Abstract: 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 ho

Abstract: 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 ho

Abstract: A method for updating a map including receiving a first image depicting a geographical area including a first roadway and an occluded area, determining a location of the first roadway segment in response to the first image, receiving a plurality of vehicle telemetry data associated with the first roadway segment and a second roadway segment within the occluded area, updating a map data with the location of the first roadway, determining a location of the occluded area in response to the first image and the plurality of vehicle telemetry data associated with the second roadway segment, requesting an alternate data in response to determination of the location of the occluded area, determining a location of a second roadway segment in response to the alternate data wherein the second roadway segment was occluded in the first image, and updating the map data with the location of the second roadway segment.

Abstract: The present application relates to predicting an automated driving system disengagement for a motor vehicle by calculating a route between a host vehicle location and a destination, segmenting the route into at least a first route segment and a second route segment, generating a first motion path for the first route segment and controlling the host vehicle over the first route segment, generating a second motion path for the second route segment and simulating a simulated host vehicle operation over the second route segment, predicting a disengagement event in response to the simulated host vehicle operation over the second route segment, and providing a driver alert indicative of the disengagement event while controlling the host vehicle over the first route segment.