to execute the method embodiment provided in the foregoing embodiment 1, and the specific functions are not described herein again.
  • the candidate boarding vehicle is determined according to the autonomous flight route of the drone from the flight starting point to the flight destination; the current location of each candidate boarding vehicle is used to determine the flying route of the drone;
  • the man-machine takes at least one candidate vehicle to travel from the starting point of the flight to the end of the flight.
  • the UAV can greatly reduce the distance and time of the UAV flying on its own power by boarding at least one vehicle. It greatly saves the power consumption of the drone and extends the distance of the drone.
  • the vehicle selection module is also used for:
  • the vehicle selection module is also used to:
  • the vehicle selection module is also used to:
  • the driving direction of the initial candidate vehicle in the geofence area is from the direction start point to the direction end point; the straight line distance of the area is the straight line length from the direction start point to the direction end point; the actual distance of the area is The actual travel length of the initial candidate vehicle along the travel route from the start of the direction to the end of the direction.
  • the direction starting point is the starting point of a part of the route within the geofence of the initial candidate vehicle; the direction end point is the ending point of the part of the route within the geofence of the initial candidate vehicle.
  • the second speed threshold is the product of the preset ratio value and the average flight speed of the drone.
  • the riding route calculation module is also used to:
  • the flying route of the drone is determined.
  • the riding route calculation module is also used to:
  • each candidate boarding vehicle calculates the candidate first boarding point and candidate final departure point on the driving route of each candidate boarding vehicle; according to the candidate first boarding point on the driving route of each candidate boarding vehicle Calculate the candidate UAV transfer route with the candidate final departure point; According to the candidate first boarding point and candidate final departure point on the driving route of each candidate boarding vehicle, and the candidate UAV transfer route, generate at least one candidate Take the flight route.
  • the riding route calculation module is also used to:
  • the first candidate transfer route corresponding to the candidate first boarding point refers to:
  • the candidate first boarding point corresponds to the first midway departure point on the driving route, and the flight route to the first midway boarding point on the driving route of a candidate transfer object; each candidate boarding on the driving route that contains the candidate final departure point Vehicles are used as candidate transfer objects.
  • the second candidate transfer route corresponding to each first candidate transfer route is calculated.
  • the second candidate transfer route corresponding to the first candidate transfer route refers to:
  • the first midway boarding point of the transfer route corresponds to the second midway departure point on the travel route and the flight route to the second midway boarding point on the travel route of a candidate transfer object.
  • the riding route calculation module is also used to:
  • each candidate boarding vehicle calculates the candidate boarding point on the driving route of each candidate boarding vehicle. While the drone flies from the flight starting point to the candidate boarding point, each candidate boarding vehicle travels to the corresponding Candidate boarding points; if there are multiple candidate boarding points on the driving route of a candidate boarding vehicle, calculate the UAV boarding and turning time corresponding to the multiple candidate boarding points, and minimize the corresponding UAV boarding and turning time
  • the candidate boarding point of is used as the candidate first boarding point on the driving route of the candidate boarding vehicle; wherein the UAV boarding and turning time refers to the time required for the UAV to fly from the flight starting point to the candidate boarding point.
  • the riding route calculation module is also used to:
  • the riding route calculation module is also used to:
  • the point closest to the end of the flight among the road sections where the drone is allowed to fly away on the driving route of each candidate boarding vehicle is taken as the candidate final departure point.
  • the riding route calculation module is also used to:
  • the average flight speed of the drone and the average travel speed of each candidate boarding vehicle calculate the total travel time of at least one candidate boarding flight route; exclude candidate boarding flight routes whose total travel time is greater than the flight limit time.
  • the riding route calculation module is also used to:
  • the boarding control module is also used to:
  • the device provided in the embodiment of the present application may be specifically used to execute the method embodiment provided in the second embodiment above, and the specific functions are not repeated here.
  • the candidate boarding vehicle is determined according to the autonomous flight route of the drone from the flight starting point to the flying destination; according to the current position, driving route and driving speed of each candidate boarding vehicle, the flying route of the drone is calculated; According to the flight route, the drone is controlled to take at least one candidate boarding vehicle to travel from the starting point to the end of the flight. During the period from the starting point to the end of the flight, the drone can greatly reduce the drone's dependence on itself by taking at least one vehicle. The distance and time of powered flight greatly saves the power consumption of the drone and extends the transportation distance of the drone.
  • FIG. 5 is a schematic structural diagram of a UAV boarding route processing device provided in Embodiment 5 of the application.
  • the UAV boarding route processing device 50 includes a processor 501, a memory 502, and a computer program stored in the memory 502 and executable by the processor 501.
  • the candidate boarding vehicle is determined according to the autonomous flight route of the drone from the flight starting point to the flight destination; the current location of each candidate boarding vehicle is used to determine the flying route of the drone;
  • the man-machine takes at least one candidate vehicle to travel from the starting point of the flight to the end of the flight.
  • the UAV can greatly reduce the distance and time of the UAV flying on its own power by boarding at least one vehicle. It greatly saves the power consumption of the drone and extends the distance of the drone.
  • an embodiment of the present application also provides a computer-readable storage medium that stores a computer program, and when the computer program is executed by a processor, it implements the drone riding route processing method provided by any of the foregoing method embodiments.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components can be combined or It can be integrated into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit may be implemented in the form of hardware, or may be implemented in the form of hardware plus software functional units.
  • the above-mentioned integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium.
  • the above-mentioned software functional unit is stored in a storage medium and includes several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor execute the method described in the various embodiments of the present application. Part of the steps.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program code .

