Baidu USA LLC

Google Inc.

Baidu.com Times Technology (beijing) Co. Ltd.

National Instruments Corporation

Theravance, Inc.

Other

Nokia Corporation

Advanced Medicine, Inc.

Nokia Technologies Oy

Core Wireless Licensing S.a.r.l.

Guang Yu Yang

Jingao Wang

Fan Zhu

Qi Kong

Dong Li

Yifei Jiang

Xiang Yu

Qi Luo

Sen Hu

Tushar Udeshi

Jiangtao Hu

Andrew Robert Kirmse

Emil Constantin Praun

Dale Kris Hawkins

Keir Banks Mierle

Pablo Bellver

Liyun Li

James Anthony Guggemos

Jiaming Tao

Yuchang Pan

Zhenguang Zhu

Gokay Baris Gultekin

Tom Carl Stamm

Jeffrey N Correll

J Kevin Judice

Jacob Kornerup

Li Zhuang

Kaushik Ravindran

Bill Connor

Paul Ross Fatheree

YongQi Mu

Martin Sheringham Linsell

Michael Robert Leadbetter

Yan Zhu

Sean Gary Trapp

Shuang Wu

Rhishikesh Limaye

Guoqiang Wang

Michael J Trimborn

Bernice M T Lam

Zhuang Li

Jiarui He

Yu Long Cao

Thomas Carl Stamm

Jun Zhan

Yiqing Yang

Siyang Yu

Arkadeb Ghosal

Xuan Liu

Zhang Li

Sadia B Malik

Hugo A Andrade

Haoyang Fan

Wenli Yang

Zhongpu Xia

Xiaoxin Fu

Hongye Li

Charles E Crain, Ii

Chunming Zhao

Liangliang Zhang

David Singleton

Brian Edmond Brewington

Zhigang Liu

Ian C Wong

Weicheng Zhu

Du Li

Steve Okamoto

Youling Zou

Gregory Michael Blevins

Lei Ma

Erez Louider

Jinghao Miao

Newton G Petersen

Yajia Zhang

Peter Boda

Donald E Schmidt, Jr

John R Allen

Trung N Tran

Deping Xie

Jingtao Hu

A computing system is described that obtains, based at least in part on information included in at least one previous communication associated with a user of a computing device, an indication of a future location and a future time and event information associated with the future location and the future time. The computing system obtains a duration of time for the user to travel from a current location of the computing device to the future location, and, based at least in part on the duration of time, obtains a departure time at which the user is predicted to need to depart from the current location in order to arrive at the future location by an arrival time based on the event. The computing system outputs, for transmission to the computing device, an indication associated with the event and including information indicative of the departure time.

Presenting information for a current location or time

According to one embodiment, a first phrase having one or more keywords is received to be added to a phrase blacklist, where the first phrase has been determined to be related to unwanted content. An analysis is performed on the keywords of the first phrase to identifying a set of one or more related phrases that are related to the first phrase. The first phrase and the set of related phrases are added in the phrase blacklist. The phrase blacklist contains a plurality of phrases that have been determined to be related to unwanted content. The phrase blacklist is utilized to prevent a content item from appearing in a search result, in response to a search query having a phrase matching at least one of the phrases in the phrase backlist.

Method and system for generating phrase blacklist to prevent certain content from appearing in a search result in response to search queries

In response to a search query received from a client, a content item is identified from a content database based on one or more keywords associated with the search query. In addition, a search is performed in an image store to identify a list of image candidates based on one or more keywords associated with the search query. An image is selected from the list of image candidates using an image selection algorithm. Metadata associated with the content provider is inscribed onto the selected image to generate a customized image. The customized image is integrated with the content item to generate a composite content item such as a poster. As a result, the content represented by the composite content item is closely tied to the content provider. The composite content item is then transmitted to the client.

Method and system for dynamically overlay content provider information on images matched with content items in response to search queries

A social driving style learning framework or system for autonomous vehicles is utilized, which can dynamically learn the social driving styles from surrounding vehicles and adopt the driving style as needed. Each of the autonomous vehicles within a particular driving area is equipped with the driving style learning system to perceive the driving behaviors of the surrounding vehicles to derive a set of driving style elements. Each autonomous vehicle transmits the driving style elements to a centralized remote server. The server aggregates the driving style elements collected from the autonomous vehicles to determine a driving style corresponding to that particular driving area. The server transmits the driving style back to each of the autonomous vehicles. The autonomous vehicles can then decide whether to adopt the driving style, for example, to follow the traffic flow with the rest of the vehicles nearby.

Group driving style learning framework for autonomous vehicles

According to one embodiment, a first image identifier (ID) is received identifying a first of a first set of images, where the first image is currently displayed at a mobile device of a user. A number of additional images the user likely accesses from the first image in sequence is determined based on user interactions of a current browsing session and user interactions of a prior browsing session associated with the user. A second set of images are identified based on the number of additional images the user likely accesses. A sequential order is determined based on rankings of the images in the second set in view of a set of image selection rules. The second set of images is transmitted to the mobile device to be displayed on the mobile device in sequence one at a time.

