Patents by Inventor Jane MacFarlane

Jane MacFarlane has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10371545
    Abstract: An approach is provided for classifying probe data into qualitative categories to determine a point of interest. The approach involves processing and/or facilitating a processing of probe data to determine one or more trajectories associated with one or more probes. The approach also involves determining one or more clips of the one or more trajectories associated with one or more locations at which the one or more probes lingered based, at least in part, on at least one space threshold value, at least one time threshold value, or a combination thereof. The approach further involves causing, at least in part, an extraction of one or more probe parameter values from the one or more clips. The approach also involves causing, at least in part, a classification of the one or more probe parameter values into one or more qualitative categories.
    Type: Grant
    Filed: March 4, 2015
    Date of Patent: August 6, 2019
    Assignee: HERE Global B.V.
    Inventor: Jane Macfarlane
  • Patent number: 10359295
    Abstract: An approach is provided for generating trajectory bundles for map data analysis. The approach involves receiving probe data associated with the bounded geographic area. The probe data are collected from sensors of a plurality of devices traveling in the bounded geographic area, and includes probe points indicating a position, a heading, a speed, a time, or a combination thereof. The approach also involves constructing a plurality of trajectories from the probe points to represent respective movement paths of said each of the plurality of devices. The approach further involves computing similarities among a plurality of curves represented by the plurality of trajectories. The approach further involves clustering the plurality of trajectories into trajectory bundles based on the similarities with each bundle representing a possible maneuver within the bounded geographic area. The approach further involves generating a map of the bounded geographic area based on the trajectory bundles.
    Type: Grant
    Filed: September 8, 2016
    Date of Patent: July 23, 2019
    Assignee: HERE Global B.V.
    Inventors: Matei Stroila, Bo Xu, Jane Macfarlane
  • Patent number: 10332309
    Abstract: An approach is provided for identifying objects present in mesh representation of a geo-location, generating accurate 3D models for the objects, and aligning the 3D models to their corresponding objects in an application. The approach comprises processing and/or facilitating a processing of textured three-dimensional mesh data in one or more regions of interest to cause, at least in part, a generation of at least one two-dimensional depth image representation. The approach further comprises causing, at least in part, a filtering of the textured three-dimensional mesh data in the one or more regions of interest to remove mesh data below at least one threshold height based, at least in part, on the at least one two-dimensional depth image representation.
    Type: Grant
    Filed: September 23, 2015
    Date of Patent: June 25, 2019
    Assignee: HERE Global B.V.
    Inventors: Xiaoqing Liu, Jeffrey Adachi, Antonio Haro, Jane MacFarlane
  • Patent number: 10314001
    Abstract: An approach is provided for providing adaptive location sampling in mobile devices. The approach involves determining one or more maneuvers from among a plurality of one or more links representing a localized area of a transportation network. Each of the one or more maneuvers is a combination of two or more adjacent links of the one or more links. The approach also involves determining a road length and a speed attribute for each link in said each maneuver. The approach further involves calculating a travel time for said each maneuver based on the road length and the speed attribute of said each link. The approach further involves calculating a sampling interval for the mobile device traveling in the localized area based on the travel time. The mobile device is configured to collect probe data using one or more sensors at the sampling interval while traveling in the localized area.
    Type: Grant
    Filed: December 22, 2016
    Date of Patent: June 4, 2019
    Assignee: HERE Global B.V.
    Inventors: Jane Macfarlane, Bo Xu
  • Publication number: 20190051154
    Abstract: The disclosed embodiments relate to prediction of traffic dynamics. A descriptive model is provided that uses historical probe data to create “tidal-like” patterns for the usual dynamics on the road network and creates a framework for taking a future time, e.g. in terms of month, day, time, and suggesting a typical speed for the specified road network link at that specific time. With this model, better predictions for estimated time of arrival will be derived. As opposed to blindly extrapolating from a static model, the disclosed embodiments dynamically adapt to current conditions using real time data to adapt, based on current conditions, the model from which a predicted speed may be determined.
