Integration of historical user experience analytics into route recommendations

• US 9,400,186 B1
• Filed: 02/16/2015
• Issued: 07/26/2016
• Est. Priority Date: 02/16/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bank, Judith H., Harpur, Liam S., Lyle, Ruthie D., O'Sullivan, Patrick J., Sun, Lin
• Primary Examiner(s): Jeanglaud, Gertrude Arthur
• Application Number:
  US14/623,266
• Publication Number:
  US 20160238400A1
• Time in Patent Office: 526 Days
• Field of Search: 701/410, 701/424, 701/439, 701/532, 701/538, 705/14.58
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3617 using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• CPC Class Codes: G06Q 30/0261 based on user location

Abstract

Situational traveler experiences are collected over time from a number of diverse travelers. The situational traveler experiences are associated with one or more locations traversed by the number of diverse travelers using previous travel route recommendations. Contextual categories of the situational traveler experiences are identified. Historical analytics are performed on the collected situational traveler experiences within the contextual categories of the situational traveler experiences. A historically-contextual travel route suggestion, derived from the historical analytics performed on the collected situational traveler experiences within the contextual categories of the situational traveler experiences, is provided as part of a new travel route recommendation requested by a new traveler.

Claims

1. A computer-implemented method, comprising:

collecting over time, from a plurality of diverse travelers, adverse situational travel experiences associated with traveling along a travel route used during travel by the plurality of diverse travelers responsive to previous travel route recommendations;

identifying contextual categories of the adverse situational travel experiences associated with traveling along the travel route;

performing historical analytics on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences; and

providing, as part of a new travel route recommendation that recommends the travel route to a new traveler, a historically-contextual travel route suggestion, derived from the historical analytics performed on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, that improves travel of the new traveler while traveling along the travel route.

2. The computer-implemented method of claim 1, where collecting over time, from the plurality of diverse travelers, the adverse situational travel experiences associated with traveling along the travel route used during travel by the plurality of diverse travelers responsive to the previous travel route recommendations comprises:

formulating a historical travel route situational context model usable to identify travel route recommendations in accordance with the contextual categories of the adverse situational travel experiences; and

capturing the adverse situational travel experiences associated with traveling along the travel route used during travel by the plurality of diverse travelers responsive to the previous travel route recommendations into the contextual categories of the adverse situational travel experiences within the formulated historical travel route situational context model.

3. The computer-implemented method of claim 1, where performing historical analytics on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences comprises:

determining, within a historical travel route situational context model that captures into the contextual categories of the adverse situational travel experiences, similarities among the collected adverse situational travel experiences; and

identifying the determined similarities as the historically-contextual travel route suggestion that is provided as part of the new travel route recommendation that recommends the travel route to the new traveler.

4. The computer-implemented method of claim 3, where the determined similarities among the collected adverse situational travel experiences within the historical travel route situational context model comprise similarities in at least one of traffic conditions, time of day, weather conditions, percentage of drivers missing an exit, and road conditions associated with traveling along the travel route used during travel by the plurality of diverse travelers.

5. The computer-implemented method of claim 1, where providing, as part of the new travel route recommendation that recommends the travel route to the new traveler, the historically-contextual travel route suggestion, derived from the historical analytics performed on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, that improves the travel of the new traveler while traveling along the travel route comprises:

identifying, within a historical travel route situational context model that captures into the contextual categories of the adverse situational travel experiences, the collected adverse situational travel experiences that are pertinent to contemporaneous travel along the travel route at a travel time associated with the new travel route recommendation; and

providing the pertinent adverse situational travel experiences identified within the historical travel route situational context model to the new traveler along with the new travel route recommendation.

6. The computer-implemented method of claim 1, where the contextual categories of the adverse situational travel experiences are selected from a group consisting of a traffic conditions category, a time of day category, a weather conditions category, a percentage of drivers missing an exit category, and a road conditions category.

7. The computer-implemented method of claim 1, further comprising providing a user interface (UI) that allows users to provide the adverse situational travel experiences as user situational travel feedback input regarding traveling along the travel route in association with the previous travel route recommendations into a historical travel route situational context model.

8. A system, comprising:

a memory; and

a processor programmed to;

collect within the memory over time, from a plurality of diverse travelers, adverse situational travel experiences associated with traveling along a travel route used during travel by the plurality of diverse travelers responsive to previous travel route recommendations;

identify contextual categories of the adverse situational travel experiences associated with traveling along the travel route;

perform historical analytics on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences; and

provide, as part of a new travel route recommendation that recommends the travel route to a new traveler, a historically-contextual travel route suggestion, derived from the historical analytics performed on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, that improves travel of the new traveler while traveling along the travel route.

9. The system of claim 8, where, in being programmed to collect within the memory over time, from the plurality of diverse travelers, the adverse situational travel experiences associated with traveling along the travel route used during travel by the plurality of diverse travelers responsive to the previous travel route recommendations, the processor is programmed to:

formulate a historical travel route situational context model usable to identify travel route recommendations in accordance with the contextual categories of the adverse situational travel experiences; and

capture the adverse situational travel experiences associated with traveling along the travel route used during travel by the plurality of diverse travelers responsive to the previous travel route recommendations into the contextual categories of the adverse situational travel experiences within the formulated historical travel route situational context model.