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Abstract

一种无人机搭乘路线处理方法、装置、设备及可读存储介质。通过根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆（S101）；根据各候选搭乘车辆的当前位置，确定无人机的搭乘飞行路线（S102）；根据搭乘飞行路线，控制无人机搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点（S103），实现了在由飞行起点行驶到飞行终点期间，无人机通过搭乘至少一个车辆大大减少无人机依靠自身动力飞行的路程和时间，大大节省了无人机电量消耗，延长了无人机的运送距离。

Description

无人机搭乘路线处理方法、装置、设备及可读存储介质
本申请要求于2019年05月28日提交中国专利局、申请号为201910452768.5、申请名称为“无人机搭乘路线处理方法、装置、设备及可读存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请实施例涉及无人机技术领域，尤其涉及一种无人机搭乘路线处理方法、装置、设备及可读存储介质。
背景技术
随着无人机技术的发展，无人机已经开始应用于物流领域。目前，无人机运送包裹飞行都是依靠自身动力、从起点按照既定飞行路线飞往终点。
但是，通常的运送路线都较长，无人机的电池容量有限，无人机依靠自身动力飞行的路程较短，无法完成某些较长运送路线的单程或者往返的行程。
发明内容
本申请实施例提供一种无人机搭乘路线处理方法、装置、设备及可读存储介质，用以解决现有技术中无人机电池容量有限，无人机依靠自身动力飞行的路程较短的问题。
本申请实施例的一个方面是提供一种无人机搭乘路线处理方法，包括：
根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；
根据各候选搭乘车辆的当前位置，确定所述无人机的搭乘飞行路线；
根据所述搭乘飞行路线，控制所述无人机搭乘至少一个所述候选搭乘车辆。
本申请实施例的另一个方面是提供一种无人机搭乘路线处理装置，包括：
车辆选择模块，用于根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；
搭乘路线计算模块，用于根据各候选搭乘车辆的当前位置，确定所述无人机的搭乘飞行路线；
搭乘控制模块，用于根据所述搭乘飞行路线，控制所述无人机搭乘至少一个所述候选搭乘车辆。
本申请实施例的另一个方面是提供一种无人机搭乘路线处理设备，包括：
存储器，处理器，以及存储在所述存储器上并可在所述处理器上运行的计算机程序，
所述处理器运行所述计算机程序时实现上述所述的无人机搭乘路线处理方法。
本申请实施例的另一个方面是提供一种计算机可读存储介质，存储有计算机程序，
所述计算机程序被处理器执行时实现上述所述的无人机搭乘路线处理方法。
本申请实施例提供的无人机搭乘路线处理方法、装置、设备及可读存储介质，通过根 据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；根据各候选搭乘车辆的当前位置，确定所述无人机的搭乘飞行路线；根据所述搭乘飞行路线，控制所述无人机搭乘至少一个所述候选搭乘车辆由所述飞行起点行驶到达所述飞行终点，实现了在由飞行起点行驶到所述飞行终点期间，无人机通过搭乘至少一个车辆大大减少无人机依靠自身动力飞行的路程和时间，大大节省了无人机电量消耗，延长了无人机的运送距离。
附图说明
图1为本申请实施例一提供的无人机搭乘路线处理方法流程图；
图2为本申请实施例二提供的无人机搭乘路线处理方法流程图；
图3为本申请实施例二提供的无人机搭乘路线示意图；
图4为本申请实施例三提供的无人机搭乘路线处理装置的结构示意图；
图5为本申请实施例五提供的无人机搭乘路线处理设备的结构示意图。
通过上述附图，已示出本申请明确的实施例，后文中将有更详细的描述。这些附图和文字描述并不是为了通过任何方式限制本申请实施例构思的范围，而是通过参考特定实施例为本领域技术人员说明本申请的概念。
具体实施方式
这里将详细地对示例性实施例进行说明，其示例表示在附图中。下面的描述涉及附图时，除非另有表示，不同附图中的相同数字表示相同或相似的要素。以下示例性实施例中所描述的实施方式并不代表与本申请实施例相一致的所有实施方式。相反，它们仅是与如所附权利要求书中所详述的、本申请实施例的一些方面相一致的装置和方法的例子。
首先对本申请实施例所涉及的名词进行解释：
地理围栏(Geo-fencing)：是LBS(Location Based Service，基于位置服务)的一种新应用，就是用一个虚拟的栅栏围出一个虚拟的地理边界。当手机等移动终端进入、离开地理围栏内的地理区域，或在该区域内活动时，移动终端可以接收到自动通知和警告信息。
POI：是“Point of Interest”的缩写，也称为“兴趣点”。在地图中，一个POI可以是一栋房子、一个商铺、一个邮筒、一个公交站等。
有向线段：是指规定了方向的线段。有向线段的方向是从一点到另一点的指向，这时有向线段的两个端点有顺序，我们把前一点叫做有向线段的起点，另一点叫做有向线段的终点。
此外，术语“第一”、“第二”等仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。在以下各实施例的描述中，“多个”的含义是两个以上，除非另有明确具体的限定。
下面这几个具体的实施例可以相互结合，对于相同或相似的概念或过程可能在某些实施例中不再赘述。下面将结合附图，对本申请的实施例进行描述。
实施例一
图1为本申请实施例一提供的无人机搭乘路线处理方法流程图。本申请实施例针对现有技术中无人机电池容量有限，无人机依靠自身动力飞行的路程较短的问题，提供了无人机搭乘路线处理方法。本实施例中的方法应用于无人机搭乘路线处理设备，该无人机搭乘 路线处理设备可以是无人机，无人机控制设备，也可以是用于对无人机进行飞行控制与管理的服务器等，在其他实施例中，该方法还可应用于其他设备，本实施例以无人机搭乘路线处理设备为例进行示意性说明。如图1所示，该方法具体步骤如下：
步骤S101、根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆。
本实施例中，首先获取在不搭乘任何车辆时、无人机由飞行起点到飞行终点的自主飞行路线。本实施例可以应用于无人机前往运送物品的行程或者运行物品到目的地后的返回行程。
其中，飞行起点是无人机的起飞地点，飞行终点是无人机的目的地。
