Autobrains Technologies Ltd.

Shay Ieizerovitch

Igal Raichelgauz

Karina Odinaev

Roi Saida

A method for lane boundary detection. The method may include obtaining an image of an environment of a vehicle. The environment may include at least one lane boundary; the images may include image segments; calculating image segment lane boundary metadata for relevant image segments. The calculating is executed by a neural network and is based on the image segments; wherein each relevant image segment comprises one or more lane boundary points candidates; wherein image segment lane boundary metadata that is related to a relevant image segment which may include (i) location information about location of the one or more lane boundary points candidates of the relevant image segment, and (ii) angular information regarding an angle between lane boundary points candidates of the image; and determining an estimate of a lane boundary of the at least one lane boundary; wherein the determining is based on the image segment lane boundary metadata of the relevant image segments; wherein the determining comprises applying a process that differs from neural network processing.

Lane boundary detection

A method for unsupervised learning of drivable space, the method may include receiving, by a processing circuit, an image of an environment of a vehicle; searching, in the image and by the processing circuit, for a drivable space within the environment of the vehicle, wherein the drivable space is associated with a statistically significant drivable space behavior; wherein the association is learnt by applying an unsupervised learning process; and responding, by the processing circuit, to a finding of the drivable space.

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Mikhmoret, Israel

Shay Ieizerovitch