METHOD AND APPARATUS FOR FORECASTING FLOW OF TRAFFIC

• US 20160321923A1
• Filed: 02/16/2015
• Published: 11/03/2016
• Est. Priority Date: 02/17/2014
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: SEO, Youngjun
• Granted Patent: US 10,235,880 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096758 where no selection takes place on the transmitted or the received information
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/096791 where the origin of the information is another vehicle
• CPC Class Codes: G08G 1/162 event-triggered
• CPC Class Codes: G08G 1/163 involving continuous checking
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles

Abstract

Disclosed are a method and an apparatus for forecasting the flow of traffic. The method includes: detecting measurement information of a vehicle by using a sensor; generating vector data based on the measurement information; and transmitting the generated vector data.

Claims

1. A measurement method using an electronic device installed in a vehicle, the measurement method comprising:

detecting measurement information of the vehicle by using a sensor;

generating vector data based on the measurement information; and

transmitting the generated vector data.

2. The measurement method of claim 1, wherein the detecting of the measurement information comprises:

detecting angular velocity information of the vehicle by using a gyro sensor;

detecting location information of the vehicle by using a Global Positioning System (GPS) sensor; and

detecting acceleration information of the vehicle by using an acceleration sensor.

3. The measurement method of claim 2, wherein the generating of the vector data comprises:

generating the vector data by using at least one of the angular velocity information, the location information, and the acceleration information; and

correcting the vector data by using an earth magnetic field sensor.

4. The measurement method of claim 1, wherein the generating of the vector data comprises:

receiving sensor information from a sensor installed in the vehicle or another vehicle adjacent to the vehicle; and

using the sensor information as the measurement information of the vehicle or correcting the vector data by using the sensor information.

5. The measurement method of claim 1, further comprising:

receiving sensor information from a sensor installed in the vehicle or another vehicle adjacent to the vehicle;

detecting dangerous situation information based on the sensor information; and

informing of the detected dangerous situation information.

6. The measurement method of claim 5, further comprising:

comparing the dangerous situation information with a preset degree of danger; and

differently informing of the dangerous situation information according to a corresponding degree of danger based on a result of the comparison.

7. The measurement method of claim 6, wherein the differently informing of the dangerous situation information comprises:

differently setting at least one of sound information, voice information, and display information associated with the dangerous situation information according to the degree of danger; and

outputting at least one of the set sound information, voice information, and display information.

8. The measurement method of claim 1, further comprising:

receiving dangerous situation information from an external device; and

differently informing of the dangerous situation information according to a distance.

9. A method of measuring the flow of traffic using an electronic device, the method comprising:

collecting vector data from a portable device within a vehicle;

determining an accident type based on the vector data; and

filtering the accident type to forecast the flow of traffic.

10. The method of claim 9, wherein the determining of the accident type comprises determining the accident type by using at least one of a size, acceleration, and angular velocity of the vector data.

11. The method of claim 9, wherein the filtering of the accident type comprises filtering the accident type based on at least one of road information, road history information, road condition information, weather information, and time information.

12. The method of claim 9, wherein the filtering of the accident type comprises:

generating vehicle vector data based on location information of the vehicle;

calculating sensor error information by using the vehicle vector data; and

filtering the accident type based on the calculated sensor error information.

13. The method of claim 9, wherein the filtering of the accident type comprises:

detecting a vector pattern based on vector data of a plurality of vehicles; and

filtering the accident type based on the vector pattern.

14. The method of claim 9, further comprising:

generating dangerous situation information associated with the flow of traffic;

calculating a distance from the vehicle based on location information of the dangerous situation information; and

informing a portable device within the vehicle of different dangerous situation information according to the distance.

15. An electronic device comprising:

a sensor for detecting measurement information of a vehicle;

a controller for generating vector data based on the measurement information; and

a communication unit for transmitting the generated vector data.

16. The electronic device of claim 15, wherein the sensor includes at least one of a gyro sensor, a GPS sensor, and an acceleration sensor, and the gyro sensor detects angular velocity information of the vehicle, the GSP sensor detects location information of the vehicle, and the acceleration sensor detects acceleration information of the vehicle.

17. The electronic device of claim 16, wherein the controller generates the vector data by using at least one of the location information and the acceleration information and corrects the vector data by using an earth magnetic field sensor.

18. The electronic device of claim 15, wherein the communication unit receives sensor information from a sensor installed in the vehicle or another vehicle adjacent to the vehicle and the controller uses the received sensor information as measurement information of the vehicle or detects dangerous situation information based on the sensor information and informs of the detected dangerous situation information.

19. The electronic device of claim 18, wherein the controller compares the dangerous situation information with a preset degree of danger and differently sets the dangerous situation information according to a corresponding degree of danger based on a result of the comparison.

20. The electronic device of claim 19, wherein the controller differently sets at least one of sound information, voice information, and display information associated with the dangerous situation information according to the degree of danger, the electronic device further comprising an output unit for outputting at least one of the set sound information, voice information, and display information.

21. An electronic device comprising:

a communication unit for collecting vector data from a portable device within a vehicle; and

a controller for determining an accident type based on the vector data and filtering the accident type to forecast the flow of traffic.

22. The electronic device of claim 21, wherein the controller filters the accident type based on at least one of road information, road history information, road condition information, weather information, and time information.

23. The electronic device of claim 21, wherein the controller generates vehicle vector data based on location information of the vehicle, calculates sensor error information by using the vehicle vector data, and filters the accident type based on the calculated sensor error information.

24. The electronic device of claim 21, wherein the controller detects a vector pattern based on vector data of a plurality of vehicles and filters the accident type based on the vector pattern.

25. The electronic device of claim 21, wherein the controller generates dangerous situation information associated with the flow of traffic, calculates a distance from the vehicle based on location information of the dangerous situation information, and informs different dangerous situation information according to the distance to a portable device within the vehicle through the communication unit.