Abstract: Embodiments include methods, systems and computer program products method for transferring one or more packages between delivery vehicles. The computer-implemented method includes monitoring, using a processor, a plurality of delivery vehicles. The processor determines that one or more packages should be transferred between a first delivery vehicle and a second delivery vehicle of the plurality of delivery vehicles. The processor further instructs the first delivery vehicle and the second delivery vehicle to meet at a rendezvous location. The processor identifies one or more packages to transfer from the first delivery vehicle to the second delivery vehicle. The processor further transfers the identified one or more packages from the first delivery vehicle to the second delivery vehicle. The processor further stores the identified one or more packages in the second delivery vehicle.

Abstract: A system for automatic unloading of articles from a container or trailer comprising a control system comprising at least one processor configured via computer executable instructions to perform automated unloading operations utilizing a plurality of unloading apparatuses, generate, on a display, an identification for each of the plurality of unloading apparatuses, generate, on the display, an identification of an operating status for each of the plurality of unloading apparatuses, monitor the automated unloading operations, automatically detect an exception of an automated unloading operation performed by an unloading apparatus, halt the automated unloading operation based on a detected exception, and modify, on the display, the identification of the operation status of the unloading apparatus indicating that the automated unloading operation has halted.

Abstract: Systems and methods for a feeder system for fulfilling lockbox pick-up requests are provided. A feeder system includes a network interface configured to communicate with a computing system associated with a provider of lockbox services and at least one robotic device. Each robotic device includes at least one secure compartment configured to hold one or more items associated with a lockbox pick-up request. The feeder system further includes a processing circuit including a processor and a memory. The memory is structured to store instructions that are executable by the processor and cause the processing circuit to receive, by the network interface, instructions for fulfilling the lockbox pick-up request and control the at least one robotic device to fulfill the lockbox pick-up request based on the instructions.

Abstract: An autonomous control system combines sensor data from multiple sensors to simulate sensor data from high-capacity sensors. The sensor data contains information related to physical environments surrounding vehicles for autonomous guidance. For example, the sensor data may be in the form of images that visually capture scenes of the surrounding environment, geo-location of the vehicles, and the like. The autonomous control system simulates high-capacity sensor data of the physical environment from replacement sensors that may each have lower capacity than high-capacity sensors. The high-capacity sensor data may be simulated via one or more neural network models. The autonomous control system performs various detection and control algorithms on the simulated sensor data to guide the vehicle autonomously.

Abstract: A system and method for egocentric-vision based future vehicle localization that include receiving at least one egocentric first person view image of a surrounding environment of a vehicle. The system and method also include encoding at least one past bounding box trajectory associated with at least one traffic participant that is captured within the at least one egocentric first person view image and encoding a dense optical flow of the egocentric first person view image associated with the at least one traffic participant. The system and method further include decoding at least one future bounding box associated with the at least one traffic participant based on a final hidden state of the at least one past bounding box trajectory encoding and the final hidden state of the dense optical flow encoding.

Abstract: A processor coupled to memory is configured to receive image data based on an image captured by a camera of a vehicle. The image data is used as a basis of an input to a trained machine learning model trained to predict a three-dimensional trajectory of a machine learning feature. The three-dimensional trajectory of the machine learning feature is provided for automatically controlling the vehicle.

Abstract: A vehicle control system includes an operation detector configured to detect that an operation element has been operated by an occupant, an automated driving controller configured to execute automated driving control, a switching controller configured to switch a driving mode to one of a plurality of driving modes including a first driving assistance mode and a second driving assistance mode, and an output controller configured to cause an information outputter to output prescribed information when the driving mode is switched from the second driving assistance mode to the first driving assistance mode. The switching controller continues the second driving assistance mode until it is detected that the operation element has been operated after the prescribed information is output and switches the driving mode to the first driving assistance mode by cancelling the second driving assistance mode when it is detected that the operation element has been operated.

