DYNAMICALLY PROVIDING POSITION INFORMATION OF A TRANSIT OBJECT TO A COMPUTING DEVICE

• US 20140129135A1
• Filed: 11/08/2012
• Published: 05/08/2014
• Est. Priority Date: 11/08/2012
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uber Technologies, Inc.
• Inventors: Holden, Paul-Phillip, Sweeney, Matthew
• Granted Patent: US 9,671,233 B2
• Time in Patent Office: Days
• US Class Current: 701/420
• CPC Class Codes: G01C 21/30 Map- or contour-matching
• CPC Class Codes: G01S 19/39 the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
• CPC Class Codes: G06F 21/552 involving long-term monitoring or reporting
• CPC Class Codes: G06F 2221/2111 Location-sensitive, e.g. geographical location, GPS
• CPC Class Codes: G06F 2221/2115 Third party
• CPC Class Codes: G06Q 10/0833 Tracking
• CPC Class Codes: G08G 1/13 the indicator being in the form of a map
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental
• CPC Class Codes: H04W 4/024 Guidance services
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]
• CPC Class Codes: H04W 4/44 for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]

Abstract

A system and method for providing position information of a transit object to a computing device is provided. Global positioning satellite (GPS) information of a transit object can be periodically received. For each of some of the GPS information, one or more candidate points of a transit system can be identified based on the GPS information. Using the one or more candidate points, a most likely path of travel can be determined. Additional position points along the most likely path of travel can be extrapolated and transmitted to a computing device.

Claims

1. A method of providing position information of a transit object to a computing device, the method being performed by one or more processors and comprising:

periodically receiving global positioning satellite (GPS) information of the transit object, the GPS information including a latitude of the transit object, a longitude of the transit object, and a GPS error amount at a given instance;

identifying, for each of some of the GPS information, one or more candidate points of a transit system that are within the GPS error amount for that GPS information;

determining a most likely path of travel of the transit object on the transit system based on the identified one or more candidate points of the transit system;

extrapolating points along the most likely path of travel; and

transmitting a set of extrapolated points to the computing device.

2. The method of claim 1, wherein identifying one or more candidate points of the transit system includes referencing a transit model stored in a database.

3. The method of claim 1, wherein each of the one or more candidate points corresponds to a location on a path of travel on the transit system.

4. The method of claim 1, wherein determining the most likely path of travel includes using at least one of a routing engine, a physics engine, or a hidden Markov model solver.

5. The method of claim 4, wherein the GPS information includes a time stamp, and wherein determining the most likely path of travel includes using the time stamp of each of some of the GPS information with at least one of the routing engine, the physics engine, or the hidden Markov model solver.

6. The method of claim 1, wherein extrapolating points along the most likely path of travel includes generating position information corresponding to each of the extrapolated points with an extrapolated time stamp.

7. The method of claim 1, wherein transmitting the set of extrapolated points to the computing device includes determining the current time of the computing device and transmitting extrapolated points based on the current time.

8. The method of claim 1, wherein the transit object includes at least one of a bicycle, a car, a train, or a plane.

9. The method of claim 1, wherein the computing device can use the set of extrapolated points to present, on a display of the computing device, a graphic representing the transit object on a map.

10. A system for providing position information of a transit object to a computing device, the system comprising:

memory resources;

a network interface;

one or more processors coupled to the memory resources and the network interface, the one or more processors to;

periodically receive global positioning satellite (GPS) information of the transit object via the network interface, the GPS information including a latitude of the transit object, a longitude of the transit object, and a GPS error amount at a given instance;

identify, for each of some of the GPS information, one or more candidate points of a transit system that are within the GPS error amount for that GPS information;

determine a most likely path of travel of the transit object on the transit system based on the identified one or more candidate points of the transit system;

extrapolate points along the most likely path of travel; and

transmit a set of extrapolated points to the computing device via the network interface.

11. The system of claim 10, wherein the one or more processors identify one or more candidate points of the transit system by referencing a transit model stored in a database.

12. The system of claim 10, wherein each of the one or more candidate points corresponds to a location on a path of travel on the transit system.

13. The system of claim 10, wherein the one or more processors determine the most likely path of travel by using at least one of a routing engine, a physics engine, or a hidden Markov model solver.

14. The system of claim 13, wherein the GPS information includes a time stamp, and wherein the one or more processors determine the most likely path of travel by using the time stamp of each of some of the GPS information with at least one of the routing engine, the physics engine, or the hidden Markov model solver.

15. The system of claim 10, wherein the one or more processors extrapolate points along the most likely path of travel by generating position information corresponding to each of the extrapolated points with an extrapolated time stamp.

16. The system of claim 10, wherein the one or more processors transmit the set of extrapolated points to the computing device by determining the current time of the computing device and transmitting extrapolated points based on the current time.

17. The system of claim 10, wherein the transit object includes at least one of a bicycle, a car, a train, or a plane.

18. The system of claim 10, wherein the computing device can use the set of extrapolated points to present, on a display of the computing device, a graphic representing the transit object on a map.

19. A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform steps comprising:

periodically receiving global positioning satellite (GPS) information of a transit object, the GPS information including a latitude of the transit object, a longitude of the transit object, and a GPS error amount at a given instance;

referencing a transmit model to identify, for each of some of the GPS information, one or more candidate points of a transit system that are within the GPS error amount for that GPS information;

determining a most likely path of travel of the transit object on the transit system based on the identified one or more candidate points of the transit system;

extrapolating points along the most likely path of travel; and

transmitting a set of extrapolated points to the computing device.

20. The non-transitory computer readable medium of claim 19, wherein the instructions cause the one or more processors to determine the most likely path of travel by using at least one of a routing engine, a physics engine, or a hidden Markov model solver.