Honda Research Institute Europe Gmbh

Jannik Fritsch

Thomas Weisswange

Tobias Kühnl

Thomas Michalke

Christian Goerick

Robert Kastner

Edoardo Casapietra

A method and a system computationally performs scene analysis of semantic traffic spaces based on an adaptive spatio-temporal ray-based approach. The method includes acquiring a spatial semantic environment map including semantic context data, calculating at least one feature for at least one location on the spatial environment map taking into account the semantic context of the location and determining a category for the at least one location based on the at least one calculated feature. A feature is a ray based feature calculated by integrating input values along at least one ray extending in least one of a space dimension and a time dimension. The ray may have a ray shape corresponding to a general shape of a road and/or the at least one spatially extending ray follows a course of the road and/or is perpendicular to a surrounding road segment orientation.

Method and system for adaptive ray based scene analysis of semantic traffic spaces and vehicle equipped with such system

An environment of an ego vehicle is physically sensed and sensor data is produced. A representation of the environment is generated. The representation includes a plurality of representation segments each of which corresponds to a limited area of the environment. Characteristic information is generated for at least a part of the limited areas of the environment and the characteristic information is assigned to the representation segment which corresponds to the respective area of the environment. Furthermore, future or past movement behavior for a traffic object is estimated and characteristic information for at least one limited area of the environment is inferred based upon the estimated movement behavior. This characteristic information is assigned to the representation segment corresponding to the respective area of the environment and an evaluation is performed for determining a preferred path for the ego vehicle. An assistance signal based on the determined path is output.

Method for assisting a driver in driving an ego vehicle and corresponding driver assistance system

The present invention describes a road terrain detection system that comprises a method for classifying selected locations in the environment of a vehicle based on sensory input signals such as pixel values of a camera image. The method comprises a high level spatial feature generation for selected locations in the environment called base points. The spatial feature generation of the base points is based on a value-continuous confidence representation that captures visual and physical properties of the environment, generated by so called base classifiers operating on raw sensory data. Consequently, the road terrain detection incorporates both local properties of sensor data and their spatial relationship in a two-step feature extraction process.

Road-terrain detection method and system for driver assistance systems

The invention relates to a system and method for lane relative position estimation. The environment of a vehicle is first sensed, and spatial features are then extracted and classified from information obtained from the sensing. The spatial features capture lateral position information within a lane, and an output signal including the result of the classification, which represents the relative lateral positioning of a road location with respect to the overall lane shape, is generated.

Lane relative position estimation method and system for driver assistance systems

The present invention relates to a technique for detecting dynamic (i.e., moving) objects using sensor signals with 3D information and can be deployed e.g. in driver assistance systems.

Growing community of inventors

Offenbach, Germany

Jannik Fritsch