Abstract: The present disclosure relates to improvements in the stability of work machines. A method for predicting a risk of instability for one or more work machine(s) moving along a route along terrain of a worksite is provided. Ground condition data indicative of the ground condition of the terrain along the route is obtained. Surface topography data indicative of the surface topography of the terrain along the route is obtained. Route data indicative of the route along the terrain is generated. The ground condition data, the surface topography data and the route data are processed to generate risk data indicative of a risk of instability along the route.

Abstract: An information processing apparatus installed in a vehicle includes a driving control section and a preparation control section. The driving control section executes automated driving of the vehicle. The preparation control section executes, when the automated driving is being executed by the driving control section, preparation control which is control that stops at least a part of the automated driving and makes the driver perform a preparation switching to driving by the driver of the vehicle.

Abstract: A method for controlling a driving condition component of an autonomous vehicle is presented. The method includes determining whether current conditions would limit a driver's visibility. The method also includes predicting whether the driver will enable a manual mode during the current conditions. The method further includes controlling the driving condition component to mitigate the current conditions prior to the driver enabling the manual mode.

Abstract: A vehicle control system includes an object-detector, a location-detector, a configuration-map, and a controller-circuit. The object-detector is configured to detect objects proximate to a host-vehicle. The location-detector is configured to indicate a location of the host-vehicle. The configuration-map is configured to indicate a configuration of the object-detector for the location of the host-vehicle when the host-vehicle is operated in an automated-mode. The controller-circuit is in communication with the location-detector, the configuration-map, and the object-detector. The controller-circuit is configured to operate the object-detector in accordance with the configuration for the location of the host-vehicle when the host-vehicle is operated in an automated-mode, detect a human-override of the automated-mode at the location, and update the configuration-map for the location in accordance with objects detected and in response to the human-override of the automated-mode.

Abstract: A system and method for assembling and using a map supports advanced driver assistance systems (ADAS) on a host vehicle. The map indicates which roadway segments can support automated driving. The map may also indicate which vehicle sensor signal interpretation and vehicle control algorithms shall be used on those segments. The map may be assembled on a host vehicle, transmitted to a server and collated with maps from other vehicles equipped with ADAS. The host vehicle may download the other maps from the server for use in locations where the driver assistance sensor input from the host vehicle may not be dependable.

Abstract: A control system for an automated vehicle includes a receiver, an alert-device, and a controller-circuit. The receiver is configured to receive a report of a takeover-event broadcast by another-vehicle at a location, said takeover-event characterized by an other-operator of the other-vehicle engaging a manual-mode of operation of the other-vehicle at the location while the other-vehicle was being operated in an automated-mode. The alert-device is operable to notify a host-operator of a host-vehicle. The controller-circuit is in communication with the receiver and the alert-device. The controller-circuit is configured to, in response to a determination that the host-vehicle is approaching the location, operate the alert-device to notify the host-operator of the host-vehicle about the takeover-event by the other-operator of the other-vehicle at the location.

Abstract: A robotic orchard spraying system having autonomous delivery vehicles (ADV), each autonomously delivering an amount of a premixed solution over a non-overlapping path verified by a forward-looking sensor, video, or both. Also, a mobile control center, configured to wireles sly inform the autonomous delivery vehicle of the path within the areas and to confirm that the autonomous delivery vehicle is following the path within the area. Additionally, a mapper vehicle generates the path within the area, the mapper vehicle being configured to communicate information about the path and the area to the command center. The mapper vehicle senses the path with a forward-looking LiDAR sensor, and senses the area with a GPS sensor. Moreover, a nurse truck has a reservoir of premixed solution for replenishing a tank of the ADV. ADVs and the control center communicate over a radio network, which may be a mesh network, a cellular network, or both.