    Type: Application
    Filed: October 12, 2018
    Publication date: February 14, 2019
    Inventors: Jane Macfarlane, Robert Grossman, Collin Bennett, James Pivarski
  • Publication number: 20180350232
    Abstract: An approach is provided for next token prediction based on previously observed tokens. The approach involves receiving an observed time series of tokens, wherein each of the tokens represents an observed data pattern. The approach also involves adding a most recent token from the observed time series of tokens into a variable token set. The approach further involves processing a historical token set to determine a historical token sequence comprising the variable token set followed by a next token. The approach further involves recursively adding a next most recent token from the observed time series of tokens into the variable token set for processing until the next token following the variable token set in the determined historical token sequence is unique or meets a target number of possible predictions. The approach further involves presenting the next token as a predicted next token of the observed time series of tokens.
    Type: Application
    Filed: May 30, 2018
    Publication date: December 6, 2018
    Inventors: Davide PIETROBON, Andrew LEWIS, Jane MACFARLANE, Robert BERRY
  • Patent number: 10127809
    Abstract: The disclosed embodiments relate to prediction of traffic dynamics. A descriptive model is provided that uses historical probe data to create “tidal-like” patterns for the usual dynamics on the road network and creates a framework for taking a future time, e.g. in terms of month, day, time, and suggesting a typical speed for the specified road network link at that specific time. With this model, better predictions for estimated time of arrival will be derived. As opposed to blindly extrapolating from a static model, the disclosed embodiments dynamically adapt to current conditions using real time data to adapt, based on current conditions, the model from which a predicted speed may be determined.
    Type: Grant
    Filed: December 18, 2017
    Date of Patent: November 13, 2018
    Assignee: HERE Global B.V.
    Inventors: Jane Macfarlane, Robert Grossman, Collin Bennett, James Pivarski
  • Publication number: 20180240026
    Abstract: An approach is provided for semantic-free traffic prediction. The approach involves dividing a travel-speed data stream into a plurality of travel-speed patterns. The travel-speed data stream represents vehicle travel speeds occurring in a road network. The approach also involves representing each of the plurality of travel-speed patterns by a respective token. The respective token is selected from a dictionary of tokens representing a plurality of travel-speed templates determined from historical travel-speed data. The approach further involves matching a sequence of the respective tokens corresponding to said each of the plurality of travel-speed patterns to a best-fit sequence of tokens determined from the historical travel-speed data. The approach further involves determining a predicted sequence of tokens based on the best-fit sequence of tokens, and generating a traffic prediction for the road network based on the predicted sequence of tokens.
    Type: Application
    Filed: February 22, 2017
    Publication date: August 23, 2018
    Inventors: Davide PIETROBON, Andrew LEWIS, Jane MACFARLANE
  • Publication number: 20180218614
    Abstract: Drone space is defined according to a building model and a buffer space. At least one three-dimensional geometry is identified from the building model. The buffer space is calculated from the three-dimensional geometry. Coordinates for a drone air space are defined based on the buffer space. At least one path segment may be identified based on the coordinates for the drone air space, and the coordinates for drone air space are stored in a map database in association with the at least one path segment.
    Type: Application
    Filed: March 22, 2018
    Publication date: August 2, 2018
    Inventors: Jane Macfarlane, Jeffrey Adachi, Aaron Dannenbring
  • Patent number: 10025771
    Abstract: An approach is provided for sharing annotations and recalling geospatial information. The approach involves processing and/or facilitating a processing of communication information exchanged between a plurality of devices engaged in a communication session to cause, at least in part, a parsing of geospatial information from the communication information. The approach also involves determining whether the geospatial information meet, at least in part, one or more logic thresholds. The one or more logic thresholds are for determining a potential relevance of the geospatial information to the communication session, the plurality of devices, one or more users of the plurality of devices, or a combination thereof. The approach further involves causing, at least in part, a presentation of the geospatial information to the plurality of devices, the one or more users, or a combination thereof based, at least in part, on the determination.
    Type: Grant
    Filed: May 7, 2015
    Date of Patent: July 17, 2018
    Assignee: HERE Global B.V.
