Gm Global Technolgoy Operations, Inc.

Ashok Yendluri

Fan Bai

Bo Yu

Donald K Grimm

Vivek Vijaya Kumar

Hariharan Krishnan

Lawrence A Bush

David A Craig

Sandeep Vig

Kevin K Hoang

Quan Zhang

Jonathan Wilson

A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: receive safety messages from a plurality of vehicles in communication with the edge server, determine an uplink frequency recommendation for transmitting safety messages from at least one vehicle of the plurality of vehicles based on at least one of a position error or a collision risk, determine a downlink frequency recommendation for transmitting safety messaging to at least one vehicle of the plurality of vehicles based on at least one of a position error or a collision risk, and transmit the frequency recommendations to the at least one vehicle.

Adaptive messaging within a cloud and edge computing environment for V2X applications

A sequence of images and a vehicle location associated with each of the images is received at a traffic light ROI management system. At least one traffic light is detected in each image. A ECS traffic light ROI is defined for each image. The ECS traffic light ROI encloses the detected traffic lights. A visual feature template is generated for each image. The visual feature template is based on the ECS traffic light ROI for the image. Each visual feature template is mapped to the vehicle location associated with the image to a HD map. The HD map is transmitted to an autonomous vehicle to enable the autonomous vehicle to identify a real-time traffic light ROI in a real-time image based on a match between a first visual feature template and real-time visual features of the real-time image at the vehicle location associated with the first visual feature template.

Systems and methods for providing traffic light region of interest parameters to an autonomous vehicle

Systems and methods are provided for interpreting traffic information. A method includes: receiving, by a processor, visual data from vehicles, wherein the visual data is associated with an intersection of a roadway having one or more lanes; receiving, by the processor, vehicle data from the vehicles, wherein the vehicle data is associated with the intersection of the roadway; determining, by the processor, a first state of a traffic light associated with the intersection based on the visual data; determining, by the processor, a second state of the traffic light associated with the intersection based on the vehicle data; correlating, by the processor, the first state and the second state based on a time synchronization; assigning, by the processor, the traffic light to a lane of the roadway based on the correlating; and communicating, by the processor, the traffic light to lane assignment for use in controlling a vehicle.

Methods and systems for traffic light state monitoring and traffic light to lane assignment

A system and method for locating a traffic light at a host vehicle. A probe vehicle obtains image data on an intersection that includes the traffic light when the probe vehicle is at the intersection and identifies the traffic light in the intersection from the data. A remote processor creates an observed node in a digital map corresponding to the traffic light and updates a mapped position of a mapped node within the digital map based on an observed position of the observed node. The host vehicle uses the mapped node of the digital map to locate the traffic light when the host vehicle is at the intersection.

Method and apparatus for traffic light positioning and mapping using crowd-sensed data

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Southfield, MI, United States of America

Ashok Yendluri