AT&T Intellectual Property I, LP

Beihang University

Apollo Intelligent Driving Technology (beijing) Co., Ltd.

Hailong Sun

Rittwik Jana

Bin Wei

Yih-Farn Robin Chen

Ping-Fai Yang

Daniel Leon Stern

Yue Wang

David Crawford Gibbon

Jian Zhang

Bernard S Renger

Xu Wang

Giuseppe Di Fabbrizio

Jingjing Xue

Yingnan Liu

Wenlong Rao

Shi Hu

Zijie Wang

Xudong Liu

The present disclosure provides a method and an apparatus for remotely controlling a self-driving vehicle, including: a control device receives operation state information of the vehicle to be controlled transmitted by the vehicle, and video data and/or audio data of a passenger in the vehicle; determines a first abnormal parameter of the vehicle according to the operation state information of the vehicle; determines a second abnormal parameter of an emotion of the passenger in the vehicle according to the video data and/or audio data of the passenger in the vehicle; and controls the vehicle remotely according to the first abnormal parameter and the second abnormal parameter. It is possible to avoid the situation that the passenger in the vehicle performs a wrong manipulation on the vehicle due to a large emotional fluctuation in an emergency, thus making the control of the vehicle more safe and reliable in the emergency.

Method and apparatus for remotely controlling self-driving vehicle

The invention provides a vectorized representation method of a software source code. The vectorized representation method is an AST-based neural network which is a hierarchical vector representation method comprising the following implementation steps: step 1-1, converting an original software source code into an AST at the lowest layer, and then further dividing the AST according to source code statements to acquire a smaller statement tree sequence, wherein statement trees in the statement tree sequence are different in sequence, and the statement tree sequence is consistent with an original statement sequence; step 1-2, encoding the statement trees into statement vectors e, e, . . . , eby a recursive neural encoder; step 1-3, enabling an acquired statement vector sequence to pass through a bidirectional recurrent neural network layer to extract dependency features between statements; and step 1-4, sampling multi-dimensional features of all time steps of the bidirectional recurrent neural network layer through a pooling layer to acquire a final vector representation.

Vectorized representation method of software source code

A video-on-demand (VOD) server in an Internet protocol television (IPTV) network with a network of set-top boxes includes IPTV operational data and an analysis module that selects a content item. The VOD server divides the content item into sequential chunks, divides the chunks into stripes, pre-populates set-top boxes in a peering network with at least one stripe from each chunk, receives a request for the content item, and directs each set-top box to sequentially stream its stripes. A method includes selecting a content item based upon IPTV operational data, dividing the content item into sequential chunks, dividing the chunks into stripes, pre-populating set-top boxes in a peering network with at least one stripe from each chunk, receiving a request for the content item, and directing each set-top box to sequentially stream its stripes.

Analyzing internet protocol television data to support peer-assisted video-on-demand content delivery

A method and apparatus for accessing media with a portable communication device presents media available for display to a user based on user preferences. A user can select media to be output from an external display by entering commands into the portable communications device. In addition, a second external display can be used to display a subset of the media available for display.

Portable communication interface for accessing media content

Growing community of inventors

Beijing, China

Hailong Sun