Abstract: A detection system for a vehicle is provided. The detection system may include at least one image capture device configured to acquire a plurality of images of an area forward of the vehicle, the area including a curb separating a road surface from an off-road surface and a data interface. The detection system may also include at least one processing device programmed to receive the plurality of images via the data interface, and determine a plurality of curb edge line candidates in the plurality of images. The at least one processing device may be further programmed to identify at least one edge line candidate as an edge line of the curb.

Abstract: 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.

Abstract: Systems and methods are provided for interacting with a plurality of autonomous vehicles. In one implementation, a system may include at least one processor. The at least one processor may be programmed to receive from each of the plurality of autonomous vehicles navigational situation information associated with an occurrence of an adjustment to a determined navigational maneuver, analyze the navigational situation information, determine, based on the analysis of the navigational situation information, whether the adjustment to the determined navigational maneuver was due to a transient condition, and update the predetermined model representative of the at least one road segment if the adjustment to the determined navigational maneuver was not due to a transient condition.

Abstract: 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.

Abstract: 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.

Abstract: A detection system for a vehicle is provided. The detection system may include at least one image capture device configured to acquire a plurality of images of an area forward of the vehicle, the area including a curb separating a road surface from an off-road surface and a data interface. The detection system may also include at least one processing device programmed to receive the plurality of images via the data interface, and determine a plurality of curb edge line candidates in the plurality of images. The at least one processing device may be further programmed to identify at least one edge line candidate as an edge line of the curb.

Abstract: 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.

Abstract: A detection system for a vehicle is provided. The detection system may include at least one image capture device configured to acquire a plurality of images of an area forward of the vehicle, the area including a curb separating a road surface from an off-road surface and a data interface. The detection system may also include at least one processing device programmed to receive the plurality of images via the data interface, and determine a plurality of curb edge line candidates in the plurality of images. The at least one processing device may be further programmed to identify at least one edge line candidate as an edge line of the curb.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system for autonomously navigating a 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 at least one image representative of an environment of the vehicle. The processor may also be programmed to analyze the at least one image to identify at least one recognized landmark. Further, the processor may be programmed to determine a current location of the vehicle relative to a predetermined road model trajectory associated with the road segment based, at least in part, on a predetermined location of the recognized landmark. In addition, the processor may be programmed to determine an autonomous steering action for the vehicle based on a direction of the predetermined road model trajectory at the determined current location of the vehicle relative to the predetermined road model trajectory.

Abstract: Systems and methods are provided for interacting with a plurality of autonomous vehicles. In one implementation, a system may include at least one processor. The at least one processor may be programmed to receive from each of the plurality of autonomous vehicles navigational situation information associated with an occurrence of an adjustment to a determined navigational maneuver, analyze the navigational situation information, determine, based on the analysis of the navigational situation information, whether the adjustment to the determined navigational maneuver was due to a transient condition, and update the predetermined model representative of the at least one road segment if the adjustment to the determined navigational maneuver was not due to a transient condition.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system for autonomously navigating a 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 at least one image representative of an environment of the vehicle. The processor may also be programmed to analyze the at least one image to identify at least one recognized landmark. Further, the processor may be programmed to determine a current location of the vehicle relative to a predetermined road model trajectory associated with the road segment based, at least in part, on a predetermined location of the recognized landmark. In addition, the processor may be programmed to determine an autonomous steering action for the vehicle based on a direction of the predetermined road model trajectory at the determined current location of the vehicle relative to the predetermined road model trajectory.