Baidu USA LLC

Future Wei Technologies, Inc.

I-Hsuan Yang

Jingao Wang

Jinghao Miao

Liyun Li

Shiyuan Fang

Liangliang Zhang

Maoter Chen

Paihan Huang

Hsien-Ting Cheng

Yaya Chu

Embodiments provide methods and apparatuses to manage hardware resource access on a mobile device comprising detecting an attempt by the first application to access the first hardware resource when the application is executing in the background and determining that there is not a policy for the first application to access the first hardware, providing a notification requesting user input thereof, and adding a new policy accordingly.

Method and apparatus for managing hardware resource access in an electronic device

A surrounding environment of an autonomous vehicle is perceived to identify one or more vehicles nearby. For each of the identified vehicles, based on a current location of the identified vehicle, vehicle-independent information is obtained to determine context surrounding the identified vehicle, where the vehicle-independent information includes vehicle surrounding information that defines physical constraints imposed on the identified vehicle. For each of the identified vehicles, one or more trajectories for the identified vehicle are predicted based at least in part on the vehicle-independent information associated with the identified vehicle. The autonomous vehicle is controlled based on the one or more predicted trajectories of the one or more identified vehicles.

Method and system to predict one or more trajectories of a vehicle based on context surrounding the vehicle

A user can issue a query about a process that has a number of stages. A stage of the process is determined using the query and location data associated with the query, and a stage prediction model. A stage learning system can select a sample of query logs for a category from a database of millions or billions of users' queries. Queries can be parsed into keywords. A category can be determined from location information associated with each query and from query keywords. Queries are aligned based on location and, optionally, keywords. TF-IDF values are computed for queries and are used to determine a difference significance between aligned, adjacent queries. If aligned, adjacent queries have a substantially difference in keywords and TF-IDF, then a conversion stage is identified. Content can be presented to the user based on the category, keywords, location, and conversion stage.

Automatic conversion stage discovery

Route segment information is received from a first autonomous vehicle over a network. The route segment information includes one or more route segments and estimated entrance times, each of the entrance times being associated with one of the route segments and representing a time the first autonomous vehicle enters the route segment. Whether the first autonomous vehicle is within a specific route segment is determined based on an entrance time associated with the specific route segment and a current location of the first autonomous vehicle. If the first autonomous vehicle is within the specific route segment, a request is sent to invite the first autonomous vehicle to join a vehicle group of one or more vehicles associated with the specific route segment. The vehicle group is one of a plurality of vehicle groups that were determined based on route segment information received from a plurality of autonomous vehicles.

Method and system to manage vehicle groups for autonomous vehicles

The disclosure relates to determining thermal insulation levels of clothing a user should wear when traveling to a destination. To do this, a thermal insulation level of clothing worn by a user and levels worn by a crowd can be analyzed from images including the user or the crowd. A thermal sensitivity bias for the user can be determined by comparing those levels for similar locations. Environment data can then be collected for the destination. A thermal insulation level of clothing worn by the crowd for the destination can be predicted based on the environment data. This level can be adjusted with the bias for the user to generate a thermal insulation level of clothing to be worn by the user at the destination. An image having clothing with that level can be displayed to recommend a style of clothing for the user to wear at the destination.

Determining thermal insulation levels of clothing to wear at a destination

Responsive to sensor data received from one or more sensors of an autonomous vehicle, one or more predicted trajectories are generated, with each of the predicted trajectories having an associated probability. One or more driving scenarios that trigger gesture recognition are identified. For each of the identified driving scenarios, one or more gestures from one or more vehicles are detected in accordance with a gesture detection protocol. One or more gestures from the autonomous vehicle are emitted for communication with the vehicles in accordance with a gesture emission protocol based on the detected gestures. The predicted trajectories are modified based on the detected gestures, the emitted gestures and the associated probabilities of the predicted trajectories. The autonomous vehicle is controlled based on the modified predicted trajectories.

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Sunnyvale, CA, United States of America

I-Hsuan Yang