Abstract: The invention relates to a control system for an autonomous vehicle, a method and an autonomous vehicle. The system comprises an image capturing means capable of capturing at least a first image of the environment of the vehicle and a second image of the environment, wherein the images are captured in a close time relationship but with different image capturing parameters. A processing means configured to obtain and process the images captured with different image capturing parameters separately and taking into consideration a first intensity threshold when processing the first image and a second, different intensity threshold when processing the second image. A control means for generating and outputting a control signal on the basis of a result of the at least one of the processed images.

Abstract: The invention relates to an autonomous lawn mower comprising a control unit in electrical connection with electrical connection means, and at least one replaceable part. The electrical connection means is located such that connection and disconnection of the electrical connection means and its counterpart of the replaceable part can be performed when replacing the replaceable part. The module for such autonomous lawn mower can replace the replaceable part of the lawn mower and comprises a signal generation unit and a counterpart for the electrical connection means of the lawn mower for transmitting electrical signals to a control unit of the autonomous lawn mower. The autonomous lawn mower forms an autonomous lawn mower system together with the module.

Abstract: 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.

Abstract: 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.

Abstract: The invention regards to a method for assisting a driver in driving a vehicle, comprising the steps of producing sensor data by at least one sensor physically sensing the environment of a host vehicle and/or obtaining data conveying information about the environment of a host vehicle, generating a plurality of representation segments each segment being a portion of an entire area of representation of the environment of the host vehicle at a particular point in time wherein a relative position of the portion of such representation segment with respect to a current position of the host vehicle corresponds to a possible position of the host vehicle at that particular point in time, combining the representation segments to a spatio-temporal representation of the environment of the host vehicle; evaluating the spatio-temporal representation and outputting an assistance signal on the basis of an evaluation result.

Abstract: 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.

Abstract: A method for analyzing related images corresponding system and vehicle including such system as well as a computer program product for executing the method. The method comprises obtaining at least a first and a second image, defining a pixel patch in the first image for which a correlation shall be calculated, calculating matching cost values between each pixel of the pixel patch in the first image and its corresponding pixel in each of a plurality of pixel patches in the second image, wherein the pixel patches in the second image differ in position in the second image and include the pixel patch with a target position, aggregating the matching cost values of those corresponding pixels of all patches in the second image which match best to generate an aggregation window associated with the target position, and producing a signal including information on the target position.

Abstract: A computer-implemented method of analyzing data representing the optimization of real-world designs of physical entities according to at least one criterion. Different modifications of the design are generated by a cyclic optimization algorithm. The design data is represented by unstructured triangular surface meshes. A displacement measure representing local differences between two design modifications of the different modifications is calculated. Performance difference between the two design modifications is calculated. The performance difference is represented by at least one criterion. Sensitivity information representing correlation between the displacement measure and the performance differences is outputted.

Abstract: The invention relates to a method for controlling a driver assistance system comprising the steps of providing information on an environment of a host vehicle, receiving a spoken instruction from a host vehicle driver, generating an attention delegation task for evaluation of the provided information from the spoken instruction, performing evaluation of provided information in accordance with said attention delegation task and outputting a result of the evaluation.

Abstract: The invention regards a method for assisting a driver of a vehicle by computationally predicting a future movement behavior of a target vehicle. The method comprises steps of acquiring data describing a traffic environment of a host vehicle, computing a plurality of future movement behavior alternatives for a target vehicle, by predicting movement behavior of the target vehicle based on the data describing the traffic environment. The prediction step calculates a probability that the target object will execute a movement behavior and information relating to future behavior of the target vehicle is output. The method estimates a global scene context and adapts the predicted behavior based on the estimated global scene context. The adaptation of the behavior prediction is performed by at least one of adapting indicator values in situation models employed by a context-based prediction, by adapting a result of the context-based prediction and adapting the overall prediction result.

Abstract: 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.

Abstract: The inventive system comprises an autonomous robot device, a base station and a method operating the same. The autonomous robot device includes a sensor means, e.g. an optical sensor, and a propulsion means. The base station includes a cleaning means specifically adapted for cleaning the sensor means of the autonomous robot device. In a preferred embodiment the propulsion means of the autonomous robot device is configured to move the autonomous robot device in a manner suitable to generate a relative movement of the autonomous robot device with respect to the passive cleaning means arranged at the stationary base station to effect the cleaning of the sensor means of the autonomous robot device.

Abstract: The present invention provides an Advanced Driver Assistant System (ADAS) 10 and an operating method thereof, which work on long time scales, and guide an ego vehicle 20 away from upcoming risks, rather than only reacting to risks to mitigate the consequences of a crash. To this end, information comprising the orientation of other traffic participants 30, 40, 50, 60, a free driving area of the ego vehicle 20, and/or a driving trajectory of the vehicle 20 as intended by the driver is taken into account, in order to determine potential risks.

Abstract: A distance measurement method determines the distance of a sensor system to a physical object. The method includes obtaining at least a pair of stereoscopic images including the physical object, and applying to each element of at least a portion of a first image of the pair of stereoscopic images and to each element of at least a portion of a second image of the pair of stereoscopic images at least two differently shaped or sized filters, respectively. Correlation values for each filter applied to the first and second image are determined, and, combined correlation values are determined for the applied filters by combining the determined correlation values for each applied filter. The combined correlation values are evaluated for different disparities for an extremum value of the combined correlation values. A distance value to the physical object is calculated and output based on a disparity value at which the extremum occurs.

Abstract: The present invention presents a sensing system 1 and a corresponding method for detecting moving objects 11 in the surroundings of a vehicle 10. The sensing system 1 comprises an imaging unit 2 for obtaining an image stream 2a, a computing unit 3 for analyzing the image stream 2a, and a control unit 4 for controlling the vehicle 10 based on the analysis result of the computing unit 3. The sensing system 1 particularly employs a background-model-free estimation. The sensing system 1 is configured to perform a local analysis of two neighboring motion vectors 6, which are computed from points 7a in images 5a, 5b of the image stream 2a, and to determine, whether the points 7a corresponding to these motion vectors 6 belong to a particularly moving object.

Abstract: 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.

Abstract: 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.

Abstract: The invention relates to a method for determining a static element in images captured by an imaging means mounted on a movable device. The method comprises steps of acquiring a first image and a second image captured by the imaging means. The first image and the second image are captured at capture times separated by a time difference and the method is characterized by the time difference being selected depending on motion parameters of the movable device. A determination measure for corresponding regions of the first and the second image for representing a similarity of the corresponding regions is calculated and a static element of the first and the second image is determined based on the calculated determination measure. An output signal comprising information on the determined static element is generated.

Abstract: The invention provides a driver assistance method, comprising the steps of: sensing a vehicle's state and the environment, on the basis of sensing output signals, determining whether a critical state of the vehicle is to be expected in the future, if yes, determining a total amount and a time duration of an activation of at least one vehicle actuator required in order to avoid occurrence of the critical state, the activation being of a nature which can be sensed by the driver of the vehicle, and partially performing, by a control module, the activation, i.e. for a portion of the amount and/or a portion of the time duration of the determined total amount and time duration.

Abstract: 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.