Abstract: A surrounding environment of an autonomous vehicle is perceived to identify one or more vehicles nearby. For each of the identified vehicles, based on a current location of the identified vehicle, vehicle-independent information is obtained to determine context surrounding the identified vehicle, where the vehicle-independent information includes vehicle surrounding information that defines physical constraints imposed on the identified vehicle. For each of the identified vehicles, one or more trajectories for the identified vehicle are predicted based at least in part on the vehicle-independent information associated with the identified vehicle. The autonomous vehicle is controlled based on the one or more predicted trajectories of the one or more identified vehicles.

Abstract: A method includes receiving, by a computing system of a vehicle, a planned trajectory for the vehicle based on first sensor data associated with an external environment. The planned trajectory is generated by a primary computing system associated with a first sensor. The method further includes determining an environmental condition associated with the external environment. The environmental condition is included in second sensor data generated by a second sensor. The method further includes analyzing one or more parameters associated with the planned trajectory to determine whether the planned trajectory is based on the environmental condition, and, in response to determining that the primary computing system fails to base the planned trajectory upon the environmental condition, altering the one or more parameters associated with the planned trajectory to generate an altered planned trajectory. The method thus includes instructing the vehicle to execute the altered planned trajectory.

Abstract: Disclosed is a vehicular advertisement providing device including a processor configured to receive data generated by at least one server, to generate augmented reality (AR) advertisement data that matches the outside of a road in which a vehicle travels based on the data, and to provide a signal for displaying a graphic object based on the advertisement data on at least one display included in the vehicle. The vehicular advertisement providing device is included in an autonomous vehicle. The autonomous vehicle is associated with a robot. The vehicular advertisement providing device is implemented using an artificial intelligence (AI) algorithm.

Abstract: An information processing apparatus manages a ride-sharing system in which a plurality of users travels together on the same moving vehicle. The apparatus includes a control unit configured to calculate a second evaluation value for a user group traveling on the same moving vehicle, based on a first evaluation value based on a user's attribute and a time during which the user group is maintained, and in a case where there is a candidate user who is a candidate of a user newly riding in a predetermined moving vehicle, calculate the second evaluation value when a predetermined user group is formed for the predetermined moving vehicle, and determine a response policy for the candidate user based on whether or not the second evaluation value satisfies a predetermined policy.

Abstract: A system with a first floor processing device and a second floor processing device that is designed to orient and localize itself within an environment based on an area map. The first floor processing device is set up to detect a movement path during a movement by the first floor processing device and transmit information about the detected movement path to the second floor processing device. The second floor processing device has a control and evaluation unit that is set up to analyze the received information and, based upon the movement path detected by the first floor processing device and/or a partial area of the environment not traversed by the movement path, enter a no-go area into the area map which the second floor processing device is not allowed to traverse.

Abstract: A vehicle control device mounted to a vehicle and configured to control a traveling state of the vehicle is provided. The vehicle control device sets control contents for functions for automated driving of the vehicle, respectively, and to control the vehicle according to the control contents. The functions are each associated with one or more items of vehicle vicinity information in advance. The vehicle control device determines, for each of the functions, whether it is possible to recognize the associated one or more items of the vehicle vicinity information. The vehicle control device maintains the automated driving that uses a function associated with one or more items of the vehicle vicinity information recognized by the recognition determination unit, and switches over, into manual driving, the automated driving that uses a function associated with one or more items of the vehicle vicinity information not recognized by the recognition determination unit.

Abstract: A vehicle control device is equipped with a detection unit configured to detect lane markings and another vehicle on the basis of peripheral information, and a control unit which, in the case that the lane marking is detected on one side of a host vehicle, but the lane marking is not detected on another side of the host vehicle, is configured to control the host vehicle on the basis of the positions of a plurality of the other vehicles that are traveling respectively in mutually different lanes.

Abstract: Systems, methods, and computer-readable media are disclosed for automated multimodal delivery. Example methods may include determining information associated with the delivery; determining, based on at least a first portion of the information, that a first confidence level indicative of a delivery capability using a first vehicle is above a first threshold; and determining, based on at least a second portion of the information, a second confidence level indicative of a delivery preference for delivery using the first vehicle relative to a second vehicle.

