Abstract: Embodiments described herein disclose methods and systems for discrete mobile object monitoring. Using location and information from the recognition process, historical action information about a discrete mobile object, and associated object statistical information derived from the historical action information, a hypothesis can be generated for future actions and movements of the discrete mobile object. The information can then be stored for later hypothesis derivation, thus providing a more human-like understanding of the discrete mobile object, useful in a variety of automated tasks.

Abstract: This disclosure relates to systems and methods for determining predicted risk for a flight path of an unmanned aerial vehicle. A previously stored three-dimensional representation of a user-selected location may be obtained. The three-dimensional representation may be derived from depth maps of the user-selected location generated during previous unmanned aerial vehicle flights. The three-dimensional representation may reflect a presence of objects and object existence accuracies for the individual objects. The object existence accuracies for the individual objects may provide information about accuracy of existence of the individual objects within the user-selected location. A user-created flight path may be obtained for a future unmanned aerial flight within the three-dimensional representation of the user-selected location. Predicted risk may be determined for individual portions of the user-created flight path based upon the three-dimensional representation of the user-selected location.

Abstract: An unmanned aerial vehicle (UAV) includes one or more processors, and a memory storing instructions. When executed by the one or more processors, the instructions cause the UAV to perform operations including: recognizing a first gesture of a hand; responsive to a recognition of the first gesture, moving the unmanned aerial vehicle to hover above the hand; detecting a distance between the unmanned aerial vehicle and the hand; responsive to a determination that the distance falls in a range, monitoring the hand to recognize a second gesture of the hand; and responsive to a recognition of the second gesture, landing the unmanned aerial vehicle on the hand.

Abstract: A line detector apparatus and method on a vehicle for detecting a line on a road with a higher degree of accuracy. The vehicle includes front, right-side and left-side image capturing sensors mounted on a vehicle and respectively capture an image, including a road surface, at the front and right and left sides of the vehicle to respectively generate front, right-side and left-side images. The line detector includes a processor that calculates a line on a road as a first line from the front image, the line on the road as a second line from the right-side image, and the line on the road as a third line from the left-side image. The processor selects one of multiple mutually-different algorithms based on the first to third lines, and calculates the line on the road based on the first to third lines by using the selected algorithm.

Abstract: A system includes a camera mounted on an aircraft, one or more processors, and computer readable memory, for determining a location of an aircraft relative to fiducial markings of airport byways. The method includes the steps of capturing, by a camera disposed on the aircraft, a time-sequence of images of a scene external to the aircraft, wherein the scene includes the byways and the fiducial markings; identifying, by image processing circuitry, pixel coordinates within each of the time sequence of captured images corresponding to the fiducial markings; and determining, by the image processing circuitry, the location of the aircraft relative to the fiducial markings based on the identified pixel coordinates.

Abstract: Interaction-aware decision making may include training a first agent based on a first policy gradient, training a first critic based on a first loss function to learn goals in a single-agent environment using a Markov decision process, training a number N of agents based on the first policy gradient, training a second policy gradient and a second critic based on the first loss function and a second loss function to learn goals in a multi-agent environment using a Markov game to instantiate a second agent neural network, and generating an interaction-aware decision making network policy based on the first agent neural network and the second agent neural network. The N number of agents may be associated with a driver type indicative of a level of cooperation. When a collision occurs, a negative reward or penalty may be assigned to each agent involved based on a lane priority level of respective agents.

Abstract: An apparatus for controlling a lane change of an autonomous vehicle and a method thereof. The apparatus includes a learning device that performs deep learning by subdividing situation information into groups to be considered when the autonomous vehicle changes a lane, and a controller that controls the lane change of the autonomous vehicle based on a learning result of the learning device.

Abstract: A navigation system includes: a control unit configured to: identify a route obstacle in a travel environment of a user vehicle during operation of the user vehicle in an autonomous operation mode; generate an obstacle handling assessment of whether the user vehicle is capable of navigation beyond the route obstacle in the autonomous operation mode; generate an obstacle orientation alert based on the obstacle handling assessment and an engagement state of a system user of the user vehicle; a user interface, coupled to the control unit, configured to present the obstacle orientation alert.

