Abstract:
At least certain embodiments of the present disclosure include an environment with a framework of software code interacting with a plurality of applications to provide gesture operations in response to user inputs detected on a display of a device. A method for operating through an application programming interface (API) in this environment includes displaying a user interface that includes a respective view that is associated with a respective application of the plurality of applications. The method includes, while displaying the respective view, detecting, via the software code, a user input within the region of the touch-sensitive surface that corresponds to the respective view, and, in response, in accordance with a determination that the user input is an inadvertent user input, ignoring the user input. The determination that the user input is an inadvertent user input is made based on an inadvertent user input call transferred through the API.
Abstract:
Some embodiments of the invention provide a navigation application that allows a user to peek ahead or behind during a turn-by-turn navigation presentation that the application provides while tracking a device (e.g., a mobile device, a vehicle, etc.) traversal of a physical route. As the device traverses along the physical route, the navigation application generates a navigation presentation that shows a representation of the device on a map traversing along a virtual route that represents the physical route on the map. While providing the navigation presentation, the navigation application can receive user input to look ahead or behind along the virtual route. Based on the user input, the navigation application moves the navigation presentation to show locations on the virtual route that are ahead or behind the displayed current location of the device on the virtual route. This movement can cause the device representation to no longer be visible in the navigation presentation. Also, the virtual route often includes several turns, and the peek ahead or behind movement of the navigation presentation passes the presentation through one or more of these turns. In some embodiments, the map can be defined presented as a two-dimensional (2D) or a three-dimensional (3D) scene.
Abstract:
The embodiments described relate to techniques and systems for utilizing a portable electronic device to monitor, process, present and manage data captured by a series of sensors and location awareness technologies to provide a context aware map and navigation application. The context aware map application offers a user interface including visual and audio input and output, and provides several map modes that can change based upon context determined by data captured by a series of sensors and location awareness technologies.
Abstract:
Methods and apparatus for a map tool displaying a three-dimensional view of a map based on a three-dimensional model of the surrounding environment. The three-dimensional map view of a map may be based on a model constructed from multiple data sets, where the multiple data sets include mapping information for an overlapping area of the map displayed in the map view. For example, one data set may include two-dimensional data including object footprints, where the object footprints may be extruded into a three-dimensional object based on data from a data set composed of three-dimensional data. In this example, the three-dimensional data may include height information that corresponds to the two-dimensional object, where the height may be obtained by correlating the location of the two-dimensional object within the three-dimensional data.
Abstract:
Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user. In some embodiments, the prediction engine only relies on user-specific data stored on the device on which this engine executes. Alternatively, in other embodiments, it relies only on user-specific data stored outside of the device by external devices/servers. In still other embodiments, the prediction engine relies on user-specific data stored both by the device and by other devices/servers.
Abstract:
On a mobile device a “live” network-based query for search is performed (e.g., performed automatically) in response to a map display update or other trigger event. In some implementations, when the map display is updated (or other trigger event occurs) a network-based map service is queried to obtain information related to the current location of the mobile device. The information can be presented on the map display. In some implementations, when multiple search results matching the query are provided by the map service, a confirmation request is presented on the mobile device to allow the user to select a search result. The selected search result (e.g., a destination) can be presented on the map display. A route from the current location of the mobile device to a destination can be drawn on the map display.
Abstract:
Embodiments may include determining a navigation route between an origination and a destination; the route may span multiple portions of a map. Embodiments may also include receiving an order of priority in which to receive the multiple portions of the map; the order may be generated based on distinct levels of expected signal strength for each of the multiple portions. For instance, within the order of priority, map portions associated with areas of low signal strength may be ranked higher than areas of higher signal strength. Embodiments may also include acquiring at least some of the portions of the map according to the order of priority, and generating a map display comprising the multiple portions of the map. For instance, map portions associated with areas of poor reception may be downloaded first whereas map portions associated with strong signal strength may be downloaded on-the-fly during route navigation.
Abstract:
Some embodiments provide a device that automatically orients and displays a map of a region according to the natural viewing orientation of the map. In some embodiments, the device examines data associated with the map to determine whether it can identify a natural viewing orientation of the map that differs from the geographic orientation of the map. When the device is able to identify such a natural viewing orientation, it displays the map according to this natural viewing orientation instead of the geographic orientation of the map. On the other hand, when the device is not able to identify a natural viewing orientation that differs from the geographic orientation, the device displays the map according to its geographic orientation. In some embodiments, the geographic orientation of the map is north-up orientation (where north is up (e.g., top center of the page), south is down, west is left, and east is right). In other embodiments, the geographic orientation of the map can be another orientation that is set by one of the geographic directions, such as south-up map orientation, where south is up, north is down, east is left and west is right.
Abstract:
A mobile computing device can be used to locate a vehicle parking location. In particular, the mobile device can automatically identify when a vehicle in which the mobile device is located has entered into a parked state. The mobile device can determine that the vehicle is in a parked state by analyzing one or more parameters that indicate a parked state or a transit state. The location of the mobile device at a time corresponding to when the vehicle is identified as being parked can be associated with an identifier for the current parking location.
Abstract:
Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user. In some embodiments, the prediction engine only relies on user-specific data stored on the device on which this engine executes. Alternatively, in other embodiments, it relies only on user-specific data stored outside of the device by external devices/servers. In still other embodiments, the prediction engine relies on user-specific data stored both by the device and by other devices/servers.