Mobileye Vision Technologies Ltd.

Ori Buberman

Gideon Stein

Amnon Shashua

Shai Shalev-Shwartz

Shaked Shammah

Yoram Gdalyahu

Yoav Taieb

Aran Reisman

Gaby Hayon

Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques. In one implementation, a navigation system for a host vehicle may include at least one processing device programmed to: receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify a navigational state associated with the host vehicle; provide the navigational state to a trained navigational system; receive, from the trained navigational system, a desired navigational action for execution by the host vehicle in response to the identified navigational state; analyze the desired navigational action relative to one or more predefined navigational constraints; determine an actual navigational action for the host vehicle, wherein the actual navigational action includes at least one modification of the desired navigational action determined based on the one or more predefined navigational constraints; and cause at least one adjustment of a navigational actuator of the host vehicle in response to the determined actual navigational action for the host vehicle.

Navigating a vehicle based on predictive aggression of other vehicle

Systems and methods are provided for interacting with a plurality of autonomous vehicles. In one implementation, a navigation system for a vehicle may include a memory including a predetermined road model representative of at least one road segment and at least one processor. The at least one processor may be programmed to selectively receive, from the plurality of autonomous vehicles, road environment information based on navigation by the plurality of autonomous vehicles through their respective road environments, determine whether one or more updates to the predetermined road model are required based on the road environment information, and update the predetermined road model to include the one or more updates.

Road model management based on selective feedback

A navigation system for a vehicle is provided. The system includes at least one processor programmed to receive, from one or more sensors, outputs indicative of a motion of the vehicle. The at least one processor is also programmed to determine an actual trajectory of the vehicle based on the outputs from the one or more sensors; receive, from a camera, at least one environmental image associated with the vehicle; and analyze the at least one environmental image to determine information associated with at least one navigational constraint. The at least one processor is further programmed to determine a target trajectory, including the actual trajectory of the vehicle and one or more modifications to the actual trajectory based on the determined information associated with the at least one navigational constraint; and transmit the target trajectory from the vehicle to a server.

Systems and methods for uploading recommended trajectories

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Tel Aviv, Israel

Ori Buberman