Method for processing and rendering feed-like based images for mobile devices

A set of driving scenarios are determined for different types of vehicles. Each driving scenario corresponds to a specific movement of a particular type of autonomous vehicles. For each of the driving scenarios of each type of autonomous vehicles, a set of driving statistics is obtained, including driving parameters used to control and drive the vehicle, a driving condition at the point in time, and a sideslip caused by the driving parameters and the driving condition under the driving scenario. A driving scenario/sideslip mapping table or database is constructed. The scenario/sideslip mapping table includes a number of mapping entries. Each mapping entry maps a particular driving scenario to a sideslip that is calculated based on the driving statistics. The scenario/sideslip mapping table is utilized subsequently to predict the sideslip under the similar driving environment, such that the driving planning and control can be compensated.

Sideslip compensated control method for autonomous vehicles

In one embodiment, systems and methods are disclosed for a planning-driven framework for an driving vehicle (ADV) driving decision system. Driving decisions are classified into at least seven categories, including: conservative decision, aggressive decision, conservative parameters, aggressive parameters, early decision, late decision, and non-decision problem. Using the outputs of an ADV decision planning module, an ADV driving decision problem is identified, categorized, and diagnosed. A local driving decision improvement can be determined and executed in a short time frame on the ADV. For a long term solution, if needed, the driving decision problem can be uploaded to an analytics server. The driving decision problems from a large plurality of ADVs can be aggregated and analyzed for improving the ADV decisions system for all ADVs.

Planning feedback based decision improvement system for autonomous driving vehicle

According to one embodiment, in response to a search query received from a client, a search is performed in a content database to identify a list of one or more content items based on one or more keywords of the search query. A first search is performed in an image store to identify a first set of one or more images using a first image searching method. A second search is performed in the image store to identify a second set of one or more images using a second image searching method that is different than the first image searching method. A search result is transmitted to the client, the search result having at least a portion of the content items to the client. Each content item is associated with one of the images selected from the first set of images or the second set of images.

Method and system for multi-dimensional image matching with content in response to a search query

An autonomous driving system includes a number of sensors and a number of autonomous driving modules. The autonomous driving system further includes a global store to store data generated and used by processing modules such as sensors and/or autonomous driving modules. The autonomous driving system further includes a task scheduler coupled to the sensors, the autonomous driving modules, and the global store. In response to output data generated by any one or more of processing modules, the task scheduler stores the output data in the global store. In response to a request from any of the processing modules for processing data, the task scheduler provides input data stored in the global store to the processing module. The task scheduler is executed in a single thread that is responsible for managing data stored in the global store and dispatching tasks to be performed by the processing modules.

Centralized scheduling system for operating autonomous driving vehicles

An event queue is maintained to store IO events generated from a number of sensors and timer events generated for a number of autonomous driving modules. For each of the events pending in the event queue, in response to determining that the event is an IO event, the data associated with the IO event is stored in a data structure associated with the sensor in a global store. In response to determining that the event is a timer event, a worker thread associated with the timer event is launched. The worker thread executes one of the autonomous driving modules triggered or initiated the timer event. Input data is retrieved from the global store and provided to the worker thread to allow the worker thread to process the input data.

Centralized scheduling system using event loop for operating autonomous driving vehicles

In response to sensor data received from sensors mounted on an autonomous vehicle, a surrounding environment is perceived based on the sensor data. The surrounding environment includes multiple sub-environments. For each of the sub-environments, one of a plurality of driving scenario handlers associated with the sub-environment is identified, each driving scenario handler corresponding to one of a plurality of driving scenarios. The identified driving scenario handler is invoked to determine an individual driving condition within the corresponding sub-environment. An overall driving condition for the surrounding environment is determined based on the individual driving conditions provided by the identified driving scenario handlers. A route segment is planned based on the overall driving condition of the surrounding environment, the route segment being one of a plurality of route segments associated with a route. The autonomous vehicle is controlled and driven based on the planned route segment.

Method and system to construct surrounding environment for autonomous vehicles to make driving decisions

In one embodiment, a steering control delay is measured, where the steering delay represents the delay between the time of issuing a steering control command and the time of a response from one or more wheels of an autonomous vehicle. A speed control delay is measured between the time of issuing a speed control command and the time of a response from one or more wheels of the autonomous vehicle or the time of supplying pressure to the gas pedal or brake pedal. In response to a given route subsequently, an overall system delay is determined based on the steering control delay and the speed control delay using a predetermined algorithm. Planning and control data is generated in view of the system delay for operating the autonomous vehicle.

System delay estimation method for autonomous vehicle control

Described is a data integration technique and system for providing data in response to a request. The data integration system may overcome the limits of a fixed scheduling system by implementing a service dependency graph (SDG). In particular, the data integration system may represent the SDG as a directed acyclic graph (DAG). Accordingly, the system may leverage the nature of DAGs in order to derive an efficient topological ordering for calling one or more services. Thus, the data integration system may retrieve and compile data in an efficient and scalable manner.

Managing complex service dependencies in a data integration system

A global store is maintained to store a number of data structures. Each data structure includes a number of entries and each entry stores data of at least one event in a chronological order. Each data structure is associated with at least one sensor or an autonomous driving module of an autonomous driving vehicle. When a first event associated with a first autonomous driving module is received, where the first event includes a first topic ID, the first topic ID is hashed to identify a first data structure corresponding to the first event. A pointer pointing to a head of the first data structure is passed to the first autonomous driving module to allow the first autonomous driving module to process data associated with the first event.

Centralized scheduling system using global store for operating autonomous driving vehicles

Growing community of inventors

Wesley Chapel, FL, United States of America

Guang Yu Yang