Abstract: A vehicle control handoff system includes a controller comprising a processor and a non-transitory computer readable memory, one or more environment sensors and an imaging device communicatively coupled to the controller, and a machine-readable instruction set stored in the non-transitory computer readable memory of the controller. The machine-readable instruction set causes the system to: receive image data from at least one imaging device, receive one or more signals corresponding to an environment of a vehicle from the one or more environment sensors, define a gaze pattern comprising a first gaze direction corresponding to a first location within the environment of the vehicle, determine a first gaze based on the image data of the driver, determine whether the first gaze corresponds to at least one gaze direction of the gaze pattern, and transfer control of a vehicle operation from control by the controller to the driver in response to determining that the first gaze corresponds to the gaze pattern.

Abstract: An unmanned lawn mowing system includes a plurality of unmanned lawn mowers that perform work while traveling without a human operator and a management server. Each of the unmanned lawn mowers includes an information transmission section that transmits operation information including information indicating a work state to the management server. The management server includes: a case storage section that stores a case related to a failure in and/or a case related to maintenance of each of the unmanned lawn mowers; a maintenance determination section that determines whether or not maintenance of the unmanned lawn mower is necessary, based on the case associated with operation information identical or similar to the operation information; and a maintenance notification transmission section that notifies maintenance to the unmanned lawn mowers, based on a determination result made by the maintenance determination section.

Abstract: A method for controlling a motion of a robot based on map prediction mainly carries out estimation and calculation for a wall surface by combining an external sensor with internal map information about a robot, so as at least to enable the robot to walk along the estimated wall surface. The method for controlling the motion of the robot based on map prediction can be adapted to various different wall surfaces based on map prediction, including different colors and shapes, thereby reducing an operation time; and the accuracy of map prediction can be continuously corrected during an operation process, thereby realizing a good wall-following behavior.

Abstract: An autonomous traveler 1 includes an information acquisition part 11, a map storage part 12 and a travel control part 7. The information acquisition part 11 acquires information on a traveling area. The map storage part 12 creates and stores a base map, by determining the traveling area on the basis of the information acquired by the information acquisition part 11 at a predetermined timing. The travel control part 7 controls traveling on the basis of a map stored in the map storage part 12. The travel control part 7 controls the traveling on the basis of the base map, even when a traveling obstacle stored in the base map is removed.

Abstract: A method for localizing a sensor in a vehicle includes using a first sensor mounted on a vehicle to capture at least one image of a moveable element of the vehicle, the moveable element having a predetermined spatial relationship to a second sensor mounted on the vehicle, the moveable element being moveable relative to the first sensor; determining spatial information on the moveable element on the basis of the at least one image; and localizing the second sensor on the basis of the spatial information by a transformation rule representing the predetermined spatial relationship between the moveable element and the second sensor.

Abstract: A system controlling method according to an embodiment of the present invention comprises operating a plurality of agents having mutually independent processes using a shared memory; obtaining hardware control data for controlling one or more devices from each of references generated from the plurality of agents and stored in the shared memory; and transferring control signals according to the references to the one or more devices selected from the hardware control data.

Abstract: A vehicle running control method includes: acquiring, at least one of a first traveling state information of an autonomous vehicle and a second traveling state information of adjacent vehicles traveling in a traveling lane or in a lane adjacent to the traveling lane through a sensor unit; determining, by a determination processor, a candidate cut-in vehicle that travels behind the autonomous vehicle among the adjacent vehicles based on the first and second traveling state information; searching, by a controller, for a potential cut-in space, which is determined based on the relative velocity of a preceding vehicle that is the closest to the autonomous vehicle among the adjacent vehicles and the distance between the preceding vehicle and the autonomous vehicle; and performing, by the controller, deceleration, acceleration, or velocity maintenance of the autonomous vehicle depending on whether the potential cut-in space is present.