10. The system of claim 8, where, in being programmed to perform historical analytics on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, the processor is programmed to:

determine, within a historical travel route situational context model that captures into the contextual categories of the adverse situational travel experiences, similarities among the collected adverse situational travel experiences; and

identify the determined similarities as the historically-contextual travel route suggestion that is provided as part of the new travel route recommendation that recommends the travel route to the new traveler; and

where the determined similarities among the collected adverse situational travel experiences within the historical travel route situational context model comprise similarities in at least one of traffic conditions, time of day, weather conditions, percentage of drivers missing an exit, and road conditions associated with traveling along the travel route used during travel by the plurality of diverse travelers.

11. The system of claim 8, where, in being programmed to provide, as part of the new travel route recommendation that recommends the travel route to the new traveler, the historically-contextual travel route suggestion, derived from the historical analytics performed on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, that improves the travel of the new traveler while traveling along the travel route, the processor is programmed to:

identify, within a historical travel route situational context model that captures into the contextual categories of the adverse situational travel experiences, the collected adverse situational travel experiences that are pertinent to contemporaneous travel along the travel route at a travel time associated with the new travel route recommendation; and

provide the pertinent adverse situational travel experiences identified within the historical travel route situational context model to the new traveler along with the new travel route recommendation.

12. The system of claim 8, where the contextual categories of the adverse situational travel experiences are selected from a group consisting of a traffic conditions category, a time of day category, a weather conditions category, a percentage of drivers missing an exit category, and a road conditions category.

13. The system of claim 8, where the processor is further programmed to provide a user interface (UI) that allows users to provide the adverse situational travel experiences as user situational travel feedback input regarding traveling along the travel route in association with the previous travel route recommendations into a historical travel route situational context model.

14. A computer program product, comprising:

a computer readable storage medium having computer readable program code embodied therewith, wherein the computer readable storage medium is not a transitory signal per se and where the computer readable program code when executed on a computer causes the computer to;

collect over time, from a plurality of diverse travelers, adverse situational travel experiences associated with traveling along a travel route used during travel by the plurality of diverse travelers using responsive to previous travel route recommendations;

identify contextual categories of the adverse situational travel experiences associated with traveling along the travel route;

perform historical analytics on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences; and

provide, as part of a new travel route recommendation that recommends the travel route to a new traveler, a historically-contextual travel route suggestion, derived from the historical analytics performed on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, that improves travel of the new traveler while traveling along the travel route.

15. The computer program product of claim 14, where, in causing the computer to collect over time, from the plurality of diverse travelers, the adverse situational travel experiences associated with traveling along the travel route used during travel by the plurality of diverse travelers responsive to the previous travel route recommendations, the computer readable program code when executed on the computer causes the computer to:

formulate a historical travel route situational context model usable to identify travel route recommendations in accordance with the contextual categories of the adverse situational travel experiences; and

capture the adverse situational travel experiences associated with traveling along the travel route used during travel by the plurality of diverse travelers responsive to the previous travel route recommendations into the contextual categories of the adverse situational travel experiences within the formulated historical travel route situational context model.

16. The computer program product of claim 14, where, in causing the computer to perform historical analytics on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, the computer readable program code when executed on the computer causes the computer to:

determine, within a historical travel route situational context model that captures into the contextual categories of the adverse situational travel experiences, similarities among the collected adverse situational travel experiences; and

identify the determined similarities as the historically-contextual travel route suggestion that is provided as part of the new travel route recommendation that recommends the travel route to the new traveler.

17. The computer program product of claim 16, where the determined similarities among the collected adverse situational travel experiences within the historical travel route situational context model comprise similarities in at least one of traffic conditions, time of day, weather conditions, percentage of drivers missing an exit, and road conditions associated with traveling along the travel route used during travel by the plurality of diverse travelers.

18. The computer program product of claim 14, where, in causing the computer to provide, as part of the new travel route recommendation that recommends the travel route to the new traveler, the historically-contextual travel route suggestion, derived from the historical analytics performed on the collected adverse situational travel experiences associated with traveling along the travel route within the contextual categories of the adverse situational travel experiences, that improves the travel of the new traveler while traveling along the travel route, the computer readable program code when executed on the computer causes the computer to:

identify, within a historical travel route situational context model that captures into the contextual categories of the adverse situational travel experiences, the collected adverse situational travel experiences that are pertinent to contemporaneous travel along the travel route at a travel time associated with the new travel route recommendation; and

provide the pertinent adverse situational travel experiences identified within the historical travel route situational context model to the new traveler along with the new travel route recommendation.

19. The computer program product of claim 14, where the contextual categories of the adverse situational travel experiences are selected from a group consisting of a traffic conditions category, a time of day category, a weather conditions category, a percentage of drivers missing an exit category, and a road conditions category.

20. The computer program product of claim 14, where the computer readable program code when executed on the computer further causes the computer to provide a user interface (UI) that allows users to provide the adverse situational travel experiences as user situational travel feedback input regarding traveling along the travel route in association with the previous travel route recommendations into a historical travel route situational context model.