Abstract: Proposed are a mobile object, an information processing apparatus, an information processing method, and a program that are capable of improving the accuracy of determining whether to land a drone aircraft on a landing surface. The mobile object of the present technology includes a control unit. The control unit calculates a temporal change of a landing surface from images in which the landing surface for the mobile object is imaged in time series by an imaging unit of the mobile object in a hovering state, and determines whether to land the mobile object on the landing surface on the basis of the calculated temporal change.

Abstract: An autonomous mobile device (AMD) moves around a physical space while performing tasks. The AMD may have sensors with fields of view (FOVs) that are forward-facing. As the AMD moves forward, a safe region is determined based on data from those forward-facing sensors. The safe region describes a geographical area clear of obstacles during recent travel. Before moving outside of the current FOV, the AMD determines whether a move outside of the current FOV keeps the AMD within the safe region. For example, if a path that is outside the current FOV would result in the AMD moving outside the safe region, the AMD modifies the path until poses associated with the path result in the AMD staying within the safe region. The resulting safe path may then be used by the AMD to safely move outside the current FOV.

Abstract: An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Abstract: A method for vehicle (V) environment mapping, comprising the operations of: receiving a set of input values from a plurality of sensors, applying temporal fusion processing to the set of input values, resulting in a respective set of occupancy grid maps, applying data fusion processing to the set of occupancy grid maps, resulting in at least one fused occupancy grid map, detecting discrepancies by comparing occupancy grid maps in the set of maps, resulting in a set of detected discrepancies, processing the at least one fused occupancy grid map and outputting a fused occupancy grid map of drivable spaces. The processing operation includes the step of performing an arbitration of conflict in the at least one fused occupancy grid map. The compound fused occupancy grid map of drivable spaces is supplied (IA) to a user circuit, such as a drive assistance interface.

Abstract: A device for generating vehicle data-based boarding and alighting point information includes a time series data processor that resamples a plurality of time series data including first speed data of the vehicle based on a preset first time; a GPS data processor that resamples GPS data including second speed data of the vehicle based on a preset second time, a location data deriving device that integrates the time series data and the GPS data based on the first speed data, the second speed data, and DTW algorithm, and obtains location data of the vehicle from the integrated data; a location integrating device that integrates location information of a vehicle boarding point and an alighting point received from a public institution; and an identifier generator that generates a boarding point identifier and an alighting point identifier related to a location of the boarding point and the alighting point, respectively.

Abstract: Systems and methods for multi-modal trips. Systems and methods are provided for integrating multiple legs of a trip using different modes of transportation into a single, personalized transportation experience. In particular, systems and methods are provided for integrating multiple modes of transportation, such as an electric scooter ride and an autonomous vehicle ride, into a single trip.

Abstract: In a vehicle control system, a control unit executes a stop process by which the vehicle is parked in a prescribed stop position when it is detected that the control unit or the driver has become incapable of properly maintaining a traveling state of the vehicle, and, in the stop process, if a sidewalk or a road sign is recognized ahead of the vehicle according to a signal from an external environment recognition device, the control unit determines the stop position according to the recognized sidewalk or road sign.

Abstract: A flight control apparatus that enables a flying object to safely pass another flying object includes a detection unit configured to detect, in a predetermined range from a flying object, another flying object. A specifying unit is configured to specify a moving direction of the detected other flying object. A judging unit is configured to judge, based on the specified moving direction, whether or not passing is possible. A determination unit is configured to determine, based on a relationship between the flying object and the other flying object, content of a passing operation to be performed with respect to the other flying object. A flight control unit is configured to, if it is judged that passing is possible, control flight of the flying object and perform the passing operation according to the determined content.