The present invention provides a vehicle control apparatus capable of traveling a vehicle by automated driving, comprising a state detection unit configured to detect a state of an occupant in the vehicle, and a control unit configured to set a traveling mode of automated driving in accordance with a change in the state of the occupant detected by the state detection unit.

Embodiments of the present invention disclose an information processing method, a server, and an intelligent mobile robot, so that when the intelligent mobile robot encounters a danger, the intelligent mobile robot exchanges information with the server to achieve a purpose of escaping from a scene to a safe place. The method in the embodiments of the present invention includes: receiving, by a server, a danger alarm sent by an intelligent mobile robot, where the danger alarm is used to indicate that the intelligent mobile robot detects a dangerous event; determining, by the server, a safe position for the intelligent mobile robot, where the safe position is a position in which the dangerous event does not occur currently; and sending, by the server, an escape instruction to the intelligent mobile robot, where the escape instruction includes the safe position.

An automotive vehicle according to the present disclosure is an automotive vehicle deployed at an airport, the automotive vehicle including: an information collection unit configured to collect arrival and departure information of an aircraft which a user boards; a derivation unit configured to derive a boarding place and a boarding time for the user to board the aircraft based on the arrival and departure information pieces; a user recognition unit configured to recognize the user; a distance measurement unit configured to measure a distance between the automotive vehicle and the user; and a traveling control unit configured to control traveling of the automotive vehicle. The traveling control unit controls the automotive vehicle to travel to the boarding place by the boarding time while guiding the user and preventing the automotive vehicle and the user from being spaced apart from each other by a predetermined distance or more.

The invention relates to a system and method for navigating an autonomous driving vehicle (ADV) that utilizes an-onboard computer and/or one or more ADV control system nodes in an ADV network platform. The on-board computer receives battery monitoring and management data concerning a battery stack. The on-board computer, utilizing a battery management system, determines the current state of charge (SOC) and other information concerning the battery stack and determines if the estimated total amount of electrical power required to navigate an ADV along a generated route to reach the predetermined destination is available. In response to determining that the ADV cannot reach the predetermined destination, the on-board computer automatically initiates a dynamic routing algorithm, which utilizes artificial intelligence, to generate alternative routes in an effort to find a route that the ADV can navigate to reach the destination utilizing the current state of charge (SOC) of the battery stack.

[Problem] To achieve an optimum operation following purpose change.

[Solution] Provided is an information processing device including an action value calculation unit configured to calculate an action value that determines behavior of an operation unit, and the action value calculation unit dynamically calculates, based on an acquired purpose change factor and a plurality of first action values learned based on rewards different from each other, a second action value to be input to the operation unit. In addition, provided is an information processing device including a feedback unit configured to determine, based on an operation result of an operation unit that performs dynamic behavior based on a plurality of action values learned based on rewards different from each other, excess and insufficiency related to the action values, and control information notification related to the excess and insufficiency.

The present disclosure provides a probabilistic decision engine for autonomous vehicles. Briefly described, one embodiment comprises taking a network connection matrix (based on maps and graph theory) and a cost matrix (with entries of the cost's mean values and probability distributions) as input and generates the probability distribution of optimal routes as output. The disclosed probabilistic decision engine comprises a stochastic network standardization module, a stochastic network decomposition module and a probabilistic optimization kernel. A deterministic network reduction method is first used to derive a standard reduced network, augmented by the stochastic network reduction. The standard network is then decomposed into a series of stochastic subnetworks by using the convolution, probability density function (PDF) shifting, and PDF reshaping techniques. A pure-analytical probabilistic solver is finally used to solve the stochastic optimization problem.

An autonomous deceleration control apparatus includes a brake module that receives an input signal; and a brake control module that controls an operational state of the brake module. The brake module includes a pedal link having a preset length and provided to be rotatable within a preset range; and a pedal encoder located adjacent to the one end of the pedal link and configured to detect a rotational state of the pedal link. The brake control module includes: a driver; a movable link rotatable about a movable link shaft located at one end thereof by the driver and provided to press the pedal link downwards according to a rotational state thereof; and a driver encoder connected to the movable link and configured to provide an operational state of the driver and movable link state information on the location of the movable link according to the operational state of the driver.

An automatic driving vehicle has an automatic mode to automatically operate along a predetermined travel route in accordance with an operation schedule provided from an operation management center through communication and so as to arrive at a predetermined spot at predetermined time. In a case where the communication is normal, the automatic driving vehicle operates automatically in accordance with the operation schedule provided in the automatic mode through the communication, and in a case where abnormality occurs in the communication, the automatic mode shifts to a semiautomatic mode to operate the automatic driving vehicle in a state where a function of communicating with the operation management center is limited.

System, method and product for vehicle navigation. A method comprising obtaining a location of a vehicle and obtaining a data about the passenger in the vehicle. Based on the data, a constraint on a driving route of the vehicle is determined. The constraint is characterized in extending the driving route so as to extend a driving time to the destination to be longer than a minimal driving time from the location to the destination. A driving plan is generated based on the constraint, wherein the driving plan defining a route from the location to the destination, whereby the vehicle can be driven according to the driving plan.

The invention relates to a system and method for navigating an autonomous driving vehicle (ADV) that utilizes an-onboard computer and/or one or more ADV control system nodes in an ADV network platform. The on-board computer receives battery monitoring and management data concerning a battery stack. The on-board computer, utilizing a battery management system, determines the current state of charge (SOC) and other information concerning the battery stack and determines if the estimated total amount of electrical power required to navigate an ADV along a generated route to reach the predetermined destination is available. In response to determining that the ADV cannot reach the predetermined destination, the on-board computer automatically initiates a dynamic routing algorithm, which utilizes artificial intelligence, to generate alternative routes in an effort to find a route that the ADV can navigate to reach the destination utilizing the current state of charge (SOC) of the battery stack.