Abstract: A system for order fulfillment using one or more robots includes: a server configured to receive an order comprising an order item; inventory storage operably connected to the server, the inventory storage comprising order items; an actor robot operably connected to and selected by the server, the actor robot configured to perform one or more of picking the order item from inventory storage, moving the order item, and positioning the order item; and an order robot operably connected to the server, the order robot configured to collect the order item, wherein the order item is positioned by the actor robot so as to be accessible to the order robot, so as to perform order fulfillment using one or more robots.

Abstract: The present teaching relates to method, system, medium, and implementation of human-like vehicle control for an autonomous vehicle. Recorded human driving data are first received, which include vehicle state data, vehicle control data, and environment data. For each piece of recorded human driving data, a vehicle kinematic model based vehicle control signal is generated in accordance with a vehicle kinematic model based on a corresponding vehicle state and vehicle control data of the piece of recorded human driving data. A human-like vehicle control model is obtained, via machine learning, based on the recorded human driving data as well as the vehicle kinematic model based vehicle control signal generated based on vehicle kinematic model. Such derived human-like vehicle control model is to be used to generate a human-like vehicle control signal with respect to a target motion of an autonomous vehicle to achieve human-like vehicle control behavior.

Abstract: This vehicle control device comprises an autonomous driving control unit which automatically controls the stopping of a vehicle. If it is determined by a crossing determination unit that there is no crossing, the autonomous driving control unit controls the stopping of the vehicle so that the vehicle is stopped at a standard target stop position corresponding to a stop line on the basis of the positional information of the stop line, whereas if it is determined by the crossing determination unit that there is a crossing, the autonomous driving control unit controls the stopping of the vehicle so that the vehicle is stopped at a position before the standard target stop position on the basis of the positional information of the stop line.

Abstract: Example systems and methods are disclosed for implementing vehicle operation limits to prevent vehicle load failure during vehicle teleoperation. The method may include receiving sensor data from sensors on a vehicle that carries a load. The vehicle may be controlled by a remote control system. The load weight and dimensions may be determined based on the sensor data. In order to prevent a vehicle load failure, a forward velocity limit and an angular velocity limit may be calculated. Vehicle load failures may include the vehicle tipping over, the load tipping over, the load sliding off of the vehicle, or collisions. The vehicle carrying the load may be restricted from exceeding the forward velocity limit and/or the angular velocity limit during vehicle operation. The remote control system may display a user interface indicating to a remote operator the forward velocity limit and the angular velocity limit.

Abstract: A method of transitioning from an autonomous driving mode to a manual driving mode for a vehicle is provided. The method includes comparing a steering device input angle to an autonomously controlled steering angle to determine a steering angle error. The method also includes comparing an acceleration or deceleration input to an autonomously controlled acceleration or deceleration input to determine an acceleration or deceleration error. The method further includes progressively transitioning to the manual driving mode in a weighted manner based on a confidence level factor determined by a calculation that factors in the steering angle error and the acceleration or deceleration error.

Abstract: A method and system for enabling a vehicular parking location identification improvement process is provided. The method includes generating a first database comprising parking locations associated with specified regulations. Parking requirement data associated with parking requirements of a driver of a vehicle at an initial location is received and a second database comprising revised parking locations is generated. Recommended parking locations are generated based on analysis of the first database the said second database and a selection for a parking location of the recommended parking locations is received. The driver is directed from the initial location to the parking location and movement of the vehicle from the initial location to parking location is monitored via sensors.

Abstract: A driving mode switching device includes a determination section, a notification section, a detection section, and a control section. The determination section is configured to determine whether a state has occurred in which automatic driving needs to be terminated. The notification section is configured to notify a driver of the instruction for performing a switching operation as a predetermined operation of a vehicle in the case of determining, by the determination section, that the state has occurred in which the automatic driving needs to be terminated. The detection section is configured to detect the switching operation. The control section is configured to switch travelling from automatic driving to manual driving in the case of detecting the switching operation by the detection section.

