Navigation using crowdsourcing data

• US 8,972,175 B2
• Filed: 03/14/2013
• Issued: 03/03/2015
• Est. Priority Date: 03/14/2013
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Annapureddy, Koushik, Finlow-Bates, Keir
• Primary Examiner(s): EL CHANTI, HUSSEIN A
• Application Number:
  US13/826,794
• Publication Number:
  US 20140278074A1
• Time in Patent Office: 719 Days
• Field of Search: 701/414, 701/423, 701/468
• US Class Current: 701/423
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/3453 Special cost functions, i.e. other than distance or default speed limit of road segments
• CPC Class Codes: G01C 21/3469 Fuel consumption; Energy use; Emission aspects
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G01C 21/36 Input/output arrangements for on-board computers
• CPC Class Codes: G01C 21/3691 Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions arrangements for giving variable traffic instructions G08G1/09
• CPC Class Codes: G01S 19/42 Determining position
• CPC Class Codes: G06F 21/552 involving long-term monitoring or reporting
• CPC Class Codes: G06F 21/572 Secure firmware programming, e.g. of basic input output system [BIOS]
• CPC Class Codes: G06F 2221/2111 Location-sensitive, e.g. geographical location, GPS
• CPC Class Codes: G06F 2221/2115 Third party
• CPC Class Codes: G06F 2221/2151 Time stamp
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/096791 where the origin of the information is another vehicle
• CPC Class Codes: G08G 1/096811 where the route is computed offboard
• CPC Class Codes: G08G 1/14 indicating individual free spaces in parking areas
• CPC Class Codes: H04W 4/024 Guidance services
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]
• CPC Class Codes: H04W 4/46 : for vehicle-to-vehicle communication [V2V]

Abstract

Method, computer program product, and apparatus for providing navigation guidance to vehicles are disclosed. The method may include receiving crowdsourcing data from a plurality of vehicles, determining information corresponding to a route of interest to at least one vehicle using the crowdsourcing data, and providing navigation guidance to the at least one vehicle using the information determined. The crowdsourcing data includes on board diagnostics data (OBD) correlated with time stamps and GPS locations of a vehicle, where the on board diagnostics data includes odometer information, speedometer information, fuel consumption information, steering information, and impact data.

Claims

1. A method of providing navigation guidance to vehicles, comprising:

receiving crowdsourcing data from a plurality of vehicles, wherein the crowdsourcing data includes on board diagnostics data (OBD) correlated with time stamps and GPS locations of a vehicle; and

wherein the on board diagnostics data includes odometer information, speedometer information, fuel consumption information, steering information, and impact data;

determining information corresponding to a route of interest to at least one vehicle using the crowdsourcing data; and

providing navigation guidance to the at least one vehicle using the information determined.

2. The method of claim 1, wherein determining information corresponding to a route of interest to at least one vehicle comprises at least one of:

predicting closing of a lane using the crowdsourcing data;

predicting an avoidance maneuver using the crowdsourcing data;

predicting a congestion with respect to a segment of the route of the at least one vehicle using the crowdsourcing data; and

predicting traffic light patterns using the crowdsourcing data.

3. The method of claim 2, wherein predicting closing of a lane comprises:

monitoring changes of vehicle direction at a location on the route of the at least one vehicle; and

determining a lane is closed in response to a number of changes of vehicle direction being larger than a predetermined threshold value.

4. The method of claim 2, wherein predicting an avoidance maneuver comprises:

monitoring change of vehicle direction and distance traveled at a close vicinity of a location on the route of the at least one vehicle; and

determining an avoidance maneuver in response to a ratio of change of vehicle direction and distance traveled being less than a predetermined threshold value.

5. The method of claim 1, wherein determining information corresponding to a route of interest to at least one vehicle further comprises at least one of:

determining a route based at least in part on an amount of time predicted for travelling from a starting location to a destination location of the route using the crowdsourcing data; and

determining a route based at least in part on a predicted fuel consumption of the route using the crowdsourcing data.

6. The method of claim 1, wherein determining information corresponding to a route of interest to at least one vehicle further comprises at least one of:

monitoring a distance traveled by the at least one vehicle after reaching a destination, and predicting availability of parking spaces at the destination based at least in part on the distance traveled; and

monitoring an amount of time traveled by the at least one vehicle after reaching a destination, and predicting availability of parking spaces at the destination based at least in part on the amount of time traveled.

