Abstract: The present disclosure relates to systems and methods for host vehicle navigation. 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; receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the images to identify a target vehicle in the environment of the host vehicle; cause a navigational change of the host vehicle to signal to the target vehicle an intent of the host vehicle to make a subsequent navigational maneuver; analyze the images to detect a change in a navigational state of the target vehicle; determine a navigational action for the host vehicle; and cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action for the host vehicle.

Abstract: A navigation system includes a processor programmed to receive, from a sensor, an output related to a motion of the host vehicle. The output is generated at a first time that is later than a data acquisition time, when a measurement or data acquisition on which the output is based is acquired, and earlier than a second time at which the sensor output is received processor; generate, for a motion prediction time, a prediction of at least one aspect of host vehicle motion based, on the output and how the aspect of host vehicle motion changes over a time interval between the data acquisition time and the motion prediction time; determine a navigational action for the host vehicle; generate a navigational command for implementing at least a portion of the navigational action; and provide the navigational command to at least one actuation system of the host vehicle.

Abstract: Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: A system for navigating a host vehicle may: receive, from an image capture device, an image representative of an environment of the host vehicle; determine a navigational action for accomplishing a navigational goal of the host vehicle; analyze the image to identify a target vehicle in the environment of the host vehicle; determine a next-state distance between the host vehicle and the target vehicle that would result if the navigational action was taken; determine a maximum braking capability of the host vehicle, a maximum acceleration capability of the host vehicle, and a speed of the host vehicle; determine a stopping distance for the host vehicle; determine a speed of the target vehicle and assume a maximum braking capability of the target vehicle; and implement the navigational action if the stopping distance for the host vehicle is less than the next-state distance summed together with a target vehicle travel distance.

Abstract: A navigational system for a host vehicle may comprise at least one processing device. The processing device may be programmed to receive a first output and a second output associated with a host vehicle, wherein at least one of the outputs is received from a sensor onboard the host vehicle. The processing device may identify a target object in the first output and determine whether a characteristic of the target object triggers a navigational constraint by verifying the identification of the target object based on the first output; and, if the navigational constraint is not verified based on the first output, then verifying the identification of the target object based on a combination of the first output and the second output. In response to the verification, the processing device may cause at least one navigational change to the host vehicle.

Abstract: A navigational system for a host vehicle may comprise at least one processing device. The processing device may be programmed to receive a first output and a second output associated with the host vehicle and identify a representation of a target object in the first output. The processing device may determine whether a characteristic of the target object triggers a navigational constraint by verifying the identification of the target object based on the first output and, if the at least one navigational constraint is not verified based on the first output, then verifying the identification of the target object based on a combination of the first output and the second output. In response to the verification, the processing device may cause at least one navigational change to the host vehicle.

Abstract: Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: The present disclosure relates to systems and methods for host vehicle navigation. Disclosed systems and methods may receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify at least one pedestrian in the environment of the host vehicle; identify eyes of the at least one pedestrian represented in at least one of the plurality of images; and determine, based on analysis of the at least one of the plurality of images and based on the identification of the eyes of the at least one pedestrian in the at least one of the plurality of images, a looking direction of the at least one pedestrian.

Abstract: Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: A system for navigating an autonomous vehicle using reinforcement learning techniques is provided. The system includes 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 present navigational state associated with the host vehicle; select a second potential navigational action based on a determination that an expected reward associated with a fourth indicator is greater than an expected reward associated with a second indicator.

Abstract: Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: A navigational system for a host vehicle may comprise at least one processing device. The processing device may be programmed to receive a first output and a second output associated with the host vehicle; identify a representation of a target object in the first output; and determine whether a characteristic of the target object triggers a navigational constraint. If the navigational constraint is not triggered, the processing device may verify the identification of the representation of the target object based on a combination of the first output and the second output. If the navigational constraint is triggered, the processing device may verify the identification of the representation of the target object based on the first output; and in response to the verification, cause at least one navigational change to the host vehicle.

Abstract: A navigation system for a host vehicle is provided. The system may comprise 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; determine a first predefined navigational constraint and a second predefined navigational constraint implicated by the navigational state; determine, based on the identified navigational state, a first navigational action for the host vehicle where both the first predefined navigational constraint and the second predefined navigational constraint can be satisfied; determine, based on the identified navigational state, a second navigational action for the host vehicle where the first predefined navigational constraint and the second predefined navigational constraint cannot both be satisfied; and cause at least one adjustment of a navigational actuator of the host vehicle.

Abstract: A navigation system for a host vehicle is provided. The system may comprise 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; determine a first predefined navigational constraint implicated by at least one aspect of the navigational state; identify, based on analysis of the plurality of images, a presence of at least one navigational constraint augmentation factor; determine a second navigational constraint based on identification of the at least one navigational constraint augmentation factor; determine, based on the identified navigational state, a navigational action for the host vehicle satisfying the second navigational constraint; and cause at least one adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

Abstract: The present disclosure relates to navigational systems for vehicles. In one implementation, such a navigational system may receive a first output from a first sensor and a second output from a second sensor; identify a target object in the first output; determine whether the target object is included in the second output; and determine a detected driving condition associated with the target object and whether the condition triggers a navigational constraint. If the navigational constraint is not triggered, the system may cause a first navigational adjustment if the target object is included in both the first output and the second output, and may forego any navigational adjustments if the target object is included in the first output but not in the second output. If the navigational constraint is triggered and the target object is included either in the first or second output, the system may cause a second navigational adjustment.

Abstract: A navigation system for a host vehicle may include at least one processor programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle.

Abstract: A navigation system includes a processor programmed to receive, from a sensor, an output related to a motion of the host vehicle. The output is generated at a first time that is later than a data acquisition time, when a measurement or data acquisition on which the output is based is acquired, and earlier than a second time at which the sensor output is received processor; generate, for a motion prediction time, a prediction of at least one aspect of host vehicle motion based, on the output and how the aspect of host vehicle motion changes over a time interval between the data acquisition time and the motion prediction time; determine a navigational action for the host vehicle; generate a navigational command for implementing at least a portion of the navigational action; and provide the navigational command to at least one actuation system of the host vehicle.

Abstract: A navigation system for a host vehicle is provided. The system may comprise 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 at least one target vehicle in the environment of the host vehicle; analyze the plurality of images to identify at least one adverse characteristic of the target vehicle relative to the host vehicle; and cause at least one navigational change of the host vehicle to initiate a pass of the target vehicle after identifying the at least one characteristic of the target vehicle.