Abstract: An autonomous terrestrial compaction testing vehicle includes a compaction density meter coupled to the vehicle and a controller. The controller is communicatively connected to the compaction density meter and to a controller of a compactor machine that is compacting or has compacted an area of terrain. The controller is configured to autonomously control movement of the vehicle over the compacted area and control the compaction density meter to take a plurality of compaction density measurements at a plurality of locations of the compacted area.

Abstract: A trajectory planning method for lane changing of a vehicle includes steps of: calculating a current position of a reference point of the vehicle on a preliminary lane change trajectory that is received from an LCA system of the vehicle at a current time point; based on kinematics data received from an IMU of the vehicle, calculating longitudinal and lateral displacements of the reference point moving during a unit of time from the current time point to a next time point, and a yaw angle of the vehicle at the next time point; and obtaining a calibrated lane change trajectory based on the preliminary lane change trajectory, the current position, the longitudinal and lateral displacements, and the yaw angle.

Abstract: A parking control apparatus includes an input device configured to acquire an operation command acquired from inside or outside of a vehicle and a control device configured to control the vehicle in accordance with the operation command. The control device is configured to determine a communication environment around the vehicle and control the vehicle to park in accordance with a result of the determination.

Abstract: Systems and methods are provided herein for obstacle detection and avoidance. An obstacle (e.g., a fallen object, an area of congestion, etc.) may be detected utilizing sensor data and/or navigational information provided by various components of a workspace (e.g., mobile drive units, standalone sensors, etc.). Obstacle information corresponding to the obstacle may be utilized to identify tasks within the workspace that may be affected by the obstacle. Paths for these affected tasks may be altered and any subsequent path generated by the system may be generated based at least in part on the obstacle, so long as the obstacle exists. Utilizing the techniques provided herein, the workflows/tasks/paths of the components of the system may be managed so as to avoid interactions between the components of the system and any known obstacle.

Abstract: The present disclosure relates to electronic system and methods for switching a driving mode of a vehicle. The electronic system may include at least one sensor configured to connect to a driving system of a vehicle; at least one gateway module connected to the at least one sensor through a controller area network; and processing circuits connected to the at least one gateway module. During operation, the processing circuits may receive at least one trigger signal from the at least one sensor; determine that the at least one trigger signal meets a predetermined condition; and send at least one switching signal to the gateway module to switch the vehicle from a current driving mode to a target driving mode.

Abstract: Aspects of the disclosure relate controlling autonomous vehicles or vehicles having an autonomous driving mode. More particularly, these vehicles may identify and respond to other vehicles engaged in a parallel parking maneuver by receiving sensor data corresponding to objects in an autonomous vehicle's environment and including location information for the objects over time. An object corresponding to another vehicle in a lane in front of the first vehicle may be identified from the sensor data. A pattern of actions of the other vehicle identified form the sensor data is used to determine that the second vehicle is engaged in a parallel parking maneuver based on a pattern of actions exhibited by the other vehicle identified from the sensor data. The determination is then used to control the autonomous vehicle.

Abstract: An autonomous driving device is configured to switch a driving mode, and includes a destination setting type autonomous driving mode in which a vehicle is made to travel to a destination and a following road autonomous driving mode in which, when a destination is not set, the vehicle is made to travel along a road. The autonomous driving device includes a display unit and an electronic control unit. The electronic control unit is configured to, when the display unit is made to display a traveling route along a following road traveling route, make the display unit display a traveling route from a current position of the vehicle to a nearest branch road in front in a moving direction along the following road traveling route and a moving direction on the nearest branch road along the following road traveling route.

Abstract: A vehicle control device includes a processor configured to determine a danger of collision between a user located within a specific distance from a first vehicle and a second vehicle that is traveling, warn the danger of collision through the first vehicle or a user terminal of the user according to the danger of collision, or control movement of the first vehicle, or transmit warning information to the second vehicle, and a storage configured to store information calculated by the processor.

