Abstract: Aspects of the disclosure relate to generating a puddle occupancy grid including a plurality of cells. For instance, a first probability value for a puddle being located at a first location generated using sensor data from a first sensor may be received. A second probability value for a puddle being located at a second location generating using sensor data from a second sensor different from the first sensor may be received. A first cell may be identified from the plurality of cells using the first location. The first cell may also be identified using the second location. A value for the cell may be generated using the first probability value and the second probability value.

Abstract: A virtual visor system is disclosed that includes a visor having a plurality of independently operable pixels that are selectively operated with a variable opacity. A camera captures images of the face of a driver or other passenger and, based on the captured images, a controller operates the visor to automatically and selectively darken a limited portion thereof to block the sun or other illumination source from striking the eyes of the driver, while leaving the remainder of the visor transparent. The virtual visor system advantageously limits the rate of change of the opacity of each pixel of the visor while updating the optical state of the visor. In this way, rapid and distracting changes in the optical state of the visor are avoided, thereby improving the safety of the vehicle.

Abstract: Disclosed is an autonomous mobile robot including a main body, and a driving part positioned below the main body and configured to move the main body, wherein the driving part includes a rotation part that is rotatably provided and is configured to dispose a sensor module including one or more sensors outwards, a base positioned below the rotation part, and a driving wheel installed on the base, thereby embodying a sensing system with low cost and high efficiency.

Abstract: When following control that causes a user vehicle to follow a following target that is a first other vehicle travelling in a user path in which the user vehicle is travelling is being performed, a travel control section transitions from a state in which the first other vehicle is the following target to a state in which the first other vehicle is not the following target, and in a case where an outside recognizing section recognizes a second other vehicle, which is travelling in another path that is not the user path, the travel control section determines whether to set the second other vehicle as the following target based on a prescribed condition.

Abstract: An example method includes receiving, from one or more sensors associated with an autonomous vehicle, sensor data associated with a target object in an environment of the vehicle during a first environmental condition, where at least one sensor of the sensor(s) is configurable to be associated with one of a plurality of operating field of view volumes. The method also includes based on the sensor data, determining at least one parameter associated with the target object. The method also includes determining a degradation in the parameter(s) between the sensor data and past sensor data, where the past sensor data is associated with the target object in the environment during a second environmental condition different from the first and, based on the degradation, adjusting the operating field of view volume of the at least one sensor to a different one of the operating field of view volumes.

Abstract: An industrial truck, configured for driverless, autonomously-acting operation for a load to be transported, includes at least a control system configured to control and to steer the industrial truck, and an evaluation unit configured to generate a signal for stopping the industrial truck. A detector device configured to recognize persons and/or objects located in a route is connected to the control system. The control system is configured to check a protective field and/or a warning field of the detector device, and the protective field and/or the warning field is automatically switchable in dependence on a position of the industrial truck and/or detected obstacles in the route of the industrial truck.

Abstract: A communication module may receive communications from a vehicle. A collision detection module may determine that a collision has occurred at a vehicle based on one or more of the communications received from a vehicle. A participant identification module may identify one or more participants involved in the collision based on one or more communications received from the vehicle. A fault determination module may identify one of the participants as the at-fault participant based on a comparison of a fault determination ruleset to vehicle telematics data included in one or more of the communications received from the vehicle. A claims processing module may determine whether to file an insurance claim associated with one of the participants based on the estimated repair cost.

Abstract: Techniques for parking space light are provided. A parking space light can identify, via one or more instruments of the parking space light, a set of parking spaces in a defined region of a parking structure in which the parking space light is installed, monitor, via the one or more instruments, the set of parking spaces, and determine respective occupied statuses of parking spaces of the set of parking spaces, wherein the respective occupied statuses indicate whether the parking spaces are occupied or unoccupied.

Abstract: Methods for performing maintenance operations using unmanned aerial vehicles (UAVs). The methods are enabled by equipping a UAV with a maintenance tool capable of performing a desired maintenance operation (e.g., nondestructive inspection) on a limited-access surface of a large structure or object (e.g., a wind turbine blade). The UAV uses re-orientation of lifting means (e.g., vertical rotors) to move the maintenance tool continuously or intermittently across the surface of the structure while maintaining contact with the surface of the structure undergoing maintenance.

