Systems and methods for predicting traffic signal information

• US 8,972,145 B2
• Filed: 03/15/2013
• Issued: 03/03/2015
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Bayerische Motoren Werke AG, Clemson University
• Original Assignee: Bayerische Motoren Werke AG
• Inventors: Winckler, Andreas, Mahler, Grant, Vahidi, Ardalan, Luckow, Andre
• Primary Examiner(s): Trammell, James
• Assistant Examiner(s): LANG, MICHAEL DEAN
• Application Number:
  US13/840,830
• Publication Number:
  US 20140277986A1
• Time in Patent Office: 718 Days
• Field of Search: 701/93
• US Class Current: 701/93
• CPC Class Codes: B60K 2310/24 Speed setting methods
• CPC Class Codes: B60K 31/00 Vehicle fittings, acting on a single sub-unit only, for automatically controlling vehicle speed, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator fittings acting on two or more sub-units B60W30/14; speedometers G01P; systems or devices for controlling speed in general G05D13/00 ; in traffic anti-collision system for road vehicles G08G1/16
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2556/45 External transmission of data to or from the vehicle
• CPC Class Codes: G06F 7/00 Methods or arrangements for processing data by operating upon the order or content of the data handled logic circuits H03K19/00
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• 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

Abstract

Systems and methods for predicting traffic signal information are provided. An exemplary method includes obtaining data from a plurality of types of sources and analyzing the data to predict states of a plurality of traffic signals. The data include crowdsourced data. The predictive traffic signal information may be used to adjust an operation of an on-board system of a vehicle.

Claims

1. A method of using predictive traffic signal information to adjust an operation of an on-board system of a vehicle, the method comprising:

receiving the predictive traffic signal information from outside of the vehicle;

integrating the predictive traffic signal information with internal information about the vehicle; and

adjusting the operation of the on-board system based on the predictive traffic signal information and the internal information about the vehicle;

wherein the predictive traffic signal information is generated by;

obtaining data from a plurality of types of sources; and

analyzing the data to predict states of a plurality of traffic signals,

wherein the data comprise crowdsourced data.

2. The method according to claim 1,

wherein the data comprise at least one of data from a traffic center or data from the plurality of traffic signals.

3. The method according to claim 1, wherein the crowdsourced data comprise historical data obtained from a plurality of vehicles.

4. The method according to claim 1, wherein the crowdsourced data comprise real-time data obtained from a plurality of vehicles.

5. The method according to claim 1, wherein the crowdsourced data comprise global positioning system (GPS) data from at least one of cellular telephones, cellular tower triangulation, vehicles, or navigation devices.

6. The method according to claim 1, wherein the crowdsourced data comprise data from cameras embedded in vehicles.

7. The method according to claim 1, wherein the data comprise at least one of real-time or historical data from the traffic center.

8. The method according to claim 1, wherein the data comprise real-time data from the plurality of traffic signals.

9. The method according to claim 1, wherein the data are analyzed by at least one of modeling, data mining, or machine learning.

10. The method according to claim 1, further comprising generating at least one optimal velocity profile based on the predictive traffic signal information.

11. The method according to claim 1, wherein the internal information comprises at least one of an engine map, a transmission map, a position of the vehicle, or a current vehicle speed.

12. The method according to claim 1, wherein the on-board system is an eco-driving system, and the method further comprises modifying a speed recommendation of the eco-driving system based on the predictive traffic signal information and the internal information about the vehicle.

13. The method according to claim 1, wherein the on-board system is an eco-driving system, and the method further comprises modifying a gear recommendation of the eco-driving system based on the predictive traffic signal information and the internal information about the vehicle.

14. The method according to claim 1, wherein the on-board system is a differential control system, and the method further comprises modifying a differential parameter based on the predictive traffic signal information and the internal information about the vehicle.

15. The method according to claim 1, wherein the on-board system is a navigation system, and the method further comprises modifying a directional recommendation of the navigation system based on the predictive traffic signal information and the internal information about the vehicle.

16. The method according to claim 1, wherein the on-board system is an engine-start-stop system, and the method further comprises modifying a timing of turning an engine on or off based on the predictive traffic signal information and the internal information about the vehicle.

17. The method according to claim 1, wherein the on-board system is an cruise control system, and the method further comprises modifying a speed of the vehicle based on the predictive traffic signal information and the internal information about the vehicle.