Visteon Global Technolgoies, Inc.

Sri International

Faroog Abdel-kareem Ibrahim

Rakesh Kumar

Feng Han

Jayan Eledath

Yi Tan

Markus Klein

Christoph Schmidt

A method for determining whether a target vehicle in front of a host vehicle intends to change lanes using radar data and image data is disclosed, comprising the steps of processing the image data to detect the boundaries of the lane of the host vehicle; estimating a ground plane by determining a projected vanishing point of the detected lane boundaries; using a camera projection matrix to map the target vehicle from the radar data to image coordinates; and determining lane change intentions of the target vehicle based on a moving trajectory and an appearance change of the target vehicle. Determining lane change intentions based on a moving trajectory of the target vehicle is based on vehicle motion trajectory relative to the center of the lane such that the relative distance of the target vehicle from the center of the lane follows a predetermined trend. Determining lane change intentions based on an appearance change of the target vehicle is based on a template that tracks changes to the appearance of the rear part of the target vehicle due to rotation.

Radar guided vision system for vehicle validation and vehicle motion characterization

An in-vehicle system and method for warning a driver of upcoming curves in a road including. In general, a vehicle positioning module determines the vehicle's position in a global positioning system and a map matching module determines the vehicle's position on a map based on the position in the global positioning system. A look ahead module looks ahead on the map for a curve, determines a candidate list of probable driving paths through the curve, and from this candidate list determines the most likely path of the vehicle around the curve. A warning module then assesses the threat the upcoming curve poses to the vehicle.

Curve warning system

A system for predictive front lighting of a vehicle. The system includes a first and second headlamps, a first and second swivel mechanisms and a controller. The first and second headlamps project a beam pattern for illumination of the vehicle path. The controller receives vehicle position data, for example from a GPS system, and accesses a map database to identify a map location of the vehicle. The controller further analyzes the map to determine a most likely path of the vehicle based on the map location and other vehicle heading parameters. The controller then calculates the desired swivel angle of the first and second headlamps based on the most likely path of the vehicle, and the first and second swivel mechanisms manipulate the first and second headlamps to accordingly change the swivel angle of the headlamps.

Single path road geometry predictive adaptive front lighting algorithm using vehicle positioning and map data

A system for predictive front lighting of a vehicle. The system includes at least two headlamps, at least two swivel mechanisms and a controller. The first and second headlamps project a beam pattern for illumination of the vehicle path. The controller receives vehicle position data, as well as, data regarding a most likely path and a secondary path of the vehicle. The controller then calculates the desired swivel angle of the headlamps based on the most likely path of the vehicle and the secondary path of the vehicle, and the swivel mechanisms respectively manipulate each of the headlamps to accordingly change alignment of the headlamps based on the swivel angle for each of the of the headlamps.

Predictive adaptive front lighting algorithm for branching road geometry

The present invention provides a system and method of selecting a most likely path of a vehicle from a list of candidate paths. If only one candidate path exists, that path is identified as the most likely path. For multiple candidate paths, cost functions determine the weight of various parameters associated with each candidate. The parameters may include lane information, the vehicle speed, the vehicle travel direction, the lateral speed of the vehicle, the state of various signals, such as the turn signals. From the various weights determined by the cost functions, the candidate path with the highest confidence level is determined to be the most likely path.

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Dearborn Heights, MI, United States of America

Faroog Abdel-kareem Ibrahim