Here Global B.v.

Nokia Technologies Oy

Navteq B.v.

Navteq North America, LLC

Xin Chen

Xiang Ma

Roman Ostrovskiy

David Doria

Xi Zhang

Andi Zang

Ruigang Yang

Vladimir Zhukov

Xinyu Huang

Di Ma

Xiaotao Zou

Fangning He

Vlad Zhukov

Matei Stroila

Narayanan Alwar

Victor Lu

Bradley Dean Kohlmeyer

Pamela T Korda

Xiangheng Yang

Junzhou Huang

Terence Zhao

Roger B Hui

Belle Walker

Uyen Nguyen

Daniel Weinstein

Phillip Bernard

Ralf Herrtwich

Hang Dou

William N Gale

Sanjay Chand Sood

Charles Morcom

Mark David Tabb

Zichen Li

Mahsa Kamali Moghaddam

David Vandebunte

Alexandri Gregor Zavodny

Masha Kamali Moghaddam

Qilin Zhang

Chen Luo

Coby Spolin Parker

Peter Forbes

Sanjay Sood

Methods described herein relate to self-localization. Methods may include: receiving sensor data from a vehicle traveling along a road segment; identifying one or more objects of the environment from the sensor data; determining a coarse location of the vehicle; comparing the identified one or more objects with corresponding ground truth objects; calculating an observation in response to the comparison of the identified one or more objects with the corresponding ground truth objects; determining a location of the vehicle with a higher precision than the coarse location based, at least in part, on the observation; and allocating resources of the apparatus based, at least in part, on the observation.

Method and apparatus for self localization

Methods, apparatuses, and systems are provided for detecting overhead obstructions along a path segment. One exemplary method includes receiving three-dimensional data collected by a depth sensing device traveling along a path segment, wherein the three-dimensional data comprises point cloud data positioned above a ground plane of the path segment. The method further includes identifying data points of the point cloud data positioned within a corridor positioned above the ground plane. The method further includes projecting the identified data points onto a plane. The method further includes detecting the overhead obstruction based on a concentration of point cloud data positioned within a plurality of cells of the plane. The method further includes storing the detected overhead obstruction above the path segment within a map database.

Automatic detection of overhead obstructions

An apparatus comprising a processor and memory including computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to:

Apparatus and associated methods for use in lane-level mapping of road intersections

Embodiments include apparatus and methods for automatic generation of object polylines that represent roadside objects at a region of a roadway and automatic localization based on the object polylines. Object polylines are generated based on occupied voxels closest to the roadway of one or more voxel occupancy grids associated with the region of the roadway. The object polylines 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 object polylines and the received sensor data are compared. Based on the comparison, localization of the user located at the region of the roadway is performed.

Automatic identification of roadside objects for localization

An apparatus, method and computer program product are provided to facilitate the navigation of a vehicle, such as an autonomous vehicle, utilizing map data in which the quality associated with the map data is provided in a more computationally efficient manner. In the context of a method a plurality of different types of sensor data are received including map data, camera data and detector data. The method determines a quality index associated with the map data and weights the reliance upon the map data relative to other types of sensor data based upon the quality index associated with the map data. The method further includes determining navigation information for the vehicle based at least partly upon the weighting of the map data relative to other types of sensor data.

Apparatus, method and computer program product for facilitating navigation of a vehicle based upon a quality index of the map data

Embodiments include apparatus and methods for generating a localization geometry or occupancy grid for a geographic location. Point cloud that describes a vicinity of a pathway is collected by a distance sensor and describing a vicinity of the pathway. The point cloud data is reduced or filtered to a predetermined volume with respect to the roadway. The remaining point cloud data is projected onto a two-dimensional plane including at least one pixel formation. A volumetric grid is defined according to the at least one pixel formation, and a voxel occupancy for each of a voxels forming the volumetric grid is determined. The arrangement of the voxel occupancies or a sequence of data describing the voxel occupancies is a localization geometry that describes the geographic location of the pathway.

Automatic localization geometry detection

Lane level traffic levels are determined based on traffic camera images. A controller aligns a three-dimensional map with a traffic camera view, and identifies multiple lanes in the traffic camera view based on lane delineations of the three-dimensional map. The controller calculates a traffic parameter based on the multiple lanes in image frames from the traffic camera view and provides a traffic graphic based on the traffic parameter.

Lane level traffic

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.

Local window-based 2D occupancy grids for localization of autonomous vehicles

Apparatus and methods are described for generating geometries for stripe-shaped objects. An image is identified that includes a roadway having one or more stripe-shaped objects. The stripe-shaped objects may include lane lines for road edges or lanes of the roadway. The stripe-shaped objects may include a barrier. At least one targeted region within the image is determined. The at least one targeted region is shaped to intersect the one or more stripe-shaped objects and includes a plurality of pixels. An image analysis is performed on the image to determine when the at least one target region includes a pixel in common with the one or more stripe-shaped objects. A geometry is constructed using the pixel in common. The geometry may be used to update a map or subsequently perform localization.

Automatic localization geometry generator for stripe-shaped objects

The present embodiments provide for automatically detecting the location and severity of occluded regions within input data. A grid representation of a scene is generated from a data set, characterizing spaces of the grid representation as free, occupied, and hidden/occluded. The grid is bounded, and a connected component analysis is performed on the hidden space to identify the occluded regions.

Automatic occlusion detection in road network data

An approach is provided for providing a digital elevation model. For example, the approach involves processing, by a processor, map elevation data to create a hierarchical resolution tile representation of the digital elevation model for a geographic area. The hierarchical resolution tile representation includes a plurality of resolution levels, wherein each of the plurality of levels represents the digital elevation model at a different resolution. The digital elevation model includes a plurality of control points, wherein each of the plurality of control points is associated with an elevation data point determined from the map elevation data.

Method and apparatus for providing a tile-based digital elevation model

A method includes identifying, by a processor, a first range data set. The first range data set is generated by a first device and includes first range data points. The processor identifies a second range data set. The second range data set is generated by a second device and includes second range data points. The processor compares the second range data points to the first range data points. The processor identifies a third range data set based on the comparison. The third range data set includes a subset of the second range data points. The processor adjusts distance values for first range data points of the first range data set corresponding to a portion of the surface of interest based on the third range data set.

Range sensing using a hybrid range sensing device

Growing community of inventors

Evanston, IL, United States of America

Xin Chen