Travel path identification based upon statistical relationships between path costs

• US 9,714,831 B2
• Filed: 07/07/2014
• Issued: 07/25/2017
• Est. Priority Date: 07/07/2014
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Dey, Debadeepta, Kolobov, Andrey, Eden, Semiha Ece Kamar, Caruana, Richard, Kapoor, Ashish, Horvitz, Eric
• Primary Examiner(s): Olszewski, John R
• Assistant Examiner(s): BOOMER, JEFFREY C
• Application Number:
  US14/324,861
• Publication Number:
  US 20160003620A1
• Time in Patent Office: 1,114 Days
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G01C 21/3446 Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G08G 1/096827 where the route is computed onboard
• CPC Class Codes: G08G 1/096844 where the complete route is dynamically recomputed based on new data
• CPC Class Codes: G08G 5/0008 with other aircraft
• CPC Class Codes: G08G 5/0021 located in the aircraft
• CPC Class Codes: G08G 5/0039 Modification of a flight plan
• CPC Class Codes: G08G 5/0078 for monitoring traffic from the aircraft radar or analogous systems specially adapted for traffic control G01S13/91
• CPC Class Codes: G08G 5/0091 for monitoring atmospheric conditions radar or analogous systems specially adapted for meteorological use G01S13/95; meteorology G01W

Abstract

Various technologies pertaining to dynamically identifying travel segments to be taken by a traveler traveling in a region are described herein, where observations about travel segments in the region are sparse and subject to alteration. A computer-implemented graph can be loaded into a memory, where the computer-implemented graph is representative of the region. The computer-implemented graph includes nodes that represent locations in the region and edges that represent travel segments of the region, where the edges have costs assigned thereto, and further where there is a defined statistical relationship between the costs. When an observation about a travel path is received, using the computer-implemented graph, inferences can be made about costs of traversing other travel paths in the region.

Claims

1. A method executed by a processor of a computing device, the method comprising:

receiving a computer-implemented graph that comprises nodes and edges, the computer-implemented graph representative of a region over which a machine is able to travel, the nodes representative of respective locations in the region, the edges representative of travel segments between locations, wherein each edge in the edges connects a respective pair of nodes in the nodes, each node in the nodes connected to at least one other node by a respective edge in the edges, the edges have respective distributions over costs assigned thereto, and the respective costs have a statistical relationship therebetween;

receiving data from a sensor, the data being about a travel segment in the travel segments;

responsive to receiving the data, updating the respective distributions over the costs of the edges in the computer-implemented graph based upon the data and the statistical relationship;

identifying a particular travel segment in the travel segments over which the machine is to travel, the identifying based upon the updating of the respective distributions over the costs of the edges and a destination location of the machine; and

responsive to identifying the particular travel segment, directing the machine to travel along the particular travel segment in the travel segments, wherein directing the machine to travel along the particular travel segment comprises outputting a signal that causes the machine to travel along the particular travel segment in the travel segments.

2. The method of claim 1, wherein the machine comprises the processor.

3. The method of claim 2, wherein the respective distributions over the costs of the edges are updated in the computer-implemented graph as the machine travels in the region.

4. The method of claim 1, the machine being one of an airplane, a water vessel, a spacecraft, a drone, a robot, or an automobile.

5. The method of claim 1, the machine comprises the sensor.

6. The method of claim 1, another machine in the region comprises the sensor.

7. The method of claim 1, the statistical relationship being a joint probability distribution over the costs.

8. The method of claim 7, the joint probability distribution being a Gaussian distribution.

9. The method of claim 7, wherein identifying the particular travel segment in the travel segments over which the machine is to travel comprises:

sampling from the joint probability distribution to acquire respective discrete cost values for the edges;

identifying, from amongst possible travel routes from a current location of the machine to the destination location, a travel route that has a lowest aggregate cost from amongst the possible travel routes, the travel route being over multiple travel segments; and

identifying the particular travel segment based upon the identifying of the travel route, wherein the particular travel segment is a first travel segment in the travel route that begins at the current location of the machine.

