Method for Differentiating Traffic Data Obtained from Probe Vehicles

• US 20120173530A1
• Filed: 01/03/2011
• Published: 07/05/2012
• Est. Priority Date: 01/03/2011
• Status: Active Grant

• Current Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Original Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Inventors: Kurciska, Maja, Vaghefinazari, Pedram
• Granted Patent: US 8,452,771 B2
• Time in Patent Office: Days
• US Class Current: 707/738
• CPC Class Codes: G06F 16/29 Geographical information databases
• 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 1/0133 for classifying traffic situation

Abstract

A remote server receives traffic data from a plurality of probe vehicles traveling on roadways. The remote server stores the received traffic data in a regular lane database and/or a carpool lane database. The remote server differentiates the received traffic data for storage in the appropriate database based on the number of probe vehicles associated with each speed pattern observed within the received traffic data.

Claims

1. A method for storing probe data gathered by a navigation system at a remote server, comprising:

receiving data from a plurality of probe vehicles at the remote server;

determining at least two speed patterns associated with the received data;

classifying the received data from each of the plurality of probe vehicles according to one of a first speed pattern and a second speed pattern;

calculating a number of probe vehicles associated with each of the first speed pattern and the second speed pattern;

storing the data classified as the first speed pattern in a regular lanes database;

storing the data classified as the second speed pattern in a carpool lanes database; and

wherein the data is classified as the first speed pattern if the number of probe vehicles associated with the first speed pattern is greater than the number of probe vehicles associated with the second speed pattern.

2. The method according to claim 1, further comprising:

matching the received data from each of the plurality of probe vehicles to one of a plurality of links included in a map database in communication with the remote server.

3. The method according to claim 2, wherein the step of matching the received data includes a step of identifying a carpool lane link.

4. The method according to claim 1, further comprising:

receiving traffic information from a traffic database in communication with the remote server; and

comparing the received data from each of the plurality of probe vehicles to the traffic information.

5. The method according to claim 4, wherein the traffic database is a real-time traffic database.

6. The method according to claim 4, wherein the traffic database is an historical traffic database.

7. The method according to claim 1, wherein the step of calculating the number of probe vehicles is performed for a set time interval.

8. The method according to claim 1, wherein the at least two speed patterns are each determined based on an average speed value of the plurality of probe vehicles associated with a particular roadway, road link, and/or travel lane at a particular time.

9. A method for differentiation of collected probe data from a navigation system at a remote server in communication with a regular lanes database and a carpool lanes database, comprising:

receiving probe data from a plurality of vehicles at the remote server;

fitting the received probe data to one of a first speed pattern and a second speed pattern;

determining a first number of vehicles associated with the received probe data fitting the first speed pattern;

determining a second number of vehicles associated with the received probe data fitting the second speed pattern;

wherein the received probe data associated with the smaller of the first number and the second number is stored in the carpool lanes database; and

wherein the remaining received probe data is stored in the regular lanes database.

10. The method according to claim 9, further comprising:

matching the received probe data to a plurality of road links included in a map database in communication with the remote server;

assigning link identifiers to the matched probe data identifying specific road links contained in the map database; and

wherein the received probe data stored in the carpool lanes database and/or the regular lanes database includes the link identifiers.

11. The method according to claim 10, wherein the step of matching the received probe data includes a step of identifying a carpool lane link.

12. The method according to claim 9, further comprising:

receiving traffic information from a traffic database in communication with the remote server; and

comparing the received probe data to the traffic information.

13. The method according to claim 12, wherein the traffic database is a real-time traffic database.

14. The method according to claim 12, wherein the traffic database is an historical traffic database.

15. The method according to claim 9, wherein the steps of determining the first number of vehicles and determining the second number of vehicles are performed for a substantially similar time interval.

16. The method according to claim 9, wherein the first speed pattern is determined based on a first average speed value of the plurality of probe vehicles associated with a first road link obtained at a particular time;

and

wherein the second speed pattern is determined based on a second average speed value of the plurality of probe vehicles associated with a second road link at a particular time.