7. The method of claim 1, wherein determining information corresponding to a route of interest to at least one vehicle further comprises:

measuring a time taken to travel a predefined percent of the route until the at least one vehicle comes to a halt at a predetermined location; and

predicting an average amount of time used to find parking at the predetermined location using the time taken to travel a predefined percent of the route.

8. The method of claim 1, wherein determining information corresponding to a route of interest to at least one vehicle further comprises at least one of:

determining popularity of a fueling station along the route;

determining type of fuel sold at the fueling station along the route;

determining popularity of a business along the route; and

determining popularity of a rest area along the route.

9. The method of claim 1, wherein determining information corresponding to a route of interest to at least one vehicle further comprises:

determining location of a stolen vehicle in accordance with crowdsourcing data received from the stolen vehicle.

10. A computer program product comprising non-transitory medium storing instructions for execution by one or more computer systems, the instructions comprising:

instructions configured to receive crowdsourcing data from a plurality of vehicles, wherein the crowdsourcing data includes on board diagnostics data (OBD) correlated with time stamps and GPS locations of a vehicle; and

wherein the on board diagnostics data includes odometer information, speedometer information, fuel consumption information, steering information, and impact data;

instructions configured to determine information corresponding to a route of interest to at least one vehicle using the crowdsourcing data; and

instructions configured to provide navigation guidance to the at least one vehicle using the information determined.

11. The computer program product of claim 10, wherein instructions for determining information corresponding to a route of interest to at least one vehicle comprises at least one of:

instructions configured to predict closing of a lane using the crowdsourcing data;

instructions configured to predict an avoidance maneuver using the crowdsourcing data;

instructions configured to predict a congestion with respect to a segment of the route of the at least one vehicle using the crowdsourcing data; and

instructions configured to predict traffic light patterns using the crowdsourcing data.

12. The computer program product of claim 11, wherein instructions for predicting closing of a lane comprises:

instructions configured to monitor changes of vehicle direction at a location on the route of the at least one vehicle; and

instructions configured to determine a lane is closed in response to a number of changes of vehicle direction being larger than a predetermined threshold value.

13. The computer program product of claim 11, wherein instructions for predicting an avoidance maneuver comprises:

instructions configured to monitor change of vehicle direction and distance traveled at a close vicinity of a location on the route of the at least one vehicle; and

instructions configured to determine an avoidance maneuver in response to a ratio of change of vehicle direction and distance traveled being less than a predetermined threshold value.

14. The computer program product of claim 10, wherein instructions for determining information corresponding to a route of interest to at least one vehicle further comprises at least one of:

instructions configured to determine a route based at least in part on an amount of time predicted for travelling from a starting location to a destination location of the route using the crowdsourcing data; and

instructions configured to determine a route based at least in part on a predicted fuel consumption of the route using the crowdsourcing data.

15. The computer program product of claim 10, wherein instructions for determining information corresponding to a route of interest to at least one vehicle further comprises at least one of:

instructions configured to monitor a distance traveled by the at least one vehicle after reaching a destination, and predicting availability of parking spaces at the destination based at least in part on the distance traveled; and

instructions configured to monitor an amount of time traveled by the at least one vehicle after reaching a destination, and predicting availability of parking spaces at the destination based at least in part on the amount of time traveled.

16. The computer program product of claim 10, wherein instructions for determining information corresponding to a route of interest to at least one vehicle further comprises:

instructions or configured to measure a time taken to travel a predefined percent of the route until the at least one vehicle comes to a halt at a predetermined location; and

instructions configured to predict an average amount of time used to find parking at the predetermined location using the time taken to travel a predefined percent of the route.

17. The computer program product of claim 10, wherein instructions for determining information corresponding to a route of interest to at least one vehicle further comprises at least one of:

instructions configured to determine popularity of a fueling station along the route;

instructions configured to determine type of fuel sold at the fueling station along the route;

instructions configured to determine popularity of a business along the route; and

instructions configured to determine popularity of a rest area along the route.

18. The computer program product of claim 10, wherein instructions for determining information corresponding to a route of interest to at least one vehicle further comprises:

instructions configured to determine location of a stolen vehicle in accordance with crowdsourcing data received from the stolen vehicle.