Abstract: A computer-implemented method and a system for training a computer-based autonomous driving model used for an autonomous driving operation by an autonomous vehicle are described. The method includes: creating time-dependent three-dimensional (3D) traffic environment data using at least one of real traffic element data and simulated traffic element data; creating simulated time-dependent 3D traffic environmental data by applying a time-dependent 3D generic adversarial network (GAN) model to the created time-dependent 3D traffic environment data; and training a computer-based autonomous driving model using the simulated time-dependent 3D traffic environmental data.

Abstract: A method and a labeling system for generating a label object for the symbolic description of an object of an environment of a mobile device, e.g., a robot or a vehicle. The label object includes at least one attribute of an object at a first point in time, from observations of this object. The method includes selecting, from the observations, a first observation recorded at a first point in time, a second observation recorded at a second point in time, the second point in time being a point in time before the first point in time, as well as a third observation recorded at a third point in time, the third point in time being a point in time after the first point in time; and ascertaining, by using the selected observations, the at least one attribute of the object.

Abstract: A position calculation system includes a managing unit managing a current position of a plurality of automated guided vehicles; and a position calculating unit calculating a position of the target automated guided vehicle based on a detection result, detected by the laser measuring device mounted on the target automated guided vehicle, of detecting each reflection light reflected from a specific number being two or more of reflection sources, position information of which is obtainable, existing at positions on mutually different directions viewing from the target automated guided vehicle.

Abstract: A method, an apparatus and a control system for controlling a mobile robot are provided. The method includes: receiving a motion mode change request sent by a target mobile robot, the motion mode change request including motion mode information, and the motion mode information being information of a motion mode to be obtained by change requested by the target mobile robot; determining whether the target mobile robot has a permission to move in the motion mode; and sending motion confirmation information for the motion mode change request to the target mobile robot to control the target mobile robot to move in the motion mode, in response to determining that the target mobile robot has the permission.

Abstract: Autonomous ground vehicles equipped with one or more sensors may capture data regarding ground conditions at a location. The data may refer to or describe slopes, surface textures, terrain features, weather conditions, moisture contents or the like at the location, and may be used to select one or more areas for receiving a delivery of an item. The sensors may include one or more inclinometers, imaging devices or other systems. The autonomous ground vehicles may also engage in one or more direct interactions or communications with a delivery vehicle, and may select an appropriate area that is suitable for such interactions. The autonomous ground vehicles may also prepare the area for an arrival of a delivery vehicle, such as by making one or more visible markings in ground surfaces at the area.

Abstract: The technology relates to enhancing or extending the field of view of sensors for vehicles configured to operate in an autonomous driving mode. One or more mirrors are used to reflect or redirect beams emitted from onboard sensors that would otherwise be wasted, for instance due to obstruction by a portion of the vehicle or because they are emitted at high pitch angles to the side. The mirrors are also used to redirect incoming beams from the external environment toward one or more of the onboard sensors. Using mirrors for such redirection can reduce or eliminate blind spots around the vehicle. A calibration system may be employed to account for mirror movement due to vibration or wind drag. Each mirror may be a front surface mirror. The mirrors may be positioned on the vehicle body, on a faring, or extending from a sensor housing on the vehicle.

Abstract: An arrangement determination apparatus is provided comprising a target region identifying unit configured to identify a target region for providing service by a plurality of flying objects, the plurality of flying objects forming a wireless communication area on a ground by emitting a beam toward the ground, a flying object number retrieving unit configured to retrieve a number of the plurality of flying objects, a point retrieving unit configured to retrieve a point for each of a plurality of meshes obtained by dividing the target region, and an arrangement determination unit configured to determine an arrangement of the plurality of flying objects over the target region based on the number of flying objects and the point for each of the plurality of meshes.

Abstract: A parking assistance apparatus includes at least one camera sensor installed in a vehicle, a control unit configured to analyze an image obtained through the camera sensor to recognize a space and object in a parking lot by matching a detailed parking lot map to an object, search for an available parking space by calculating a parking region on the basis of recognized space and object information, and generate a path to the available parking space searched for, or perform autonomous parking until reaching the available parking space, and a storage unit configured to store the detailed parking lot map for recognizing the space and object.

Abstract: A vehicle control device includes: a driving controller configured to perform first driving control such that one or both of an acceleration or deceleration speed and steering of a vehicle is controlled to travel the vehicle; an occupant intention detector configured to detect an intention of the occupant to switch from manual driving to a state in which the driving controller performs the first driving control; and a one-way traffic determiner configured to determine whether a road on which the vehicle is predicted to be traveling or travel in future is a one-way traffic road. The driving controller determines whether to start the first driving control based on whether the one-way traffic determiner determines the road on which the vehicle is predicted to be traveling or travel in future is the one-way traffic road.

