Gm Global Technolgoy Operations, Inc.

Michael A Losh

Upali Priyantha Mudalige

Donald K Grimm

Manoj Sharma

Sayyed Rouhollah Jafari Tafti

Orhan Bulan

Lawrence A Bush

Brent Navin Roger Bacchus

Aravindhan Mani

Fan Bai

Shuqing Zeng

Bo Yu

David Hahn Clifford

Soheil Samii

Kamran Ali

Syed B Mehdi

Joon Hwang

Shu Chen

Guangyu J Zou

Peter John Giles

Grant L Meade

Gui Chen

Keun Jae Kim

Yehenew G Mengistu

Sheetal Mahesh

Indranil Palit

A preemptive maneuvering system for viewing a status of a traffic control device by one or more cameras of an autonomous vehicle includes one or more controllers, where a moving obstruction is in front of the autonomous vehicle. The one or more controllers execute instructions to instruct the autonomous vehicle to execute one or more preemptive maneuvers to position the autonomous vehicle at the target following distance from the moving obstruction along the roadway.

Preemptive maneuvering system for viewing a traffic control device

A system for facilitating interaction between an autonomous vehicle and an external interface in proximity to the autonomous vehicle including a plurality of external sensors positioned on the autonomous vehicle and adapted to collect data relative to an environment surrounding and in proximity to the autonomous vehicle, a controller having a wireless communication module, the wireless communication module adapted to facilitate wireless data exchange between the controller and remote entities, the controller adapted to receive data collected from the plurality of external sensors and identify an interaction mode for the external interface, a microphone and a speaker adapted to facilitate audible communication between the controller and the external interface, and a video display adapted to display visual information to the external interface, wherein the controller is adapted to perform an interaction with the external interface.

Autonomous vehicle interaction with physical environment

A system for providing information related to a charge status of an electric vehicle when the electric vehicle is connected to a charging station includes a system controller in communication with an electrical system within the electric vehicle and adapted to monitor information related to a charge status of the electric vehicle, and provide notification, to a third-party, of the charge status of the electric vehicle.

Method of providing information related to status of electric vehicle

A method for quantifying map errors includes receiving first map data and second map data. The method includes receiving a road topographic map. The method further includes dividing the road into road segments. The method further includes creating a plurality of bounding boxes for each of the plurality of road segments. The method includes creating a first map tile and a second map tile by filtering out the bounding boxes. The method includes executing point cloud registration to align the plurality of first data points in the first map tile with the plurality of second data points in the second map tile to determine a plurality of absolute offsets between the plurality of first data points and the plurality of second data points. The method includes determining a relative map error between the first map and the second map based on the absolute offsets.

Method and system for quantifying map errors

A method of providing information related to a charge status of an electric vehicle includes monitoring, with a system controller in communication with an electrical system within the vehicle, information related to a charge status of the vehicle, and, displaying, with the system controller, for a person in proximity of the vehicle, information related to a charge status of the vehicle.

A scene creation system for an autonomous vehicle includes one or more controllers executing instructions to receive perception data and map data of a roadway the autonomous vehicle is traveling along, and identify a plurality of lane segments of the roadway that the autonomous vehicle travels along based on the perception data and the map data. The one or more controllers connect the plurality of lane segments together based on a spatial relationship between the plurality of lane segments to create a lane graph. The one or more controllers classify each of the plurality of lane segments of the lane graph to one or more lane attributes and reassemble the plurality of lane segments to create a representation of the roadway. The one or more controllers recreate a scene of an environment surrounding the autonomous vehicle based on the representation of the lanes that are part of the roadway.

Scene creation system for an autonomous vehicle

In one example implementation according to aspects of the present disclosure, a computer-implemented method for generating map features includes receiving, by a processing device, aerial image data. The method further includes receiving, by the processing device, telemetry data. The method further includes performing, by the processing device, data fusion on the aerial image data and the telemetry data to generate map features. The method further includes controlling, by the processing system, a vehicle based at least in part on the map features.