Abstract: A method for ascertaining an expected contour of a mobile or stationary device for avoiding collisions, using at least one control unit that is internal external to the device includes: obtaining a movement trajectory of the device, which contains probability densities based on state estimation, at least based on expected values and covariances; obtaining a base polyhedron and an approximate contour of the device having a limited number of corners, a confidence interval within which a collision with the static and dynamic surroundings of the device is to be avoided being defined; transforming the base polyhedron to the at least one probability density of the movement trajectory that describes the state estimation; and, for each corner of the transformed base polyhedron, computing a transformed device contour, and ascertaining the expected contour of the device with inclusion of all transformed device contours.

Abstract: An automated driving assist apparatus includes a traffic information acquirer, a traffic congestion determiner, a distance comparator, a lane-change start determiner, and a lane-change controller. When the traffic congestion determiner determines that a passing lane adjacent to a lane regulation zone is congested, the distance comparator calculates a distance to the lane regulation zone and an estimated distance to a traffic queue based on road traffic information acquired by the traffic information acquirer, and compares the distance to the lane regulation zone with the estimated distance to the traffic queue. When the distance to the lane regulation zone is longer than the estimated distance to the traffic queue, the lane-change start determiner determines whether the estimated distance to the traffic queue reaches a lane-change start distance. When the estimated distance to the traffic queue reaches the lane-change start distance, the lane-change controller causes the own vehicle to change lanes.

Abstract: A machine learning engine may correlate characteristics of obstacles identified during remotely piloted UAV flights with manual course deviations performed for obstacle avoidance. An obstacle detection application may access computer vision footage to determine notable characteristics (e.g. a direction of travel and/or velocity) of obstacles identified during the piloted UAV flights. A deviation characteristics application may access flight path information identify course deviations performed by a pilot in response to the obstacles. A machine learning engine may use the obstacle characteristic data and the deviation characteristics data as training data to generate an optimal course deviation model to use by an autopilot module to autonomously avoid obstacles during autonomous UAV flights.

Abstract: An autonomous vehicle is described, wherein the autonomous vehicle is configured to estimate a change in direction of a vehicle that is on a roadway and is proximate to the autonomous vehicle. The autonomous vehicle has a mechanical system, one or more sensors that generate one or more sensor signals, and a computing system in communication with the mechanical system and the one or more sensors. The autonomous vehicle is configured to detect an imminent lane change by another vehicle based on at least one of a computed angle between a wheel of the other vehicle and a longitudinal direction of travel of the other vehicle, a degree of misalignment between the wheel of the other vehicle and a body of the other vehicle, and/or an eccentricity of the wheel of the other vehicle. The mechanical system of the autonomous vehicle is controlled by the computing system based upon the detected imminent lane change.

Abstract: Various aspects of this disclosure provide an area occupancy determining device. The device may include a memory configured to store at least one occupancy grid of a predetermined region, and a processor. The processor may be configured to generate the occupancy grid of the predetermined region. The occupancy grid includes a plurality of grid cells, each grid cell framed by respective grid cell frame lines. At least some of the grid cells have been assigned an information about the occupancy of the region represented by the respective grid cell. The processor may further be configured to dynamically update the occupancy grid, thereby successively generating a plurality of updated occupancy grids. Each updated occupancy grid is moved relative to the previous occupancy grid such that an origin coordinate of the updated occupancy grid is positioned on a contact point of grid cell frame lines of adjacent grid cells.

Abstract: In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

Abstract: There are provided a road shape predictor predicts the shape of a road, based on positional information pieces, on other vehicles existing in the vicinity of a reference vehicle, that are obtained from the communicator and a road shape prediction priority determiner that determines the priorities of areas in the vicinity of the reference vehicle in the case where the road shape predictor predicts the shape of the road for the predicted route of the reference vehicle.

Abstract: An apparatus for controlling a lane change of a vehicle may include: a processor determining whether a condition of interrupting a lane change procedure occurs, during controlling the lane change. In particular, when the condition of interrupting the lane change procedure is satisfied, the processor determines whether to interrupt the lane change procedure or whether to return the vehicle to an original lane to control the vehicle depending on a result of the determinations. The apparatus further includes a storage to store the result determined by the processor.

