Mobileye Vision Technologies Ltd.

Aran Reisman

Amnon Shashua

Daniel Braunstein

Yoram Gdalyahu

Ofer Springer

Yoav Taieb

Ori Buberman

Igor Tubis

Systems and methods are provided for controlling vehicle operation. A processor may access route information for navigation of a route by the vehicle including data relating to speed along the route and calculate a speed of the vehicle along the route based on the route information. The processor may cause the vehicle to be operated at the calculated speed along the route; obtain dynamic information for the route based on data collected from one or more other vehicles on the route and indicating current conditions on the route which affect the speed of the vehicle along the route; and cause the vehicle to be operated at an updated speed along the route, based on the dynamic information.

Crowd sourcing data for autonomous vehicle navigation

Systems and methods navigate a vehicle by determining a free space region in which the vehicle can travel. In one implementation, a system may include at least one processor programmed to receive from an image capture device, a plurality of images associated with the environment of a vehicle, analyze at least one of the plurality of images to identify a first free space boundary on a driver side of the vehicle and extending forward of the vehicle, a second free space boundary on a passenger side of the vehicle and extending forward of the vehicle, and a forward free space boundary forward of the vehicle and extending between the first free space boundary and the second free space boundary. The first free space boundary, the second free space boundary, and the forward free space boundary may define a free space region forward of the vehicle. The at least one processor of the system may be further programmed to determine a navigational path for the vehicle through the free space region and cause the vehicle to travel on at least a portion of the determined navigational path within the free space region forward of the vehicle.

Navigation based on free space determination

Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

Systems and methods are provided for constructing, using, and updating the sparse map for autonomous vehicle navigation. A system may comprise a processor and a memory. The memory may include instructions, which when executed on the processor, cause the processor to maintain a map; determine, based on analysis of image data, an existence of a non-transient condition that is inconsistent with the map, the image data from a camera integrated with the autonomous vehicle; and update the map.

Self-aware system for adaptive navigation

Systems and methods are provided for constructing, using, and updating the sparse map for autonomous vehicle navigation. A method may comprise processing, by a mapping server, collected navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

Systems and methods navigate a vehicle on a road at least partially covered with snow. In one implementation, a system may include at least one processor programmed to receive from an image capture device, a plurality of images captured of an environment forward of the vehicle, including an area where snow covers a road on which the vehicle travels, analyze at least one of the plurality of images to identify a first free space boundary on a first side of the vehicle and extending forward of the vehicle, a second free space boundary on a passenger side of the vehicle and extending forward of the vehicle, and a forward free space boundary forward of the vehicle and extending between the first free space boundary and the second free space boundary.

Navigating in snow

A system for sparse map autonomous navigation of a vehicle along a road segment may include at least one processor. The at least one processor may be programmed to receive a sparse map of the road segment. The sparse map may have a data density of no more than 1 megabyte per kilometer. The at least one processor may be programmed to receive from a camera, at least one image representative of an environment of the vehicle, and determine an autonomous navigational response for the vehicle based on the analysis of the sparse map and the at least one image received from the camera.

Sparse map autonomous vehicle navigation

Systems and methods navigate a vehicle on a road with snow covering at least some lane markings and road edges. In one implementation, a system may include at least one processor programmed to receive from an image capture device, at least one environmental image forward of the vehicle, including areas where snow covers at least some lane markings and road edges, identify, based on an analysis of the at least one image, at least a portion of the road that is covered with snow and probable locations for road edges bounding the at least a portion of the road that is covered with snow, and cause the vehicle to navigate a navigational path that includes the identified portion of the road and falls within the determined probable locations for the road edges.

A non-transitory computer-readable medium is provided. The computer-readable medium includes a sparse map for autonomous vehicle navigation along a road segment. The sparse map includes a polynomial representation of a target trajectory for the autonomous vehicle along the road segment, and a plurality of predetermined landmarks associated with the road segment. The plurality of predetermined landmarks are spaced apart by at least 50 meters, and the sparse map has a data density of no more than 1 megabyte per kilometer.

Sparse map for autonomous vehicle navigation

Systems and methods are provided for self-aware adaptive navigation. In one implementation, a navigation system for a vehicle may include at least one processor. The at least one processor may be programmed to determine a navigational maneuver for the vehicle based, at least in part, on a comparison of a motion of the vehicle with respect to a predetermined model representative of a road segment. The at least one processor may be further programmed to receive, from a camera, at least one image representative of an environment of the vehicle. The at least one processor may be further programmed to determine, based on analysis of the at least one image, an existence in the environment of the vehicle of an navigational adjustment condition, cause the vehicle to adjust the navigational maneuver based on the existence of the navigational adjustment condition, and store information relating to the navigational adjustment condition.

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

A system for autonomously navigating a vehicle may include at least one processor. The processor may be programmed to receive a first navigational map associated with a first road segment and a second navigational map, different from the first navigational map, associated with a second road segment. The first road segment and the second road segment may overlap one another at an overlap segment. The processor may be programmed to determine at least a first autonomous navigational response for the vehicle along the first road segment based on analysis of the first navigational map; at least a second autonomous navigational response for the vehicle along the second road segment based on analysis of the second navigational map; and at least a third autonomous navigational response for the vehicle in the overlap segment based on at least one of the first navigational map and the second navigational map.

Navigation using local overlapping maps

A method of processing vehicle navigation information for use in autonomous vehicle navigation is provided. The method includes receiving, by a server, navigation information from a plurality of vehicles. The navigation information from the plurality of vehicles is associated with a common road segment. The method also includes storing, by the server, the navigation information associated with the common road segment. The method also includes generating, by the server, at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles. The method further includes distributing, by the server, the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating the one or more autonomous vehicles along the common road segment.

A system for navigating an autonomous vehicle along a road segment is disclosed. The system may have at least one processor. The processor may be programmed to receive from an image capture device, images representative of an environment of the autonomous vehicle. The processor may also be programmed to determine a travelled trajectory along the road segment based on analysis of the images. Further, the processor may be programmed to determine a current location of the autonomous vehicle along a predetermined road model trajectory based on analysis of one or more of the plurality of images. The processor may also be programmed to determine a heading direction based on the determined traveled trajectory. In addition, the processor may be programmed to determine a steering direction, relative to the heading direction, by comparing the traveled trajectory to the predetermined road model trajectory at the current location of the autonomous vehicle.

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Givatayim, Israel

Aran Reisman