Management of mobile objects

• US 10,535,266 B2
• Filed: 06/21/2017
• Issued: 01/14/2020
• Est. Priority Date: 06/21/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Akiyama, Kazuhito, Fukuda, Mari Abe, Ogihara, Hiroya, Sasaki, Taku, Unno, Asuka, Yamamoto, Gaku
• Primary Examiner(s): Khatib, Rami
• Application Number:
  US15/628,828
• Publication Number:
  US 20180374356A1
• Time in Patent Office: 937 Days
• Field of Search: None
• CPC Class Codes: B60W 30/08 Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 30/0953 the prediction being responsive to vehicle dynamic parameters
• CPC Class Codes: B60W 30/0956 the prediction being responsive to traffic or environmental parameters
• CPC Class Codes: G05D 1/021 specially adapted to land vehicles
• CPC Class Codes: G06F 16/489 using time information
• 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 1/0145 for active traffic flow control
• CPC Class Codes: G08G 1/162 event-triggered
• CPC Class Codes: G08G 7/00 Traffic control systems for simultaneous control of two or more different kinds of craft

Abstract

An embodiment of the invention may include a method, computer program product and computer system for managing mobile objects. The embodiment may identify, by an event agent (EA), an event occurring in a geographic space in which a plurality of mobile objects move. The embodiment may determine the event is an expected event based on predicting time-series changes of the event handled by the EA. The embodiment may manage, by a predictive environment agent (PEA), the expected event.

Claims

1. A computer-method comprising:

identifying, by an event agent (EA), an event occurring in a geographic space in which a plurality of mobile objects move;

determining the event is an expected event based on predicting time-series changes of the event, wherein determining the event is the expected event includes determining a plurality of events correspond respectively to a plurality of future timings, wherein determining the event is the expected event includes updating a plurality of predictive environment agents (PEAs) in response to reaching an origin timing of the plurality of future timings, according to passage of time; and

managing, by a predictive environment agent (PEA) of the plurality of predictive environment agents (PEAs), the expected event, wherein managing the mobile object comprises performing automatic driving or driving assist.

2. The method according to claim 1, wherein

updating the plurality of PEAs includes shifting the plurality of PEAs to be earlier in time series order, and reassigning the plurality of PEAs to the plurality of future timings updated with a future timing following the origin timing of the plurality of future timings.

3. The method according to claim 1, wherein

identifying, by the event agent (EA), an event occurring in a geographic space in which a plurality of mobile objects move includes event generation of generating the event based on information comprising information from outside a system containing the EA and detection information that is detected by at least one mobile object among the plurality of mobile objects.

4. The method according to claim 3, wherein

identifying, by the event agent (EA), an event occurring in a geographic space in which a plurality of mobile objects move further includes determining an expected event to be handled by at least one of a plurality of PEAs.

5. The method according to claim 4 further comprising:

determining a derived expected event that is predicted to derive from the generated expected event.

6. The method according to claim 4, wherein

the EA and the plurality of PEAs are assigned for every same region in the geographic space.

7. The method according to claim 6, wherein

determining the expected event to be handled by each of at least one of the plurality of PEAs in response to generation of one expected event, which is positioned in an adjacent region adjacent to a region to which one EA is assigned, corresponding to an event determined in the region according to processing of the one EA, transmitting the one expected event to an adjacent PEA assigned to an adjacent region.

8. The method according to claim 7, further comprising:

transmitting the one expected event generated based on determining the expected event to be handled by each of at least one of the plurality of PEAs in response to generation of one expected event to the adjacent PEA via an adjacent EA assigned to the adjacent region.

9. The method according to claim 8 further comprising:

deleting, from the PEA, an expected event that was completed.

10. The method of claim 1, further comprising causing an action of a mobile object of the plurality of mobile objects based on the expected event.

11. A computer program product for managing mobile object, the computer program product comprising:

a non-transitory computer-readable storage device and program instructions stored on the non-transitory computer-readable storage device, the program instructions comprising;

receiving an event detected in a geographic space by a mobile object of a plurality of mobile objects; and

determining the event is an expected event based on predicting time-series changes of the event, wherein determining the event is the expected event includes determining a plurality of events correspond respectively to a plurality of future timings, wherein determining the event is the expected event includes updating a plurality of predictive environment agents (PEAs) in response to reaching an origin timing of the plurality of future timings, according to passage of time; and

managing, by a predictive environment agent (PEA) of the plurality of predictive environment agents (PEAs), the expected event, wherein managing the mobile object comprises performing automatic driving or driving assist.

12. The computer program product according to claim 11, wherein

updating the plurality of PEAs includes shifting the plurality of PEAs to be earlier in time series order, and reassigning the plurality of PEAs to the plurality of future timings updated with a future timing following the origin timing of the plurality of future timings.

13. The computer program product according to claim 11, wherein

determining the event is the expected event includes associating information including at least one of an expected movement direction, an expected movement speed, an existence probability, a dissipation probability, and a change probability with the expected event.

14. The computer program product of claim 11, further comprising causing an action of a mobile object of the plurality of mobile objects based on the expected event.

15. A computer system for managing mobile object, the computer system comprising:

a processor, a computer-readable tangible storage device, and program instructions stored on computer-readable tangible storage device for execution by the processor, the program instructions comprising;

receiving an event detected in a geographic space by a mobile object of a plurality of mobile objects; and

determining the event is an expected event based on predicting time-series changes of the event, wherein determining the event is the expected event includes determining a plurality of events correspond respectively to a plurality of future timings, wherein determining the event is the expected event includes updating a plurality of predictive environment agents (PEAs) in response to reaching an origin timing of the plurality of future timings, according to passage of time; and

managing, by a predictive environment agent (PEA) of the plurality of predictive environment agents (PEAs) the expected event, wherein managing the mobile object comprises performing automatic driving or driving assist.

16. The computer system according to claim 15, wherein updating the plurality of PEAs includes shifting the plurality of PEAs to be earlier in time series order, and reassigning the plurality of PEAs to the plurality of future timings updated with a future timing following the origin timing of the plurality of future timings.

17. The computer system of claim 15, further comprising causing an action of a mobile object of the plurality of mobile objects based on the expected event.