Abstract: In order to provide an unmanned aircraft capable of minimizing damage due to a crash caused by malfunction or the like during flight, a flight route is set on map information including a fall avoidance area, control is performed such that the aircraft flies on a set flight route, and information at each position during flight on the flight route is acquired in relation to the map information in real time to determine whether or not the aircraft is approaching the fall avoidance area. In a case where it is determined that the aircraft is approaching the fall avoidance area, control is performed so as to increase a flight speed.

Abstract: A driving assist device includes a control unit configured to acquire event position information that is position information about a vehicle when it is detected that a driver of the vehicle is in a looking aside state in the vehicle, as an event, and configured to present attention information calling for attention, to a driver who is driving toward a position indicated by the event position information.

Abstract: Efficient and scalable three-dimensional point cloud segmentation. In an embodiment, a three-dimensional point cloud is segmented by adding points to a spatial hash. For each unseen point, a cluster is generated, the unseen point is added to the cluster and marked as seen, and, for each point that is added to the cluster, the point is set as a reference, a reference threshold metric is computed, all unseen neighbors are identified based on the reference threshold metric, and, for each identified unseen neighbor, the unseen neighbor is marked as seen, a neighbor threshold metric is computed, and the neighbor is added or not added to the cluster based on the neighbor threshold metric. When the cluster reaches a threshold size, it may be added to a cluster list. Objects may be identified based on the cluster list and used to control autonomous system(s).

Abstract: A method for receiving autonomous vehicle (AV) map data associated with an AV map of a geographic location and coverage map data associated with a coverage map of the geographic location. The AV map data is associated with an AV lane of a roadway in the geographic location, and the coverage map data is associated with a coverage lane of the roadway in the geographic location. The method includes generating a hybrid map of the geographic location based on the AV map data and the coverage map data and providing hybrid map data associated with the hybrid map for routing of an AV. The hybrid map includes the AV lane linked with the coverage lane of the roadway.

Abstract: A traveling assistance method acquires driving characteristics of another vehicle around a host vehicle, determines whether the other vehicle is in an autonomous driving mode depending on the driving characteristics of the other vehicle, and detects an action of the other vehicle in accordance with the determination result of whether the other vehicle is in the autonomous driving mode.

Abstract: Aspects of the disclosure are directed towards obstacle position and extent measurement. In accordance with one aspect, obstacle detection includes creating one or more interferometric measurements to generate a flow of response position locations using a flow of range/Doppler detections by fitting a parametric expression; and deriving one or more scatterer positions and obstacle position and extent measurements from the flow of response position locations.

Abstract: A method is disclosed. A data set including: (a) identifiers of a set of incidents occurring within a defined geographic region to which at least one service provider responded during a first time period and (b) address data identifying a location within the geographic region of each said incident of the set is retrieved over a network. An instruction to generate a heat map of the incidents occurring within the geographic region during the first time period is received from a user via a user interface generated to a display device. In response to the instruction to generate the heat map, the address data is converted to GPS data. A heat map of an aerial view of the geographic region based on the GPS data is generated. The heat map is displayed to the display device in a user interface.

Abstract: Embodiments of the disclosure provide methods and systems for acquiring map data. The system may include a mounting structure configured to adjustably mount a sensor to a vehicle. The sensor may be configured to capture data indicative of at least one surrounding object as the vehicle travels along a path. The system may further include a controller configured to dynamically determine a mounting angle based on the captured data, and cause the mounting structure to adjust the sensor according to the dynamically determined mounting angle.

Abstract: A radar apparatus includes: a detection portion that transmits a radio wave to a target and receives a radio wave reflected on the target so as to detect instantaneous data; and an allocation portion that allocates the instantaneous data to prediction data of the target so as to take continuity of the target; and the allocation portion corrects velocity of the instantaneous data and velocity of the prediction data respectively as velocities made in line with a predetermined direction set as a reference, so as to allocate the instantaneous data to the prediction data based on at least magnitudes of the respectively corrected velocities.

Abstract: A method and an apparatus for lane selection are provided. In the disclosed method that is implemented by the apparatus, a decision model used for a lane change selection is obtained based on a first model configured to decide a junction lane change and a second model configured to decide a travelling speed. In addition, travelling information of a target vehicle and target information related to the target vehicle is acquired in real time. The target information is configured to represent travelling information of one or more vehicles around the target vehicle. A target lane is subsequently defined based on the decision model, the target information related to the target vehicle and the travelling information of the target vehicle that is acquired in real time.

