Abstract: This disclosure provides systems and methods for controlling a vehicle. The method comprises receiving data from a set of sensors, wherein the data represents objects or obstacles in an environment of the autonomous vehicle; identifying objects or obstacles from the received data; determining multiple sets of attributes of the objects or obstacles, wherein each set of attributes of the objects or obstacles are determined based on data received by an individual sensor; determining a candidate trajectory for the autonomous vehicle based on the multiple sets of attributes of the objects or obstacles; and controlling the autonomous vehicle according to the candidate trajectory.

Abstract: This disclosure provides systems and methods for path planning by a planner of an autonomous vehicle. The method may include receiving by the planner perception data from a perception module, wherein the perception data comprises tracking or predicted object data associated with objects or obstacles in an environment of the autonomous vehicle, and wherein the tracking or predicted object data are determined based on high recall detection data and high precision detection data, generating by the planner a trajectory for controlling the autonomous vehicle based on the perception data received from the perception module, and transmitting to a controller of the autonomous vehicle the trajectory such that the autonomous vehicle is navigated by the controller to a destination.

Abstract: This disclosure provides systems and methods for detecting and tracking objects or obstacles in an environment of an autonomous vehicle. The method may include receiving data from a set of sensors, wherein the data represents objects or obstacles in an environment of the autonomous vehicle; and using a processor: generating high precision detection data based on the received data; identifying, from the high precision detection data, a set of objects that are classifiable by at least one known classifier; generating high recall detection data based on the received data; identifying from the high recall detection data a set of obstacles; and performing an operation on the high precision detection data of the objects and the high recall detection data of the obstacles, based on a status of the autonomous vehicle or based on one or more characteristics of the objects or the obstacles.

Abstract: This disclosure provides systems and methods for controlling a vehicle based on a combination of high precision detection and high recall detection. The disclosed systems and methods can efficiently generate trajectories by reducing duplicate detection or duplicate calculation of objects or obstacles of common and known object types and objects or obstacles without class identification.

Abstract: This disclosure provides systems and methods for controlling a vehicle. The method comprises receiving data from a set of sensors, wherein the data represents objects or obstacles in an environment of the autonomous vehicle; identifying objects or obstacles from the received data; determining multiple sets of attributes of the objects or obstacles, wherein each set of attributes of the objects or obstacles are determined based on data received by an individual sensor; determining a candidate trajectory for the autonomous vehicle based on the multiple sets of attributes of the objects or obstacles; and controlling the autonomous vehicle according to the candidate trajectory.

Abstract: This disclosure provides systems and methods for controlling a vehicle. The method comprises receiving data from a set of sensors, wherein the data represents objects or obstacles in an environment of the autonomous vehicle; determining attributes of each of the objects or obstacles based on the received data from the set of sensors; integrating the attributes of the each of the objects or obstacles; identifying objects or obstacles based on the integrated attributes; determining a candidate trajectory for the autonomous vehicle to avoid the objects or obstacles; and controlling the autonomous vehicle according to the candidate trajectory.

Abstract: This disclosure provides methods and systems for dynamically detecting and tracking objects in an environment of an autonomous vehicle. In some embodiments, the method comprises: receiving image data from sensors of the autonomous vehicle, the image data comprising a plurality of images representative of objects in a field of view of the autonomous vehicle; detecting the objects in the plurality of images through an object detector; generating image embeddings for the objects detected in the plurality of images; determining similarity scores of the image embeddings of the objects that are detected in images received from two or more different sensors; identifying the objects that are detected in the images received from the two or more different sensors as a candidate object for tracking, if the objects have a similarity score of the image embeddings equal to or greater than a threshold value; and initializing a track for the candidate object.

Abstract: Systems and methods are provided for filtering atmospheric conditions from LiDAR point clouds. The method includes generating, using a LiDAR system, at least one point cloud, wherein the LiDAR system includes a processor. The method further includes, using the processor, identifying and isolating one or more ground points within a point cloud of the at least one point cloud, wherein the one or more ground points indicate a ground portion within an environment of the point cloud, filtering out the ground portion from the point cloud, generating an initial processed point cloud, identifying and isolating one or more atmospheric condition points within the initial processed point cloud, wherein the one or more atmospheric condition points indicate one or more atmospheric conditions within an environment of the processed point cloud, and filtering out the atmospheric condition points from the initial processed point cloud, generating a final processed point cloud.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for presenting non-suggested content items to a user of a social network account are described. In one aspect, a method includes storing social network account data indicating preferred categories of content and non-preferred categories of content associated with a particular social network account. Suggested content items corresponding to the preferred categories of content are identified, and non-suggested content items corresponding to the non-preferred categories of content are identified. A graphical user interface is provided for presentation to a user of the particular social network account. The graphical user interface presents information about the suggested content items and information about the non-suggested content items. Feedback data is received based on a user interaction in response to presentation of the information about the non-suggested content items.