Abstract: A mounting system of the present disclosure includes a mounting line including multiple mounting machines aligned side by side in a predetermined arrangement direction and configured to mount components on a board, a supply device configured to move in the arrangement direction to convey members for use in the mounting machines and supply the members to the mounting machines, and a display section provided on each of the mounting machines and configured to change their display modes in accordance with a movement of the supply device.

Abstract: The disclosure relates to a procedure for operating a safety system for a motor vehicle for driving beyond a system boundary. The motor vehicle moves autonomously within a predetermined area, defined by the system boundary, in an autonomous driving mode from a delivery point to a predetermined position and back to the delivery point. To drive beyond the system boundary, a mechanical blocking device of the safety system is first detected by a detection device of the motor vehicle, the mechanical blocking device forming part of the system boundary. Subsequently, a current driving mode of the motor vehicle is detected. Next, a driving mode message is output by a communication device of the motor vehicle for opening the mechanical blocking device. Finally, the mechanical blocking device is opened when the motor vehicle is in a non-autonomous driving mode according to the driving mode message.

Abstract: Provided is a vehicle operation management system having a server device and one or more vehicles. The vehicle includes equipment configured to provide a predetermined service inside the vehicle and a running control unit configured to control autonomous running of the vehicle. The server device includes a service request information acquisition unit. At least one of the server device and the vehicle includes a position information acquisition unit configured to acquire position information on the autonomous vehicle and a running route setting unit configured to set a running route of the vehicle. The running control unit controls running of the vehicle such that the vehicle runs along the running route set by the running route setting unit.

Abstract: A method for assisting a driver during the deactivation of a highly automated driving mode of a vehicle. In this context, a takeover signal, which represents a takeover of control of the vehicle by the driver, and auxiliary information are read in. The auxiliary information includes image information representing the driver and/or vehicle-control information representing a control of the vehicle by the driver. In a further step, a degree of attentiveness of the driver is determined, using the takeover signal and the auxiliary information. Finally, using the degree of attentiveness, an assistance signal is output to assist the driver during the takeover of control, by activating at least one driver-assistance function of the vehicle.

Abstract: Embodiments of the present disclosure disclose a vehicle fault processing method, a device and a medium, and relate to the field of autonomous driving technologies. The vehicle fault processing method includes: obtaining operating index data of a target vehicle and driving environment information of the target vehicle, the operating index data being configured to determine an operating condition of the target vehicle; determining whether a fault occurs in the target vehicle based on the operating index data; and when a fault occurs in the target vehicle, controlling the target vehicle to place a warning sign at a preset position based on the driving environment information.

Abstract: Methods, devices and systems enable controlling an autonomous vehicle by identifying vehicles that are within a threshold distance of the autonomous vehicle, determining an autonomous capability metric of each of the identified vehicles, and adjusting a driving parameter of the autonomous vehicle based on the determined autonomous capability metric of each of the identified vehicles. Adjusting a driving parameter may include adjusting one or more of a minimum separation distance, a minimum following distance, a speed parameter, or an acceleration rate parameter.

Abstract: An automatic driving system includes an electronic control device configured to: detect a driving operation input amount during an automatic driving control for a vehicle; determine whether the driver is able to start manual driving during the automatic driving control for the vehicle; output a signal for performing switching from automatic driving to the manual driving based on a result of a comparison between the driving operation input amount and a driving switching threshold that is a threshold for the switching from the automatic driving to the manual driving; set the driving switching threshold to a first driving switching threshold when it is determined that the driver is able to start the manual driving; and set the driving switching threshold to a second driving switching threshold exceeding the first driving switching threshold when it is determined that the driver is not able to start the manual driving.

Abstract: A method for operating a driving assistance system of a motor vehicle includes manoeuvring the motor vehicle autonomously with a driving assistance system while a user with a mobile terminal is located outside the motor vehicle. The user performs, by the driving assistance system and during the manoeuvring, longitudinal guidance and transverse guidance of the motor vehicle. The driving assistance system is operated at a first automation level when communication between the driving assistance system and the mobile terminal is ensured. While the user activates the mobile terminal, the longitudinal guidance, and the transverse guidance in a predetermined fashion, a surrounding area of the motor vehicle is sensed, at the first automation level, by the driving assistance system, and in addition to the longitudinal guidance and the transverse guidance of the motor vehicle. The motor vehicle is then autonomously manoeuvred according to the sensed surrounding area.

