A remote driving taxi system provides a mobility service using remote driving taxis that are driven by remote drivers. Management information indicates assignment states between the remote driving taxis and the remote drivers. The remote driving taxi system executes an assignment process based on the management information, in response to a request from a user. Specifically, the remote driving taxi system selects one of unassigned taxis to each of which the remote driver has not been assigned, as a first remote driving taxi that provides the service to the user. Further, the remote driving taxi system selects one of remote drivers each of which has not been assigned to the remote driving taxi, as a first remote driver that provides the service to the user. Then, the remote driving taxi system assigns the first remote driver to the first remote driving taxi.

Deployed drones are managed. For instance, a first drone detects whether the first drone is in communication with a command center via a first communication network to determine a configuration parameter of a first message to broadcast discovery information associated with the first drone. In response to the first drone being in communication with the command center via the first communication network, the first drone broadcasts the first message configured with a first value for the configuration parameter. Or, in response to the first drone not being in communication with the command center via the first communication network, the first drone broadcasts the first message configured with a second value for the configuration parameter different from the first value.

A charge control system includes a lithium battery configured to provide lithium battery power to a set of electrical loads, a user signaling device, and control circuitry coupled with the lithium battery and the user signaling device. The control circuitry is operative to: (A) detect availability of charge from an external charger, (B) in response to detection of the availability of charge from the external charger and prior to controlling the external charger to adjust the amount of charge stored by the lithium battery, perform a set of pre-charging assessment operations, and (C) based on the set of pre-charging assessment operations, provide a user notification via the user signaling device, the user notification indicating whether the lithium battery is properly setup for charge adjustment. When the user signaling device generates the user notification, the user is informed that the utility vehicle is properly connected to the external charger.

A central management server according to an embodiment of the present disclosure includes: a selection module for selecting an unmanned aircraft and an unmanned robot to monitor a management target area; and a control module for transmitting a monitoring execution command to the selected unmanned aircraft and the unmanned robot, wherein, according to the monitoring execution command, the unmanned robot moves along a preset ground guard route and monitors the management target area on the ground, and the unmanned aircraft flies along a preset air guard route and monitors the management target area from above. When it may be determined that an event has occurred during monitoring, at least one of the unmanned aircraft and the unmanned robot may be configured to transmit event information including location information of a point at which the event has occurred to the control module.

An information processing device includes a controller. The controller is configured to generate, when information related to a request to use a cabin unit is acquired from a terminal of a first user who intends an activity in the cabin unit rather than traveling by the cabin unit, a command for causing a traveling unit to pick up the first user. The traveling unit is connected to and carrying a predetermined cabin unit associated with the activity of the first user. The controller is configured to generate, to the traveling unit connected to the predetermined cabin unit where a predetermined number of the first users or more is riding, a command for placing the predetermined cabin unit at a predetermined location.

A teleoperations system may be used to modify elements in the mapping data used by an autonomous vehicle to cause the autonomous vehicle to control its trajectory based on the modified elements. In addition, in some instances, a teleoperations system may be used to generate virtual paths of travel for an autonomous vehicle based upon teleoperations system virtual path suggestion inputs.

In a vehicle remote instruction system, a remote commander issues a remote instruction relating to travel of an autonomous driving vehicle based on sensor information from an external sensor that detects an external environment of the autonomous driving vehicle. The vehicle remote instruction system sets a range of information to be transmitted to the remote commander among the sensor information detected by the external sensor, as a limited information range, based on the external situation or an external situation obtained based on map information and a trajectory of the autonomous driving vehicle.

According to a technical aspect of the invention, there is provided a multiple unmanned aerial vehicles navigation optimization method is performed at a ground base station which operates in conjunction with unmanned aerial vehicles-base stations which are driven by a battery to move and cover a given trajectory point set, the multiple unmanned aerial vehicles navigation optimization method including: calculating an age-of-information metric by receiving an information update from the unmanned aerial vehicles-base stations through communication, when the ground base station is present within a transmission range of the unmanned aerial vehicles-base stations; setting conditions of a trajectory, energy efficiency, and age of information of each of the unmanned aerial vehicles-base stations; and executing Q-learning for finding a trajectory path policy of each of the unmanned aerial vehicles-base stations, so as to maximize total energy efficiency of an unmanned aerial vehicles-base station relay network to which the energy efficiency and the age of information are applied. According to the invention, the following effects are obtained. Age of information (AoI) that is a new matrix used to measure up-do-dateness of data is set, an edge computing environment for a remote cloud environment is provided by using the AoI, and a computing-oriented communications application can be executed by using the edge computing environment.

The present disclosure is directed to using anomaly data detected in traffic data to efficiently initiate remote assistance sessions. In particular, a computing system can receive, from a computing device associated with a human-driven vehicle, travel data for the human-driven vehicle. The computer system can identify a navigation anomaly associated with the human-driven vehicle based on the travel data. The computer system can generate, based on the identified navigation anomaly, an anomaly entry for storage in an anomaly database, the anomaly entry comprising geofence data describing a geographic area associated with the navigation anomaly. The computer system can determine, based on location data received from an autonomous vehicle and the geofence data, that the autonomous vehicle is entering the geographic area associated with the navigation anomaly. The computer system can initiate a remote assistance session with the autonomous vehicle.

A matching system that matches a first vehicle requiring substitution when being at least either loaded into or unloaded from a parking place and a remote driver driving the first vehicle as a substitute through remote operation includes a terminal and a server. The terminal transmits substitution request information to the server. The server that has received the request information transmits waiting time information to the terminal. The terminal notifies a user or a staff of the received waiting time information, accepts a waiting time information approval or additional fee payment instructions, and settles the additional fee through cooperation with the server, upon receiving the payment instructions. The server changes the turn of the first vehicle in a queue for the remote operation service such that the first vehicle is prioritized more than a second vehicle that has not paid the additional fee, upon completing the additional fee settlement.