Abstract: A computer implemented method in a communications network for determining location information about an actual location of a drone comprises obtaining a reported location of the drone at a first time point and obtaining a measurement of radio conditions between the drone and a node in the telecommunications network, at the first time point. The method then comprises predicting radio conditions at one or more locations related to the reported location of the drone, and determining the location information about the actual location of the drone based on the measured radio conditions and the predicted radio conditions.

Abstract: A target acceleration/deceleration output unit includes an acceleration/deceleration output unit which outputs an acceleration/deceleration including a deceleration, on the basis of the vehicle-to-vehicle distance from a host vehicle to a preceding vehicle and the relative speed of the host vehicle and the preceding vehicle, and a canceling unit which cancels a deceleration that causes jerking from the deceleration output from the acceleration/deceleration output unit, wherein the acceleration output from the acceleration/deceleration output unit, and the deceleration obtained by the canceling unit are output as a target acceleration/deceleration.

Abstract: A device for controlling autonomous driving includes at least one sensor disposed in an autonomous driving vehicle, wherein the sensor is configured to detect information necessary for autonomous driving of the autonomous driving vehicle. The device further includes a controller, wherein the controller is configured to diagnose a fault of the at least one sensor during autonomous driving of the autonomous driving vehicle, upon determination that the fault has occurred in the at least one sensor, to prohibit an autonomous driving related function corresponding to the fault of the at least one sensor, to determine an alternative route based on the prohibited function and to control the autonomous driving according to the determined alternative route.

Abstract: A driving assistance apparatus sets a driving condition of a vehicle, based on a risk of surrounding environment that includes an object around the vehicle. The driving assistance apparatus includes a forward-risk calculator, a backward-risk calculator, and a driving-condition setter. The forward-risk calculator is configured to calculate a forward risk corresponding to a risk of a collision with a leading vehicle that travels ahead of the vehicle. The backward-risk calculator is configured to calculate a backward risk corresponding to a risk of a collision with a trailing vehicle that travels behind the vehicle. The driving-condition setter is configured to set the driving condition of the vehicle, based on the forward risk and the backward risk.

Abstract: A vehicle drive assist apparatus for a vehicle includes a surrounding-condition-information acquiring unit that acquires surrounding condition information, a vehicle-state-information acquiring unit that acquires vehicle state information, a traveling control processor that executes traveling control in accordance with traffic lane designation, a DDI detector, and a control switch. The DDI detector detects a DDI in a front region of the vehicle on the basis of the surrounding condition information and determines whether the vehicle is entering or exiting from the DDI on the basis of the surrounding condition information and the vehicle state information. The control switch switches the traveling control from standard traveling control to non-standard traveling control when the vehicle entering the DDI is detected, and from the non-standard traveling control to the standard traveling control when the vehicle exiting from the DDI is detected on the basis of the result of the DDI determination.

Abstract: Provided is a driving assistance device that makes it possible to smoothly accelerate from a stop or from a speed close to a stop. A target acceleration/deceleration output unit of the driving assistance device has: a first map that stores first target accelerations which are associated with inter-vehicle distance and with relative speed; a second map that stores second target accelerations which are associated with inter-vehicle distance and with relative speed and which are greater than the first target accelerations with respect to inter-vehicle distance and relative speed; and a selection unit that selects, according to a vehicle speed, whether to use the output of the first map and/or whether to use the output of the second map.

Abstract: A method for controlling a plurality of autonomous mobile robots (AMRs) in a manufacturing environment having an intersection includes obtaining a plurality of routes associated with the plurality of AMRs, velocity information associated with the plurality of AMRs, and priority information associated with the plurality of AMRs, and determining a plurality of arrival times associated with the plurality of AMRs based on the velocity information and the plurality of routes. The method includes generating a plurality of intersection reservations based on the plurality of arrival times and the priority information, where each intersection reservation from among the plurality of intersection reservations corresponds to an AMR from among the plurality of AMRs, and controlling a movement of the plurality of AMRs through the intersection based on the plurality of intersection reservations.

Abstract: A method and an apparatus for generating sensor data for controlling an autonomous vehicle in an environment is provided, such as driverless transport vehicles in a factory for example. Sensor positions of static sensors and the sensors of autonomous vehicles are defined in a global coordinate system on the basis of an environment model, such as a BIM model for example. Sensor data is centrally generated in this global coordinate system for all sensors as a function of these sensor positions. The sensor data is then transformed into a local coordinate system of an autonomous vehicle and transferred for controlling the autonomous vehicle.

Abstract: Presented are intelligent vehicle systems and control logic for adaptive vehicle sensing and automation for occupants with health conditions, methods for making/using such systems, and vehicles equipped with such systems. A method of operating a vehicle includes a resident or remote vehicle controller determining an existing health condition of an occupant in the vehicle's passenger compartment. The controller then retrieves, e.g., from a resident or remote memory device, predefined sets of calibration settings and condition symptoms customized to this existing health condition. A network of sensing devices is calibrated using the predefined calibration settings to detect one or more of the predefined condition symptoms. The calibrated sensing devices monitor the occupant to detect a health event based on the predefined condition symptoms. Upon detecting the health event, the controller commands one or more resident vehicle subsystems to execute one or more vehicle operations to mitigate the health event.

Abstract: Rocket control is a difficult and unpredictable task in environments with inclement weather. As a result, launch missions are often strictly limited based on weather conditions. The present invention provides a method for controlling a rocket to account for environmental uncertainties and maintain optimal mission performance. First, sensors collect data about the rocket's environment, passing the information to storage in the rocket's database. Second, the rocket's processor manipulates the database with an optimization algorithm producing instructions. Third, the instructions command the rocket's control system for an optimal end-to-end trajectory and to enable the rocket to perform a safe landing.