Abstract: Disclosed are methods, systems, and computer-readable medium to perform operations including: registering one or more aerial vehicles and one or more land-based vehicles with a last mile delivery system, where the one or more aerial vehicles and the one or more land-based vehicles are associated with aerial vehicle information and land-based vehicle information, respectively; determining to generate a land-based vehicle transportation request for a first aerial vehicle that is performing a delivery; matching, based on the land-based vehicle transportation request and the land-based vehicle information, the first aerial vehicle with a first land-based vehicle; and generating and sending transportation instructions to the first aerial vehicle and the first land-based vehicle, where the transportation instructions include: (i) a starting location where the first aerial vehicle docks to the first land-based vehicle, and (ii) a destination to which the first land-based vehicle transports the first aerial vehicle.

Abstract: A vehicle system includes: a map processing unit that creates local map data based on high accuracy map data and a position of an own vehicle; and an autonomous driving control unit that creates a travel plan for autonomous traveling of the own vehicle based on the local map data and controls traveling of the own vehicle according to the travel plan. The map processing unit creates multiple pieces of transmission data by dividing the local map data so as to correspond to regions on a map and transmits the multiple pieces of transmission data to the autonomous driving control unit. The map processing unit changes a shape and a size of the region on the map corresponding to each piece of transmission data based on selection information which decides a travel mode.

Abstract: Methods and apparatus for automatically extending aircraft wing flaps in response to detecting an excess energy steep descent condition are described. An example control system of an aircraft includes one or more processors. The one or more processors determine whether the aircraft is experiencing an excess energy steep descent (EESD) condition. In response to determining that the aircraft is experiencing the EESD condition, the one or more processors command an actuator of the aircraft coupled to a flap of the aircraft to extend the flap from a current flap position to a subsequent flap position defined by a flap extension sequence.

Abstract: An approach is provided for automatically coding cartographic feature(s), e.g., human settlement(s). The approach involves receiving data point(s) associated with point location(s) and indicative of a cartographic feature. The approach also involves retrieving or generating a cartographic feature polygon corresponding to the cartographic feature based on the data point(s). The approach further involves generating a plurality of polygon data points that replicate the cartographic feature polygon, and/or a spider web model that represents the point location(s). The approach further involves retrieving imagery data depicting the cartographic feature based on the plurality of polygon data points and/or the spider web model. The approach further involves merging the data point(s), the plurality of polygon data points, and/or the imagery data to generate new or updated polygon structure data point(s) to represent the cartographic feature.

Abstract: Aspects of the disclosure relate to generating scouting objectives in order to update map information used to control a fleet of vehicles in an autonomous driving mode. For instance, a notification from a vehicle of the fleet identifying a feature and a location of the feature may be received. A first bound for a scouting area may be identified based on the location of the feature. A second bound for the scouting area may be identified based on a lane closest to the feature. A scouting objective may be generated for the feature based on the first bound and the second bound.

Abstract: A time master and sensor data collection module for a robotic system such as an autonomous vehicle is disclosed. The module includes a processing device, one or more sensors, and programming instructions that are configured to cause the processing device to operate as a timer that generates a vehicle time, receive data from the one or more sensors contained within the housing, and synchronize the data from the one or more sensors contained within the housing with the vehicle time. The integrated sensors may include sensors such as a global positioning system (GPS) unit and/or an inertial measurement unit (IMU). The module may interface with external sensors such as a LiDAR system and/or cameras.

Abstract: A method for partially or fully autonomously guiding a motor vehicle includes setting a target steering angle for guiding along a target trajectory. It is checked whether a zero point shift exists between a current position of the motor vehicle with respect to the target trajectory. The set target steering angle is adjusted on the basis of a correction constant in the event that a determined zero point shift exceeds a predefined threshold.

