Method and system for controlling vehicles and drones

• US 9,897,457 B2
• Filed: 02/10/2016
• Issued: 02/20/2018
• Est. Priority Date: 02/10/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bryson, Donald L., Kline, Eric V., Rakshit, Sarbajit K.
• Primary Examiner(s): Alharbi, Adam
• Application Number:
  US15/040,542
• Publication Number:
  US 20170227368A1
• Time in Patent Office: 741 Days
• CPC Class Codes: G01C 21/343 Calculating itineraries, i.e. routes leading from a starting point to a series of categorical destinations using a global route restraint, round trips, touristic trips travelling salesman problem G06Q10/04; optimisation of routes G06Q10/047
• CPC Class Codes: G01C 21/3438 Rendez-vous, i.e. searching a destination where several users can meet, and the routes to this destination for these users; Ride sharing, i.e. searching a route such that at least two users can share a vehicle for at least part of the route
• CPC Class Codes: G05D 1/0291 Fleet control monitoring fleets in traffic control systems for road vehicles G08G1/127, G08G1/127
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00
• CPC Class Codes: G06Q 50/14 Travel agencies

Abstract

Embodiments are provided for controlling a fleet of vehicles and drones. The vehicles are directed to respectively drop off passenger groups at multiple locations. Routes are calculated routes for the vehicles to respectively pick up the passenger groups from the multiple locations based on predicted pick-up times, passenger group sizes and available vehicle capacities. One or more assign drones are assigned to each passenger group at each location. Each drone is configured to broadcast a current location of the passenger group in the location and a corresponding one of the predicted pick-up times and delay the corresponding passenger group in the location based on one of the vehicles assigned as a pick-up vehicle for the passenger group being delayed.

Claims

1. A computer program product for controlling a fleet of vehicles and drones, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions being readable and executable by a processing circuit to cause the processing circuit to:

direct the vehicles to respectively drop off passenger groups at multiple locations;

calculate routes for the vehicles to respectively pick up the passenger groups from the multiple locations based on predicted pick-up times, passenger group sizes and available vehicle capacities; and

assign one or more of the drones to each passenger group at each location, each drone being configured to;

broadcast a current location of the passenger group in the location and a corresponding one of the predicted pick-up times, and

delay the corresponding passenger group in the location based on one of the vehicles assigned as a pick-up vehicle for the passenger group being delayed and based on the pick-up vehicle being delayed relative to the corresponding one of the predicted pick-up times by a threshold exceeding time.

2. The computer program product according to claim 1, wherein the multiple locations comprise tourist points of interest (POIs).

3. The computer program product according to claim 1, wherein the vehicles comprise driverless cars, vans, mini-buses and buses and the drones comprise manned or unmanned ground vehicles and manned or unmanned aircraft.

4. The computer program product according to claim 1, wherein the passenger groups have varied drop-off and pick-up priorities.

5. The computer program product according to claim 1, wherein the routes are calculated in order to limit route costs and passenger group wait times.

6. The computer program product according to claim 1, wherein each drone recalculates the corresponding one of the predicted pick-up times in real-time.

7. A computing system for controlling a fleet of vehicles and drones, the computing system comprising a memory and a processing circuit coupled to the memory, wherein the processing circuit is configured to:

direct the vehicles to respectively drop off passenger groups at multiple locations;

calculate routes for the vehicles to respectively pick up the passenger groups from the multiple locations based on predicted pick-up times, passenger group sizes and available vehicle capacities; and

assign one or more of the drones to each passenger group at each location, each drone being configured to;

broadcast a current location of the passenger group in the location and a corresponding one of the predicted pick-up times, and

delay the corresponding passenger group in the location based on one of the vehicles assigned as a pick-up vehicle for the passenger group being delayed and based on the pick-up vehicle being delayed relative to the corresponding one of the predicted pick-up times by a threshold exceeding time.

8. The computing system according to claim 7, wherein the multiple locations comprise tourist points of interest (POIs).

9. The computing system according to claim 7, wherein the vehicles comprise driverless cars, vans, mini-buses and buses and the drones comprise manned or unmanned ground vehicles and manned or unmanned aircraft.

10. The computing system according to claim 7, wherein the passenger groups have varied drop-off and pick-up priorities.

11. The computing system according to claim 7, wherein the routes are calculated in order to limit route costs and passenger group wait times.

12. The computing system according to claim 7, wherein each drone recalculates the corresponding one of the predicted pick-up times in real-time.

13. A computer-implemented method for controlling a fleet of vehicles and drones, comprising:

directing the vehicles to respectively drop off passenger groups at multiple locations;

calculating routes for the vehicles to respectively pick up the passenger groups from the multiple locations based on predicted pick-up times, passenger group sizes and available vehicle capacities;

assigning one or more of the drones to each passenger group at each location;

configuring each drone to broadcast a current location of the passenger group in the location and a corresponding one of the predicted pick-up times; and

configuring each drone to delay the corresponding passenger group in the location based on one of the vehicles assigned as a pick-up vehicle for the passenger group being delayed and based on the pick-up vehicle being delayed relative to the corresponding one of the predicted pick-up times by a threshold exceeding time and recalculate the corresponding one of the predicted pickup times in real-time.

14. The computer-implemented method according to claim 13, wherein the multiple locations comprise tourist points of interest (POIs).

15. The computer-implemented method according to claim 13, wherein the vehicles comprise driverless cars, vans, mini-buses and buses and the drones comprise manned or unmanned ground vehicles and manned or unmanned aircraft.

16. The computer-implemented method according to claim 13, wherein the passenger groups have varied drop-off and pick-up priorities.

17. The computer-implemented method according to claim 13, wherein the calculating comprises limiting route costs and passenger group wait times.