Abstract: A method and system for predicting a near future path for a vehicle. For predicting the near future path sensor data and vehicle driving data is collected. Road data is collected indicative of a roadway on the presently occupied road for the vehicle. The sensor data and the vehicle driving data is pre-processed to provide object data comprising a time series of previous positions, headings, and velocities of each of the objects relative the vehicle. The object data, the vehicle driving data, and the road data is processed in a deep neural network to predict the near future path for the vehicle. The invention also relates to a vehicle comprising the system.

Abstract: A method for predicting a trajectory of at least one secondary road user for avoiding a collision course with the secondary road user for a host vehicle. The method includes determining the present location for the host vehicle, retrieving a plurality of modelled clusters of trajectories for a present traffic situation, and detecting the position and speed of the at least one secondary road user. The method also includes predicting at least one feasible trajectory for the at least one secondary road user based on the position and the speed of the at least one secondary road user to the plurality of modelled clusters of trajectories and selecting at least one feasible trajectory of the feasible trajectories for each secondary road user based on a selection criterion. At least one action is performed based on the selected at least one feasible trajectory.

Abstract: A method for providing an alert signal to a control unit of a vehicle for controlling driver intervention. The method comprises determining a set of present driving behavior data indicative of a present driving behavior in a present driving situation and retrieving a driving model indicative of expected driving behavior for the present driving situation. Further, a plurality of expected near future paths for the vehicle are predicted and an actual path is additionally determined. The set of present driving behavior data is mapped with the driving model. When a predetermined degree of deviation in the set of present driving behavior data compared to the driving model is found and the actual path deviates from the predicted expected paths, the alert signal is provided.

Abstract: A method and a system for predicting a near future path and an associated output control signal for a vehicle. Prediction sensor data, vehicle driving data, and road data are collected. An input control signal indicative of an intended driving action is received. The sensor data and the vehicle driving data are pre-processed to provide a set of object data comprising a time series of previous positions of a respective object relative the vehicle, a time series of the previous headings of the object, and a time series of previous velocities of the object. The object data, the road data, the vehicle driving data, the control signal, and the sensor data are processed in a deep neural network. Based on the processing in the deep neural network, a predicted path output and an output control signal are provided.

Abstract: A method for predicting a trajectory of at least one secondary road user for avoiding a collision course with the secondary road user for a host vehicle. Determining the present location for the host vehicle. Retrieving a plurality of modelled clusters of trajectories for a present traffic situation. Detecting the position and speed of the at least one secondary road user. Predicting at least one feasible trajectory for the at least one secondary road user based on the position and the speed of the at least one secondary road user to the plurality of modelled clusters of trajectories. Selecting at least one feasible trajectory of the feasible trajectories for each secondary road user based on a selection criterion. Performing at least one action based on the selected at least one feasible trajectory.

Abstract: Described herein is a method for constructing and updating a behavioral layer of a multi layered road network high definition digital map. By sensors of a plurality of road vehicles travelling through the road network is detected data relating to at least the positions and velocities of static and moving objects. Data concerning the detected objects is sent to the cloud for data aggregation. The aggregated data is analyzed to determine or predict behavioral patterns of the detected objects for different segments of the map. The determined or predicted behavioral patterns of the detected objects are added to the behavioral layer of the map. Also described is a road network high definition map comprising such a behavioral layer as well as a Geographic Information System that is arranged to construct and update such a behavioral layer of a multi layered road network high definition digital map.

Abstract: A method and system for predicting a near future path for a vehicle. For predicting the near future path sensor data and vehicle driving data is collected. Road data is collected indicative of a roadway on the presently occupied road for the vehicle. The sensor data and the vehicle driving data is pre-processed to provide object data comprising a time series of previous positions, headings, and velocities of each of the objects relative the vehicle. The object data, the vehicle driving data, and the road data is processed in a deep neural network to predict the near future path for the vehicle. The invention also relates to a vehicle comprising the system.

Abstract: A method and a system for predicting a near future path and an associated output control signal for a vehicle. Prediction sensor data, vehicle driving data, and road data are collected. An input control signal indicative of an intended driving action is received. The sensor data and the vehicle driving data are pre-processed to provide a set of object data comprising a time series of previous positions of a respective object relative the vehicle, a time series of the previous headings of the object, and a time series of previous velocities of the object. The object data, the road data, the vehicle driving data, the control signal, and the sensor data are processed in a deep neural network. Based on the processing in the deep neural network, a predicted path output and an output control signal are provided.

Abstract: A method for providing an alert signal to a control unit of a vehicle for controlling driver intervention. The method comprises determining a set of present driving behavior data indicative of a present driving behavior in a present driving situation and retrieving a driving model indicative of expected driving behavior for the present driving situation. Further, a plurality of expected near future paths for the vehicle are predicted and an actual path is additionally determined. The set of present driving behavior data is mapped with the driving model. When a predetermined degree of deviation in the set of present driving behavior data compared to the driving model is found and the actual path deviates from the predicted expected paths, the alert signal is provided.

Abstract: The invention relates to a method for control of a flying wing. The flying wing is arranged to be controlled to move along a predetermined trajectory by means of a fluid stream passing a wing of the flying wing. The flying wing comprises at least one control surface for controlling the movement of the flying wing along the predetermined trajectory. The flying wing is positioned in a reference frame where the x-axis is directed horizontally along a level L above which the flying wing moves, the y-axis is perpendicular to the x-axis in a vertical direction and the z-axis is perpendicular to the x-axis along the level L in a direction along the principal direction of the fluid stream. The invention further relates to a system comprising a flying wing and a computer-readable medium for use with a flying wing.

Abstract: The invention relates to a method for control of a flying wing. The flying wing is arranged to be controlled to move along a predetermined trajectory by means of a fluid stream passing a wing of the flying wing. The flying wing comprises at least one control surface for controlling the movement of the flying wing along the predetermined trajectory. The flying wing is positioned in a reference frame where the x-axis is directed horizontally along a level L above which the flying wing moves, the y-axis is perpendicular to the x-axis in a vertical direction and the z-axis is perpendicular to the x-axis along the level L in a direction along the principal direction of the fluid stream. The invention further relates to a system comprising a flying wing and a computer-readable medium for use with a flying wing.