Abstract: An autonomous vehicle is described herein. The autonomous vehicle comprises a first sensor and a second sensor having limited fields of view, an articulation system, and a computing system. The computing system determines a first region and a second region external to the autonomous vehicle based on a sensor prioritization scheme comprising a ranking of regions surrounding the autonomous vehicle. The computing system then causes the articulation system to orient the first sensor towards the first region and the second region towards the second region. Responsive to receiving a sensor signal from the first sensor indicating that an object has entered a field of view of the first sensor, the computing system determines a third region having a higher ranking than the second region within the sensor prioritization scheme. The computing system then causes the articulation system to orient the second sensor towards the third region.

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 vehicle control system includes: a terminal configured to be carried by a user; and a control device configured to execute remote autonomous moving processing to move a vehicle from an initial position to a stop position. The terminal includes: a touch panel configured to display an acceptance area that accepts a prescribed repetitive operation performed for continuing traveling of the vehicle and to display a suspension icon that accepts an operation performed for stopping the vehicle; and a processing unit configured to make the touch panel display the suspension icon at a part where the repetitive operation has been performed when the repetitive operation is stopped. When the control device or the processing unit determines that the suspension icon is operated or that the repetitive operation is not resumed within a prescribed period after the repetitive operation has been stopped, the control device stops the vehicle.

Abstract: In one embodiment, a method for temporal smoothness in localization results for an autonomous driving vehicle includes: creating a probability offset volume that represents an overall matching cost between a first set of keypoints from the online point cloud and a second set of keypoints from a pre-built point cloud map for each of a series of sequential light detection and ranging (LiDAR) frames in an online point cloud. The method also includes compressing the probability offset volume into multiple probability vectors across a X dimension, a Y dimension and a yaw dimension; providing each probability vector of the probability offset volume to a number of recurrent neural networks (RNNs); and generating, by the RNNs, a trajectory of location results across the plurality of sequential LiDAR frames.

Abstract: A system and method for autonomous vehicle control to minimize energy cost are disclosed. A particular embodiment includes: generating a plurality of potential routings and related vehicle motion control operations for an autonomous vehicle to cause the autonomous vehicle to transit from a current position to a desired destination; generating predicted energy consumption rates for each of the potential routings and related vehicle motion control operations using a vehicle energy consumption model; scoring each of the plurality of potential routings and related vehicle motion control operations based on the corresponding predicted energy consumption rates; selecting one of the plurality of potential routings and related vehicle motion control operations having a score within an acceptable range; and outputting a vehicle motion control output representing the selected one of the plurality of potential routings and related vehicle motion control operations.

Abstract: An autonomous vehicle uses a secondary vehicle control system to supplement a primary vehicle control system to perform a controlled stop if an adverse event is detected in the primary vehicle control system. The secondary vehicle control system may use a redundant lateral velocity determined by a different sensor from that used by the primary vehicle control system to determine lateral velocity for use in controlling the autonomous vehicle to perform the controlled stop.

Abstract: There are disclosed various methods and apparatuses for multi-vehicle maneuver and impact analyses.

Abstract: Aspects relate to methods and systems for reversionary flight control for an electrical vertical take-off and landing (eVTOL) aircraft. An exemplary system includes a pilot control, a sensor configured to sense and transmit analog control data associated with a pilot interaction with the pilot control, a pilot interface module configured to receive the analog control data, convert the analog control data to digital control data, and transmit digital control, an actuator, and a flight controller. The flight controller may be configured to receive the digital control data, determine a primary command datum as a function of the digital control data, transmit the primary command datum to the actuator, determine that the digital control signal is non-functional, receive the analog control data, determine a reversionary command datum as a function of the analog control data, and transmit the reversionary command datum to the actuator.

Abstract: In some implementations, the EMV uses a calibration to inform autonomous control over the EMV. To calibrate an EMV, the system first selects a calibration action comprising a control signal for actuating a control surface of the EMV. Then, using a calibration model comprising a machine learning model trained based on one or more previous calibration actions taken by the EMV, the system predicts a response of the control surface to the control signal of the calibration action. After the EMV executes the control signal to perform the calibration action, the EMV system monitors the actual response of the control signal and uses that to update the calibration model based on a comparison between the predicted and monitored states of the control surface.

Abstract: Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, based on occluded areas in an environment. An occluded area can represent areas where sensors of the vehicle are unable to sense portions of the environment due to obstruction by another object. An occlusion grid representing the occluded area can be stored as map data or can be dynamically generated. An occlusion grid can include occlusion fields, which represent discrete two- or three-dimensional areas of driveable environment. An occlusion field can indicate an occlusion state and an occupancy state, determined using LIDAR data and/or image data captured by the vehicle. An occupancy state of an occlusion field can be determined by ray casting LIDAR data or by projecting an occlusion field into segmented image data. The vehicle can be controlled to traverse the environment when a sufficient portion of the occlusion grid is visible and unoccupied.

Abstract: The present disclosure relates to a method for generating control signals to assist occupants in a vehicle, wherein a context of the vehicle is determined, a rule of a rule-based data system is selected depending on the determined context, wherein the rule-based data system comprises a plurality of rules, wherein each rule has a condition part and a result part, wherein the condition part comprises conditions for the context of the vehicle, a confidence value associated with the selected rule is determined, wherein the confidence value indicates the probability with which the result of the rule corresponds with the preference of the user, a result of the selected rule is generated, a control signal is generated and output depending on the generated rule result, wherein the control signal automates a vehicle function with a degree of automation, wherein the degree of automation depends on the confidence value of the selected rule. The disclosure likewise relates to a device for executing this method.