Abstract: The systems and methods disclosed herein are directed to a vehicle proximity system. The vehicle proximity system uses sensors, a vehicle computing device, and a heads-up display of a host vehicle to present proximity graphic elements to a vehicle occupant, such as the driver of the host vehicle. The proximity graphic elements are displayed using a heads-up display and are projected on a transparent surface of the host vehicle, such as the windows, windshield, display screen, lenses, etc. The proximity graphic elements indicate the presence of a proximal vehicle to the host vehicle. In some embodiments, the proximal vehicle is a vehicle passing the host vehicle. Alternatively, the proximal vehicle may be inline with the host vehicle traveling in a forward or rearward direction.

Abstract: Techniques are described for configuring a monitoring system to assist users during a detected emergency condition at a property. In some implementations, sensor data from one or more sensors that are located at the property are obtained by a monitoring system that is configured to monitor the property. A determination that there is an emergency condition at the property is made by the monitoring system based on the sensor data, determining. A location of a person inside the property is determined by the monitoring system based on the sensor data. A first path to the person and a second path to guide the person away from the emergency condition are determined by the monitoring system. The first path to the person and the second path to guide the person away from the emergency condition are navigated by a computing device of the monitoring system.

Abstract: The present disclosure includes using cognitive data analytics for communication between vehicular devices using a 5G (fifth generation cellular network technology) telecommunications network. In a defined area, using an Internet of Things (IoT) enabled device in a first vehicle traveling in a direction, the present disclosure detects a second vehicle traveling in another direction in the defined area. Data is collected in the defined area using the detected IoT devices in the first and second vehicles. The collected data is analyzed to provide content data related to driving conditions for the first and second vehicles. The content data is exchanged between the IoT devices of the first vehicle and the second vehicle in the defined area, thereby providing real-time information related to the driving conditions to a vehicle traveling in another direction, and the exchanging of the content data, using the service orchestration layer of the 5G telecommunications network.

Abstract: A collision avoidance apparatus including: a first detector configured to detect another vehicle information including a longitudinal velocity and a lateral velocity of another vehicle, and distance information including a longitudinal distance and a lateral distance from another vehicle; a second detector configured to detect subject vehicle information including a velocity and a yaw rate of the subject vehicle; a calculator configured to determine whether steering avoidance is executable, on the basis of the another vehicle information, the subject vehicle information, and the distance information, and when steering avoidance is executable, calculate steering avoidance information on steering avoidance of the subject vehicle; and a control unit configured to control the subject vehicle to travel according to the steering avoidance information.

Abstract: A system for correcting road surface information related to an Electronic Control Suspension (ECS), may include a camera recognition information storage configured of securing camera recognition information related to a forward obstacle which is recognized through a navigation device and a camera; a sensor recognition information calculator configured of determining sensor recognition information related to the obstacle by receiving detecting values through vehicle behavior sensors; and a camera recognition information corrector configured of correcting the camera recognition information when a difference is generated between the camera recognition information and the sensor recognition information.

Abstract: The disclosure discloses a method and apparatus for determining a speed of an obstacle. An embodiment of the method comprises: acquiring point cloud data and millimeter wave radar data of a driving environment of a vehicle; respectively processing the point cloud data and the millimeter wave radar data to determine speed information and location information of an obstacle in the driving environment; acquiring speed information of the vehicle; and integrating the speed information and the location information of the obstacle, and the speed information of the vehicle to determine the obstacle speed. The embodiment makes full use of point cloud data obtained by a laser radar and millimeter wave radar data obtained by a millimeter wave radar, and improves the accuracy in obstacle speed detection.

Abstract: Apparatus, method and storage medium associated with UAV assisted emergency responses are disclosed herein. In embodiments, an UAV may comprise a flight controller to control at least one or more engines of the UAV to navigate the UAV to condition road traffic for an emergency vehicle on emergency en route to a destination, wherein to condition road traffic, the flight controller is to receive navigation data of the emergency vehicle, and in response, control at least the one or more engines to navigate the UAV in advance of the emergency vehicle, to alert road traffics ahead of the emergency vehicle of pending transit of the emergency vehicle. Other embodiments may be disclosed or claimed.

