An information processing apparatus is mounted in a delivery automatic driving vehicle with a monitoring device for remote monitoring. The information processing apparatus includes a controller that suppresses a monitoring function of the monitoring device when determining that a delivery person does not exist inside the automatic driving vehicle in a stopped state of the automatic driving vehicle.

A control device for a vehicle includes an upper limit value setting unit configured to set an upper limit value of an acceleration or deceleration of the vehicle, and a vehicle controller configured to control the vehicle such that the acceleration or deceleration does not exceed the upper limit value. The upper limit value setting unit is configured to change the upper limit value according to at least one predetermined condition.

Disclosed is a system for preventing drunk driving of a vehicle, the system including: an input unit through which a transfer intention to transfer a control privilege of a vehicle from a registered driver to a passenger is input; a sobriety determination unit configured to determine a current driver's inebriation state through a breathalyzer provided in the vehicle when the transfer intention is input through the input unit; a driver verification unit configured to identify personal information of the current driver seated on a driver's seat; and a control unit configured to transfer the control privilege of the vehicle to the passenger when the passenger is measured as being able to drive by the sobriety determination unit and the passenger and the current driver are identified to be the same by the driver verification unit.

An information providing device includes an acquirer configured to acquire one or more pieces of orientation information indicating orientations of one or more users, a determiner configured to determine priority item information, which is item information to be preferentially provided, based on reference information in which a specific point and item information for each item of the specific point are associated with each other, and the one or more pieces of orientation information acquired by the acquirer, and a provider configured to allow an information output device associated with at least a part of the one or more users to output the priority item information.

A technique for enabling efficient retrieval of a digital representation of personality data of a user (402) by a client device (406) from a server (404) is disclosed, wherein the digital representation of the personality data is processed at the client device (406) to provide a user-adapted service to the user (402). A method implementation of the technique is performed by the server (404) and comprises storing a neural network being trained to compute personality data of a user based on input obtained from the user (402), receiving, from the client device (406), a request for a digital representation of personality data for a user (402), and sending, to the client device (406), the requested digital representation of the personality data of the user (402), wherein the personality data of the user is computed using the neural network based on input obtained from the user (402).

A system and method for classifying a type of interaction between a human user and a mobile communication device within a defined volume, based on multiple sensors. The method may include: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on: angle of arrival, time of flight, or received intensity of radio frequency (RF) signals transmitted by the mobile communication device and received by a phone location unit located within the defined volume configured to wirelessly communicate with the mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; repeating the obtaining, to yield a time series of sensor readings; and using a computer processor to classify the type of interaction into one of many predefined types of interactions, based on the position and the time series of sensor readings.

A vehicle interlock system includes a wheelchair fixing device configured to fix a wheelchair to a vehicle, a seatbelt device having a seatbelt configured such that, an occupant seated in the wheelchair wears the seatbelt, and a control unit. The control unit is configured to limit at least one of an upper limit traveling speed and an upper limit acceleration of the vehicle or output a warning signal, or to output a warning signal while limiting at least one of the upper limit traveling speed and the upper limit acceleration of the vehicle depending on at least one of the following conditions: whether the wheelchair is fixed to the vehicle with the wheelchair fixing device; whether the occupant is wearing the seatbelt; and so forth.

A control device includes a video data acquisition unit, an orientation detection unit that determines whether a first condition that the driver faces a direction other than a traveling direction of the vehicle is met, an event detection unit, and a recording control unit that, if an event is detected, stores first video data including at least an event detection time point as event recording data.

An operation management method according to an embodiment of the present disclosure is a method, performed by an operation management apparatus, for managing operation of a plurality of vehicles for passenger transportation. The operation management method includes selecting, upon detecting an occurrence of a predetermined event, one vehicle from among the plurality of vehicles each traveling a predetermined first route, determining a second route different from the first route, and switching a route traveled by the selected vehicle from the first route to the second route.

A system for controlling an autonomous vehicle includes a memory configured to store parameters of a g-g plot defining admissible space of values of longitudinal and lateral accelerations. The g-g plot parameters define a mapping between user driving preferences and constrained control of the autonomous vehicle. The g-g plot parameters include a maximum forward acceleration, a maximum backward acceleration, a maximum lateral acceleration and a shape parameter defining profile of curves connecting maximum values of forward, backward, and lateral accelerations. The system accepts a comfort level as a feedback from a passenger of the vehicle, determines a dominant parameter corresponding to the feedback, updates the dominant parameter of the g-g plot based on the comfort level indicated in the feedback, and controls the vehicle to maintain dynamics of the vehicle within the admissible space defined by the parameters of the updated g-g plot.