Abstract: The apparatus for automated driving includes a processor configured to: determine whether a change of a travel condition or a controller of a vehicle that is being automatically driven is necessary; when the change is necessary, detect a predetermined feature that is visible to a driver, predetermined notification that is recognizable to the driver, or a predetermined situation around the vehicle; and when the feature, the notification or the situation is detected, control the vehicle so as to make the change, or notify the driver of the change with a notifying device.

Abstract: A vehicular control system includes a plurality of sensors disposed at a vehicle, and a control having a data processor. Data captured by the sensors is processed at the control to determine presence of other vehicles and to determine respective speeds and directions of travel of the determined vehicles. The system determines a respective influence value for each of the determined vehicles based on a respective determined potential hazard. The system determines a plurality of potential paths of travel for the equipped vehicle to follow based on the determined respective influence values for the determined vehicles. The system selects, from the determined plurality of potential paths of travel, a path of travel for the equipped vehicle to follow that limits conflict with the determined vehicles. The system at least in part controls steering of the equipped vehicle to guide the equipped vehicle along the selected path of travel.

Abstract: The disclosure relates to training models for identification of events likely to cause discomfort to passengers of autonomous vehicles and for assessment of overall ride quality of autonomous vehicle rides. For instance, ride data may be associated with a ride quality value indicative of a level of discomfort and/or a first overall ride quality value indicating an overall ride quality provided by the passenger for the first ride. This ride data may be used to train a model such that the model is configured to, in response to receiving ride data for a second ride as input, output a list of events likely to cause discomfort to a passenger during the second ride and/or such that the model is configured to, in response to receiving second ride data for a second ride as input, output a second overall ride quality value for the second ride.

Abstract: Example systems and methods enable an autonomous vehicle to request assistance from a remote operator in certain predetermined situations. One example method includes determining a representation of an environment of an autonomous vehicle based on sensor data of the environment. Based on the representation, the method may also include identifying a situation from a predetermined set of situations for which the autonomous vehicle will request remote assistance. The method may further include sending a request for assistance to a remote assistor, the request including the representation of the environment and the identified situation. The method may additionally include receiving a response from the remote assistor indicating an autonomous operation. The method may also include causing the autonomous vehicle to perform the autonomous operation.

Abstract: Augmented reality systems provide graphics over views from a mobile device for both in-venue and remote viewing of a sporting or other event. A server system can provide a transformation between the coordinate system of a mobile device (smart phone, tablet computer, head mounted display) and a real world coordinate system. Requested graphics for the event are displayed over a view of an event.

Abstract: The described techniques relate to modifying a trajectory of a vehicle, such as an autonomous vehicle, based on an overlap area associated with an object in the environment. In examples, map data may be used, in part, to generate an initial trajectory for an autonomous vehicle to follow through an environment. In some cases, a yield trajectory may be generated based on detection of the object, and the autonomous vehicle may evaluate a cost function to determine whether to execute the yield or follow the initial trajectory. In a similar manner, the autonomous vehicle may determine a merge location of two lanes of a junction, and use the merge location to update extents of an overlap area to prevent the autonomous vehicle from blocking the junction and/or provide sufficient space to yield to the oncoming vehicle while merging.

Abstract: A control apparatus plans a movement route of a moving body based on a recognition result of an exterior environment of the moving body; corrects the planned movement route, based on a recognition result of an obstacle in the exterior environment of the moving body; and controls the movement of the moving body based on the corrected movement route. The recognition result of the obstacle includes a recognition result of a side portion of the obstacle with respect to the movement route of the moving body, and in the correction, the planned movement route is corrected based on a correction amount continuously obtained based on the recognition result of the obstacle associated with advancement of the moving body.

Abstract: The disclosure provides an environment perception device and method of a mobile vehicle. The environment perception device includes a camera module, a LiDAR module, a database and a processing circuit. The camera module photographs a field near the mobile vehicle to generate a three-dimensional (3D) image frame. The LiDAR module scans the field to generate a 3D scanned frame. The processing circuit fuses the 3D image frame and the 3D scanned frame to generate 3D object information. The processing circuit compares the 3D object information with a 3D map in the database to determine whether an object is a static object. The processing circuit performs an analysis and calculation on the 3D object information to obtain movement characteristics of the object when the object is not the static object, and skips the analysis and calculation on the 3D object information when the object is the static object.