可选的，飞行起点和飞行终点可以采用POI的方式表示。例如，飞行起点可以是根据无人机起飞前所在地点的经纬度确定的起点POI，飞行终点可以是根据无人机运送物品的收货地址对应的无人机站点的经纬度确定的终点POI。
在确定无人机的自主飞行路线之后，可以根据无人机的自主飞行路线，将无人机自主飞行路线两侧指定宽度内的区域作为特定地理区域，从而确定本次自主飞行路线对应的地理围栏；并进一步地从行驶路线至少部分在该地理围栏内的车辆中，选取行驶速度满足预设条件的车辆，作为候选搭乘车辆。
其中，指定宽度可以根据本次的自主飞行路线计算得到，或者，指定宽度可以由技术人员根据实际应用场景进行设定，本实施例此处不做具体限定。
例如，指定宽度可以为预设比例参数乘以自主飞行路线的长度，其中预设比例参数可以由技术人员根据实际应用场景进行设定，本实施例此处不做具体限定。
其中，行驶速度满足的预设条件用于限制车辆的行驶速度不会过快或者过慢，可以由技术人员根据实际应用场景和经验值进行设定，本实施例此处不做具体限定。
另外，在确定无人机由飞行起点到飞行终点的自主飞行路线之后还可以将飞行起点、飞行终点以及自主飞行路线在电子地图上显示。
步骤S102、根据各候选搭乘车辆的当前位置，确定无人机的搭乘飞行路线。
在确定候选搭乘车辆之后，根据各候选搭乘车辆的当前位置，可以确定无人机的搭乘飞行路线。
示例性地，该步骤的另一种可行的实施方式为：
计算各候选搭乘车辆与无人机飞行起点之间的距离，将与无人机飞行起点的距离小于预设距离值的候选搭乘车辆的当前位置作为首次搭乘点，将这些候选搭乘车辆驶离本次自主飞行路线对应的地理围栏的位置作为对应的最后飞离点，针对每个候选搭乘车辆生成一条候选搭乘飞行路线。
这种实施方式中，无人机仅搭乘一辆车辆，候选搭乘车辆在当前位置等待无人机前往搭乘，待无人机搭乘上车辆后，车辆再沿行驶路线行驶。
示例性地，该步骤的另一种可行的实施方式为：
确定各候选搭乘车辆的行驶路线上的首次搭乘点，其中，各候选搭乘车辆的行驶路线上的首次搭乘点可以是该行驶路线上距离无人机的飞行起点最近的位置；将这些候选搭乘车辆驶离本次自主飞行路线对应的地理围栏的位置作为对应的最后飞离点，针对每个候选搭乘车辆生成一条候选搭乘飞行路线。
这种实施方式中，无人机仅搭乘一辆车辆，无人机和候选搭乘车辆同时前往首次搭乘 点，如果无人机先到达首次搭乘点，则无人机等待候选搭乘车辆到达；如果候选搭乘车辆先到达首次搭乘点，则候选搭乘车辆等待无人机到达。无人机在首次搭乘点搭乘车辆，待无人机搭乘上车辆后，车辆再沿行驶路线行驶。
示例性地，该步骤的另一种可行的实施方式为：
在确定候选搭乘车辆之后，根据各候选搭乘车辆的当前位置，计算各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点；并根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线；进一步地根据各候选搭乘车辆的行驶路线上的候选首次搭乘点，候选无人机转乘路线，和各候选搭乘车辆的行驶路线上的候选最后飞离点，生成至少一条候选搭乘飞行路线；然后，从至少一条候选搭乘飞行路线中选取一条最优的路线，作为无人机的搭乘飞行路线。
这种实施方式中，无人机可以搭乘一辆或者多辆车辆。
示例性地，该步骤的一种可行的实施方式为：
在确定候选搭乘车辆之后，根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点；并根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线；进一步地根据各候选搭乘车辆的行驶路线上的候选首次搭乘点，候选无人机转乘路线，和各候选搭乘车辆的行驶路线上的候选最后飞离点，生成至少一条候选搭乘飞行路线；然后，从至少一条候选搭乘飞行路线中选取一条最优的路线，作为无人机的搭乘飞行路线。
这种实施方式中，无人机可以搭乘一辆或者多辆车辆，这种实施方式结合候选搭乘车辆的行驶路线和速度，确定无人机的搭乘飞行路线，可以更加合理地安排无人机的搭乘飞行路线，使得无人机尽量搭乘车辆，减少无人机依靠自身动力飞行的路程和时间。
步骤S103、根据搭乘飞行路线，控制无人机搭乘至少一个候选搭乘车辆。
在确定无人机的搭乘飞行路线之后，控制无人机按照搭乘飞行路线，搭乘一个或者多个候选搭乘车辆由飞行起点行驶到达飞行终点，从而实现无人机搭乘车辆完成本次行程。
本申请实施例通过根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；根据各候选搭乘车辆的当前位置，确定无人机的搭乘飞行路线；根据搭乘飞行路线，控制无人机搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点，实现了在由飞行起点行驶到飞行终点期间，无人机通过搭乘至少一个车辆大大减少无人机依靠自身动力飞行的路程和时间，大大节省了无人机电量消耗，延长了无人机的运送距离。
实施例二
图2为本申请实施例二提供的无人机搭乘路线处理方法流程图；图3为本申请实施例二提供的无人机搭乘路线示意图。在上述实施例一的基础上，本实施例中，根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆，包括：根据无人机由飞行起点到飞行终点的自主飞行路线，计算自主飞行路线对应的地理围栏；获取当前行驶路线至少部分在地理围栏内的车辆，作为初始候选车辆；从初始候选车辆中筛选出行驶速度满足预设条件的车辆，作为候选搭乘车辆。另外，本实施例中，根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算得到无人机的搭乘飞行路线。具体可以采用如下方式实现：根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上 的候选首次搭乘点和候选最后飞离点；根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线；根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，以及候选无人机转乘路线，生成至少一条候选搭乘飞行路线。如图2所示，该方法具体步骤如下：
步骤S201、根据无人机由飞行起点到飞行终点的自主飞行路线，计算自主飞行路线对应的地理围栏。
本实施例中，可以根据无人机的自主飞行路线，将无人机自主飞行路线两侧指定宽度内的区域作为特定地理区域，从而确定本次自主飞行路线对应的地理围栏。例如指定宽度为2km，则自主飞行路线对应的地理围栏为自主飞行路线两侧2km宽度内的区域。
例如，地理围栏的虚拟边界可以包括：与无人机自主飞行路线平行并且与自主飞行路线相隔指定宽度的曲线(或直线)，自主飞行路线在飞行起点处的垂直线，自主飞行路线在飞行终点处的垂直线围成的边界线。