    Inventors: Jane MacFarlane, Craig Barnes
  • Publication number: 20180184395
    Abstract: An approach is provided for providing adaptive location sampling in mobile devices. The approach involves determining one or more maneuvers from among a plurality of one or more links representing a localized area of a transportation network. Each of the one or more maneuvers is a combination of two or more adjacent links of the one or more links. The approach also involves determining a road length and a speed attribute for each link in said each maneuver. The approach further involves calculating a travel time for said each maneuver based on the road length and the speed attribute of said each link. The approach further involves calculating a sampling interval for the mobile device traveling in the localized area based on the travel time. The mobile device is configured to collect probe data using one or more sensors at the sampling interval while traveling in the localized area.
    Type: Application
    Filed: December 22, 2016
    Publication date: June 28, 2018
    Inventors: Jane MACFARLANE, Bo XU
  • Patent number: 9965950
    Abstract: An approach is provided for classifying a traffic jam from probe data. The approach involves receiving the probe data that is map-matched to a roadway on which the traffic jam is detected. The probe data is collected from one or more vehicles traveling the roadway. The approach also involves determining a jam area of the roadway based on the probe data. The jam area corresponds to one or more segments of the roadway affected by the traffic jam. The approach further involves determining a set of features indicated by the probe data from a portion of the probe data collected from the jam area. The approach further involves classifying, using a machine learning classifier, the traffic jam as either a recurring traffic jam or a non-recurring traffic jam based on the set of features.
    Type: Grant
    Filed: June 3, 2016
    Date of Patent: May 8, 2018
    Assignee: HERE Global B.V.
    Inventors: Bo Xu, Tiffany Barkley, Andrew Lewis, Jane MacFarlane, Davide Pietrobon, Matei Stroila
  • Patent number: 9953540
    Abstract: Drone space is defined according to a building model and a buffer space. At least one three-dimensional geometry is identified from the building model. The buffer space is calculated from the three-dimensional geometry. Coordinates for a drone air space are defined based on the buffer space. At least one path segment may be identified based on the coordinates for the drone air space, and the coordinates for drone air space are stored in a map database in association with the at least one path segment.
    Type: Grant
    Filed: June 16, 2015
    Date of Patent: April 24, 2018
    Assignee: HERE Global B.V.
    Inventors: Jane Macfarlane, Jeffrey Adachi, Aaron Dannenbring
  • Publication number: 20180108251
    Abstract: The disclosed embodiments relate to prediction of traffic dynamics. A descriptive model is provided that uses historical probe data to create “tidal-like” patterns for the usual dynamics on the road network and creates a framework for taking a future time, e.g. in terms of month, day, time, and suggesting a typical speed for the specified road network link at that specific time. With this model, better predictions for estimated time of arrival will be derived. As opposed to blindly extrapolating from a static model, the disclosed embodiments dynamically adapt to current conditions using real time data to adapt, based on current conditions, the model from which a predicted speed may be determined.
    Type: Application
    Filed: December 18, 2017
    Publication date: April 19, 2018
    Inventors: Jane Macfarlane, Robert Grossman, Collin Bennett, James Pivarski
  • Publication number: 20180066957
    Abstract: An approach is provided for generating trajectory bundles for map data analysis. The approach involves receiving probe data associated with the bounded geographic area. The probe data are collected from sensors of a plurality of devices traveling in the bounded geographic area, and includes probe points indicating a position, a heading, a speed, a time, or a combination thereof. The approach also involves constructing a plurality of trajectories from the probe points to represent respective movement paths of said each of the plurality of devices. The approach further involves computing similarities among a plurality of curves represented by the plurality of trajectories. The approach further involves clustering the plurality of trajectories into trajectory bundles based on the similarities with each bundle representing a possible maneuver within the bounded geographic area. The approach further involves generating a map of the bounded geographic area based on the trajectory bundles.
