Bayerische Motoren Werke Aktiengesellschaft

Yang Cao

Jilei Tian

Won Tchoi

Marko Werner

Embodiments relate to a method, a computer program and a device for controlling a route connecting a plurality of destinations in a road network. The method for controlling a route connecting a plurality of destinations in a road network comprises receiving input information. The input information comprises information about a situation with impact on the route. Furthermore, the method comprises recalculating a plurality of travel times between the plurality of destinations of the route, based on the received input information and distances between the plurality of destinations. Also, the method comprises providing output information about the recalculation, which comprises information about a dynamic change of the route.

Method, computer program, and device for controlling a route

Embodiments provide a method, a machine readable medium, a device and a vehicle for determining a route connecting a plurality of destinations in a road network, and a method, a machine readable medium and a device for training a machine learning module for determining a route connecting a plurality of destinations in a road network. The method for determining a route connecting a plurality of destinations in a road network comprises receiving input information, which comprises information on distances between the plurality of destinations in the road network. The method further comprises inputting the input information on the distances into a trained machine learning module and providing output information on the route connecting the plurality of destinations based on an output of the trained machine learning module.

Method, machine readable medium, device, and vehicle for determining a route connecting a plurality of destinations in a road network, method, machine readable medium, and device for training a machine learning module

A dialog system and intelligent personal assistant capable of semantic-understanding mapping between user intents and machine services includes an interface to receive a voice or text request from a user. Semantics of the request including at least one of entities, intent, or context are extracted from the user's request. A sequence of action features is selected based on the extracted semantics. A sequence of application programming interfaces (APIs) corresponding to the sequence of action features is then executed to generate a result. An action sequence optimizer may optimize the sequence of action features based on user configuration. The examples provide a technical solution to model a richer semantic-understanding mapping between user intents and available APIs, that will be greatly improving user experience in the spoken dialogue system, as core of personal assistant.

Dialog system capable of semantic-understanding mapping between user intents and machine services

Embodiments relate to a method, computer program and system for improving a user experience. The computer-implemented method for improving a user experience inside a vehicle comprises determining an environmental context inside the vehicle, wherein the environmental context is assigned a plurality of actions, which influences the environmental context. Further, the method comprises choosing at least one action of the plurality of actions for improving the user experience.

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Yang Cao