Ford Global Technolgoies, LLC

Daniel Levine

Jinesh J Jain

Vidya Nariyambut Murali

Gintaras Vincent Puskorius

Sneha Kadetotad

Kyu Jeong Han

The present invention extends to methods, systems, and computer program products for formulating lane level routing plans. In general, aspects of the invention are used in motorized vehicles to guide a driver to a terminal vehicle configuration according to a lane level routing plan that balances travel time with routing plan robustness. A lane level routing plan can be based on terminal guidance conditions (e.g., exiting a highway in the correct off ramp lane), statistical patterns of lanes themselves, current vehicle state, and state of the local environment near the vehicle. Lane level routing plans can be communicated to the driver with audio, visual, and/or haptic cues. Lane level routing plans can be revised online and in (essentially) real-time in response to changing conditions in the local environment (e.g., a trailing vehicle in a neighboring lane has decided to increase speed).

Formulating lane level routing plans

Methods, devices and apparatuses pertaining to identifying the candidate road segments for autonomous operations are described. A method may involve obtaining data of a first plurality of road segments that are permitted for one or more autonomous operations. The method may further include generating a road segment template based on the data of the first plurality of road segments, and reconstructing a second plurality of road segments based on the road segment template to obtain a plurality of reconstructed road segments.

Autonomous driving certification generalizer

Methods, devices and apparatuses pertaining to aberrant driver classification and reporting are described. A method may involve receiving a message from a user of a first vehicle, the message indicating an instance of aberrant driving of a second vehicle. The method may also involve determining that the instance has occurred using one or more classifiers. The method may further involve collecting information of the second vehicle and generating a warning message based on the information.

Aberrant driver classification and reporting

Systems, methods, and devices for sensor fusion are disclosed herein. A system for sensor fusion includes one or more sensors, a model component, and an inference component. The model component is configured to calculate values in a joint-probabilistic graphical model based on the sensor data. The graphical model includes nodes corresponding to random variables and edges indicating correlations between the nodes. The inference component is configured to detect and track obstacles near a vehicle based on the sensor data and the model using a weighted-integrals-and-sums-by-hashing (WISH) algorithm.

Probabilistic inference using weighted-integrals-and-sums-by-hashing for object tracking

Methods, devices, and systems pertaining to in-vehicle tutorials are described. A method may involve receiving a request for an in-vehicle tutorial of an operational feature of a vehicle from a user and simulating expected driving behavior corresponding to the operational feature in the vehicle. The method may further include monitoring operational behavior of the user, comparing the operational behavior with the expected driving behavior, and providing a feedback to the user based on the comparison.

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San Mateo, CA, United States of America

Daniel Levine