Honda Research Institute Europe Gmbh

Honda Motor Co., Ltd.

Sven Rebhan

Nils Einecke

Jens Schmüdderich

Marcus Kleinehagenbrock

Julian Eggert

Robert Kastner

Naoki Mori

Morimichi Nishigaki

Volker Willert

Hiroyuki Kamiya

Shunsuke Kusuhara

Jens Schmudderich

Mathias Franzius

Keiji Muro

Jörg Deigmöller

Chen Zhang

Thomas Weiβwange

Jens Schmuedderich

Thomas H Weisswange

Jörg Klaus Deigmöller

Jens Dr Schmüdderich

A vehicle transmits vehicle data to an observer entity when the vehicle and the observer entity are in proximity. The vehicle data includes unique vehicle identification information; proximity is defined by an upper threshold for a distance between the vehicle and the observer entity. The observer entity adds data to the vehicle data, the added data including an indication of a position of the observer entity and a time stamp indicating a time of reception of the vehicle data to generate joint data. The joint data is transmitted to an external database and the aforementioned steps are repeated. From the added data a usage estimation value is calculated which is a measure for usage of the vehicle and which is compared with the vehicle usage data retrieved from the vehicle. Information on validity of the vehicle usage data based on the comparison result is generated and output.

Method and system for verifying vehicle usage data

A system comprising an autonomous mobile device and a base station connected to a boundary wire is configured to transmit information from the base station to the autonomous mobile device. The base station is configured to generate a radio signal to be emitted by the boundary wire, wherein the autonomous mobile device is configured to autonomously drive within a working area based on the signal emitted by the boundary wire. The base station on the other hand is configured to encode data and/or commands into the radio signal which is then emitted by the boundary wire. The autonomous mobile device receive the emitted radio signal and is configured to decode the encoded data and/or commands in order to retrieve the original information.

System comprising an autonomous mobile device and a base station communicating via a boundary wire

A method and a system can generate a representation of a working area of an autonomous lawn mower. The system can include an autonomous lawn mower and a base station, and a boundary wire forming a closed loop which can be connected with the base station. The lawn mower and the base station interact such that the lawn mower can determine whether it is in its home position, a predetermined position that is taken when the mower returns to the base station. The lawn mower further includes a memory, for storing values from a movement sensor. A trajectory is generated based on the values, wherein a processor is configured to calculate an error between the position and orientation according to the trajectory and the home position. This total position error and total orientation error is then used to correct the position and corresponding orientations of the trajectory.

Method for generating a representation of a working area of an autonomous lawn mower and autonomous lawn mower system

The invention relates to a driving assistant adapted for active control of a vehicle based on predictions of a behavior of a detected object. A method aspect of the invention comprises accepting a first prediction of a behavior associated with the detected object from a first prediction subsystem and a second prediction from a second prediction subsystem; determining a control signal based on a combination of the first prediction and the second prediction; and initiating active control of the vehicle based on the control signal.

Driving assistance technique for active vehicle control

The present invention relates to a method for assisting a driver in driving a vehicle, in which sensor data are produced by at least one sensor physically sensing the environment of a host vehicle or by obtaining data conveying information about the environment of a host vehicle, an object in a path of the host vehicle is detected based on the sensor data, a distance between the host vehicle and the detected object is controlled based on a preset gap (t), environmental conditions of the host vehicle are estimated based on the sensor data, gap adaption indicators associated to the estimated environmental conditions are determined, wherein each of the gap adaption indicators indicates an extension or a reduction of the preset gap (t) and the preset gap (t) is adjusted based on the gap adaption indicators.

Intelligent gap setting for adaptive cruise control

The invention regards a method for improving performance of a method for computationally predicting a future state of a target object, a driver assistance system and a vehicle with such driver assistance system. First data describing a traffic environment including a target object is acquired. On the basis of the acquired data at least one prediction step for estimating a future state of an object in the traffic environment is performed and a signal indicative of a prediction result describing an estimated future state of the target object and/or an ego vehicle is generated. An actual state of the target object and/or the ego vehicle is observed and quality of the prediction by comparing the observed actual state and the prediction result is estimated. Finally the prediction result and/or parameters of the prediction algorithm is adapted.