17. A method for sorting traffic data from a plurality of vehicles with a navigation system at a remote server;

comprising;

receiving traffic data from a plurality of vehicles at the remote server;

determining whether the received traffic data corresponds to at least two speed patterns;

comparing a first number of vehicles associated with a first speed pattern with a second number of vehicles associated with a second speed pattern;

storing a first portion of the received traffic data associated with the larger of the first number of vehicles and the second number of vehicles in a regular lanes database; and

storing a second portion of the received traffic data associated with the smaller of the first number of vehicles and the second number of vehicles in a carpool lanes database.

18. The method according to claim 17, further comprising:

matching the received traffic data to a plurality of road links included in a map database in communication with the remote server;

assigning link identifiers to the matched traffic data identifying specific road links contained in the map database; and

wherein each of the first portion of the received traffic data and the second portion of the received traffic data includes the link identifiers.

19. The method according to claim 18, wherein the step of matching the received traffic data includes a step of identifying a carpool lane link.

20. The method according to claim 17, further comprising:

receiving traffic information from a traffic database in communication with the remote server; and

comparing the received traffic data to the traffic information.

21. The method according to claim 20, wherein the traffic database is at least one of a real-time traffic database and an historical traffic database.

22. The method according to claim 17, wherein the step of comparing the first number of vehicles and the second number of vehicles is performed for a set time interval.

23. The method according to claim 17, wherein the at least two speed patterns are each determined based on an average speed value of the plurality of vehicles associated with a particular roadway, road link, and/or travel lane at a particular time.

24. A method for differentiation of collected probe data from a navigation system at a remote server in communication with a regular lanes database and a carpool lanes database, comprising:

receiving probe data from a plurality of vehicles at the remote server;

calculating a first probability for a first one of the plurality of vehicles being associated with a carpool lane;

wherein the first probability is calculated based on a first condition;

calculating a second probability for the first one of the plurality of vehicles being associated with the carpool lane;

wherein the second probability is calculated based on a second condition;

determining whether the first one of the plurality of vehicles is associated with the carpool lane or a regular lane based on the first probability and the second probability;

wherein the received probe data associated with the first one of the plurality of vehicles is stored in the carpool lanes database if the first one of the plurality of vehicles is determined to be associated with the carpool lane; and

wherein the received probe data associated with the first one of the plurality of vehicles is stored in the regular lanes database if the first one of the plurality of vehicles is determined to be associated with the regular lane.

25. The method according to claim 24, further comprising:

calculating a third probability for the first one of the plurality of vehicles being associated with the carpool lane;

wherein the third probability is calculated based on a third condition; and

determining whether the first one of the plurality of vehicles is associated with the carpool lane or the regular lane based on the first probability, the second probability, and the third probability.

26. The method according to claim 24, further comprising:

calculating a new first probability for a second one of the plurality of vehicles being associated with a carpool lane;

wherein the new first probability is calculated based on a new first condition associated with the second one of the plurality of vehicles;

calculating a new second probability for the second one of the plurality of vehicles being associated with the carpool lane;

wherein the new second probability is calculated based on a new second condition associated with the second one of the plurality of vehicles;

determining whether the second one of the plurality of vehicles is associated with the carpool lane or the regular lane based on the new first probability and the new second probability;

wherein the received probe data associated with the second one of the plurality of vehicles is stored in the carpool lanes database if the second one of the plurality of vehicles is determined to be associated with the carpool lane; and

wherein the received probe data associated with the second one of the plurality of vehicles is stored in the regular lanes database if the second one of the plurality of vehicles is determined to be associated with the regular lane.

27. The method according to claim 24, wherein the remote server determines whether the first one of the plurality of vehicles is associated with the carpool lane or the regular lane based on a single equation comprising the first probability and the second probability.

28. The method according to claim 27, wherein the step of determining whether the first one of the plurality of vehicles is associated with the carpool lane or the regular lane further comprises applying at least a first weighting factor to the first probability and a second weighting factor to the second probability.