TRAVEL DEPARTURE TIME DETERMINATION USING SOCIAL MEDIA AND REGIONAL EVENT INFORMATION

• US 20140358435A1
• Filed: 06/03/2013
• Published: 12/04/2014
• Est. Priority Date: 06/03/2013
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bell, Denise A., Geiger, Pamela F., Lawrence, Leah A., Mejia, Irgelkha D.
• Granted Patent: US 9,212,925 B2
• Time in Patent Office: Days
• US Class Current: 701/527
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• 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 1/096775 where the origin of the information is a central station
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

A request is received from a route traveler for a suggested departure time associated with travel to a destination. Community event and social media information, related to events and activities near a travel route to the destination, is evaluated. The suggested departure time is determined based upon the community event and social media information related to the events and activities near the travel route to the destination. The suggested departure time determined based upon the community event and social media information related to the events and activities near the travel route to the destination is provided.

Claims

1. A method, comprising:

receiving, at a processor, a request from a route traveler for a suggested departure time associated with travel to a destination;

evaluating community event and social media information related to events and activities near a travel route to the destination;

determining the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination; and

providing the suggested departure time determined based upon the community event and social media information related to the events and activities near the travel route to the destination.

2. The method of claim 1, where:

receiving, at the processor, the request from the route traveler for the suggested departure time associated with travel to the destination comprises receiving a plurality of requests from a plurality of route travelers for suggested departure times associated with travel to a plurality of destinations; and

determining the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination comprises determining time-distributed suggested departure times that mitigate a traffic impact of each of the plurality of route travelers to the plurality of destinations.

3. The method of claim 2, where determining the time-distributed suggested departure times that mitigate the traffic impact of each of the plurality of route travelers to the plurality of destinations comprises adjusting each of the time-distributed suggested departure times such that route travelers that have a shorter travel time are suggested to leave earlier than route travelers that have longer travel time.

4. The method of claim 1, where:

receiving, at the processor, the request from the route traveler for the suggested departure time associated with travel to the destination comprises receiving a plurality of requests from a plurality of route travelers for suggested departure times associated with travel to a plurality of destinations; and

determining the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination comprises;

determining a number of the plurality of route travelers that are requesting the plurality of requests for the suggested departure times; and

prioritizing the suggested departure times based upon specified arrival times associated with each of the plurality of requests for the suggested departure times.

5. The method of claim 1, where evaluating the community event and social media information related to the events and activities near the travel route to the destination comprises:

determining a distance along the travel route to the destination;

identifying a region of traffic influence peripheral to the travel route based upon the determined distance, where the region of traffic influence peripheral to the travel route increases proportionally to increases in the determined distance along the travel route to the destination; and

evaluating community event and social media information related to all events and activities within the identified region of traffic influence.

6. The method of claim 5, where identifying the region of traffic influence peripheral to the travel route based upon the determined distance comprises identifying a geographic circular region of traffic influence with a circumference bounded by a radius equivalent to the determined distance along the travel route to the destination that emanates from the destination.

7. The method of claim 1, further comprising:

iteratively capturing arrival times of a plurality of route travelers relative to previously-suggested departure times for the plurality of route travelers;

combining the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination;

determining an updated suggested departure time based upon the combination of the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination; and

providing the updated suggested departure time based upon the combination of the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination.

8. A system, comprising:

a memory; and

a processor programmed to;

receive a request from a route traveler for a suggested departure time associated with travel to a destination;

evaluate community event and social media information obtained from the memory related to events and activities near a travel route to the destination;

determine the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination; and

provide the suggested departure time determined based upon the community event and social media information related to the events and activities near the travel route to the destination.

9. The system of claim 8, where, in being programmed to:

receive the request from the route traveler for the suggested departure time associated with travel to the destination, the processor is programmed to receive a plurality of requests from a plurality of route travelers for suggested departure times associated with travel to a plurality of destinations; and

determine the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination, the processor is programmed to determine time-distributed suggested departure times that mitigate a traffic impact of each of the plurality of route travelers to the plurality of destinations.

10. The system of claim 9, where, in being programmed to determine the time-distributed suggested departure times that mitigate the traffic impact of each of the plurality of route travelers to the plurality of destinations, the processor is programmed to adjust each of the time-distributed suggested departure times such that route travelers that have a shorter travel time are suggested to leave earlier than route travelers that have longer travel time.

