Abstract: A vehicle driving assist system includes a storage, an autonomous sensor, a traveling environment recognizer, and a controller. The storage contains map information on an intersection where at least one intersecting road intersects at grade with a traveling road of an own vehicle. The autonomous sensor detects information on the traveling road positioned in front of the own vehicle. The traveling environment recognizer recognizes the detected information on the traveling road. The controller determines, before reaching the intersection, whether the intersecting road is a blind spot depending on presence or absence of a view-blocking object, on the basis of the recognized information on the traveling road, and changes, if the intersecting road is determined as being a blind spot, a lateral position shift amount of a course of the own vehicle in a direction away from the intersecting road when the own vehicle passes through the intersection.

Abstract: A controller includes a control unit. The control unit is configured to detect a state of at least one point, and determine depending on the detected state whether or not to include, in a flight route of a flying object transporting a package, a position above the at least one point as a passing point for the flying object to pass.

Abstract: An item repositioning method includes, in response to a request for an item, moving a vehicle along a first route to a location of the item, loading the item in the vehicle using a lift assist device mounted to the vehicle, moving the vehicle along a second route to transport the item to a desired location, and at the desired location, unloading the item from the vehicle using the lift assist device.

Abstract: Systems/methods for operating an autonomous vehicle. The methods comprise, by a computing device: using sensor data to track an object that was detected in proximity to the autonomous vehicle; classifying the object into at least one dynamic state class of a plurality of dynamic state classes; transforming the at least one dynamic state class into at least one goal class of a plurality of goal classes; transforming the at least one goal class into at least one proposed future intention class of a plurality of proposed future intention classes; determining at least one predicted future intention of the object based on the proposed future intention class; and/or causing the autonomous vehicle to perform at least one autonomous driving operation based on the at least one predicted future intention determined for the object.

Abstract: A control system in a delivery system performs a method of controlling unmanned aerial vehicles, UAVs, which are organized in a group or swarm to perform one or more missions to deliver and/or pick up goods. The method includes obtaining drag data indicative of air resistance for one or more UAVs in the group, determining, as a function of the drag data, a respective relative position of at least the one or more UAVs within the group, and controlling at least the one or more UAVs to attain the respective relative position. Such adjustment in the relative position of one or more UAVs enables improved energy efficiency and may be made to reduce energy consumption, increase reach or decrease travel time of at least one UAV in the group.

Abstract: This document describes techniques, apparatuses, and systems for standard-definition (SD) to high-definition (HD) navigation route determination. An example route builder receives a navigation route generated for a host vehicle. The navigation route includes a list of waypoints generated by an SD map database. The route builder matches the list of waypoints to lane geometry data maintained in an HD map database and outputs HD navigation route to a vehicle controller. The HD navigation route includes the list of waypoints, additional waypoints, and lane geometry data. The vehicle controller can then operate the host vehicle in a roadway environment along the HD navigation route. In this way, the described techniques and systems can provide HD navigation routes required by some assisted-driving and autonomous-driving systems based on SD navigation routes.