其中，指定宽度可以根据本次的自主飞行路线计算得到，或者，指定宽度可以由技术人员根据实际应用场景进行设定，本实施例此处不做具体限定。
可选的，例如，指定宽度可以为预设比例参数乘以自主飞行路线的长度，其中预设比例参数可以由技术人员根据实际应用场景进行设定，本实施例此处不做具体限定。例如，指定宽度可以为无人机自主飞行路线长度的二分之一。
步骤S202、选取行驶路线至少部分在地理围栏内的车辆，作为初始候选车辆。
该步骤中，首先获取具有载乘无人机能力的正在行驶的车辆的实时数据，包括：平均行驶速度、当前位置、目的地位置、以及行驶路线。其中，车辆的行驶路线是指车辆从当前位置行驶至目的地位置的行驶路线。
车辆当前位置和目的地位置可以是经纬度值，或者可以是经纬度值确定的POI信息。
可选的，可以在获取到车辆的当前位置和目的地位置之后，根据车辆的当前位置和目的地位置计算得到车辆从当前位置行驶至目的地位置的行驶路线。
例如，可以根据车辆的当前位置的经纬度和目的地的经纬度，生成车辆当前点POI和目的地POI，然后计算车辆从当前点POI到目的地POI的行驶路线。
可选的，在确定个车辆的行驶路线之后，可以将各车辆的当前位置、目的地位置和行驶路线显示在电子地图上。
本实施例中，若车辆的行驶路线完全不在地理围栏内，则说明车辆的行驶路线偏离无人机的自主飞行路线较远，这些车辆将无法作为无人机的搭乘对象。
该步骤中，根据各车辆的行驶路线，筛选出至少部分行驶路线在地理围栏内的车辆，作为初始候选车辆。
步骤S203、从初始候选车辆中筛选出行驶速度满足预设条件的车辆，作为候选搭乘车辆。
该步骤中，筛选候选搭乘车辆时，车辆的行驶速度满足的预设条件至少包括：车辆的平均行驶速度大于第一速度阈值。
其中，第一速度阈值可以由技术人员根据实际需要进行设定，本实施例此处不做具体限定。
进一步的，从初始候选车辆中筛选出行驶速度满足预设条件的车辆，作为候选搭乘车 辆，还可以包括：
计算初始候选车辆在地理围栏的区域行驶方向、区域直线路程和区域实际路程；根据初始候选车辆在地理围栏的区域实际路程，以及平均行驶速度，计算初始候选车辆在地理围栏内的预计行驶时间；根据初始候选车辆在地理围栏内的预计行驶时间，以及初始候选车辆在地理围栏的区域直线路程，计算初始候选车辆在地理围栏内的区域直线速度；根据初始候选车辆在地理围栏的区域行驶方向，计算初始候选车辆的区域直线速度、在无人机的自主飞行方向上的速度分量；将速度分量大于第二速度阈值的车辆，作为候选搭乘车辆。
其中，第二速度阈值为预设比例值与无人机的平均飞行速度的乘积，预设比例值可以由技术人员根据实际应用场景和经验进行设定，本实施此处不做具体限定。
具体的，计算初始候选车辆在地理围栏的区域行驶方向、区域直线路程和区域实际路程，可以采用如下方式实现：
确定初始候选车辆在地理围栏内的方向起点和方向终点；初始候选车辆在地理围栏的区域行驶方向由方向起点指向方向终点；区域直线路程为由方向起点到方向终点的直线长度；区域实际路程为初始候选车辆沿行驶路线由方向起点到方向终点的实际行驶长度。
其中，方向起点为初始候选车辆的行驶路线中、在地理围栏内的部分路线的起始点；方向终点为初始候选车辆的行驶路线中、在地理围栏内的部分路线的终止点。
具体的，根据初始候选车辆的当前位置，若初始候选车辆的当前位置在地理围栏内，则该初始候选车辆在地理围栏内的方向起点为：该初始候选车辆的当前位置；若初始候选车辆的当前位置不在地理围栏内，则该初始候选车辆在地理围栏内的方向起点为：该初始候选车辆沿行驶线路行驶进入地理围栏的第一点。
根据初始候选车辆的目的地位置，若初始候选车辆的目的地位置在地理围栏内，则该初始候选车辆在地理围栏内的方向终点为：该初始候选车辆的目的地位置；若初始候选车辆的目的地位置不在地理围栏内，则该初始候选车辆在地理围栏内的方向终点为：该初始候选车辆沿行驶线路行驶离开地理围栏前的最后一点。
进一步的，初始候选车辆在地理围栏的区域实际路程除以平均行驶速度，可以计算得到初始候选车辆在地理围栏内的预计行驶时间。
根据初始候选车辆在地理围栏内的预计行驶时间，用初始候选车辆在地理围栏的区域直线路程除以该预计行驶时间，可以计算初始候选车辆在地理围栏内的区域直线速度。
根据无人机的飞行起点和飞行终点，可以确定由飞行起点指向飞行终点的无人机的自主飞行方向；结合初始候选车辆在地理围栏的区域行驶方向，计算初始候选车辆的区域直线速度、在无人机的自主飞行方向上的速度分量。
例如，假设无人机的飞行起点和飞行终点分别用E和F表示，则无人机的自主飞行方向为方向(EF) →；假设某一初始候选车辆在地理围栏内的方向起点和方向终点分别为A和B，则该初始候选车辆在地理围栏内的区域直线速度的方向为(AB) →，可以计算出该初始候选车辆在地理围栏内的区域直线速度在方向(EF) →的分量，得到该初始候选车辆的区域直线速度在无人机的自主飞行方向上的速度分量。
进一步的，可以将速度分量大于第二速度阈值的车辆，作为候选搭乘车辆。
步骤S204、根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点。
其中，候选首次搭乘点指的是无人机从飞行起点直接飞往某一车辆进行本次飞行的第一次搭乘的位置点。
候选最后飞离点指的是无人机飞离当前搭乘的车辆直接飞往飞行终点时的位置点。
本实施例中，根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选首次搭乘点，具体可以采用如下方式实现：
根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选搭乘点，无人机从飞行起点飞至候选搭乘点的同时，各候选搭乘车辆行驶至对应的候选搭乘点。若一候选搭乘车辆的行驶路线上有多个候选搭乘点，则计算该多个候选搭乘点对应的无人机搭乘转飞时间，将对应的无人机搭乘转飞时间最短的候选搭乘点作为该候选搭乘车辆的行驶路线上的候选首次搭乘点。
其中，无人机搭乘转飞时间是指无人机从飞行起点飞至该候选搭乘点所需的时间。
例如，假设从当前时刻起，无人机从飞行起点飞到某一候选搭乘车辆的行驶路线上的某一位置点的飞行时间为tn1，该候选搭乘车辆从当前位置行驶到该位置点的行驶时间为tn2，若tn1＝tn2，则该位置点就是无人机搭乘该候选搭乘车辆的一个候选搭乘点。
另外，无人机从飞行起点飞到某一候选搭乘车辆的行驶路线上的某一位置点的飞行时间，可以通过无人机到该某点的飞行距离除以无人机的平均飞行速度计算得到。
候选搭乘车辆从当前位置行驶到某一位置点的行驶时间，可以通过候选搭乘车辆从当前位置行驶到某一位置点路程除以该候选搭乘车辆的平均行驶速度得到。
可选的，根据步骤S203中确定的候选搭乘车辆，给所有的候选搭乘车辆分配唯一编号，可以在电子地图上显示物理围栏，并显示物理围栏内的候选搭乘车辆的行驶路线，并可以用候选搭乘车辆的唯一编号对行驶路线进行标记。
