Bayerische Motoren Werke Aktiengesellschaft

B Ayerische M Otoren W Erke a Ktiengesellschaft

Qing Li

Jilei Tian

Yang Cao

Alvin Chin

A method for smart parking a connected vehicle is disclosed. The method determines a destination of a user's vehicle based on the user's input or historic travel data of the user. The method receives information on available parking spots in a predefined area near the user's destination based on a parking database. The method receives an input to reserve a desired parking spot among the available parking spots. The method initiates an online check-in of the reserved parking spot in the parking database.

Method, device, cloud service, system, and computer program for smart parking a connected vehicle

A method for smartly managing a plurality of potential travel destinations of a user is provided. The method includes determining a plurality of similarities between different pairs of the plurality of potential travel destinations. Further, the method includes weighting the plurality of similarities using contextual information related to the user, and clustering part of the plurality of potential travel destinations based on the plurality of weighted similarities.

Method and apparatus for smartly managing a plurality of potential travel destinations of a user

The present disclosure relates to predicting a destination of a user's current travel path. Real-time travel data associated with the current travel path is generated, wherein the real-time travel data comprises the user's current location. A plurality of potential destinations of the current travel path are determined based on historic travel data associated with one or more historic travel paths of the user. At least one destination of the current travel path is predicted from the plurality of potential destinations based on tracking a distance from the user's current location to each of the plurality of potential destinations.

Methods and apparatuses for predicting a destination of a user's current travel path

A fuel consumption prediction method and apparatus is provided. A respective historic fuel consumption is extracted from historic travel data for at least one historic travel path of a vehicle. At least one historic fuel-related quantity influencing the respective historic fuel consumption is extracted from the historic travel data for each historic travel path. Model parameters of a machine learning model for predicting fuel consumption is adjusted based on the extracted respective historic fuel consumption and the at least one historic fuel-related quantity for each historic travel path. The fuel consumption for a planned trip is predicted using the machine learning model with the adjusted model parameters.

Growing community of inventors

Chicago, IL, United States of America

Qing Li