Abstract: An apparatus for controlling a lane change of a vehicle may include: a processor determining whether a condition of interrupting a lane change procedure occurs, during controlling the lane change. In particular, when the condition of interrupting the lane change procedure is satisfied, the processor determines whether to interrupt the lane change procedure or whether to return the vehicle to an original lane to control the vehicle depending on a result of the determinations. The apparatus further includes a storage to store the result determined by the processor.

Abstract: Systems and methods for training and evaluating a deep generative model with an architecture consisting of two complementary density estimators are provided. The method includes receiving a probabilistic model of vehicle motion, and training, by a processing device, a first density estimator and a second density estimator jointly based on the probabilistic model of vehicle motion. The first density estimator determines a distribution of outcomes and the second density estimator estimates sample quality. The method also includes identifying by the second density estimator spurious modes in the probabilistic model of vehicle motion. The probabilistic model of vehicle motion is adjusted to eliminate the spurious modes.

Abstract: According to some embodiments, a system pre-processes, via a first thread, a captured image perceiving an environment surrounding the ADV obtained from an image capturing device of the ADV. The system processes, via a second thread, the pre-processed image with a corresponding depth image captured by a ranging device of the ADV using a machine learning model to detect vehicle lanes. The system post-processes, via a third thread, the detected vehicle lanes to track the vehicle lanes relative to the ADV. The system generates a trajectory based on a lane line of the tracked vehicle lanes to control the ADV autonomously according to the trajectory.

Abstract: Provided is an alert apparatus for a vehicle configured to: in a case where a connection state of a switch is an off state, determine whether or not there is an alert-target object based on vehicle peripheral information which has been acquired until an off time point at which the connection state of the switch is changed to the off state, the alert-target object being a moving object to be alerted when an occupant of the vehicle gets out of the vehicle; and configured to, when determining that there is the alert-target object, cause an alerting device to perform an alerting operation.

Abstract: A vehicle sensor includes a first light source for short-distance irradiation and a first camera for short-distance imaging mounted on one headlamp of a pair of left and right headlamps provided in a vehicle, and a second light source for long-distance irradiation and a second camera for long-distance imaging mounted on the other headlamp of the pair of left and right headlamps.

Abstract: An autonomous driving trajectory determination device that is configured to determine an autonomous driving trajectory of a vehicle is configured to include: a standard trajectory generation unit configured to generate a standard trajectory for the autonomous driving of the vehicle; a moving object behavior detection unit configured to detect a behavior of a moving object; a deviating moving object detection unit configured to detect a deviating moving object that deviates from a standard state set in advance based on the behavior of the moving object and the map information; a number-of-deviating-moving objects calculation unit configured to calculate the number of deviating moving objects, which is the number of deviating moving objects interfering with the standard trajectory; and a trajectory determination unit configured to determine whether or not to set the standard trajectory as the autonomous driving trajectory based on the number of deviating moving objects.

Abstract: An autonomous driving device 100 is configured to set a target route to merge into a first main line L11 from a branch line L20 based on waypoints P set in a lane. If it is determined by the merge determination unit 14 that the merge is not easy, the target route setting unit 15 is configured to select the waypoint P on the branch line L20 set at the position on an end edge E side of the branch line L20 as the end edge waypoint Pa closest to the end edge E side on the branch line L20 to be selected for setting the target route, compared to a case where it is determined that the merge is easy.

Abstract: An adaptive sense and avoid system for use with an aerial vehicle in an environment, the adaptive sense and avoid system comprising a processor, a plurality of sensors, an obstacle detection circuit, and an avoidance trajectory circuit. The processor may be operatively coupled with a flight controller and a memory device, wherein the memory device comprises one or more databases. The plurality of sensors generates sensor data reflecting a position of an obstacle in the environment. The obstacle detection circuit, which is operatively coupled to the processor and the plurality of sensors, may be configured to identify obstacles based at least in part on the sensor data and to generate obstacle information that reflects a best estimate of a position of the obstacle in the environment. The obstacle detection circuit is configured to weigh the sensor data as a function of the aerial vehicle's state and its environment.