19. An apparatus, comprising:

a control unit including processing logic, the processing logic comprising;

logic configured to receive crowdsourcing data from a plurality of vehicles, wherein the crowdsourcing data includes on board diagnostics data (OBD) correlated with time stamps and GPS locations of a vehicle; and

wherein the on board diagnostics data includes odometer information, speedometer information, fuel consumption information, steering information, and impact data;

logic configured to determine information corresponding to a route of interest to at least one vehicle using the crowdsourcing data; and

logic configured to provide navigation guidance to the at least one vehicle using the information determined.

20. The apparatus of claim 19, wherein logic configured to determine information corresponding to a route of interest to at least one vehicle comprises at least one of:

logic configured to predict closing of a lane using the crowdsourcing data;

logic configured to predict an avoidance maneuver using the crowdsourcing data;

logic configured to predict a congestion with respect to a segment of the route of the at least one vehicle using the crowdsourcing data; and

logic configured to predict traffic light patterns using the crowdsourcing data.

21. The apparatus of claim 20, wherein logic configured to predict closing of a lane comprises:

logic configured to monitor changes of vehicle direction at a location on the route of the at least one vehicle; and

logic configured to determine a lane is closed in response to a number of changes of vehicle direction being larger than a predetermined threshold value.

22. The apparatus of claim 20, wherein logic configured to predict an avoidance maneuver comprises:

logic configured to monitor change of vehicle direction and distance traveled at a close vicinity of a location on the route of the at least one vehicle; and

logic configured to determine an avoidance maneuver in response to a ratio of change of vehicle direction and distance traveled being less than a predetermined threshold value.

23. The apparatus of claim 19, wherein logic configured to determine information corresponding to a route of interest to at least one vehicle further comprises at least one of:

logic configured to determine a route based at least in part on an amount of time predicted for travelling from a starting location to a destination location of the route using the crowdsourcing data; and

logic configured to determine a route based at least in part on a predicted fuel consumption of the route using the crowdsourcing data.

24. The apparatus of claim 19, wherein logic configured to determine information corresponding to a route of interest to at least one vehicle further comprises at least one of:

logic configured to monitor a distance traveled by the at least one vehicle after reaching a destination, and predicting availability of parking spaces at the destination based at least in part on the distance traveled; and

logic configured to monitor an amount of time traveled by the at least one vehicle after reaching a destination, and predicting availability of parking spaces at the destination based at least in part on the amount of time traveled.

25. The apparatus of claim 19, wherein logic configured to determine information corresponding to a route of interest to at least one vehicle further comprises:

logic configured to measure a time taken to travel a predefined percent of the route until the at least one vehicle comes to a halt at a predetermined location; and

logic configured to predict an average amount of time used to find parking at the predetermined location using the time taken to travel a predefined percent of the route.

26. The apparatus of claim 19, wherein logic configured to determine information corresponding to a route of interest to at least one vehicle further comprises at least one of:

logic configured to determine popularity of a fueling station along the route;

logic configured to determine type of fuel sold at the fueling station along the route;

logic configured to determine popularity of a business along the route; and

logic configured to determine popularity of a rest area along the route.

27. The apparatus of claim 19, wherein logic configured to determine information corresponding to a route of interest to at least one vehicle further comprises:

logic configured to determine location of a stolen vehicle in accordance with crowdsourcing data received from the stolen vehicle.

28. A mobile station, comprising:

a navigation controller including processing logic, the processing logic comprising;

logic configured to send crowdsourcing data to a server, wherein logic configured to send crowdsourcing data to the server further comprises;

logic configured to receive on board diagnostics data from an on-board diagnostic module of a vehicle, logic configured to receive GPS locations of the vehicle from a GNSS module, and logic configured to correlate the on board diagnostics data and GPS locations of the vehicle with time stamps to generate the crowdsourcing data; and

wherein the on board diagnostics data comprises odometer information, speedometer information, fuel consumption information, steering information, and impact data;

logic configured to receive navigation guidance from the server, wherein the navigation guidance is based on the crowdsourcing data; and

logic configured to display the navigation guidance on a display.

29. A system, comprising:

means for receiving crowdsourcing data from a plurality of vehicles, wherein the crowdsourcing data includes on board diagnostics data (OBD) correlated with time stamps and GPS locations of a vehicle; and

wherein the on board diagnostics data includes odometer information, speedometer information, fuel consumption information, steering information, and impact data;

means for determining information corresponding to a route of interest to at least one vehicle using the crowdsourcing data; and

means for providing navigation guidance to the at least one vehicle using the information determined.