Abstract: Aspects of the present disclosure relate to automated vehicle condition grading. In examples, a set of images for a vehicle are processed using a machine learning engine to generate an optical vehicle condition grade for each image of the set. The resulting set of optical vehicle condition grades may be aggregated to generate an aggregate optical vehicle condition grade for the vehicle. In some examples, additional information associated with the vehicle is processed, which may be used to generate an adjustment grade. Accordingly, the adjustment grade and the aggregate optical vehicle condition grade are used to generate a final vehicle condition grade for the vehicle. The final vehicle condition grade is associated with the vehicle in a vehicle condition grade data store for subsequent use by the vehicle grading service and/or by an associated client device, among other examples.

Abstract: A robot cleaner for recognizing a stuck situation through artificial intelligence includes a driving unit to drive the robot cleaner, a sensing unit configured to acquire three-dimensional (3D) image data and a bumper event, a memory configured to store a stuck situation recognition model for inferring the stuck situation of the robot cleaner, and a processor configured to convert the 3D image data and the bumper event into surrounding map image data, infer the stuck situation of the robot cleaner from the 3D image data and the bumper event using the stuck situation recognition model, and control the driving unit according to an inference result.

Abstract: A vehicle control device includes an external sensor configured to acquire environmental information around a host vehicle, and an electronic control unit. The electronic control unit is configured to control the host vehicle so that the host vehicle travels along a target travel trajectory; detect an adjacent preceding vehicle that is traveling in a lane adjacent to a lane in which the host vehicle is traveling; acquire environmental information on a road side or a lane on an opposite side of the lane in which the adjacent traveling vehicle is traveling from the lane in which the host vehicle is traveling; and generate the target travel trajectory of the host vehicle so as to move away from the adjacent preceding vehicle in a width direction of the lane in which the host vehicle is traveling, within a lane width of the lane in which the host vehicle is traveling.

Abstract: A system and method for learning naturalistic driving behavior based on vehicle dynamic data that include receiving vehicle dynamic data and image data and analyzing the vehicle dynamic data and the image data to detect a plurality of behavioral events. The system and method also include classifying at least one behavioral event as a stimulus-driven action and predicting at least one behavioral event as a goal-oriented action based on the stimulus-driven action. The system and method additionally include building a naturalistic driving behavior data set that includes annotations that are based on the at least one behavioral event that is classified as the stimulus-driven action. The system and method further include controlling a vehicle to be autonomously driven based on the naturalistic driving behavior data set.

Abstract: A method for controlling automated driving operations of a vehicle includes determining vehicle origin and destination data, and generating a graphical representation of a road network with multiple candidate routes between the vehicle's origin and destination. Road-level data, including speed, turn angle, and/or gradient data, is received for each candidate route, and respective total energy uses are estimated for the vehicle to traverse across the candidate routes. Multiple candidate driving strategies, each having respective speed and acceleration profiles, are determined for the candidate route with the lowest estimated total energy use. An optimal candidate driving strategy is selected through a cost evaluation of the associated speed and acceleration profiles and forward movement simulations of the vehicle over a prediction horizon.

Abstract: A controller performs: trajectory generation processing of generating a target travel trajectory in such a way that, when a distance between a turning position of an own vehicle and a parked vehicle satisfies a predetermined condition, the own vehicle passes beside the parked vehicle at a predetermined side position with a predetermined interval interposed between the parked vehicle and the own vehicle on one side of the parked vehicle and a turning end position in a case of turning at a position before a position of the parked vehicle or a turning start position in a case of turning after having passed beside the parked vehicle on the route coincides with the predetermined side position in a width direction of a road on which the parked vehicle is parked; and processing of performing travel control, based on the target travel trajectory.