Abstract: Optical image sensor systems and process for simultaneously tracking multiple stationary or moving objects to provide attitude and geolocation information are provided. The objects are detected and tracked within subframe areas defined within a field of view of the image sensor system. Multiple objects within the field of view can be detected and tracked using parallel processing streams. Processing subframe areas can include applying precomputed detector data to image data. Image data within each subframe area obtained from a series of image frames is aggregated to enable the centroid of an object within a particular subframe to be located. Information from an inertial measurement unit can be applied to maintain a stationary object, such as a star, at the center of a respective subframe. Ephemeris data can be applied in combination with the information from the IMU to track a resident space object traversing a known trajectory.

Abstract: The disclosure describes systems and methods including for monitoring and remotely controlling a fleet of autonomous vehicles. The remote vehicle control system includes a horizontal display with vehicle graphics on a map and determines a control input to control a vehicle based on a device input from an input device.

Abstract: In a drive system of an electric assisted bicycle, a controller includes a vehicle speed calculator to calculate a change gear ratio of a change gear mechanism based on an output signal of a vehicle speed sensor and an output signal of a rotation sensor in response to acquisition of the output signal of the vehicle speed sensor, and calculate a vehicle speed based on the calculated change gear ratio and the output signal of the rotation sensor at a higher frequency than a frequency of the acquisition of the output signal of the vehicle speed sensor. The controller includes an initial target calculator to calculate target power without using the output signal of the vehicle speed sensor in a prescribed period from start of walking, when a walk command is received, and a target calculator to calculate a target power based on the vehicle speed calculated by the vehicle speed calculator after a lapse of the prescribed period.

Abstract: An aircraft includes a fuselage, a main wing, an electric field sensor, and a flight controller. The electric field sensor is configured to detect surface electric field intensities at four or more of mutually different positions on the aircraft. The flight controller includes a storage, a data extracting unit, an electric field intensity calculator, and an attitude control unit. The storage holds an electric field distribution table. The data extracting unit is configured to extract one of pieces of distribution data from the electric field distribution table. The electric field intensity calculator is configured to calculate surface electric field intensities at respective positions on the basis of the extracted piece of the distribution data. The attitude control unit is configured to perform prevention operation of the aircraft on the basis of the calculated surface electric field intensities at the respective positions.

Abstract: A method for updating a localization of an autonomous vehicle includes receiving perception input data from a sensor of the autonomous vehicle and receiving map data including road lane information in a vicinity of the autonomous vehicle. The method includes processing the perception input data to extract perceived road lane information including a perceived x position, a perceived y position, a perceived z position, a perceived lane type, a perceived lane color, and a perceived lane curvature and processing the map data to extract map road lane information including a map x position, a map y position, a map z position, a map lane type, a map lane color, and a map lane curvature. The method includes calculating a transformation matrix from the perceived road lane information and the map road lane information and updating the map data and a localization of the vehicle based on the transformation matrix.

Abstract: A system for providing remote assistance to an autonomous vehicle is disclosed herein. The system includes at least one remote assistance button configured to be selectively activated to initiate remote assistance for the autonomous vehicle. Each remote assistance button corresponds to a dedicated remote assistance function for the autonomous vehicle. For example, the system can include remote assistance buttons for causing the autonomous vehicle to stop, decelerate, or pull over. The system includes a controller configured to detect activation of the remote assistance button(s) and to cause remote assistance to be provided to the autonomous vehicle in response to the activation. For example, the autonomous vehicle may perform an action corresponding to the activated button with input assistance from the controller but without the system taking over control of the autonomous vehicle.

Abstract: Vehicle developer devices, systems and methods are disclosed. In one embodiment, a vehicle developer device includes a management computing device, a plurality of electronic control units, and a plurality peripheral devices, wherein one or more individual peripheral devices of the plurality of peripheral devices is a physical representation of an actual vehicle peripheral device. The vehicle developer device further includes a plurality of ports for receiving one or more of at least one additional electronic control units and at least one additional peripheral devices. The management computing device configures the plurality of electronic control units, and simulates operation of a full-scale simulated vehicle. The vehicle developer device is smaller in size than the full-scale simulated vehicle.