Abstract: Automation windows for RPA for attended or unattended robots are disclosed. A child session is created and hosted as a window including the UIs of applications of a window associated with a parent session. Running multiple sessions allows a robot to operate in this child session while the user interacts with the parent session. The user may thus be able to interact with applications that the robot is not using or the user and the robot may be able to interact with the same application if that application is capable of this functionality. The user and the robot are both interacting with the same application instances and file system. Changes made via the robot and the user in an application will be made as if a single user made them, rather than having the user and the robot each work with separate versions of the applications and file systems.

Abstract: A system for moving material from a first work area to a second work includes a material moving machine, a machine position sensor and a controller system. The controller system performs first material moving operations including determining a premature termination of a material stacking operation. The controller system performs additional material moving operations including instructing a material moving machine in response to the premature termination of a material stacking operation.

Abstract: An autonomous vehicle that automatically responds to an emergency service vehicle. Perception data is captured or received by the autonomous vehicle (AV) cameras, sensors, and microphones. The perception data is used to detect lanes in a road, generate a list of objects, classify one or more of the objects, and determine a state for the classified objects. In response to detecting an emergency service vehicle such as a law enforcement vehicle, a responsive action may be planned by the AV. The responsive action may include sending an acknowledgement signal, notifying passengers of the AV, generating a planned trajectory based on the emergency service vehicle location, an emergency service vehicle detected intention, and other information. A safety check may be performed, and commands may be generated by a control module to navigate the AV along the planned trajectory. The commands may then be executed by a DBW module.

Abstract: A lane trace control system for maintaining a vehicle in its intended lane of travel. The system includes a lane trace control module configured to: compare the road information obtained by a lane recognition camera with map data obtained from a map module; determine a confidence level of the lane recognition camera based on a magnitude of any differences identified between the road information obtained from the lane recognition camera and the obtained map data; generate a target wheel angle for keeping the vehicle in its intended lane based entirely on the road information obtained from the lane recognition camera when the confidence level is above a predetermined threshold; and generate the target wheel angle based on a combination of the road information obtained from the lane recognition camera and the obtained map data of the road when the confidence level is below the predetermined threshold.

Abstract: An apparatus for performing driving aid control to cause a travel trajectory of a mobile object to follow a setpoint trajectory (La) by transmitting a control command value (?) to a yaw moment controller capable of controlling a yaw moment of the mobile object. In the apparatus, a setpoint trajectory setter is configured to set the setpoint trajectory (La) of the mobile object. A control command value calculator is configured to calculate the control command value (?) based on an integrated value (?I) of a lateral error that is an error between a position of the mobile object and the setpoint trajectory. The control command value calculator is further configured to decrease the integrated value (?I) with decreasing a curvature (?) of a road on which the mobile object is traveling.

Abstract: Methods and systems for autonomous and semi-autonomous vehicle control relating to anomalies are disclosed. Anomalous conditions with a vehicle operating environment, such as ice patches or flooded roads, may be identified and categorized using autonomous vehicle operating data, and corrective actions to mitigate the impact of such anomalies may be taken. Corrective actions may include maneuvering the vehicle in the area of the anomaly or rerouting the vehicle around the area of the anomaly. A vehicle encountering an anomaly may further communicate an alert to warn other nearby vehicles, including non-autonomous vehicles. Such communication may be limited to anomalies of certain types or severity, and duplicative communications may be suppressed. Vehicles receiving such alerts may take corrective actions or present information regarding the anomaly for operator response.

Abstract: Traversing, by an autonomous vehicle, a vehicle transportation network, may include identifying a policy for a scenario-specific operational control evaluation model of a distinct vehicle operational scenario, receiving a candidate vehicle control action from the policy, wherein, in response to a determination that an uncertainty value for the distinct vehicle operational scenario exceeds a defined uncertainty threshold, the candidate vehicle control action is an orientation-adjust vehicle control action, and traversing a portion of the vehicle transportation network in accordance with the candidate vehicle control action, wherein the portion of the vehicle transportation network includes the distinct vehicle operational scenario.

