Mobileye Vision Technologies Ltd.

Barak Cohen

Gideon Stein

Amnon Shashua

Shai Shalev-Shwartz

Shaked Shammah

Oded Berberian

Zeev Adelman

Harel Livyatan

The present disclosure relates to navigational systems for vehicles. In one implementation, such a navigational system may receive a plurality of images captured by an image capture device onboard the host vehicle, the plurality of images being associated with an environment of the host vehicle; analyze at least one of the plurality of images to identify the target vehicle and at least one wheel component on a side of the target vehicle; determine, based on an analysis of at least two of the plurality of images, a rotation of the at least one wheel component of the target vehicle; and cause at least one navigational change of the host vehicle based on the rotation of the at least one wheel component of the target vehicle.

Controlling a vehicle based on detected movement of a target vehicle

Systems and methods are provided for navigating a host vehicle. At least one processing device may be programmed to receive an image of an environment of the host vehicle; detect, based on analysis of the image, a pedestrian crosswalk in the image; detect a presence of a traffic light and determine whether the traffic light is relevant to the host vehicle and the pedestrian crosswalk; determine a state of the traffic light; determine, when a pedestrian appears in the image, a proximity of the pedestrian relative to the pedestrian crosswalk; determine a planned navigational action for navigating the host vehicle relative to the pedestrian crosswalk based on a driving policy, the state of the traffic light and the proximity of the pedestrian relative to the pedestrian crosswalk; and cause one or more actuator systems of the host vehicle to implement the planned navigational action.

Navigation relative to pedestrians at crosswalks

Systems and methods are provided for navigating a host vehicle. A processing device may be programmed to receive an image representative of an environment of the host vehicle; determine a planned navigational action for the host vehicle; analyze the image to identify a target vehicle travelling toward the host vehicle; determine a next-state distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a stopping distance for the host vehicle based on a braking rate, a maximum acceleration capability, and a current speed of the host vehicle; determine a stopping distance for the target vehicle based on a braking rate, a maximum acceleration capability, and a current speed of the target vehicle; and implement the planned navigational action if the determined next-state distance is greater than a sum of the stopping distances for the host vehicle and the target vehicle.

Navigation with a safe longitudinal distance

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive an image associated with the environment of the host vehicle. The processor may analyze the image to identify a side of a parked vehicle; a first structural feature of the parked vehicle in a forward region of the side of the parked vehicle or a second structural feature of the parked vehicle in a rear region of the side of the parked vehicle; and a door feature of the parked vehicle in a vicinity of the first or the second structural features. The processor may then determine, based on a subsequent image, a change of an image characteristic of the door feature of the parked vehicle and alter a navigational path of the host vehicle based on the change of the image characteristic.

Controlling host vehicle based on detected door opening events

Systems and methods are provided for navigating a host vehicle. At least one processing device may be programmed to receive an image representative of an environment of the host vehicle; determine a planned navigational action for the host vehicle; analyze the image to identify a target vehicle in the environment of the host vehicle; determine a next-state lateral distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a lateral braking distance for the host vehicle and the target vehicle based on a maximum yaw rate capability, a maximum change in turn radius capability, and a current lateral speed of the host vehicle and the target vehicle; and implement the planned navigational action if the determined next-state distance is greater than a sum of the lateral braking distances for the host vehicle and the target vehicle.

Navigation with a safe lateral distance

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise an interface to obtain sensing data of an environment of the host vehicle. A processing device may be configured to determine a planned navigational action for the host vehicle; identify a target vehicle in the environment of the host vehicle; predict a resulting distance between the host and target vehicles if the planned action were taken; determine a host vehicle stopping distance based on a braking rate, maximum acceleration capability, and current speed of the host vehicle; determine a target vehicle stopping distance based on a braking rate and current speed of the target vehicle; and continue with the planned navigational action while the predicted distance is greater than a minimum safe longitudinal distance calculated based on the host vehicle stopping distance and the target vehicle stopping distance.