Abstract: Candidate routes, from an origination to a destination, can be produced. Information can be obtained. The information can be of likelihoods of encounters, along the candidate routes, with types of driving situations demonstrated to cause changes in a degree of confidence, of an occupant of an autonomous vehicle, that a controller of the autonomous vehicle will be able to control the autonomous vehicle so that a result of the encounters is not a collision. Take-over probabilities can be obtained. The take-over probabilities can be of likelihoods that the occupant, in response to the encounters, will cause control of the autonomous vehicle to be transferred to the occupant. Based on the information and take-over probabilities, a route from the origination to the destination can be selected from the candidate routes. The autonomous vehicle can be caused to be configured to commence to move in a direction in accordance with the route.

Abstract: Camera adjustment apparatuses are arranged in an area to be recognized by a camera that captures an image of an object to be recognized, and include: an adjustment mark position detection unit to detect adjustment marks for extracting subject information including a size, a direction, and luminance from an image captured by the camera and detect positions of the detected adjustment marks in the captured image; a subject information extraction unit to extract the subject information from the adjustment marks detected by the adjustment mark position detection unit; and a recognition feasibility determination unit to determine whether each of the adjustment marks detected by the adjustment mark position detection unit can be recognized by comparing the corresponding subject information with a predetermined determination criterion, and generate adjustment information for adjusting the camera based on subject information that corresponds to one of the adjustment marks.

Abstract: A vehicle sensor training system includes a first computing device configured to receive dynamics data from a host vehicle. A receiving device is configured to receive real time object identification data from a reference target. A second computing device is configured to compile the dynamics data from the first computing device and the real-time object identification data from the receiving device. The second computing device is configured to train a vehicle sensor with the real-time object identification data.

Abstract: Various technologies described herein pertain to causing presentation on a user interface of an immediate portion of a navigation route of an autonomous vehicle. A computing system of the autonomous vehicle determines whether an object detected by sensor(s) of the autonomous vehicle proximate to the immediate portion of the navigation route are of a type and relative position defined as one of consequential and inconsequential for a human passenger. In response to determining that an object has both a type and relative position defined as consequential, the computing system causes presentation on the user interface a representation of the object relative to the immediate portion of the navigation route to provide a confidence engendering indication that the autonomous vehicle has detected the object. Otherwise if inconsequential, presentation on the user interface of any representation of the object is not caused by the computing system to avoid creating a confusing presentation.

Abstract: This document describes Kurtosis based pruning for sensor-fusion systems. Kurtosis based pruning minimizes a total quantity of comparisons performed when fusing together large sets of data. Multiple candidate radar tracks may possibly align with one of multiple candidate visual tracks. For each candidate vision track, a weight or other evidence of matching is assigned to each candidate radar track. An inverse of matching errors between each candidate vision and each candidate radar track contributes to this evidence, which may be normalized to produce, for each candidate vision track, a distribution associated with all candidate radar tracks. A Kurtosis or shape of this distribution is calculated. Based on the Kurtosis values, some candidate radar tracks are selected for matching and other remaining candidate radar tracks are pruned. The Kurtosis aids in determining how many candidates to retain and how many to prune.

Abstract: Pixel image data of a scene is received in which the pixel image data includes a two-dimensional representation of an object in the scene. Point cloud data including three-dimensional point coordinates of a physical object within the scene corresponding to the two-dimensional representation of the object is received. The three-dimensional point coordinates include depth information of the physical object. The point cloud data is mapped to an image plane of the pixel image data to form integrated pixel image data wherein one or more pixels of the pixel image data have depth information integrated therewith. A three-dimensional bounding box is predicted for the object using a convolutional neural network based upon the integrated pixel image data.

Abstract: A condition of an unmanned aerial vehicle (UAV) is detected using one or more sensors of the UAV and signaled according to an alert definition associated with the condition. For example, an alert definition can indicate to signal the condition by using a motor of the UAV to produce an audible tone. A tonal signal having a frequency within an audible spectrum can be generated according to the alert definition. The tonal signal and a drive signal used for supplying current to the motor can be combined to produce a combined signal. The combined signal can then be transmitted to the motor to cause the motor to produce the audible tone. In some cases, an amplitude of the tonal signal can be modulated, such as where the amplitude of the combined signal exceeds a threshold associated with an operating margin of the UAV.

Abstract: The present disclosure provides a method, an apparatus and a system for processing unmanned vehicle data, and a storage medium, where the method includes: receiving data acquisition indication information sent by a cloud server; obtaining, according to the data acquisition indication information, target data from a data set; and storing the target data, and/or sending the target data to the cloud server, which can thereby achieve acquisition and storage of data meets a preset condition, reduce amount of data storage of the unmanned vehicle and amount of data sent to the cloud server, save network resources, and improve data transmission efficiency.