    Type: Application
    Filed: September 8, 2016
    Publication date: March 8, 2018
    Inventors: Matei STROILA, Bo XU, Jane MACFARLANE
  • Patent number: 9911326
    Abstract: An approach is provided for processing and/or facilitating a processing of probe trace data to determine one or more mode indicators, wherein the one or more mode indicators include, at least in part, one or more attributes of the probe trace data. The approach involves causing, at least in part, a modeling of one or more statistical patterns of at least one pedestrian mode of transport, at least one non-pedestrian mode of transport, or a combination thereof based, at least in part, on determining one or more probabilities that one or more mode indicators are associated with the at least one pedestrian mode of transport, the at least one non-pedestrian mode of transport, or a combination thereof.
    Type: Grant
    Filed: March 31, 2015
    Date of Patent: March 6, 2018
    Assignee: HERE Global B.V.
    Inventors: Bo Xu, Jane MacFarlane
  • Patent number: 9875652
    Abstract: The disclosed embodiments relate to prediction of traffic dynamics. A descriptive model is provided that uses historical probe data to create “tidal-like” patterns for the usual dynamics on the road network and creates a framework for taking a future time, e.g. in terms of month, day, time, and suggesting a typical speed for the specified road network link at that specific time. With this model, better predictions for estimated time of arrival will be derived. As opposed to blindly extrapolating from a static model, the disclosed embodiments dynamically adapt to current conditions using real time data to adapt, based on current conditions, the model from which a predicted speed may be determined.
    Type: Grant
    Filed: November 28, 2016
    Date of Patent: January 23, 2018
    Assignee: HERE Global B.V.
    Inventors: Jane Macfarlane, Robert Grossman, Collin Bennett, James Pivarski
  • Patent number: 9842282
    Abstract: An approach is provided for classifying objects that are present at a geo-location and providing an uncluttered presentation of images of some of the objects in an application such as a map application. The approach includes determining one or more regions of interest associated with at least one geo-location, wherein the one or more regions of interest are at least one textured three-dimensional representation of one or more objects that may be present at the at least one geo-location. The approach also includes processing and/or facilitating a processing of the at least one textured three-dimensional representation to determine at least one two-dimensional footprint and three-dimensional geometry information for the one or more objects.
    Type: Grant
    Filed: May 22, 2015
    Date of Patent: December 12, 2017
    Assignee: HERE Global B.V.
    Inventors: Xiaoqing Liu, Jeffrey Adachi, Antonio Haro, Jane MacFarlane
  • Publication number: 20170352262
    Abstract: An approach is provided for classifying a traffic jam from probe data. The approach involves receiving the probe data that is map-matched to a roadway on which the traffic jam is detected. The probe data is collected from one or more vehicles traveling the roadway. The approach also involves determining a jam area of the roadway based on the probe data. The jam area corresponds to one or more segments of the roadway affected by the traffic jam. The approach further involves determining a set of features indicated by the probe data from a portion of the probe data collected from the jam area. The approach further involves classifying, using a machine learning classifier, the traffic jam as either a recurring traffic jam or a non-recurring traffic jam based on the set of features.
    Type: Application
    Filed: June 3, 2016
    Publication date: December 7, 2017
    Inventors: Bo XU, Tiffany BARKLEY, Andrew LEWIS, Jane MACFARLANE, Davide PIETROBON, Matei STROILA
  • Publication number: 20170337811
    Abstract: A method comprising determining speed-time cluster application histogram data set for a link segment that comprises a plurality of speed-time cluster application histogram data elements, each speed-time cluster application histogram data element identifying a speed-time cluster and an applicable duration of the speed-time cluster for the link segment throughout a histogram duration, for each speed-time cluster application histogram data element, determining a free-flow speed that is representative of a non-congestion speed indicated by the speed-time cluster, determining a historically normalized free-flow speed for the link segment that is a weighted average of the free-flow speed determined for each speed-time cluster application histogram data element weighted by the applicable duration of the speed-time cluster application histogram data element, and identifying a transit speed of the link segment as being the historically normalized free-flow speed is disclosed.
    Type: Application
    Filed: August 7, 2017
    Publication date: November 23, 2017
    Inventor: Jane Macfarlane