Abstract: A driving assistance system for a vehicle includes a control operable to control the vehicle in an autonomous or semi-autonomous mode. When operating in the autonomous mode, driving of the vehicle is controlled by the control without human intervention and, when operating in the semi-autonomous mode, an occupant of the vehicle at least partially drives the vehicle. The control learns a driving style of a particular occupant when the vehicle is being driven by that particular occupant and when the control is operating in the semi-autonomous mode. The control, when operating in the autonomous mode, controls the vehicle in accordance with the learned driving style of the particular occupant of the vehicle. Responsive to a determination of a characteristic of an occupant in the vehicle, the control, when operating in the autonomous, may adjust control of the vehicle irrespective of the learned driving style of the particular occupant.

Abstract: Disclosed is a method and apparatus for controlling a vehicle in an autonomous driving system that controls platooning. A method of controlling a first vehicle that transports passengers in an autonomous driving system that controls platooning according to an embodiment of the present disclosure includes: receiving boarding/alighting information of the passengers from a server; determining a first platoon formation of platooning vehicles that travel in the same lane in a platoon on the basis of the boarding/alighting information; transmitting information about the first platoon formation to other vehicles included in the platoon; checking an object moving adjacent to the lane; and transmitting an object block instruction message, which changes the platoon formation into a second platoon formation such that a block distance between at least one vehicle included in the platoon and a sidewalk becomes smaller than a width of the object, to other vehicles included in the platoon.

Abstract: A vehicle control apparatus includes a notification unit configured to notify a driver of a switching request from automated driving to manual driving, and a setting unit configured to set a notification timing of the notification unit. In a case in which a course change of a vehicle is needed up to a predetermined point during the automated driving, the setting unit sets a timing that comes earliest from a plurality of candidates of the notification timing. The plurality of candidates includes a first candidate based on a condition necessary for completing the course change by the manual driving up to the predetermined point, and a second candidate based on a condition necessary for setting the vehicle in a predetermined standby state by the automated driving up to the predetermined point.

Abstract: Systems and methods for modifying operation of an autonomous vehicle in an emergency situation are disclosed. According to aspects, a computing device detects, based on sensor(s), an emergency event associated with the autonomous vehicle. In response to detecting the emergency event, the computing device determines location(s) of emergency vehicle(s) and determines an assistance location for the autonomous vehicle. The computing device transmits the assistance location to the emergency vehicle(s), obtains a current operation of the autonomous vehicle, and determines a vehicle operation modification for the autonomous vehicle.

Abstract: Disclosed is a cleaner comprising a cleaner body, a front wheel rotatably provided in a front portion of the cleaner body, a rear wheel rotatably provided in a rear portion of the cleaner body, a first member attached to an outer circumferential surface of the front wheel and configured to contact with a cleaning object surface, a second member attached to an outer circumferential surface of the rear wheel and configured to contact with the cleaning object surface, a front motor rotating the front wheel, a rear motor rotating the rear wheel and a controller driving the front motor and the rear motor, wherein the controller controls the front motor and the rear motor to become rotated in the opposite directions while cleaning is performed.

Abstract: A method for evaluating safety performance of an autonomous vehicle including comparing first sensor data characterizing a driver-operation of a vehicle to a first threshold to obtain a first driving quality value, comparing second sensor data characterizing an autonomous-vehicle-operation to a second threshold to obtain a second driving quality value, and determining, based at least in part on a comparing of the first and second driving quality values to each other, a safety performance of the autonomous-operated vehicle relative to the driver-operated vehicle, and a corresponding system.

Abstract: Among other things, a determination is made that intervention in an operation of one or more autonomous driving capabilities of a vehicle is appropriate. Based on the determination, a person is enabled to provide information for an intervention. The intervention is caused in the operation of the one or more autonomous driving capabilities of the vehicle.