优选地，在根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选搭乘点之后，还对候选搭乘点进行筛选，具体包括：剔除不在自主飞行路线对应的地理围栏内的候选搭乘点，剔除位于无人机无法搭乘位置的候选搭乘点。
进一步地，在确定各候选搭乘车辆的行驶路线上的候选搭乘点之后，如果无人机与某一个候选搭乘车辆的候选搭乘点有多个，则选取无人机从飞行起点飞到候选搭乘点的飞行时间最短的候选首次搭乘点，作为该候选搭乘车辆的候选首次搭乘点。
可选的，可以将各候选搭乘车辆的行驶路线上的候选首次搭乘点在电子地图上显示，并用候选搭乘车辆的唯一编号进行标记。
该步骤中，根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选最后飞离点，具体可以采用如下方式实现：
将各候选搭乘车辆的行驶路线上的允许无人机飞离的路段中、距离飞行终点最近的点作为候选最后飞离点。
具体地，可以循环各候选搭乘车辆，将各候选搭乘车辆的行驶路线中允许无人机飞离的路段中、离无人机飞行终点最近的点，作为各候选搭乘车辆的行驶路线上的候选最后飞离点。
可选的，可以将各候选搭乘车辆的行驶路线上的候选首次搭乘点在电子地图上显示，并用候选搭乘车辆的唯一编号进行标记。
另外，本实施例中，无人机的平均飞行速度可以根据当前天气情况(包括晴、雨、雪、 雾、风速等等相关信息)，从历史数据中得出相同天气情况下无人机平均飞行速度。
步骤S205、根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线。
本实施例中，无人机在从飞行起点向飞行终点行驶过程中，可以搭乘一辆或者多辆车辆行驶。
在从飞行起点向飞行终点行驶过程中，若搭乘车辆的数量越多，那么中途变数越大(例如车辆行驶过快或过慢等)。为了提高无人机搭乘路线的有效性，在从飞行起点向飞行终点行驶过程中，无人机搭乘的车辆的数量通常不超过预设搭乘数量。其中，预设搭乘数量可以由技术人员根据实际应用场景和经验进行设定，本实施例此处不做具体限定。
可选的，预设搭乘数量可以为3，此时可以计算2次候选无人机转乘路线。
该步骤中，根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线，具体可以采用如下方式实现：
将行驶路线上包含候选首次搭乘点的各候选搭乘车辆作为候选转乘对象，计算各候选首次搭乘点对应的首次候选转乘路线，候选首次搭乘点对应的首次候选转乘路线是指：由该候选首次搭乘点对应行驶路线上的第一中途飞离点、至一候选转乘对象的行驶路线上的第一中途搭乘点的飞行路线；将行驶路线上包含候选最后飞离点的各候选搭乘车辆作为候选转乘对象，根据首次候选转乘路线，计算各首次候选转乘路线对应的二次候选转乘路线，首次候选转乘路线对应的二次候选转乘路线是指：由该首次候选转乘路线的第一中途搭乘点对应行驶路线上的第二中途飞离点、至一候选转乘对象的行驶路线上的第二中途搭乘点的飞行路线。
具体的，可以循环行驶路线含有候选首次搭乘点的各候选搭乘车辆，各候选首次搭乘点对应的首次候选转乘路线。然后，循环各候选搭乘车辆(包括行驶路线不含有候选首次搭乘点的候选搭乘车辆)，计算首次候选转乘路线对应的二次候选转乘路线。
进一步的，计算候选首次搭乘点对应的首次候选转乘路线时，确定首次候选转乘路线的第一中途飞离点和第一中途搭乘点的过程，与计算各首次候选转乘路线对应的二次候选转乘路线时，确定二次候选转乘路线的第二中途飞离点和第二中途搭乘点的过程一致，具体可以采用如下方式实现：
确定无人机将飞离的第一车辆在第一时刻的第一运动点，与其他的第二车辆在第一时刻之后的T时刻的第二运动点连成的有向线段，作为无人机从第一车辆转乘第二车辆的有向线段。
其中，有向线段的起点为第一运动点，对应的车辆为无人机将飞离的第一车辆。有向线段的终点为第二运动点，对应的车辆为无人机将转乘的第二车辆。第一车辆为无人机当前搭乘的车辆，第二车辆为可以作为转乘对象的其他车辆。
这些有向线段满足如下条件：无人机从有向线段的起点飞离第一车辆，沿有向线段飞行，经过T时间后，到达有向线段的终点，此时，第二车辆正好行驶至有向线段的终点，无人机可以搭乘第二车辆。
这样，一个有向线段的起点和终点可以作为中途飞离点和中途搭乘点，该有向线段可以作为一条候选转乘路线。
其中，T为预设时长，可以采用现有技术中的方法，根据无人机的平均飞行速度、第 二车辆的平均行驶速度、第二车辆的行驶路线计算得到，本实施例中不再赘述。
具体的，对于一组第一车辆和第二车辆，第一时刻可以从无人机搭乘到第一车辆的时刻起，也就是，有向线段的起点的初始状态为无人机刚刚搭乘上第一车辆时的位置点。根据第一车辆和第二车辆的平均行驶速度模拟两者的有向线段在未来时间的变化情况，并选取有向线段全部在地理围栏内，并且长度最短的有向线段，作为无人机从该第一车辆转乘第二车辆的转乘路线。其中该有向线段的起点和终点分别作为中途飞离点和中途搭乘点。
如果第一车辆为无人机从飞行起点行驶到飞行终点的过程中首次搭乘的车辆，则该有向线段为无人机搭乘该第一车辆的候选首次搭乘点对应的首次候选转乘路线。
如果第一车辆为无人机从飞行起点行驶到飞行终点的过程中第一次转乘的车辆，则该有向线段为无人机转乘到该第一车辆的首次候选转乘路线对应的二次候选转乘路线。
步骤S206、根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，以及候选无人机转乘路线，生成至少一条候选搭乘飞行路线。
根据上述步骤计算得到的各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，以及候选无人机转乘路线，组合成至少一条候选搭乘飞行路线。
具体的，可以根据上述步骤计算出的候选首次搭乘点、各候选首次搭乘点对应的首次候选转乘路线、各首次候选转乘路线对应的二次候选转乘路线、候选最后飞离点，组合成至少一条候选搭乘飞行路线。其中，候选搭乘飞行路线可以不包含首次候选转乘路线，也可以不包含二次候选转乘路线。
例如，如图3所示，E和F分别表示无人机的飞行起点和飞行终点，路线AB表示候选搭乘车辆car1在地理围栏内的行驶路线，路线CD表示候选搭乘车辆Car2在地理围栏内的行驶路线，I为候选搭乘车辆car1行驶路线上的候选首次搭乘点，L为候选搭乘车辆car1行驶路线上的候选最后飞离点，M为候选搭乘车辆Car2行驶路线上的候选首次搭乘点，H为候选搭乘车辆Car2行驶路线上的候选最后飞离点。有向线段(JK) →为car1行驶路线上的候选首次搭乘点I对应的首次候选转乘路线。那么，无人机的候选搭乘飞行路线至少包括：