Abstract: An apparatus and method for providing a top view image of a parking space are provided. The apparatus includes a steering angle sensor that measures a steering angle of a vehicle, a top view image generator that generates a top view image of a parking space depending on travel of the vehicle, a display that displays the top view image generated by the top view image generator, and a controller that captures the top view image displayed by the display and generates a panorama top view image by connecting the current top view image generated by the top view image generator and the captured previous top view image, based on the steering angle measured by the steering angle sensor.

Abstract: Aspects of the disclosure relate to identifying and adjusting speed plans for controlling a vehicle in an autonomous driving mode. In one example, an initial speed plan for controlling speed of the vehicle for a first predetermined period of time corresponding to an amount of time along a route of the vehicle is identified. Data identifying an object and characteristics of that object is received from a perception system of the vehicle. A trajectory for the object that will intersect with the route at an intersection point at particular point in time is predicted using the data. A set of constraints is generated based on at least the trajectory. The speed plan is adjusted in order to satisfy the set of constraints for a second predetermined period of time corresponding to the amount of time. The vehicle is maneuvered in the autonomous driving mode according to the adjusted speed plan.

Abstract: An automated system is provided that receives and utilizes travel related data from unmanned aerial vehicles (“UAVs”) for optimizing the scheduling and routing of deliveries by UAVs. Travel routes through delivery areas are planned and when it is determined that a first UAV has deviated from a planned travel route to avoid a location in an area, a second UAV (e.g., which may have additional sensors and/or recording capabilities) may be sent to collect updated travel related data regarding the location. The updated travel related data (e.g., which may indicate that there is a new obstacle, a source of magnetic interference, a wind, etc. at the location) may be utilized for planning future travel routes for deliveries.

Abstract: A system and method for identifying a safe path in a partially unknown environment in a time critical fashion includes identifying long range paths that avoid known obstacles. Short range paths within a receding horizon are identified corresponding to the long range paths, the short range paths avoiding known obstacles and unknown regions. Each short range path is broken into segments based on subsequent control operations or timing, and abort procedures are identified corresponding to each segment to enforce time critical availability of a safe action. Short range paths are excluded unless abort procedures can be identified for subsequent segments.

Abstract: An industrial truck (2) and a method for operating the same. The industrial truck includes a load fork (4), a fork back (6) and a plurality of fork arms (8a, 8b), each of which include an arm tip at a free end and an arm root arranged on the fork back. The industrial truck includes a load carrier detection system for a load carrier (20, 30, 40) to be transported, which includes at least one spacing distance measurement sensor (14) provided on the load fork that is configured to detect a spacing distance between the load carrier and the fork back, and one or more monitoring sensors (10, 12) provided on the load fork configured to monitor a predetermined measurement region on the load fork. A processing unit for the sensors is configured to determine a reception of the load carrier picked up by the load fork.

Abstract: The inventive subject matter provides devices and methods for improving driving safety using information obtained from images taken by a camera in a device. Among other things, contemplated devices and methods can produce alarms when it appear from rates of speed and acceleration/deceleration, that a vehicle will likely go through a red light, or fail to stop or sufficiently slow down at a stop sign. A significant feature of preferred devices and methods is that they are not dependent on WI-FI, cellular, satellite and radio signals, or any other external data transmission, and are not even dependent on speed, acceleration, or other information native to the vehicle.

Abstract: A fruit and vegetable picking method and device based on machine vision and storage medium that includes: acquiring fruit image of fruit or vegetable to be picked currently, calling pre-trained neural network model to identify fruit image, and determining type of fruit or vegetable; acquiring type of fruit or vegetable, and determining cuttable area on stalk of fruit or vegetable according to type of fruit or vegetable, locating cutting point; controlling end picking apparatus to cut off stalk of fruit or vegetable, according to cutting point being determined. By using pre-trained neural network model to detect fruit and cut stalk for picking, one device may be able to pick multiple fruits and vegetables, have high versatility and picking accuracy, avoid hurting pulp, and have improved harvest efficiency and quality of fruits and vegetables picked.

Abstract: A map generator generates a replanting map designating a particular area in a field in which it is recommended to add additional seeds. A function of the agricultural machine is then controlled based at least in part on the replanting map so as to facilitate planting additional seeds in the designated particular area.

