Abstract: An apparatus for sign detection includes a point cloud analysis module, an image analysis module, a frustum comparison module, and a sign detector. The point cloud analysis module is configured to receive point cloud data associated with a geographic region and classify at least one point neighborhood in the point cloud data as planar and a sign position candidate. The image analysis module is configured to receive image data associated with the geographic region and calculate a sighting frustum from the image data. The frustum comparison module is configured to perform a comparison of the sighting frustum to the sign position candidate having at least one point neighborhood classified as planar. The sign detector is configured to provide a location for the sign detection in response to the comparison of the sighting frustum to the sign position candidate.

Abstract: A method for road surface detection includes receiving ranging data including a plurality of ranging data points, extracting one or more ranging data points lying within a height range from the plurality of ranging data points, dividing the one or more ranging data points into one or more grid cells, setting a first horizontal position of a first cell point of a first grid cell of the one or more grid cells as being centered on the first grid cell, setting a first vertical position of the first cell point, and detecting the road surface based on the first vertical position and first horizontal position of the first cell point.

Abstract: An apparatus for sign detection includes a point cloud analysis module, an image analysis module, a frustum comparison module, and a sign detector. The point cloud analysis module is configured to receive point cloud data associated with a geographic region and classify at least one point neighborhood in the point cloud data as planar and a sign position candidate. The image analysis module is configured to receive image data associated with the geographic region and calculate a sighting frustum from the image data. The frustum comparison module is configured to perform a comparison of the sighting frustum to the sign position candidate having at least one point neighborhood classified as planar. The sign detector is configured to provide a location for the sign detection in response to the comparison of the sighting frustum to the sign position candidate.

Abstract: An apparatus for sign detection includes a point cloud analysis module, an image analysis module, a frustum comparison module, and a sign detector. The point cloud analysis module is configured to receive point cloud data associated with a geographic region and classify at least one point neighborhood in the point cloud data as planar and a sign position candidate. The image analysis module is configured to receive image data associated with the geographic region and calculate a sighting frustum from the image data. The frustum comparison module is configured to perform a comparison of the sighting frustum to the sign position candidate having at least one point neighborhood classified as planar. The sign detector is configured to provide a location for the sign detection in response to the comparison of the sighting frustum to the sign position candidate.

Abstract: A method for constructing a coordinate system relative to a vehicle traveling along a path includes receiving location data, dividing the path into path segments, matching a portion of the location data to a path segment, and determining a registration of the portion of the location data relative to the path segment. The registration may be organized by non-cartesian coordinates relative to a path point lying on the path segment.

Abstract: Embodiments include apparatus and methods for automatic generation of local window-based 2D occupancy grids that represent roadside objects at a region of a roadway and automatic localization based on the 2D occupancy grids. 2D occupancy grids are generated based on an altitude threshold for point cloud data and grid cell occupancy for grid cells of local windows associated with the region of the roadway. The 2D occupancy grids are stored in a database and associated with the region of the roadway. Sensor data from a user located at the region of the roadway is received. The accessed 2D occupancy grids and the received sensor data are compared. Based on the comparison, localization of the user located at the region of the roadway is performed.

Abstract: A method for road surface detection includes receiving ranging data including a plurality of ranging data points, extracting one or more ranging data points lying within a height range from the plurality of ranging data points, dividing the one or more ranging data points into one or more grid cells, setting a first horizontal position of a first cell point of a first grid cell of the one or more grid cells as being centered on the first grid cell, setting a first vertical position of the first cell point, and detecting the road surface based on the first vertical position and first horizontal position of the first cell point.

Abstract: An apparatus for sign detection includes a point cloud analysis module, an image analysis module, a frustum comparison module, and a sign detector. The point cloud analysis module is configured to receive point cloud data associated with a geographic region and classify at least one point neighborhood in the point cloud data as planar and a sign position candidate. The image analysis module is configured to receive image data associated with the geographic region and calculate a sighting frustum from the image data. The frustum comparison module is configured to perform a comparison of the sighting frustum to the sign position candidate having at least one point neighborhood classified as planar. The sign detector is configured to provide a location for the sign detection in response to the comparison of the sighting frustum to the sign position candidate.

Abstract: Embodiments include apparatus and methods for automatic generation of local window-based 2D occupancy grids that represent roadside objects at a region of a roadway and automatic localization based on the 2D occupancy grids. 2D occupancy grids are generated based on an altitude threshold for point cloud data and grid cell occupancy for grid cells of local windows associated with the region of the roadway. The 2D occupancy grids are stored in a database and associated with the region of the roadway. Sensor data from a user located at the region of the roadway is received. The accessed 2D occupancy grids and the received sensor data are compared. Based on the comparison, localization of the user located at the region of the roadway is performed.

Abstract: A method for constructing a coordinate system relative to a vehicle traveling along a path includes receiving location data, dividing the path into path segments, matching a portion of the location data to a path segment, and determining a registration of the portion of the location data relative to the path segment. The registration may be organized by non-cartesian coordinates relative to a path point lying on the path segment.