Generating map features based on aerial data and telemetry data

A method for generating an occlusion map using crowdsourcing includes receiving occlusion data from a host vehicle. The occlusion data includes a plurality of virtual detection lines each extending from the sensor and intersecting an off-road area. The method further includes marking all non-occluded points that are located inside the off-road area and that are located within a predetermined distance from each plurality of virtual detection lines. The method further includes determining a non-occluded region inside the off-road area using the non-occluded points that have been previously marked inside the off-road area, wherein the non-occluded region is part of non-occlusion data. The method further includes generating an occlusion map using the non-occlusion data. The method further includes transmitting the occlusion map to the host vehicle. The method can also determine an occlusion caused by an elevation peak.

System and method for generating an occlusion map using crowdsourcing

Systems and methods are provided for generating a map for use in controlling a vehicle. In one embodiment, a method includes: receiving, by a processor, aerial image data depicting an environment; processing, by the processor, the aerial image data with a plurality of trained deep learning models to produce a predicted radar map; and controlling the vehicle based on the predicted radar map.

Methods and systems for generating radar maps

A system for generating a map includes a processing device configured to determine a provenance of each received map of a plurality of maps, parse each received map into objects of interest, and compare the objects of interest to identify one or more sets of objects representing a common feature. For each set of objects, the processing device is configured to select a subset of the set of objects based on the provenance associated with each object in the set of objects, and calculate a similarity metric for each object in the subset. The similarity metric is selected from an alignment between an object and a reference object in the subset, and/or a positional relationship between the object and the reference object. The processing device is configured to generate a common object representing the common feature based on the similarity metric, and generate a merged map including the common object.

Combining heterogeneous types of maps

Systems and methods are provided for interpreting traffic information by a vehicle. In one embodiment, a method includes: receiving, by a processor, sensor data from one or more sensing devices of the vehicle, where the sensor data depicts a traffic device in an environment of the vehicle; receiving, by the processor, map data associated with the environment of the vehicle, where the map data includes traffic devices; matching, by the processor, the traffic device of the sensor data with a traffic device of the map data; determining, by the processor, a probability distribution of a traffic signal associated with the matched traffic devices based on a Hidden Markov model (HMM); and planning, by the processor, control of the vehicle based on the probability distribution.

Methods and systems for interpretating traffic signals and negotiating signalized intersections

A system and method for providing a map via a cloud-based system is disclosed. The method includes requesting, by a controller of an autonomous vehicle, a map data from a cloud-based server. The map data is stored on the cloud-based server. The method also includes receiving map data from the cloud-based server. The method also includes autonomously navigating the autonomous vehicle based on the received map data.

System and method for providing a map to autonomous vehicles via a cloud-based system

A method for vehicle-to-vehicle communication is disclosed. The method includes establishing a communication connection between the first vehicle and the second vehicle, receiving one or more communications from the second vehicle, determining, by the first vehicle, vehicle parameter targets based on the one or more communications, communicating the vehicle parameter targets and one or more vehicle device commands to the second vehicle, and determining at least one vehicle control signal for the second vehicle based on the vehicle parameter targets and the one or more vehicle device commands.

Methods and systems for vehicle-to-vehicle communication

A method for prioritizing potential threats identified by vehicle active safety systems. The method includes providing context information including map information, vehicle position information, traffic assessment information, road condition information, weather condition information, and vehicle state information. The method calculates a system context value for each active safety system using the context information. Each active safety system provides a system threat level value, a system braking value, a system steering value, and a system throttle value. The method calculates an overall threat level value using all of the system context values and all of the system threat level values. The method then provides a braking request value to vehicle brakes based on all of the system braking values, a throttle request value to a vehicle throttle based on all of the system throttle values, and a steering request value to vehicle steering based on all of the system steering values.

Context-aware threat response arbitration

A system and method for providing lane changing maneuvers in an autonomously driven vehicle. The vehicle includes a navigation controller that provides a planned route for the vehicle to follow and a vehicle controller that receives route information from the navigation controller and provides steering, braking and throttle control for the vehicle to follow the route. Either the navigation controller or the vehicle controller may initiate a lane change maneuver to cause the vehicle to be steered from a travel lane to an adjacent lane. In response to the lane change requirement, the navigation controller provides a route segment to the vehicle controller and a lane-change zone so that the vehicle controller can steer the vehicle to the adjacent lane while in the lane-change zone.

Growing community of inventors

Rochester Hills, MI, United States of America

Michael A Losh