候选搭乘飞行路线1(可以用“EI-JK-HF”表示)：无人机从飞行起点E沿着EI方向飞行，无人机到达点I时，car1正好到达点I，无人机搭乘car1。当到达点J时，无人机飞离car1，沿着JK方向飞行到达K点时，car2正好到达K点。无人机在K点转乘car2，当到达点H，无人机飞离car2，沿着HF方向飞往飞行终点F。
候选搭乘飞行路线2(可以用“EI-LF”表示)：无人机从飞行起点E沿着EI方向飞行，无人机到达点I时，car1正好到达点I，无人机搭乘car1，当car1到达点L，无人机飞离car1，沿着LF方向飞往飞行终点F。
候选搭乘飞行路线3(可以用“EM-HF”表示)：无人机从飞行起点E沿着EM方向飞行，无人机到达点M时，car2正好到达点M，无人机搭乘car2，当car2到达点H，无人机飞离car2，沿着LF方向飞往飞行终点F。
步骤S207、从至少一条候选搭乘飞行路线中选取一条路线作为无人机的搭乘飞行路线。
本实施例中，在根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，以及候选无人机转乘路线，生成至少一条候选搭乘飞行路线之后，从至少一条候选搭乘飞行路线中选取一条路线作为无人机的搭乘飞行路线。
具体的，根据无人机的平均飞行速度，各候选搭乘车辆的平均行驶速度，计算至少一条候选搭乘飞行路线的总行驶时长；剔除总行驶时长大于飞行限定时长的候选搭乘飞行路线。
其中，候选搭乘飞行路线的总行驶时长包括无人机的飞行时长与无人机搭乘车辆的时长之和，可以根据候选搭乘飞行路线，无人机的平均飞行速度，无人机搭乘的车辆的平均行驶速度计算得到。
飞行限定时长可以采用如下方式计算得到：
计算当前时间距离无人机到达飞行终点的预计到达时间的剩余时长；获取无人机本次由飞行起点到达飞行终点的最大总时长；将剩余时长和最大总时长中的最小值作为无人机本次由飞行起点到达飞行终点的飞行限定时长。
其中，无人机本次由飞行起点到达飞行终点的最大总时长，可以由技术人员根据无人机后续飞行任务的需求等进行设定，本实施例此处不做具体限定。
进一步地，剔除总行驶时长大于飞行限定时长的候选搭乘飞行路线之后，还包括：采用以下公式，计算至少一条候选搭乘飞行路线的最终指标值：Z＝aX+bY；将最终指标值最小的候选搭乘飞行路线，作为无人机的搭乘飞行路线。
其中，Z为以候选搭乘飞行路线的最终指标值，X为候选搭乘飞行路线的总行驶时长，Y为无人机在候选搭乘飞行路线中的飞行路程或者飞行时间，a和b为预设的权重值，a>＝0，b>＝0。
可选的，在确定无人机的搭乘飞行路线之后，可以在电子地图上显示该无人机的搭乘飞行路线。
步骤S208、控制无人机根据搭乘飞行路线，搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点。
在确定无人机的搭乘飞行路线之后，控制无人机按照搭乘飞行路线，搭乘一个或者多个候选搭乘车辆由飞行起点行驶到达飞行终点，从而实现无人机搭乘车辆完成本次行程。
本实施例中，控制无人机在根据搭乘飞行路线行驶的过程中，每隔预设时段，实时地获取无人机下一个将搭乘的目标车辆的行驶速度和所在位置，根据无人机的平均飞行速度和所在位置，更新无人机搭乘该目标车辆的搭乘点位置，并根据更新后的搭乘点位置，控制无人机搭乘目标车辆。
进一步的，若更新后的搭乘点位置与更新前的搭乘点位置的偏移距离大于预设偏移值，则将无人机的当前位置作为新的飞行起点，采用本实施例提供的方法，将当前位置到飞行终点的直线作为无人机新的自主飞行路线，根据新的自主飞行路线更新地理围栏，并重新计算无人机的搭乘飞行路线。
本申请实施例通过根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算得到无人机的搭乘飞行路线；控制无人机根据搭乘飞行路线，搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点，实现了在由飞行起点行驶到飞行终点期间，无人机通过搭乘至少一个车辆大大减少无人机依靠自身动力飞行的路程和时间，大大节省了无人机电量消耗，延长了无人机的运送距离。
实施例三
图4为本申请实施例三提供的无人机搭乘路线处理装置的结构示意图。本申请实施例提供的无人机搭乘路线处理装置可以执行无人机搭乘路线处理方法实施例提供的处理流程。如图4所示，该无人机搭乘路线处理装置40包括：车辆选择模块401，搭乘路线计算模块402和搭乘控制模块403。
具体地，车辆选择模块401用于根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆。
搭乘路线计算模块402用于根据各候选搭乘车辆的当前位置，确定无人机的搭乘飞行路线。
搭乘控制模块403用于根据搭乘飞行路线，控制无人机搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点。
本申请实施例提供的装置可以具体用于执行上述实施例一所提供的方法实施例，具体功能此处不再赘述。
本申请实施例通过根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；根据各候选搭乘车辆的当前位置，确定无人机的搭乘飞行路线；根据搭乘飞行路线，控制无人机搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点，实现了在由飞行起点行驶到飞行终点期间，无人机通过搭乘至少一个车辆大大减少无人机依靠自身动力飞行的路程和时间，大大节省了无人机电量消耗，延长了无人机的运送距离。
实施例四
在上述实施例三的基础上，本实施例中，车辆选择模块还用于：
根据无人机由飞行起点到飞行终点的自主飞行路线，计算自主飞行路线对应的地理围栏；选取行驶路线至少部分在地理围栏内的车辆，作为初始候选车辆；从初始候选车辆中筛选出行驶速度满足预设条件的车辆，作为候选搭乘车辆。
可选的，车辆选择模块还用于：
计算初始候选车辆在地理围栏的区域行驶方向、区域直线路程和区域实际路程；根据初始候选车辆在地理围栏的区域实际路程，以及平均行驶速度，计算初始候选车辆在地理围栏内的预计行驶时间；根据初始候选车辆在地理围栏内的预计行驶时间，以及初始候选车辆在地理围栏的区域直线路程，计算初始候选车辆在地理围栏内的区域直线速度；根据初始候选车辆在地理围栏的区域行驶方向，计算初始候选车辆的区域直线速度、在无人机的自主飞行方向上的速度分量；将速度分量大于第二速度阈值的车辆，作为候选搭乘车辆。
可选的，车辆选择模块还用于：
确定初始候选车辆在地理围栏内的方向起点和方向终点；初始候选车辆在地理围栏的区域行驶方向由方向起点指向方向终点；区域直线路程为由方向起点到方向终点的直线长度；区域实际路程为初始候选车辆沿行驶路线由方向起点到方向终点的实际行驶长度。