Abstract: A navigation system for an automated guided vehicle comprises a set of marking elements which are to be arranged in grid form on the floor and in which navigation information is encoded; a sensor device to be arranged at the automated guided vehicle for reading navigation data from the marking elements; and an evaluation device connected to the sensor device for generating control signals for the automated guided vehicle with reference to read navigation data. Each of the marking elements has at least two graphical code patterns that are each designed as one-dimensional code patterns and comprise a code applied along a scanning direction, with the scanning directions of the at least two graphical code patterns being aligned offset from one another by an angular offset.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining data specifying a plurality of alternative candidate routes for travel by an unmanned aerial vehicle (UAV) from a current location of the UAV to a destination location; selecting one of the alternative candidate routes as a selected route for travel by the UAV; and controlling the UAV so that while the UAV travels along the selected route the UAV emulates a ground based vehicle (GBV).

Abstract: Aspects of the disclosure relate to controlling a transition between a manual driving mode and an autonomous driving mode of a vehicle. For instance, one or more processors of one or more control computing devices may control the vehicle in the autonomous driving mode. While controlling the vehicle in the autonomous driving mode and decelerating at a given rate, the processors may receive at a user input of the vehicle input requesting a transition from the autonomous driving mode to the manual driving mode. In response to the input, the processors may transition the vehicle to the manual driving mode. After transitioning the vehicle to the manual driving mode, the processors may send deceleration signals to a deceleration actuator thereby causing the vehicle to continue to decelerate at the given rate.

Abstract: Provided are a map building method, a navigation method, a device and a system. A detected obstacle is identified, and a type of the obstacle is determined according to an identification result from multiple obstacle types obtained through classification according to an obstacle characteristic; a map is built and the obstacle is marked, and the type of the obstacle is recorded. A newly added obstacle detected on a path is identified during navigation, and obstacle avoidance process is performed according to the type of the newly added obstacle.

Abstract: An autonomous vehicle system includes an autonomous vehicle in signal communication with a data server via a communication network. The autonomous vehicle is configured to travel autonomously according to a traveling route. The data server outputs at least one driving command to control the autonomous vehicle based, at least on in part, on a point of interest (POI) included in the traveling route and at least one surrounding vehicle located in a vicinity of the autonomous vehicle.

Abstract: Disclosed herein are an autonomous vehicle and a service providing system and method using the same. The autonomous vehicle includes a navigation system setting, as a destination, a service zone adjacent to a parking lot when there is a previously registered vehicle service input through a user terminal, and setting, as a destination, the parking lot adjacent to the service zone after completion of the previously registered vehicle service, and an operation system moving the vehicle to the destination through autonomous driving. One or more of the autonomous vehicle, the user terminal, and the server may be associated with artificial intelligence, a robot, augmented reality (AR), virtual reality (VR), or the like.

Abstract: A parking assist apparatus according to an embodiment includes a memory and a hardware processor coupled to the memory. The hardware processor: sets a first circumference being in contact with a first straight line extending in a traveling direction of a vehicle and passing through a position of the vehicle; sets a second circumference being in contact with a second straight line extending in an exit direction from a parking target area of the vehicle and passing through the parking target area; sets a third circumference obtained by shifting the second circumference along the second straight line until the second circumference comes in contact with the first circumference; acquires a guidance route including part of the first circumference as a route for moving the vehicle forward and part of the third circumference as a route for moving the vehicle backward; and guides the vehicle along the acquired guidance route.

Abstract: A vehicle includes a set of sound sensors coupled to one or more processing systems that process sound data from the set of sound sensors in order to provide assisted driving features or functionality such as an emergency vehicle avoidance.

Abstract: An automated driving device includes: a navigation unit configured to retrieve one or more partial routes with a predetermined length other than a guide route which branch from the guide route at a branch point through which a vehicle is expected to pass before the vehicle passes through the branch point; and an electronic control unit configured to control automated driving of the vehicle based on information of a specific partial route out of the one or more partial routes in a period until the navigation unit completes retrieval of a redundant route for guiding the vehicle to a destination point when the vehicle departs from the guide route at the branch point and travels on the specific partial route.

Abstract: Systems and methods are provided for generating a map for use in controlling a vehicle. In one embodiment, a method includes: receiving, by a processor, aerial image data depicting an environment; processing, by the processor, the aerial image data with a plurality of trained deep learning models to produce a predicted radar map; and controlling the vehicle based on the predicted radar map.