Abstract: A bale monitoring system includes an imaging device that is operable to capture a stereoscopic image of a bale. A computing compares the stereoscopic image of the bale to a three-dimensional standard to identify a deviation of the bale from the three-dimensional standard. The computing device may then assign the bale a shape quality score based on the deviation of the bale from the three-dimensional standard. The shape quality score may indicate a magnitude of the deviation of the bale from the three-dimensional standard. Additionally, the stereoscopic image may be analyzed to identify characteristics of the bale, such as a broken wrap material or an improperly formed bale.

Abstract: A system for assisting in aligning a vehicle for hitching with a trailer includes a steering system that adjusts a vehicle steering angle, a braking system that adjusts a vehicle speed, an imaging system that receives image data of a drawbar assembly being receivable in a hitch receiver, and a controller. The controller is configured to detect an edge of the drawbar assembly from the image data, target an endpoint at a fixed offset from the edge and a stationary point on the vehicle, and maneuver, via the steering and braking systems, the vehicle along a path to align the endpoint with the trailer.

Abstract: In some examples, a system may determine a plurality of routes between a source location and a destination location. Further, the system may segment each route of the plurality of routes into multiple road segments. The system may determine a first field of view (FOV) for each road segment. In addition, the system may receive vehicle sensor configuration information for vehicle sensors on board a vehicle. The system may determine a second FOV for the vehicle sensors. Additionally, the system may select a route for the vehicle based at least on comparing the second FOV with the first FOV for a plurality of the road segments.

Abstract: Vision based guidance system and method for lawn mowing devices are disclosed. An exemplary method for operating an autonomous lawn mower includes receiving, via a receiver, a perimeter data set from a handheld computer. The perimeter data set includes a perimeter outline of at least one perimeter that is determined utilizing a GPS unit of the handheld computer. The exemplary method also includes collecting, via at least one camera, images of a set area within the perimeter outline and mowing, via a mowing blade, grass within the set area. The exemplary method also includes autonomously steering, via a controller, the autonomous lawn mower based on the perimeter outline of the at least one perimeter and the images captured by the at least one camera.

Abstract: The present disclosure provides an autonomous mobile apparatus and a control method thereof. The method includes: starting a SLAM mode; obtaining first image data captured by a first camera; extracting a first tag image of positioning tag(s) from the first image data; calculating a three-dimensional camera coordinate of feature points of the positioning tag(s) in a first camera coordinate system of the first camera based on the first tag image; calculating a three-dimensional world coordinate of the feature points of the positioning tag(s) in a world coordinate system based on a first camera pose of the first camera when obtaining the first image data in the world coordinate system and the three-dimensional camera coordinate; and generating a map file based on the three-dimensional world coordinate of the feature points of the positioning tag(s).

Abstract: Disclosed is an unmanned aerial vehicle adapted to be positioned against a substantially vertical wall while hovering in the air, including a body and rotors, an arm end, a first leg end and a second leg end intersected by a front plane and adapted for together contacting the wall at three spaced apart positions, the front plane intersecting a vertical axis of the UAV at an upper side of a first plane spanned by a lateral and longitudinal axis of the UAV, the front plane extending at a first angle of between 45 to 85 degrees to the first plane; wherein the UAV is adapted for tilting upon contact of the first and second leg ends with the wall while the arm end approaches the wall, about the first and second leg ends and towards the wall, until the arm end contacts the wall.

Abstract: Deep learning to improve or gauge the performance of a surface-penetrating radar (SPR) system for localization or navigation. A vehicle may employ a terrain monitoring system including SPR for obtaining SPR signals as the vehicle travels along a route. An on-board computer including a processor and electronically stored instructions, executable by the processor, may analyze the acquired SPR images and computationally identify subsurface structures therein by using the acquired image as input to a predictor that has been computationally trained to identify subsurface structures in SPR images.

Abstract: A support device includes a wheel, a base member, a leg coupled to the wheel and the base member, the leg including an upper leg segment, a lower leg segment positioned below the upper leg segment, a joint positioned between the upper leg segment and the lower leg segment, the joint including a cam defining a non-circular perimeter, and an actuator coupled to one of the upper leg segment and the lower leg segment, the actuator including an engagement member that is engaged with the non-circular perimeter of the of the cam of the joint, where the actuator selectively moves the engagement member to move the cam and the upper leg segment and the lower leg segment about the joint.

Abstract: Disclosed herein are a robot navigating based on obstacle avoidance and a navigation method. In the robot or the navigation method of the robot according to an embodiment, a navigation route may be generated on the basis of position information on a waypoint and on objects sensed by a sensor, such that the robot may move via one or more waypoints.

