Ford Global Technolgoies, LLC

Kyle J Carey

Vidya Nariyambut Murali

Tejaswi Koduri

Alexandru Mihai Gurghian

Timothy D Zwicky

Aakar Mehra

Surjya Sarathi Ray

Rajiv Sithiravel

Smita Vinayak Bailur

David A LaPorte

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to generate a first map, based on vehicle sensor data, of a free space on a roadway in which a first vehicle can operate without contacting roadway edges and non-stationary objects on the roadway, the first map including roadway lane markings in an environment around the first vehicle, wherein the non-stationary objects include one or more second vehicles and generate a second map of free space in the environment around the first vehicle by determining B-splines corresponding to first roadway lanes based on the roadway lane markings and the roadway edges included in the first map. The instructions include further instructions to determine second roadway lanes based on determining locations of the non-stationary objects, determine combined roadway lanes based on the first roadway lanes and the second roadway lanes and operate the first vehicle based on the combined roadway lanes.

Vehicle lane mapping

Example highway detection systems and methods are described. In one implementation, a method receives data from a vehicle data bus in a first vehicle and detects a speed of the first vehicle based on the received data. The method also determines a speed of an oncoming vehicle and a lateral distance between the first vehicle and the oncoming vehicle based on the received data. One or more processors determine whether the first vehicle is driving on a highway based on the speed of the first vehicle, the speed of the oncoming vehicle, and the lateral distance between the first vehicle and the oncoming vehicle.

Highway detection systems and methods

Example lane detection systems and methods are described. In one implementation, a method received an image from-facing vehicle camera and applies a geometric transformation to the image to create a birds-eye view of the image. The method analyzes the birds-eye view of the image using a neural network, which was previously trained using side-facing vehicl camera images, to determine a lane position associated with the birds-eye view of the image.

Lane detection systems and methods

A method for determining a position of a vehicle in a lane includes receiving perception information from a first camera positioned on a first side of a vehicle and a second camera positioned on a second side of the vehicle. The method includes determining, using one or more neural networks, a position of the vehicle with respect to lane markings on the first side and the second side of the vehicle. The method further includes notifying a driver or control system of the position of the vehicle.

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Ypsilanti, MI, United States of America

Kyle J Carey