Abstract: A guidance system includes an outputter configured to output information, a first acquirer configured to acquire position information indicating an occurrence position of a predetermined event that occurred due to at least the feelings of an occupant in a moving body, a second acquirer configured to acquire position information indicating a position of a first moving body, and an output controller that is configured to cause the outputter to output guidance information for providing guidance to the occupant in the first moving body regarding the fact that there is a possibility of the predetermined event occurring in the first moving body according to the position information acquired by the first acquirer and the position information acquired by the second acquirer.

Abstract: A control stand is disclosed for controlling a crane, an excavator, a crawler, or a similar construction machine having a seat, control elements actuable from the seat for inputting control commands, a display apparatus for displaying information, and a control unit for generating adjustment signals in dependence on input control commands and/or for providing information to the display apparatus. A crane is disclosed having such a control stand that can be configured in the form of a crane operator's cabin. The control elements and/or the display apparatus of the control stand and various further auxiliary units can be individually configurable. Personal pre-settings can be saved and can be reinvoked when the control stand or the crane is to be controlled by a certain machine operator.

Abstract: A vehicle system includes a steering wheel configured to output an output based on an input from a user, and a controller configured to: determine a target orientation of front wheels of a vehicle based on vehicle environment information, determine whether an orientation of the front wheels of the vehicle based on the output from the steering wheel deviates from the target orientation, disengage the steering wheel from the front wheels in response to determination that the orientation of the front wheels deviates from the target orientation, adjust the orientation of the front wheels to the target orientation and provide a feedback in response to adjusting the orientation of the front wheels to the target orientation.

Abstract: Systems and methods for situational modification of autonomous vehicle operation are disclosed. According to aspects, a computing device may detect the occurrence of an emergency event and may determine a current operation of an autonomous vehicle that may be associated with the emergency event. The computing device may determine a modification to operation of the autonomous vehicle, where the modification may represent a violation of a roadway regulation that may enable effective handling of the emergency event. The computing device may generate a set of instructions for the autonomous vehicle to execute to cause the autonomous vehicle to undertake the operation modification.

Abstract: An autonomous robot is provided. In one example embodiment, an autonomous robot can include a main body including one or more compartments. The one or more compartments can be configured to provide support for transporting an item. The autonomous robot can include a mobility assembly affixed to the main body and a sensor configured to obtain sensor data associated with a surrounding environment of the autonomous robot. The autonomous robot can include a computing system configured to plan a motion of the autonomous robot based at least in part on the sensor data. The computing system can be operably connected to the mobility assembly for controlling a motion of the autonomous robot. The autonomous robot can include a coupling assembly configured to temporarily secure the autonomous robot to an autonomous vehicle. The autonomous robot can include a power system and a ventilation system that can interface with the autonomous vehicle.

Abstract: The present disclosure is directed toward systems and methods for providing an indicator of a direction between a requester and a transportation vehicle. For example, the systems and methods described herein can provide a dynamic digital compass from the current orientation of a requester client device to the location of a transportation vehicle. For example, the systems and methods described herein can determine a location of a requester client device, a location of a transportation vehicle, and an orientation of the requester client device. The systems and methods can also utilize the location of the requester client device, the location of the transportation vehicle, and the orientation of the requester client device to identify a direction from the requester client device to the transportation vehicle relative to the current orientation of the requester client device and provide a digital compass to indicate the direction to the transportation vehicle.

Abstract: An ADV includes a method to combine data from multiple sensors. The method compresses video data from a camera to generate compressed video data. The compressed video data are segmented. The method time synchronizes each segment of the compressed video data with data from other sensors. The method then combines each segment of the compressed video data with the corresponding time-synchronized sensor data for the other sensors. In one embodiment, each segment of the compressed video data is independently decodable. In another embodiment, each segment of the compressed video data includes a compressed video unit that is prepended with a buffered portion of the compressed video data that immediately precede the compressed video unit. The length of the compressed video unit is smaller than the length of the independently decodable segment to offer finer granularity in time synchronizing the compressed video data with the other sensor data with a tradeoff.

Abstract: A navigation server includes a network interface controller through which identification information and movement line information of a mobile terminal are received from the mobile terminal, the movement line information including location information and a timestamp, a storage device in which movement line data of the mobile terminal and location data of different places are stored, and a processor configured to extract the movement line data from the movement line information and record the extracted movement line data in the storage device. The processor, in response to a search criteria received from the mobile terminal through the network interface controller, generates using the movement line data and the location data of the different places, a navigation map that shows a place that is located along a route defined by the movement line data and meets the search criteria, and transmits the navigation map to the mobile terminal for display.

Abstract: An image captured by a far-infrared camera is analyzed to analyze a distribution of a road-surface temperature, and a course of a highest road-surface temperature is determined to be a traveling route. Further, automatic driving along the course of the highest road-surface temperature is performed. Furthermore, a state of the distribution of a road-surface temperature, and a direction of the course of the highest road-surface temperature are displayed on a display section, so that a user (a driver) recognizes them. For example, a state analyzer detects a candidate course travelable for a vehicle, the state analyzer detecting a plurality of the candidate courses, calculates an average value of a road-surface temperature of each of the plurality of the candidate courses, and determines the candidate course having a largest average value of a road-surface temperature to be a traveling route.