Abstract: Methods and systems are provided for tracking an object. The system includes a data receiving module receiving two dimensional imaging data including an object and height map data correlating ground height and location. A two dimensions to three dimensions transformation module determines a location of the object in three dimensional space based on the two dimensional imaging data and the height map data. A tracking module tracks the object using the location of the object.

Abstract: A multi-mode transportation system and method are provided in which a scheduler service (SS) generates an initial transportation schedule (TS) including a list of transport legs where transport over one or more transport legs is via an autonomous vehicle (AV) from an initial scheduled pick-up location (ISPUL) at an initial scheduled pick-up time (ISPUT). The SS monitors for any changes to the initial TS, and if any are detected, updates the initial TS based on the changes to generate a current TS that includes a currently scheduled pick-up time (CSPUT) and a currently scheduled pick-up location (CSPUL) for the transport leg. The CSPUT/CSPUL can be the same as or different than the ISPUT/ISPUL depending on whether or not there were changes to the ISPUT/ISPUL. An AV can be selected from the fleet of AVs and automatically controlled to arrive at the CSPUL to pick-up the passenger by the CSPUT.

Abstract: A multi-mode transportation system and method are provided in which a scheduler service (SS) generates an initial transportation schedule (TS) including a list of transport legs where transport over one or more transport legs is via an autonomous vehicle (AV) from an initial scheduled pick-up location (ISPUL) at an initial scheduled pick-up time (ISPUT). The SS monitors for any changes to the initial TS, and if any are detected, updates the initial TS based on the changes to generate a current TS that includes a currently scheduled pick-up time (CSPUT) and a currently scheduled pick-up location (CSPUL) for the transport leg. The CSPUT/CSPUL can be the same as or different than the ISPUT/ISPUL depending on whether or not there were changes to the ISPUT/ISPUL. An AV can be selected from the fleet of AVs and automatically controlled to arrive at the CSPUL to pick-up the passenger by the CSPUT.

Abstract: One embodiment is directed to a system for presenting views of a very large point data set, comprising: a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to automatically and deterministically organize the point data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: One method embodiment comprises storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

Abstract: One embodiment is directed to a method for presenting views of a very large point data set, comprising: storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; automatically and deterministically organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: A system comprises a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to organize the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

Abstract: A method for image-based vehicle localization includes measuring, at a vehicle, a position and a heading of the vehicle; capturing, at an image capture system of the vehicle, road surface image data of a road surface; processing the road surface image data to correct for distortion in the road surface image data due to pitch and roll of the vehicle; performing feature detection on the processed road surface image data to detect lane markers on the road surface; generating a local map based on the detected lane markers; wherein generating the local map comprises identifying a lane demarcated by the detected lane markers; and controlling the vehicle according to the local map.

Abstract: One embodiment is directed to a system for presenting views of a very large point data set, comprising: a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to automatically and deterministically organize the point data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: One embodiment is directed to a method for presenting views of a very large point data set, comprising: storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; automatically and deterministically organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: One method embodiment comprises storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

Abstract: A system comprises a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to organize the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

Abstract: A method for image-based vehicle localization includes measuring, at a vehicle, a position and a heading of the vehicle; capturing, at an image capture system of the vehicle, road surface image data of a road surface; processing the road surface image data to correct for distortion in the road surface image data due to pitch and roll of the vehicle; performing feature detection on the processed road surface image data to detect lane markers on the road surface; generating a local map based on the detected lane markers; wherein generating the local map comprises identifying a lane demarcated by the detected lane markers; and controlling the vehicle according to the local map.

Abstract: One embodiment is directed to a system for presenting views of a very large point data set, comprising: a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to automatically and deterministically organize the point data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: One method embodiment comprises storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

Abstract: One embodiment is directed to a method for presenting views of a very large point data set, comprising: storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; automatically and deterministically organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: One embodiment is directed to a system for presenting views of a very large point data set, comprising: a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to automatically and deterministically organize the point data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: One method embodiment comprises storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.

Abstract: One embodiment is directed to a method for presenting views of a very large point data set, comprising: storing data on a storage system that is representative of a point cloud comprising a very large number of associated points; automatically and deterministically organizing the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; receiving a command from a user of a user interface to present an image based at least in part upon a selected viewing perspective origin and vector; and assembling the image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy.

Abstract: A system comprises a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to organize the data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy, the plurality of data sectors being assembled such that sectors representative of points closer to the selected viewing origin have a higher octree mesh resolution than that of sectors representative of points farther away from the selected viewing origin.