IP Library Granted Patent US 8,972,145
Granted Patent B2
US 8,972,145 · App. 13/840,830 · Granted Mar 3, 2015

Systems and methods for predicting traffic signal information

Inventors: Grant Mahler (Clemson, SC); Andreas Winckler (Mountain View, CA); Ardalan Vahidi (Clemson, SC); Andre Luckow (Pullach, DE)
Assignee: Bayerische Motoren Werke Aktiengesellscahft
G06N5/02G06F7/00B60K31/00
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Quick Facts
Patent No.
US 8,972,145
App. No.
13/840,830
Granted
Mar 3, 2015
Kind
B2
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 (25)

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.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 25, 2013
From: MAHLER, GRANT; WINCKLER, ANDREAS; VAHIDI, ARDALAN; LUCKOW, ANDRE
To: BAYERISCHE MOTOREN WERKE AKTIENGESELLSCHAFT; CLEMSON UNIVERSITY
Reel/Frame 030286/0571 →
Continuity (1)
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