System for providing traffic data and driving efficiency data

• US 9,390,620 B2
• Filed: 05/12/2014
• Issued: 07/12/2016
• Est. Priority Date: 05/18/2011
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Pelmorex Canada Inc.
• Inventors: Poulain, Damien, Faure, Romain, Gueziec, Andre
• Primary Examiner(s): Jabr, Fadey
• Assistant Examiner(s): SHUDY, ANGELINA M
• Application Number:
  US14/275,702
• Publication Number:
  US 20140249734A1
• Time in Patent Office: 792 Days
• Field of Search: 701/117, 701/118
• US Class Current: 1/1
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/09675 where a selection from the received information takes place in the vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/096783 where the origin of the information is a roadside individual element
• CPC Class Codes: G08G 1/096791 where the origin of the information is another vehicle
• CPC Class Codes: G08G 1/0969 having a display in the form of a map
• CPC Class Codes: H04W 4/60 Subscription-based services using application servers or record carriers, e.g. SIM application toolkits
• CPC Class Codes: H04W 88/02 Terminal devices

Abstract

Current and predicted traffic information is provided from incident data, traffic flow data, and media related to traffic received from multiple sources. The crowd sourced data may be provided passively by applications on remote mobile devices or actively by users operating the remote mobile devices. An application on a mobile device may receive the multiple data types, aggregate and validate the data, and provides traffic information for a user. The traffic information may relate to the current position and route of the user or a future route. The present technology may also provide driving efficiency information such as fuel consumption data, carbon footprint data, and a driving rating for a user associated with a vehicle.

Claims

1. A system for processing traffic data, the system comprising:

a network interface that receives traffic data at a mobile device, the traffic data originating from multiple sources, wherein the traffic data is received at least in part from crowd sourced data, a portion of the crowd sourced data originating passively through a plurality of mobile devices and another portion of the crowd sourced data originating actively from a remote user through a plurality of mobile devices, and wherein the traffic data includes incident data, traffic flow data, and media data associated with the traffic;

a memory that stores instructions;

a processor that executes the instructions stored in memory to;

validate the traffic data by;

aggregating the traffic data, and

removing anomalies in the traffic data;

provide traffic information to a user through an interface of the mobile device according to user criteria, wherein the user criteria includes at least a user location and at least one type of traffic information the user is interested in receiving, and wherein the traffic information is generated based on the validated traffic data;

provide driving efficiency information through the interface; and

update the traffic information at a frequency based on accuracy of the traffic information and battery performance of the mobile device.

2. The system of claim 1, wherein the system further includes a user interface for receiving user input, the user input including vehicle information.

3. The system of claim 1, wherein the driving efficiency information includes carbon footprint data.

4. The system of claim 1, wherein the traffic information includes predicted traffic information.

5. The system of claim 1, wherein the driving efficiency information includes fuel consumption data.

6. The system of claim 5, wherein execution of instructions by the processor further:

retrieves vehicle specification information, including vehicle mass, front area, and drag efficiency, based on the received vehicle information.

7. The system of claim 6, wherein the fuel consumption data is based at least in part on vehicle specification information.

8. The system of claim 5, wherein the fuel consumption data is filtered.

9. A method for predicting traffic, the method comprising:

receiving traffic data by a mobile device, the traffic data originating from multiple sources, wherein the traffic data is received at least in part from crowd sourced data, a portion of the crowd sourced data originating passively through a plurality of mobile devices and another portion of the crowd sourced data originating actively from a remote user through a plurality of mobile devices;

receiving user input by an interface of the mobile device, wherein the user input specifies a location and a time; and

executing instructions stored in memory, wherein execution of the instructions by a processor;

analyzes the traffic data received over time to determine recurring traffic speeds associated with locations, wherein a plurality of recurring traffic speeds are determined for each location, and wherein each of the plurality of recurring traffic speeds is associated with a respective time,

predicts traffic information based on the determined recurring traffic speeds associated with the specified location and the specified time, and

displays the predicted traffic information to a user at an interface of the mobile device.

10. The method of claim 9, wherein the method further comprises validating the received traffic data by aggregating the traffic data and removing anomalies in the received traffic data.

11. The method of claim 10, wherein the recurring traffic speeds are generated by processing the validated traffic data.

12. The method of claim 9, wherein the user input specifies a starting point, an ending point, and a departure time, and wherein the predicted traffic information includes a trip time prediction for a route between the starting point and the ending point, the trip time prediction associated with the specified departure time.

13. The method of claim 12, wherein the predicted traffic information includes a plurality of trip time predictions for the route, wherein each of the plurality of trip time predictions is associated with a respective departure time.

14. The method of claim 9, wherein the predicted traffic information is displayed on a user-centered map at the time specified by the user input.

15. The method of claim 9, wherein the user input specifies a period of time, and wherein the predicted traffic information is displayed on a user-centered map at the period of time specified by the user input.

16. The method of claim 9, wherein the traffic data includes incident data, traffic flow data, and media data associated with the traffic.

17. The method of claim 9, wherein the predicted traffic information is updated based on the accuracy of the predicted traffic information and battery performance of the device.