Abstract: In general, the subject matter described in this specification can be embodied in methods, systems, and program products for determining if a web application is cached. A source web application that is executed by a web browser that is installed on a computing device determines that the web browser is to navigate to a target web application. The source web application determines whether resources for the target web application are cached at the computing device. The source web application performs actions to request resources for the target web application based on the determination whether resources for the target web application are cached, wherein the actions comprise requesting resources for the target web application using a first address if the target web application is determined to be cached and using a second address if the target web application is determined to not be cached.

Abstract: A system and a computer-implemented methods for email management are disclosed. The method includes storing messages for electronic mail accounts provided by remote electronic mail server systems. The method further includes determining that the remote electronic mail server systems each have a different hostname than the others of the remote electronic mail server systems. The method further includes displaying messages from a first one of the electronic mail accounts and displaying a hostname of a first remote electronic mail server system providing the first one of the electronic mail accounts. The method further includes receiving a request to view messages from a second one of the electronic mail accounts. The method further includes displaying messages from the second one of the electronic mail accounts and displaying a hostname of a second remote electronic mail server system providing the second one of the electronic mail accounts.

Abstract: The methods track abnormal events on mobile client devices, such as web application crashes, and use that information to associate the abnormal events with device characteristics. A first method executes on mobile client devices. When a web application starts, the method looks for a crash indicator cookie in persistent memory. If the cookie does not exist, the method creates and stores it. If the cookie already exists, the method collects information about the client device, such as device type, browser type, and operating system, and sends the information to a web server. The web application deletes the cookie when the application terminates normally. A second method executes on a web server. This method receives information from client devices relating to abnormal events for web applications. The information includes device characteristics of each client device. This method stores the information and associates a pattern of abnormal events with device characteristics.

Abstract: A server system receives a first request for a data item from a web application on a client device, wherein the first request includes an identifier of the data item. In response to the first request, the server system calculates a first checksum of the data item and sends the data item and the first checksum to the web application, for storage in the local database. The server system receives a second request for the data item from the web application, calculates a second checksum of the data item and compares the first and second checksums. The server system, determines that the data item has been updated by comparing the first checksum to the second checksum; and in response to determining that the data item has been updated, the server system a reply to the web application a indicating that the data item has been updated.

Abstract: In general, the subject matter described in this specification can be embodied in methods, systems, and program products for determining if a web application is cached. A source web application that is executed by a web browser that is installed on a computing device determines that the web browser is to navigate to a target web application. The source web application determines whether resources for the target web application are cached at the computing device. The source web application performs actions to request resources for the target web application based on the determination whether resources for the target web application are cached, wherein the actions comprise requesting resources for the target web application using a first address if the target web application is determined to be cached and using a second address if the target web application is determined to not be cached.

Abstract: A server system receives a first request for a data item from a web application on a client device, wherein the first request includes an identifier of the data item. In response to the first request, the server system calculates a first checksum of the data item and sends the data item and the first checksum to the web application, for storage in the local database. The server system receives a second request for the data item from the web application, calculates a second checksum of the data item and compares the first and second checksums. The server system, determines that the data item has been updated by comparing the first checksum to the second checksum; and in response to determining that the data item has been updated, the server system a reply to the web application a indicating that the data item has been updated.

Abstract: The methods track abnormal events on mobile client devices, such as web application crashes, and use that information to associate the abnormal events with device characteristics. A first method executes on mobile client devices. When a web application starts, the method looks for a crash indicator cookie in persistent memory. If the cookie does not exist, the method creates and stores it. If the cookie already exists, the method collects information about the client device, such as device type, browser type, and operating system, and sends the information to a web server. The web application deletes the cookie when the application terminates normally. A second method executes on a web server. This method receives information from client devices relating to abnormal events for web applications. The information includes device characteristics of each client device. This method stores the information and associates a pattern of abnormal events with device characteristics.