Abstract: An illustrative example method of classifying a detected object includes detecting an object, determining that an estimated velocity of the object is below a preselected threshold velocity requiring classification, determining a time during which the object has been detected, determining a first distance the object moves during the time determining a speed of the object from the first distance and the time, determining a second distance that a centroid of the detected object moves during the time, and classifying the detected object as a slow moving object or a stationary object based on a relationship between the first and second distances and a relationship between the estimated velocity and the speed.

Abstract: Disclosed is an automatic obstacle avoidance optimization method for a connecting line of graphical programming software. A breadth-first search method is adopted to search an optimal connecting line path, and a result is displayed in a front-end interface. In a generated connecting line, a user can drag the connecting line with a mouse to regulate a position of the connecting line. At the time, the mouse is viewed as an unavoidable point, that is, the connecting line starts from a starting point of the connecting line to the unavoidable point and then reaches an end point of the connecting line. By means of the method, high instantaneity requirements of the user can be met, and when the user drags the connecting line with the mouse, a new connecting line is generated in real time without a stuck phenomenon.

Abstract: Implementations of the present disclosure can include a method and apparatus for processing point cloud data. Specifically, the method for processing point cloud data can be provided, including: acquiring a first frame and a second frame respectively from the point cloud data; extracting a first candidate object from the first frame and a second candidate object corresponding to the first candidate object from the second frame, respectively; determining a first location of the first candidate object and a second location of the second candidate object in a coordinate system of the point cloud data, respectively; and identifying any one of the first candidate object and the second candidate object as a moving object, in response to an offset between the first location and the second location.

Abstract: A vehicle collision avoidance system has a side-view camera positioned on a side portion of a vehicle and configured to present a driver with a rear side view exterior to the vehicle. A display is coupled to the side-view camera and disposed in view of the driver to output a video stream from the side-view camera. A turn signal sensor is configured to detect activation of a turn signal. A controller is configured to receive signals from the turn signal sensor and to adjust a field of view of the side-view camera based on activation of the turn signal.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a vehicle includes at least one processing device programmed to receive, from an image capture device, a plurality of images associated with an environment of the vehicle, analyze at least one of the plurality of images to identify a navigable region in the environment of the vehicle, identify, based on the at least one of the plurality of images, at least one barrier associated with an edge of the navigable region, and determine a type of the at least one barrier. The at least one processing device is also programmed to determine a navigational path of the vehicle based on the determined type of the at least one barrier, and cause the vehicle to travel on at least a portion of the determined navigational path.

Abstract: An integrated object formation unit of a vehicle control device forms integrated objects, which are integral objects, the boundaries of the integrated objects being determined from the positional relationship between two or ore objects in a prescribed distance range. An interference prediction unit of the vehicle control device predicts the probability of the integrated objects, instead of each of the objects, coming into contact with, or near, a vehicle.

Abstract: A method for detecting fallen cargo, the method may include receiving by a computerized system, sensed information related to driving sessions of multiple vehicles; applying a machine learning process on the sensed information to detect fallen cargo and to classify the fallen cargo to fallen cargo classes; estimating, from the sensed information, an impact of at least some of the fallen cargo classes on a behavior of at least some of the multiple vehicles; and determining, based on the impact, at least one suggested vehicle behavior as a response to a detection of at least some of the fallen cargo classes.

Abstract: A collision avoidance control system and method are provided. The system includes a GPS receiver that obtains location information of a vehicle, a navigation system having map information, and a sensor unit that senses a target vehicle located near a roundabout. The sensor obtains traveling information of the target vehicle and forward view image information of the vehicle. A controller then calculates an estimated collision point based on the map information, the location information of the vehicle and the traveling information of the target vehicle to determine a risk of collision based on an absolute value of a difference between an arrival time of the vehicle to the estimated collision point and an arrival time of the target vehicle to the estimated collision point. The speed of the vehicle is then adjusted in response to the determined risk of collision.

Abstract: A system for automated execution of a maneuver or behavior determines at first a situation in which the system currently is based on environment sensing. Then, based on the determined situation, maneuver options or behavior options are determined. Such options are maneuvers or behaviors which potentially can be executed by the system in the determined situation. Then information on at least one of the determined maneuver options or behavior options are output using a haptic display. The system receives an input selecting one of the options from a user. On the basis of the selected option then the selected option or maneuver is executed in an automated fashion.