10. The method of claim 9, wherein identifying the particular travel segment in the travel segments over which the machine is to travel further comprises:

sampling from the joint probability distribution multiple times to acquire multiple discrete cost values for each edge in the edges;

for each edge in the edges, computing a respective average cost value; and

identifying the travel route based upon respective average cost values for the edges.

11. The method of claim 1, further comprising repeating the acts of:

receiving data from the sensor;

updating the respective costs of the edges;

identifying a particular travel segment in the travel segments; and

outputting a signal that directs the machine to travel along the particular travel segment in the travel segments until the machine reaches the destination location.

12. The method of claim 1, the statistical relationship is a function of time.

13. A computing system comprising:

a processor; and

memory that stores instructions that, when executed by the processor, cause the processor to perform acts comprising;

receiving a computer-implemented graph that comprises nodes and edges, the computer-implemented graph representative of a region over which a machine is able to travel, the nodes representative of respective locations in the region, the edges representative of travel segments between locations, wherein each edge in the edges connects a respective pair of nodes in the nodes, each node in the nodes connected to at least one other node by a respective edge in the edges, the edges have respective distributions over costs assigned thereto, and the respective costs have a statistical relationship therebetween;

receiving data from a sensor, the data being about a travel segment in the travel segments;

responsive to receiving the data, updating the respective distributions over the costs of the edges in the computer-implemented graph based upon the data and the statistical relationship;

identifying a particular travel segment in the travel segments over which the machine is to travel, the identifying based upon the updating of the respective distributions over the costs of the edges and a destination location of the machine; and

responsive to identifying the particular travel segment, directing the machine to travel along the particular travel segment in the travel segments, wherein directing the machine to travel along the particular travel segment comprises outputting a signal that causes the machine to travel along the particular travel segment in the travel segments.

14. The computing system of claim 13, the machine being one of an airplane, a water vessel, a spacecraft, a drone, a robot, or an automobile.

15. The computing system of claim 13, the machine comprises the sensor.

16. The computing system of claim 13, another machine in the region comprises the sensor.

17. The computing system of claim 13, the statistical relationship being a joint probability distribution over the costs.

18. The computing system of claim 17, the joint probability distribution being a Gaussian distribution.

19. The computing system of claim 18, wherein identifying the particular travel segment in the travel segments over which the machine is to travel comprises:

sampling from the joint probability distribution to acquire respective discrete cost values for the edges;

identifying, from amongst possible travel routes from a current location of the machine to the destination location, a travel route that has a lowest aggregate cost from amongst the possible travel routes, the travel route being over multiple travel segments; and

identifying the particular travel segment based upon the identifying of the travel route, wherein the particular travel segment is a first travel segment in the travel route that begins at the current location of the machine.

20. A computer-readable storage medium comprising instructions that, when executed by a processor, cause the processor to perform acts comprising:

receiving a computer-implemented graph that comprises nodes and edges, the computer-implemented graph representative of a region over which a machine is able to travel, the nodes representative of respective locations in the region, the edges representative of travel segments between locations, wherein each edge in the edges connects a respective pair of nodes in the nodes, each node in the nodes connected to at least one other node by a respective edge in the edges, the edges have respective distributions over costs assigned thereto, and the respective costs have a statistical relationship therebetween;

receiving data from a sensor, the data being about a travel segment in the travel segments;

responsive to receiving the data, updating the respective distributions over the costs of the edges in the computer-implemented graph based upon the data and the statistical relationship;

identifying a particular travel segment in the travel segments over which the machine is to travel, the identifying based upon the updating of the respective distributions over the costs of the edges and a destination location of the machine; and

responsive to identifying the particular travel segment, directing the machine to travel along the particular travel segment in the travel segments, wherein directing the machine to travel along the particular travel segment comprises outputting a signal that causes the machine to travel along the particular travel segment in the travel segments.