Gm Global Technolgoy Operations, Inc.

Kaydee Hartmann

Mason D Gemar

Najah Ghalyan

Sean Douglas Vermillion

Rajesh Ayyalasomayajula

Mubassira Khan

A method for detecting road edges at a predetermined intersection, comprising: receiving, by the controller, aerial imagery data about the predetermined intersection; receiving, by the controller, vehicle telemetry data from at least one vehicle passing through the predetermined intersection; detecting, using the aerial imagery data and generative adversarial networks (GANs) executed on the controller, road edges at the predetermined intersection; classifying, using the vehicle telemetry data and a random forest classifier (RFC) executed on the controller, each vehicle trajectory passing through the predetermined intersection with a label corresponding to a unique maneuver to create a maneuver labeling at the predetermined intersection; constructing, using the maneuver labeling determined by the RFC and the road edges, a probabilistic finite state automata (PFSA) to pair inbound lanes with outbound lanes at the predetermined intersection; and determining lane edges at the predetermined intersection using a homotopy model.

System and method for detecting road and lane connections at intersections

A system, map server and method of navigating a vehicle through an intersection. The map server includes a remote processor and a communication device. The remote processor determines a first road edge for a first road entering an intersection and a second road edge for a second road entering the intersection. The remote processor constructs an intersection edge that connects a first point on the first road edge to a second point on the second road edge. The communication device communicates the intersection edge to the vehicle. A vehicle processor at the vehicle navigates the vehicle through the intersection using the intersection edge.

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Austin, TX, United States of America

Kaydee Hartmann