Honda Research Institute Europe Gmbh

Julian Eggert

Nils Einecke

Sven Rebhan

Tim Puphal

Volker Willert

Bernhard Sendhoff

Jens Schmüdderich

Florian Damerow

Heiko Wersing

Benedict Flade

Chen Zhang

Joerg Deigmoeller

Christian Goerick

Herbert Janssen

Juergen Adamy

Jörg Deigmöller

Andreas Richter

Malte Probst

Mark Dunn

Oliver Fuchs

Jens Schmudderich

Daniel Weiler

Tsukasa Sugino

Simon Kohaut

Raphael Stahl

Axel Koppert

Berthold Bäuml

Chao Wang

Matti KRÜGER

Janssen Herbert

The present invention provides an advanced driver assistance system for assisting a driver of a vehicle. The system comprises a sensor unit, a processing unit and a display unit. The sensor unit is configured to sense an environment of the vehicle. The processing unit is configured to determine, based on a sensing output, at least one feature of the environment. The processing unit is configured to determine, for a current time, a risk zone of the feature, by estimating, based on at least one parameter of the vehicle at the current time, at each virtual position of two or more virtual positions of the vehicle a respective risk with regard to the feature; and by forming the risk zone based on the two or more risks. The display unit is configured to display the environment of the vehicle with the feature and the risk zone of the feature.

Advanced driver assistance system for assisting a driver of a vehicle

A method for improving prediction results of advanced driver assistance systems of a vehicle includes obtaining map data including information about a road geometry in a proximity of the vehicle. A sensor means is assigned, sensing a surrounding of the vehicle. A virtual sensing means output is generated, corresponding to an output of the sensing means if the sensing means. The generation is based on a mathematical model of the sensing means. The surrounding of the vehicle is sensed, and a sensing means output is generated. The sensing means output is compared to the virtual sensing means output. Parameters of the mathematical model are modified, and the virtual sensing means output are generated and compared to the sensing means output. Map data is combined with information derived from the sensing means output to generate combined information, which is output for further processing.

Method and system in a vehicle for improving prediction results of an advantageous driver assistant system

The invention relates to a method for analyzing localization errors, wherein the method includes the steps of obtaining relative positions and absolute positions of an object moving within a mapped environment, which are generated sequentially over time, calculating differences between the relative positions and absolute positions to determine sequential localization errors, and decomposing the localization errors into a systematic error that is dependent on the orientation of the object and into a systematic error that is independent on the orientation of the object by analyzing the intrinsic dynamics of the localization errors.

Analysis of localization errors in a mobile object

The present invention relates to a method for use in a driver assistance system of an ego-vehicle. The method supports driving of the ego-vehicle and comprises the steps of retrieving a priority relationship between the ego-vehicle and at least one traffic participant involved in a traffic situation; selecting a prediction model for the at least one traffic participant depending on the priority relationship; predicting at last one hypothetical future trajectory for the ego-vehicle and, based on the selected prediction model, at last one hypothetical future trajectory for the at least one traffic participant; and calculating a behavior relevant score for ego-vehicle based on the calculated hypothetical future trajectories.

Method for assisting a driver, driver assistance system, and vehicle including such driver assistance system

The method for assisting a person in operating in a dynamic environment may form part of a mobility assistance system. The method comprises a step of acquiring sensor data comprising a time sequence of at least two consecutive images of the dynamic environment from at least one sensor, for example a camera. Optical flows are calculated based on the at least two consecutive images. Feature scores associated to spatial positions for selected regions in an image space are determined in order to generate a feature score field. An output signal including directional stimulus information is generated based on the generated feature score field, wherein the directional stimulus information comprises information on relative spatial relations between the selected regions. The generated output signal is provided to at least one actuator, which signals the directional stimulus information to the person.

Optical flow based assistance for operation and coordination in dynamic environments

An automotive driver assistance for a vehicle with an improved capability to handle obstructed sensor coverage includes steps of acquiring sensor data on an environment of the vehicle from at least one sensor, of generating an environment representation based on the acquired sensor data and of predicting at least one behavior of the vehicle. The method determines at least one area in the environment of the vehicle wherein for the at least one area either a confidence for the sensor data is below a threshold or no sensor data is available and generates at least one virtual traffic entity in the at least one determined area, wherein the virtual traffic entity is adapted to interact with the at least one predicted behavior of the vehicle. A risk measure for each combination of the at least one virtual traffic entity and the predicted behavior of the vehicle is estimated, the calculated risk measure is evaluated and a controlling action for the vehicle is executed based on the evaluated risk measure.