Abstract: Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, a virtual log of data regarding performance of the features in a virtual test environment may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include evasive maneuvers performed by the vehicle under the control of the features. The performance data in the virtual log may be used to determine risk levels associated with vehicle operation by the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Abstract: An autonomous moving body capable of appropriately avoiding an approaching autonomous moving body and efficiently executing a given task even when the autonomous moving bodies are not controlled by a single system or without intercommunication between them and a control program for the autonomous moving body are provided. An autonomous moving body moves along a planned moving path in order to execute a given task, and includes an external sensor that recognizes another autonomous moving body given another task and an operation state thereof, an avoidance determination unit that determines, when it predicts that the autonomous moving body and the another autonomous moving body recognized by the external sensor may come into contact with each other as they approach each other, whether to avoid the another autonomous moving body, and a movement control unit that controls a movement unit based on the determination of the avoidance determination unit.

Abstract: Disclosed is a method and apparatus for detecting a state of a vehicle occupant, wherein a bio-signal of an occupant riding in a vehicle may be acquired by executing an artificial intelligence (AI) algorithm or a machine learning algorithm, and a physical change of the occupant may be measured by a movement signal, a respiratory signal, and a heart rate signal from the acquired bio-signal of the vehicle occupant, such that it is possible to control an operation of an internal vehicle device or to control operation of the vehicle so as to correspond to the physical change of the occupant estimated by communicating with the internal vehicle device in a 5G communication environment.

Abstract: A mobile robot, including: a body, a drive system for driving the movement of the mobile robot, a light emitter for emitting light towards a detection face, a photoelectric sensor for responding to light coming from an environment and/or light emitted by the light emitter, an adjustable impedance unit connected to the photoelectric sensor, and a controller. The controller adjusts the adjustable impedance unit to form at least two types of gear values with different impedances and responds to, under the condition of each type of gear values, a sampling difference value determined when the light emitter is in a turn-on and a turn-OFF state, so as to prevent the generation of a misjudgment from causing the mobile robot to carry out an accidental action, such that the mobile robot can work in a special working environment with strong light exposure and a black light-absorption detection face.

Abstract: Methods and apparatus related to training and/or utilizing a convolutional neural network to generate grasping parameters for an object. The grasping parameters can be used by a robot control system to enable the robot control system to position a robot grasping end effector to grasp the object. The trained convolutional neural network provides a direct regression from image data to grasping parameters. For example, the convolutional neural network may be trained to enable generation of grasping parameters in a single regression through the convolutional neural network. In some implementations, the grasping parameters may define at least: a “reference point” for positioning the grasping end effector for the grasp; and an orientation of the grasping end effector for the grasp.

Abstract: A method of controlling a cleaning robot includes: acquiring a marked position of a charging station in a map; controlling the cleaning robot to travel to a front position of the marked position and identifying the charging station; when the charging station is not identified, generating a finding path based on the marked position; and controlling the cleaning robot to travel in accordance with the finding path and identifying the charging station in a traveling process.

Abstract: A method for predicting whether another vehicle in the driving-environment of an ego-vehicle will execute a lane-change, based on observations of the driving-environment of the ego-vehicle, including: the observations are supplied to individual classificators; based on at least a portion of the observations, each individual classificator, in accordance with an individual instruction, ascertains an individual probability that the other vehicle will change lanes; the driving situation in which the ego-vehicle finds itself is classified as a whole by a situation classificator into one of several discrete classes; a record of weighting factors, assigned to the class into which the situation-classificator has classified the driving-situation, is ascertained, that indicates the relative weighting of the individual classificators for this driving situation; the individual probabilities are set off against the weighting-factors to form an overall probability that the other vehicle will change lanes.

Abstract: A vehicle control system includes a direction detector configured to detect a direction of a face or line of sight of an occupant of a host vehicle; an automated driving controller configured to execute automated driving; and a switching controller configured to switch an automated driving mode executed by the automated driving controller to any one of a plurality of automated driving modes including a first automated driving mode in which a predetermined task is required of the occupant or a predetermined automation rate is set and a second automated driving mode in which a level of the task required of the occupant is lower than in the first automated driving mode or an automation rate is lower than in the first automated driving mode, wherein the switching controller includes the direction detected by the direction detector being a predetermined direction in switching conditions for switching from the second automated driving mode to the first automated driving mode.

Abstract: A floor maintenance system can employ one or more autonomous assemblies that evaluate, characterize, and optimize a floor. A floor maintenance device can have one or more sensors connected to a local controller and a mapping circuit. The mapping circuit may be configured to change from a first floor detection resolution to a different second floor detection resolution in response to a detected floor condition.