VEHICLE MANAGEMENT AND CONTROL FOR SAFE DRIVING AND COLLISION AVOIDANCE

• US 20140032015A1
• Filed: 07/30/2013
• Published: 01/30/2014
• Est. Priority Date: 07/30/2012
• Status: Active Grant

• Current Assignee: KT Corporation
• Original Assignee: KT Corporation
• Inventors: CHUN, Young-Sam, KIM, Han-Lim, BAEK, Jin-Woo, CHOI, Jae-Won
• Granted Patent: US 8,948,929 B2
• Time in Patent Office: Days
• US Class Current: 701/2
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/164 Centralised systems, e.g. external to vehicles
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network

Abstract

The disclosure is related to a method of managing and controlling vehicles for safe driving. In the method, at least one virtual zone may be defined based on information collected from a plurality of vehicles in motion and related servers in real time. Vehicles may be grouped into at least one vehicle groups according to a predetermined similarity condition based on the collected information. An abnormal driving pattern model may be generated based on a driving pattern of each vehicle in each vehicle group. At least one area of a virtual zone may be designated as a spot when at least one vehicle having a driving pattern matched with the abnormal driving pattern model in the at least one area. Safe driving information may be transmitted to at least one vehicle having driving patterns matched with attributes of the spot among vehicles entering each virtual zone.

Claims

1. A method of managing and controlling vehicles for safe driving, the method comprising:

collecting information from a plurality of vehicles in motion and related servers in real time;

defining at least one virtual zone based on the collected information;

grouping vehicles into at least one vehicle group according to a predetermined similarity condition based on the collected information;

generating an abnormal driving pattern model based on a driving pattern of each vehicle in each vehicle group;

designating at least one area of a virtual zone as a spot when at least one vehicle having a driving pattern matched with the abnormal driving pattern model is in the at least one area; and

transmitting safe driving information to at least one vehicle having driving patterns matched with attributes of the spot among vehicles entering each virtual zone.

2. The method of claim 1, wherein the collected information includes vehicle information, user profile information, weather information, traffic information, road condition information, accident information, and construction information.

3. The method of claim 1, wherein:

the collecting the information includes continuously collecting and updating the information from the plurality of vehicles in motion and the related servers; and

modifying or eliminating the at least one defined virtual zone according to the continuously collected and updated information.

4. The method of claim 1, wherein:

the at least one defined virtual zone is a target geographical area for managing and controlling vehicles passing through the target geographical area; and

the target geographical area has attributes matched with predetermined management conditions.

5. The method of claim 1, wherein the grouping vehicles includes:

detecting vehicles having similarities matched with the predetermined similarity condition based on vehicle information and user profile information obtained from the collected information; and

grouping the detected vehicles as a same vehicle group.

6. The method of claim 5, wherein the predetermined similarity condition includes at least one of similarities between drivers, similarities between vehicles, and similarities between drivers and vehicles.

7. The method of claim 1, wherein the grouping vehicles includes:

grouping vehicles entering into or locating in a virtual zone to at least one vehicle group according to the predetermined similarity condition.

8. The method of claim 1, wherein the grouping vehicles includes:

updating the at least one vehicle group when at least one of associated vehicles leaves the virtual zone and when at least one vehicle having the predetermined similarities enters the virtual zone.

9. The method of claim 1, wherein the generating an abnormal driving pattern model includes:

obtaining driving patterns of vehicles in each vehicle group based on the collected information;

analyzing the obtained driving patterns by comparing a driving pattern of one vehicle with others and finding abnormal driving patterns among the obtained driving patterns; and

modeling the abnormal driving patterns based on the analysis result to generate the abnormal driving pattern model for each vehicle group.

10. The method of claim 9, wherein the generating an abnormal driving pattern model includes:

updating the generated abnormal driving pattern model of each vehicle group by repeatedly performing the obtaining the driving patterns, the analyzing the obtained driving patterns, and the modeling the abnormal driving patterns.

11. The method of claim 1, wherein the spot is generated, modified, and eliminated according to at least one of movements of vehicles, road conditions, weather conditions, and constructions in a corresponding virtual zone.

12. The method of claim 1, wherein the designating at least one area of a virtual zone as a spot includes:

analyzing correlation between one spot with others in an associated virtual zone; and

updating the associated virtual zone based on the analysis result.

13. The method of claim 1, wherein the designating at least one area of a virtual zone as a spot includes:

collecting information from vehicles passing through the generated spot;

maintaining the generated spot when the vehicles have driving patterns matched with attributes of the generated spot based on the collected information;

eliminating the generated spot when the vehicles have no driving patterns matched with attributes of the generated spot based on the collected information.

14. The method of claim 1, wherein the safe driving information includes velocity matching information for synchronizing speeds of vehicles associated with a same vehicle group or associated with a same spot.

15. A server of managing and controlling vehicles for safe driving, the server comprising:

a virtual zone generator configured to define at least one virtual zone based on information collected from a plurality of vehicles in motion and related servers in real time;

a vehicle group generator configured to group vehicles into at least one vehicle group according to a predetermined similarity condition based on the collected information;

a pattern model generator configured to generate an abnormal driving pattern model based on a driving pattern of each vehicle in each vehicle group;

a spot generator configured to designate at least one area of a virtual zone as a spot when at least one vehicle having a driving pattern matched with the abnormal driving pattern model in the at least one area; and

a vehicle controller configured to transmit safe driving information to at least one vehicle having driving patterns matched with attributes of the spot among vehicles entering each virtual zone.

16. The server of claim 15, wherein the vehicle group generator is configured to:

detect vehicles having similarities matched with the predetermined similarity condition based on vehicle information and user profile information obtained from the collected information; and

group the detected vehicles as a same vehicle group.

17. The server of claim 15, wherein the vehicle group generator is configured to:

group vehicles entering into or locating in a virtual zone to at least one vehicle group according to the predetermined similarity condition; and

update the at least one vehicle group when at least one of associated vehicles leaves the virtual zone and when at least one vehicle having the predetermined similarities enters the virtual zone.

18. The server of claim 15, wherein the pattern model generator is configured to:

obtain driving patterns of vehicles in each vehicle group based on the collected information;

analyze the obtained driving patterns by comparing a driving pattern of one vehicle with others and find abnormal driving patterns among the obtained driving patterns;

model the abnormal driving patterns based on the analysis result to generate the abnormal driving pattern model for each vehicle group; and

update the generated abnormal driving pattern model of each vehicle group by repeatedly performing the obtaining the driving patterns, the analyzing the obtained driving patterns, and the modeling the abnormal driving patterns.

19. The server of claim 15, wherein the spot generator is configured to:

analyze correlation between one spot with others in an associated virtual zone; and

update the associated virtual zone based on the analysis result.

20. The server of claim 15, wherein the spot generator is configured to:

collect information from vehicles passing through the generated spot;

maintain the generated spot when the vehicles have driving patterns matched with attributes of the generated spot based on the collected information;

eliminate the generated spot when the vehicles have no driving patterns matched with attributes of the generated spot based on the collected information.