Risk based driver assistance for approaching intersections of limited visibility

An advanced driver assistant system and a method for assisting a driver of a vehicle in driving the vehicle. The system includes sensing means for sensing an environment of the vehicle, a storing unit for storing a database for storing prototypical situations associated with risk information, a processing unit and an output unit to output an assistance signal on the basis of which driver information can be output and/or vehicle operators can be actuated. The processing unit is configured to determine parameters of the vehicle and/or objects in the environment of the vehicle based upon the sensing means output, to classify a traffic situation on the basis of the determined parameters by comparing the determined parameters with parameters of the prototypical traffic situations, to extract risk information from the database and to calculate an expected risk for the encountered traffic situation on the basis of the extracted risk information.

Method and system for assisting a driver of a vehicle in driving the vehicle, vehicle and computer program

In one aspect, an image processing method for processing images is provided, comprising the steps of: obtaining, from an optical sensor, at least two images, determining an image warping function at least partially compensating the distortion, applying the determined image warping function to the image including the distortion, and calculating by a processing unit, and outputting, a depth and/or disparity image from the at least two images.

Depth sensing method and system for autonomous vehicles

The present invention presents a sensing systemand a corresponding method for detecting moving objectsin the surroundings of a vehicle. The sensing systemcomprises an imaging unitfor obtaining an image stream, a computing unitfor analyzing the image stream, and a control unitfor controlling the vehiclebased on the analysis result of the computing unit. The sensing systemparticularly employs a background-model-free estimation. The sensing systemis configured to perform a local analysis of two neighboring motion vectors, which are computed from pointsin imagesof the image stream, and to determine, whether the pointscorresponding to these motion vectorsbelong to a particularly moving object.

Sensing system and method for detecting moving objects

A method supports driving an ego-vehicle including a driver assistance system. A traffic participant or infrastructure element involved in the traffic situation is selected and taken into consideration for traffic scene analysis. A hypothetical future trajectory for the ego-vehicle is predicted by predicting the current state of the ego-vehicle and varied to generate a plurality of ego-trajectory alternatives including the calculated hypothetical future ego-trajectory. A hypothetical future trajectory from another traffic participant gained by predicting the current state of the traffic participant or calculating a hypothetical future state sequence of the infrastructure element is determined. Based upon at least one pair of ego-trajectory plus one other trajectory risk functions over time or along the calculated hypothetical future ego-trajectory alternatives are calculated. One risk function corresponds to one ego-trajectory alternative. The risk functions are combined into a risk map. From an analysis result a control signal is generated.

Method and vehicle with an advanced driver assistance system for risk-based traffic scene analysis

The invention provides an image processing method for processing a sequence of images, comprising the steps of: obtaining, from a visual sensor, at least two images of the sequence of images, detecting whether the images include a distortion, determining an image warping function at least partially compensating the distortion, applying the determined warping function to the image(s) including the distortion, and calculating by a processing unit, and outputting, an optical flow as a displacement vector field form the images.

System and method for distorted camera image correction

The invention presents a method for comparing the similarity between image patches comprising the steps of receiving form at least two sources at least two image patches, wherein each source supplies an image patch, comparing the received image patches by extracting a number of corresponding subpart pairs from each image patch, calculating a normalized local similarity score between all corresponding subpart pairs, calculating a total matching score by integrating the local similarity scores of all corresponding subpart pairs, and using the total matching score as an indicator for an image patch similarity, determining corresponding similar image patches based on the total matching score.

Two-stage correlation method for correspondence search

The present invention proposes a warning system that can be implemented in any kind of vehicle, in order to efficiently detect moving objects. The system utilizes at least one camera for a continuous imaging of the surroundings of the vehicle. Thereby, moving objects can be monitored. A computing unit is programmed to estimate a motion of any moving object based on a pixel motion in the camera image. If a dangerously moving object is detected, a warning unit can be used for issuing a warning signal. To take such a decision, the estimated motion of at least one of the moving objects can be correlated or compared to predetermined motion patterns.

Video-based warning system for a vehicle

Estimating the dynamic states of a real-world object over time using a camera, two dimensional (2D) image information and a combination of different measurements of the distance between the object and the camera. The 2D image information is used to track a 2D position of the object as well as its 2D size of the appearance and change in the 2D size of the appearance of the object. In addition, the distance between the object and the camera is obtained from one or more direct depth measurements. The 2D position, the 2D size, and the depth of the object are coupled to obtain an improved estimation of three dimensional (3D) position and 3D velocity of the object. The object tracking apparatus uses the improved estimation to track real-world objects. The object tracking apparatus may be used on a moving platform such as a robot or a car with mounted cameras for a dynamic visual scene analysis.

Visually tracking an object in real world using 2D appearance and multicue depth estimations

The invention proposes a method for object and object configuration tracking based on sensory input data, the method comprising the steps of:

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Offenbach, Germany

Julian Eggert