可选的，方向起点为初始候选车辆的行驶路线中、在地理围栏内的部分路线的起始点；方向终点为初始候选车辆的行驶路线中、在地理围栏内的部分路线的终止点。
可选的，第二速度阈值为预设比例值与无人机的平均飞行速度的乘积。
可选的，搭乘路线计算模块还用于：
根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，确定所述无人机的搭乘飞行路线。
可选的，搭乘路线计算模块还用于：
根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点；根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线；根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，以及候选无人机转乘路线，生成至少一条候选搭乘飞行路线。
可选的，搭乘路线计算模块还用于：
将行驶路线上包含候选首次搭乘点的各候选搭乘车辆作为候选转乘对象，计算各候选首次搭乘点对应的首次候选转乘路线，候选首次搭乘点对应的首次候选转乘路线是指：由该候选首次搭乘点对应行驶路线上的第一中途飞离点、至一候选转乘对象的行驶路线上的第一中途搭乘点的飞行路线；将行驶路线上包含候选最后飞离点的各候选搭乘车辆作为候选转乘对象，根据首次候选转乘路线，计算各首次候选转乘路线对应的二次候选转乘路线，首次候选转乘路线对应的二次候选转乘路线是指：由该首次候选转乘路线的第一中途搭乘点对应行驶路线上的第二中途飞离点、至一候选转乘对象的行驶路线上的第二中途搭乘点的飞行路线。
可选的，搭乘路线计算模块还用于：
根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选搭乘点，无人机从飞行起点飞至候选搭乘点的同时，各候选搭乘车辆行驶至对应的候选搭乘点；若一候选搭乘车辆的行驶路线上有多个候选搭乘点，则计算该多个候选搭乘点对应的无人机搭乘转飞时间，将对应的无人机搭乘转飞时间最短的候选搭乘点作为该候选搭乘车辆的行驶路线上的候选首次搭乘点；其中，无人机搭乘转飞时间是指无人机从飞行起点飞至该候选搭乘点所需的时间。
可选的，搭乘路线计算模块还用于：
剔除不在自主飞行路线对应的地理围栏内的候选搭乘点；剔除位于无人机无法搭乘位置的候选搭乘点。
可选的，搭乘路线计算模块还用于：
将各候选搭乘车辆的行驶路线上的允许无人机飞离的路段中、距离飞行终点最近的点作为候选最后飞离点。
可选的，搭乘路线计算模块还用于：
根据无人机的平均飞行速度，各候选搭乘车辆的平均行驶速度，计算至少一条候选搭乘飞行路线的总行驶时长；剔除总行驶时长大于飞行限定时长的候选搭乘飞行路线。
可选的，搭乘路线计算模块还用于：
采用以下公式，计算至少一条候选搭乘飞行路线的最终指标值：Z＝aX+bY，其中Z为以候选搭乘飞行路线的最终指标值，X为候选搭乘飞行路线的总行驶时长，Y为无人机在候选搭乘飞行路线中的飞行路程或者飞行时间，a和b为预设的权重值，a>＝0，b>＝0；将最终指标值最小的候选搭乘飞行路线，作为无人机的搭乘飞行路线。
可选的，搭乘控制模块还用于：
每隔预设时段，获取无人机下一个将搭乘的目标车辆的行驶速度和所在位置；根据无人机的平均飞行速度和所在位置，更新无人机搭乘目标车辆的搭乘点位置；根据更新后的搭乘点位置，控制无人机搭乘目标车辆。
本申请实施例提供的装置可以具体用于执行上述实施例二所提供的方法实施例，具体功能此处不再赘述。
本申请实施例通过根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算得到无人机的搭乘飞行路线；控制无人机根据搭乘飞行路线，搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点，实现了在由飞行起点行驶到飞行终点期间，无人机通过搭乘至少一个车辆大大减少无人机依靠自身动力飞行的路程和时间，大大节省了无人机电量消耗，延长了无人机的运送距离。
实施例五
图5为本申请实施例五提供的无人机搭乘路线处理设备的结构示意图。如图5所示，该无人机搭乘路线处理设备50包括：处理器501，存储器502，以及存储在存储器502上并可由处理器501执行的计算机程序。
处理器501在执行存储在存储器502上的计算机程序时实现上述任一方法实施例提供的无人机搭乘路线处理方法。
本申请实施例通过根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；根据各候选搭乘车辆的当前位置，确定无人机的搭乘飞行路线；根据搭乘飞行路线，控制无人机搭乘至少一个候选搭乘车辆由飞行起点行驶到达飞行终点，实现了在由飞行起点行驶到飞行终点期间，无人机通过搭乘至少一个车辆大大减少无人机依靠自身动力飞行的路程和时间，大大节省了无人机电量消耗，延长了无人机的运送距离。
另外，本申请实施例还提供一种计算机可读存储介质，存储有计算机程序，计算机程序被处理器执行时实现上述任一方法实施例提供的无人机搭乘路线处理方法。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
上述以软件功能单元的形式实现的集成的单元，可以存储在一个计算机可读取存储介 质中。上述软件功能单元存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本申请各个实施例所述方法的部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。上述描述的装置的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
本领域技术人员在考虑说明书及实践这里公开的发明后，将容易想到本申请的其它实施方案。本申请旨在涵盖本申请的任何变型、用途或者适应性变化，这些变型、用途或者适应性变化遵循本申请的一般性原理并包括本申请未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的，本申请的真正范围和精神由下面的权利要求书指出。
应当理解的是，本申请并不局限于上面已经描述并在附图中示出的精确结构，并且可以在不脱离其范围进行各种修改和改变。本申请的范围仅由所附的权利要求书来限制。

Claims (15)

  1. 一种无人机搭乘路线处理方法，其特征在于，包括：
    根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；
    根据各候选搭乘车辆的当前位置，确定所述无人机的搭乘飞行路线；
    根据所述搭乘飞行路线，控制所述无人机搭乘至少一个所述候选搭乘车辆。