Method for improving performance of a method for computationally predicting a future state of a target object,  driver assistance system, vehicle including such driver assistance system and respective program storage medium and program

A system and method assists a driver of a host vehicle in potential lane change situations. The method includes producing sensor data by a sensor physically sensing the environment of the host vehicle, predicting future movement behavior of at least one sensed vehicle, and determining whether a gap on a neighboring lane of the host vehicle exists. If the neighboring lane of the host vehicle would fit better for the predicted future movement behavior, a recommendation information signal is generated. Feasibility is determined by combining the determination result of the existence of a gap and the predicted future behavior. A notification for the host vehicle is output or, if lane change is feasible, signals for performing autonomous lane change based upon the recommendation information signal by the host vehicle are output.

Method and system for predictive lane change assistance, program software product and vehicle

A method predicts trajectories of traffic objects to avoid collisions. The method estimates the probability for at least two traffic objects to collide, and predicts a potential movement of the traffic objects presumably involved in the collision after the collision. This information about a potential movement of the traffic objects can be used to plan a suitable trajectory path of an evasion maneuver for a host-vehicle employing the method. A system detects the collision situation and applies crash situation models to predict the future dynamic properties of other traffic objects that collide or are about to collide with each other. The method and system applies specific crash models like collision models, models derived from crash simulations and tests or models of human reactions in emergency situations.

Method and system for post-collision manoeuvre planning and vehicle equipped with such system

In an intelligent forward collision warning system that takes into account not only a first preceding vehicle traveling immediately ahead of the ego vehicle but also a second preceding vehicle traveling immediately ahead of the first preceding vehicle, a warning signal is produced upon detecting a critical state of the first or second preceding vehicle or an external condition that is predicted to cause the first preceding vehicle and the ego vehicle to be in a same lane with the first time to collision (TTC) below a prescribed value.

Intelligent forward collision warning system

The invention relates to a driver assistance system for a vehicle, the vehicle comprising at least one sensor means, at least one actuating means and a control means. The method comprises the steps of generating a decision signal by a first evaluation of sensor data acquired by the sensor means, generating an activation signal for the actuating means when the decision signal exceeds a signal threshold, generating a interrupt decision signal based on a second evaluation, stabilizing the activation signal in a temporal manner, deciding based on the decision interrupt signal if to interrupt stabilizing the activation signal, and interrupting stabilizing the activation signal, when it is decided to interrupt stabilizing the activation signal.

Consistent behavior generation of a predictive advanced driver assistant system

A method for detecting the position of a target object in the environment of a host vehicle. The method may include receiving a first position of the target object as detected by an object position sensor which emits waves and receives the waves that are reflected back by the target object, and receiving an image containing the target object as detected by an image sensor. The method may also include projecting the first position on the image, and refining the first position by computing a second refined position of the target object on the basis of a symmetry search within the image.

Vehicle with improved traffic-object position detection using symmetric search

A technique for assigning lanes on a road to objects moving in a vicinity of a vehicle on the road is proposed. A method embodiment of the invention comprises the steps of providing trajectories, wherein the or each trajectory represents a time sequence of positions of a moving object; selecting first and second objects and determining a distance between a current position of the first object and the trajectory of the second object; comparing the distance with a predefined threshold; and providing, based on a result of the comparison, a lane assignment indicating a lane to which the second object is assigned.

Technique for lane assignment in a vehicle

A method for computationally predicting future movement behaviors of at least one target object can have the steps of The context based prediction step uses a set of classifiers, each classifier estimating a probability that said sensed target object will execute a movement behavior at a time. The method can also include

Method and system for predicting movement behavior of a target traffic object

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

Generally the background of the present invention is the field of artificial vision systems, i.e. systems having a visual sensing means (e.g. a video camera) and a following processing stage implemented using a computing unit. The processing stage outputs a representation of the visually analysed scene, which output can then be fed to control different actors, such as e.g. parts of a vehicle (automobile, plane, . . . ) or a robot, preferably an autonomous robot such as e.g. a humanoid robot.

Growing community of inventors

Offenbach, Germany

Sven Rebhan