Abstract: Implementations are described herein for analyzing vision data depicting undesirable plants such as weeds to detect various attribute(s). The detected attribute(s) of a particular undesirable plant may then be used to select, from a plurality of available candidate remediation techniques, the most suitable remediation technique to eradicate or otherwise eliminate the undesirable plants.

Abstract: A vehicle passenger detection device, a system including the same, and a method thereof are provided. The vehicle passenger detection device includes a processor configured to determine a location of a passenger per at least one or more seats based on strength of radar signals reflected from the at least one or more seats including medium with different reflection characteristics and a storage storing information associated with strength of a radar signal for each distance and information associated with strength of a radar signal according to the reflection characteristics of the medium.

Abstract: The present invention relates to the efficient use of both local and remote computational resources and communication bandwidth to provide distributed environment mapping using a plurality of mobile sensor-equipped devices. According to a first aspect, there is provided a method of determining a global position of one or more landmarks on a global map, the method comprising the steps of determining one or more differences between sequential sensor data captured by one or more moving devices; determining one or more relative localisation landmark positions with respect to the one or more moving devices; determining relative device poses based one or more differences between sequential sensor data relative to the one or more relative localisation landmark positions; and determining a correlation between each device pose and the one or more relative localisation landmarks positions.

Abstract: A vehicle external environment recognition apparatus to be applied to a vehicle includes a road surface determination processor and a three-dimensional object determination processor. The road surface determination processor determines a road surface region that corresponds to a road surface in an image, plots representative distances of respective horizontal lines in the road surface region at respective vertical positions of the horizontal lines, and generates first and second road surface models. The second road surface model represents a farther portion of the road surface region from the vehicle than the first road surface model and differs in a gradient from the first road surface model. On a condition that an angle formed by the first and second road surface models is greater than a predetermined angle, the three-dimensional object determination processor cancels the second road surface model and extends far the first road surface model.

Abstract: Systems, vehicles and methods for determining wrong direction driving are disclosed. In one embodiment, a system for determining a vehicle traveling in a wrong direction includes one or more sensors that produce sensor data, one or more processors, and one or more non-transitory computer-readable medium storing computer readable-instructions. When the computer-readable instructions are executed by the one or more processors, the computer-readable instructions cause the one or more processors to determine one or more lanes within a roadway using the sensor data, determine a direction of travel of the one or more lanes using the sensor data, and identify a non-compliant vehicle traveling in a direction in the one or more lanes that is different from the determined direction of travel in the one or more lanes.

Abstract: A vehicle control method executed by a processor capable of making a subject vehicle change a lane includes: acquiring surrounding information of the subject vehicle by a sensor provided in the subject vehicle; determining whether a distractive factor for a driver of another vehicle is present when the subject vehicle enters the front of the other vehicle traveling on the second lane for changing lanes from a first lane to a second lane adjacent to the first lane; setting a lane change time required for the subject vehicle to change lanes longer than when determining none of the distractive factor to be present when determining distractive the factor to be present; and controlling a traveling position of the subject vehicle on the first lane within the lane change time.

Abstract: A method and system for inspecting and monitoring an elevator installation includes sending an autonomous flying object having at least one sensor to the elevator installation, and granting access to a hoistway of the elevator installation to the autonomous flying object. The autonomous flying object is positioned within the hoistway, and data collected by the associated sensor is sent to a remote elevator service center. The autonomous flying object and the associated sensor can be used to monitor and inspect the elevator installation on a temporary basis, for example for a specific number of hours, days or weeks. Once the autonomous flying object has gained access to the hoistway, the elevator installation can resume normal operation thereby keeping downtime to a minimum. After completing its tasks at one elevator installation, the autonomous flying object can be directed by the remote elevator service center to monitor and inspect another elevator installation.

Abstract: A method for adjusting a safety distance between a first vehicle and a second vehicle preceding the first vehicle at a bunched traffic site by at least one control device is disclosed which includes receiving measurement data of at least one sensor unit with the at least one control device. The method includes evaluating the measurement data of the at least one sensor unit with the at least one control device to identify a bunched traffic site in front of the second vehicle and identifying a safety distance of the first vehicle from the second vehicle, wherein the identified safety distance accounts for a possible reverse motion of the second vehicle. The method further includes establishing the identified safety distance with the at least one control device based upon the identified bunched traffic site. A control device, a computer program and a machine-readable storage medium are further disclosed.