  2. 根据权利要求1所述的方法，其特征在于，所述根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆，包括：
    根据无人机由飞行起点到飞行终点的自主飞行路线，计算所述自主飞行路线对应的地理围栏；
    选取行驶路线至少部分在所述地理围栏内的车辆，作为初始候选车辆；
    从所述初始候选车辆中筛选出行驶速度满足预设条件的车辆，作为候选搭乘车辆。
  3. 根据权利要求2所述的方法，其特征在于，所述从所述初始候选车辆中筛选出行驶速度满足预设条件的车辆，作为候选搭乘车辆，包括：
    计算所述初始候选车辆在所述地理围栏的区域行驶方向、区域直线路程和区域实际路程；
    根据所述初始候选车辆在所述地理围栏的区域实际路程，以及平均行驶速度，计算所述初始候选车辆在所述地理围栏内的预计行驶时间；
    根据所述初始候选车辆在所述地理围栏内的预计行驶时间，以及所述初始候选车辆在所述地理围栏的区域直线路程，计算所述初始候选车辆在所述地理围栏内的区域直线速度；
    根据所述初始候选车辆在所述地理围栏的区域行驶方向，计算所述初始候选车辆的区域直线速度、在所述无人机的自主飞行方向上的速度分量；
    将所述速度分量大于第二速度阈值的车辆，作为候选搭乘车辆。
  4. 根据权利要求3所述的方法，其特征在于，所述计算所述初始候选车辆在所述地理围栏的区域行驶方向、区域直线路程和区域实际路程，包括：
    确定所述初始候选车辆在所述地理围栏内的方向起点和方向终点；
    所述初始候选车辆在所述地理围栏的区域行驶方向由所述方向起点指向所述方向终点；
    所述区域直线路程为由所述方向起点到所述方向终点的直线长度；
    所述区域实际路程为所述初始候选车辆沿行驶路线由所述方向起点到所述方向终点的实际行驶长度。
  5. 根据权利要求4所述的方法，其特征在于，所述方向起点为所述初始候选车辆的行驶路线中、在所述地理围栏内的部分路线的起始点；
    所述方向终点为所述初始候选车辆的行驶路线中、在所述地理围栏内的部分路线的终止点。
  6. 根据权利要求3或4所述的方法，其特征在于，所述第二速度阈值为预设比例值与所述无人机的平均飞行速度的乘积。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，所述根据各候选搭乘车辆 的当前位置，确定所述无人机的搭乘飞行路线，包括：
    根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，确定所述无人机的搭乘飞行路线。
  8. 根据权利要求7所述的方法，其特征在于，所述根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算得到所述无人机的搭乘飞行路线，包括：
    根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点；
    根据所述各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线；
    根据各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，以及所述候选无人机转乘路线，生成至少一条候选搭乘飞行路线。
  9. 根据权利要求8所述的方法，其特征在于，所述根据所述各候选搭乘车辆的行驶路线上的候选首次搭乘点和候选最后飞离点，计算候选无人机转乘路线，包括：
    将行驶路线上包含所述候选首次搭乘点的各候选搭乘车辆作为候选转乘对象，计算各所述候选首次搭乘点对应的首次候选转乘路线，所述候选首次搭乘点对应的首次候选转乘路线是指：由该候选首次搭乘点对应行驶路线上的第一中途飞离点、至一候选转乘对象的行驶路线上的第一中途搭乘点的飞行路线；
    将行驶路线上包含所述候选最后飞离点的各候选搭乘车辆作为候选转乘对象，根据所述首次候选转乘路线，计算各所述首次候选转乘路线对应的二次候选转乘路线，所述首次候选转乘路线对应的二次候选转乘路线是指：由该首次候选转乘路线的第一中途搭乘点对应行驶路线上的第二中途飞离点、至一候选转乘对象的行驶路线上的第二中途搭乘点的飞行路线。
  10. 根据权利要求8或9所述的方法，其特征在于，所述根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选首次搭乘点，包括：
    根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选搭乘点，所述无人机从所述飞行起点飞至所述候选搭乘点的同时，各候选搭乘车辆行驶至对应的所述候选搭乘点；
    若一候选搭乘车辆的行驶路线上有多个候选搭乘点，则计算该多个候选搭乘点对应的无人机搭乘转飞时间，将对应的无人机搭乘转飞时间最短的候选搭乘点作为该候选搭乘车辆的行驶路线上的候选首次搭乘点；
    其中，所述无人机搭乘转飞时间是指所述无人机从所述飞行起点飞至该候选搭乘点所需的时间。
  11. 根据权利要求8-10任一项所述的方法，其特征在于，根据各候选搭乘车辆的当前位置、行驶路线和行驶速度，计算各候选搭乘车辆的行驶路线上的候选最后飞离点，包括：
    将各候选搭乘车辆的行驶路线上的允许无人机飞离的路段中、距离所述飞行终点最近的点作为候选最后飞离点。
  12. 根据权利要求1-11任一项所述的方法，其特征在于，所述控制所述无人机根 据所述搭乘飞行路线，搭乘至少一个所述候选搭乘车辆，包括：
    每隔预设时段，获取所述无人机下一个将搭乘的目标车辆的行驶速度和所在位置；
    根据所述无人机的平均飞行速度和所在位置，更新所述无人机搭乘所述目标车辆的搭乘点位置；
    根据更新后的所述搭乘点位置，控制所述无人机搭乘所述目标车辆。
  13. 一种无人机搭乘路线处理装置，其特征在于，包括：
    车辆选择模块，用于根据无人机由飞行起点到飞行终点的自主飞行路线，确定候选搭乘车辆；
    搭乘路线计算模块，用于根据各候选搭乘车辆的当前位置，确定所述无人机的搭乘飞行路线；
    搭乘控制模块，用于根据所述搭乘飞行路线，控制所述无人机搭乘至少一个所述候选搭乘车辆。
  14. 一种无人机搭乘路线处理设备，其特征在于，包括：
    存储器，处理器，以及存储在所述存储器上并可在所述处理器上运行的计算机程序，
    所述处理器运行所述计算机程序时实现如权利要求1-12中任一项所述的方法。
  15. 一种计算机可读存储介质，其特征在于，存储有计算机程序，
    所述计算机程序被处理器执行时实现如权利要求1-12中任一项所述的方法。
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