Patents by Inventor Mark Tenzer

Mark Tenzer 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).

  • Generating trajectories from implicit neural models
    Patent number: 12287213
    Abstract: Generating trajectories from an implicit neural representation (INR) model to predict human mobility in uncertain traffic conditions includes receiving geocoordinate data representing vehicle motion observations of a traffic pattern; receiving a road network based on the geocoordinate data; training the INR model to learn continuous, latent fields of stochastic traffic properties over space and time based on the geocoordinate data; utilizing the INR model to extract spatio-temporal speed distributions from the geocoordinate data; applying a near-shortest-path, heuristic algorithm, weighted by predictions of the INR model, to produce real-world routing choices for traversing the road network; generating trajectories for transportation between an origin and destination in the road network using the algorithm and the predictions of the INR model, wherein the trajectories reflect non-deterministic and diverse route choices in the road network; and outputting generated trajectories to improve routing choices for a
    Type: Grant
    Filed: October 20, 2024
    Date of Patent: April 29, 2025
    Assignee: Novateur Research Solutions
    Inventors: Mark Tenzer, Emmanuel Tung, Khurram Hassan-Shafique, Zeeshan Rasheed
  • Generating trajectories from implicit neural models
    Patent number: 12152889
    Abstract: Generating trajectories from an implicit neural representation (INR) model to predict human mobility in uncertain traffic conditions includes receiving geocoordinate data representing vehicle motion observations of a traffic pattern; receiving a road network based on the geocoordinate data; training the INR model to learn continuous, latent fields of stochastic traffic properties over space and time based on the geocoordinate data; utilizing the INR model to extract spatio-temporal speed distributions from the geocoordinate data; applying a near-shortest-path, heuristic algorithm, weighted by predictions of the INR model, to produce real-world routing choices for traversing the road network; generating trajectories for transportation between an origin and destination in the road network using the algorithm and the predictions of the INR model, wherein the trajectories reflect non-deterministic and diverse route choices in the road network; and outputting generated trajectories to improve routing choices for a
    Type: Grant
    Filed: December 7, 2023
    Date of Patent: November 26, 2024
    Assignee: Novateur Research Solution
    Inventors: Mark Tenzer, Emmanuel Tung, Khurram Hassan-Shafique, Zeeshan Rasheed