11. The system of claim 8, where, in being programmed to:

receive the request from the route traveler for the suggested departure time associated with travel to the destination, the processor is programmed to receive a plurality of requests from a plurality of route travelers for suggested departure times associated with travel to a plurality of destinations; and

determine the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination, the processor is programmed to;

determine a number of the plurality of route travelers that are requesting the plurality of requests for the suggested departure times; and

prioritize the suggested departure times based upon specified arrival times associated with each of the plurality of requests for the suggested departure times.

12. The system of claim 8, where, in being programmed to evaluate the community event and social media information obtained from the memory related to the events and activities near the travel route to the destination, the processor is programmed to:

determine a distance along the travel route to the destination;

identify a region of traffic influence peripheral to the travel route based upon the determined distance, where the region of traffic influence peripheral to the travel route increases proportionally to increases in the determined distance along the travel route to the destination; and

evaluate community event and social media information obtained from the memory related to all events and activities within the identified region of traffic influence.

13. The system of claim 8, where the processor is further programmed to:

iteratively capture arrival times of a plurality of route travelers relative to previously-suggested departure times for the plurality of route travelers;

combine the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination;

determine an updated suggested departure time based upon the combination of the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination; and

provide the updated suggested departure time based upon the combination of the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination.

14. A computer program product, comprising:

a computer readable storage medium having computer readable program code embodied therewith, where the computer readable program code when executed on a computer causes the computer to;

receive a request from a route traveler for a suggested departure time associated with travel to a destination;

evaluate community event and social media information related to events and activities near a travel route to the destination;

determine the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination; and

provide the suggested departure time determined based upon the community event and social media information related to the events and activities near the travel route to the destination.

15. The computer program product of claim 14, where, in causing the computer to:

receive the request from the route traveler for the suggested departure time associated with travel to the destination, the computer readable program code when executed on the computer causes the computer to receive a plurality of requests from a plurality of route travelers for suggested departure times associated with travel to a plurality of destinations; and

determine the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination, the computer readable program code when executed on the computer causes the computer to determine time-distributed suggested departure times that mitigate a traffic impact of each of the plurality of route travelers to the plurality of destinations.

16. The computer program product of claim 15, where, in causing the computer to determine the time-distributed suggested departure times that mitigate the traffic impact of each of the plurality of route travelers to the plurality of destinations, the computer readable program code when executed on the computer causes the computer to adjust each of the time-distributed suggested departure times such that route travelers that have a shorter travel time are suggested to leave earlier than route travelers that have longer travel time.

17. The computer program product of claim 14, where, in causing the computer to:

receive the request from the route traveler for the suggested departure time associated with travel to the destination, the computer readable program code when executed on the computer causes the computer to receive a plurality of requests from a plurality of route travelers for suggested departure times associated with travel to a plurality of destinations; and

determine the suggested departure time based upon the community event and social media information related to the events and activities near the travel route to the destination, the computer readable program code when executed on the computer causes the computer to;

determine a number of the plurality of route travelers that are requesting the plurality of requests for the suggested departure times; and

prioritize the suggested departure times based upon specified arrival times associated with each of the plurality of requests for the suggested departure times.

18. The computer program product of claim 14, where, in causing the computer to evaluate the community event and social media information related to the events and activities near the travel route to the destination, the computer readable program code when executed on the computer causes the computer to:

determine a distance along the travel route to the destination;

identify a region of traffic influence peripheral to the travel route based upon the determined distance, where the region of traffic influence peripheral to the travel route increases proportionally to increases in the determined distance along the travel route to the destination; and

evaluate community event and social media information related to all events and activities within the identified region of traffic influence.

19. The computer program product of claim 18, where, in causing the computer to identify the region of traffic influence peripheral to the travel route based upon the determined distance, the computer readable program code when executed on the computer causes the computer to identify a geographic circular region of traffic influence with a circumference bounded by a radius equivalent to the determined distance along the travel route to the destination that emanates from the destination.

20. The computer program product of claim 14, where the computer readable program code when executed on the computer further causes the computer to:

iteratively capture arrival times of a plurality of route travelers relative to previously-suggested departure times for the plurality of route travelers;

combine the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination;

determine an updated suggested departure time based upon the combination of the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination; and

provide the updated suggested departure time based upon the combination of the captured arrival times of the plurality of route travelers with the community event and social media information related to the events and activities near the travel route to the destination.