Systems and methods for navigating with safe distances

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise an interface to obtain sensing data of an environment of the host vehicle. A processing device may be configured to determine a planned navigational action for the host vehicle; identify a target vehicle in the environment of the host vehicle; predict a following distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a host vehicle braking distance based on a braking capability, acceleration capability, and speed of the host vehicle; determine a target vehicle braking distance, based on a speed and maximum braking capability of the target vehicle; and implement the planned navigational action when the predicted following distance is greater than a minimum safe longitudinal distance based on the determined host vehicle braking distance and the determined target vehicle braking distance.

Systems and methods for navigating a vehicle

Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a vehicle includes at least one processing device programmed to receive, from an image capture device, a plurality of images associated with an environment of the vehicle, analyze at least one of the plurality of images to identify a navigable region in the environment of the vehicle, identify, based on the at least one of the plurality of images, at least one barrier associated with an edge of the navigable region, and determine a type of the at least one barrier. The at least one processing device is also programmed to determine a navigational path of the vehicle based on the determined type of the at least one barrier, and cause the vehicle to travel on at least a portion of the determined navigational path.

Navigating a vehicle based on a detected barrier

Systems and methods are provided for vehicle navigation. In one implementation, a processing device may be configured to obtain a planned driving action for accomplishing a navigational goal of a host vehicle; receive sensor data from an environment surrounding the host vehicle; identify a target vehicle moving in the environment and a velocity of the target vehicle; calculate a stopping distance and a predicted trajectory for the target vehicle; calculate a planned trajectory for the host vehicle corresponding to the planned driving action; identify an intersection of the planned trajectory for the host vehicle with the predicted trajectory for the target vehicle; determine a braking action of the host vehicle to comply with a safety requirement; and cause the braking action to be applied to decelerate the host vehicle to change the planned trajectory, until the changed trajectory does not intersect the predicted trajectory of the target vehicle.

The present disclosure relates to systems and methods for road edge detection and mapping, for vehicle wheel identification and navigation based thereon, and for classification of objects as moving or non-moving. Such systems and methods may include the use of trained systems, such as one or more neural networks. Further, autonomous vehicle systems may incorporate aspects of one or more of the disclosed systems and methods.

Detection and classification systems and methods for autonomous vehicle navigation

Determining three-dimensional structure in a road environment using a system mountable in a host vehicle including a camera connectible to a processor. Multiple image frames are captured in the field of view of the camera. In the image frames, a line is selected below which the road is imaged. The line separates between upper images essentially excluding images of the road and lower images essentially including images of the road. One or more of the lower images is warped, according to a road homography to produce at least one warped lower image. The three-dimensional structure may be provided from motion of a matching feature within the upper images or from motion of a matching feature within at least one of the lower images and at least one warped lower image.

Dense structure from motion

A system for navigating a host vehicle may receive an image representative of an environment of the host vehicle and determine a planned navigational action for accomplishing a navigational goal of the host vehicle. The system may identify a target vehicle, determine a current speed of the target vehicle, and assume a maximum braking rate capability of the target vehicle. The system may determine a next-state distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken. The system may implement the planned navigational action if the host vehicle may be stopped using a predetermined sub-maximal braking rate within a distance that is less than the determined next-state distance summed together with a target vehicle travel distance determined based on the current speed of the target vehicle and the maximum braking rate capability of the target vehicle.

Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for detecting whether a road on which a host vehicle travels is a one-way road may include at least one processing device. The processing device may be programmed to receive at least one image associated with an environment of the host vehicle, identify a first plurality of vehicles on a first side of the road, identify a second plurality of vehicles on a second side of the road, determine a first facing direction associated with the first plurality of vehicles, determine a second facing direction associated with the second plurality of vehicles, and cause at least one navigational change of the host vehicle when the first facing direction and the second facing direction are both opposite to a heading direction of the host vehicle.

Controlling host vehicle based on detection of a one-way road

Determining three-dimensional structure in a road environment using a system mountable in a host vehicle including a camera connectable to a processor. Multiple image frames are captured in the field of view of the camera. In the image frames, a line is selected below which the road is imaged. The line separates between upper images essentially excluding images of the road and lower images essentially including images of the road. One or more of the lower images is warped, according to a road homography to produce at least one warped lower image. The three-dimensional structure may be provided from motion of a matching feature within the upper images or from motion of a matching feature within at least one of the lower images and at least one warped lower image.

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Modiin, Israel

Barak Cohen