Abstract: A processor is configured to execute instructions stored in a memory to determine, in response to identifying vehicle operational scenarios of a scene, an action for controlling the AV, where the action is from a selected decision component that determined the action based on level of certainty associated with a state factor; generate an explanation as to why the action was selected, such that the explanation includes respective descriptors of the action, the selected decision component, and the state factor; and display the explanation in a graphical view that includes a first graphical indicator of a world object of the selected decision component, a second graphical indicator describing the state factor, and a third graphical indicator describing the action.

Abstract: An apparatus for remote support of autonomous operation of a vehicle includes a processor that is configured to perform a method including receiving, from a vehicle traversing a driving route from a start point to an end point at a destination, an assistance request signal identifying an inability of the vehicle at the destination to reach the end point, generating a first map display including a representation of a geographical area and the vehicle within the geographical area, receiving, from the vehicle, sensor data from one or more sensing devices of the vehicle, generating a remote support interface including the first map display and the sensor data, and transmitting instruction data to the vehicle that includes an alternative end point at the destination responsive to an input signal provided to the remote support interface.

Abstract: A method of exception handing for an autonomous vehicle (AV) includes identifying an exception situation; identifying relevant sensors for the exception situation; identifying relevant tools to the exception situation, the relevant tools usable by a tele-operator to resolve the exception situation; and presenting, on a display of the tele-operator, data from the relevant sensors and the relevant tools.

Abstract: A processor is configured to execute instructions stored in a memory to determine, in response to identifying vehicle operational scenarios of a scene, an action for controlling the AV, where the action is from a selected decision component that determined the action based on level of certainty associated with a state factor; generate an explanation as to why the action was selected, such that the explanation includes respective descriptors of the action, the selected decision component, and the state factor; and display the explanation in a graphical view that includes a first graphical indicator of a world object of the selected decision component, a second graphical indicator describing the state factor, and a third graphical indicator describing the action.

Abstract: An apparatus for remote support of autonomous operation of a vehicle includes a processor that is configured to perform a method including receiving, from a vehicle traversing a driving route from a start point to an end point at a destination, an assistance request signal identifying an inability of the vehicle at the destination to reach the end point, generating a first map display including a representation of a geographical area and the vehicle within the geographical area, receiving, from the vehicle, sensor data from one or more sensing devices of the vehicle, generating a remote support interface including the first map display and the sensor data, and transmitting instruction data to the vehicle that includes an alternative end point at the destination responsive to an input signal provided to the remote support interface.

Abstract: A method of exception handing for an autonomous vehicle (AV) includes identifying an exception situation; identifying relevant sensors for the exception situation; identifying relevant tools to the exception situation, the relevant tools usable by a tele-operator to resolve the exception situation; and presenting, on a display of the tele-operator, data from the relevant sensors and the relevant tools.

Abstract: A method and apparatus can ascertain a location of a personal portable wireless communication device. Movement of the personal portable wireless communication device can be sensed using a plurality of movement sensors on the personal portable wireless communication device. Wireless network signal strengths can be measured by the personal portable wireless communication device. A location of the personal portable wireless communication device can be ascertained based on the sensed movement of the personal portable wireless communication device and the measured wireless network signal strengths through Bayesian filtering.

Abstract: Implementations relate to systems and methods for generating compensated speed values for a Doppler-enabled device. A portable wireless device can contain a GPS navigation engine (110) to capture position data (120) and Doppler speed data (118) from positioning satellites. The device can also generate position-based speed values from successive position readings and time intervals, to determine the current speed independently of the Doppler-based speed values. During degraded signal conditions, the Doppler-based speed values can drop to invalid levels. The device incorporates a combiner module (450) which compares the position-based and Doppler-based speed values and performs combination operations on those quantities to produce a compensated speed value (490). By selecting the maximum or otherwise combining those values, extreme excursions in speed values are avoided and accuracy promoted.

Abstract: Systems and methods for speed estimation based on stride data using predictive modeling relate to portable wireless devices (202) that contain GPS or other location resources to generate position and speed data. The device (202) also incorporates an accelerometer (212) or other motion sensor. When GPS signals are interrupted, an estimation module (216) and associated logic generates a speed estimate based solely on stride frequency data from the accelerometer (212). Unlike conventional estimators, the estimation module (216) operates on a non-deterministic basis, generating an estimated speed using a joint probability distribution derived from previous speed and stride data captured while positioning signals are available. The estimation module (216) can continue to operate when GPS signals are available, and either filter the GPS speed measures for spurious signals, or further train the estimation module (216) with new position data.

Abstract: A method uses a computing device that includes a first processor in a first, inactive state operatively coupled to a second processor in an active state. While the first processor is in the first state (301) the second processor uses sensors to determine (303) that a first condition occurred. In response to determining that the first condition has occurred, the first processor initializes (305) to a second, active state. If the first or second processor determines (311) that a second condition has occurred within a given time period (307 and 309) after the first condition occurred, the first processor performs (315) a first action such as launching a software application, capturing a digital photograph, or placing a phone call.

Abstract: A method and apparatus can ascertain a location of a personal portable wireless communication device. Movement of the personal portable wireless communication device can be sensed using a plurality of movement sensors on the personal portable wireless communication device. Wireless network signal strengths can be measured by the personal portable wireless communication device. A location of the personal portable wireless communication device can be ascertained based on the sensed movement of the personal portable wireless communication device and the measured wireless network signal strengths through Bayesian filtering.

Abstract: A method (100) and apparatus (900) for determining displacement from acceleration data is disclosed. The method (100) comprises partitioning (106), for an axis of acceleration, filtered acceleration data into a sequence of segments with at least one positive acceleration time segment and at least one negative acceleration time segment. The method (100) further comprises force fitting (118), by a processor (910), each positive acceleration time segment and an adjacent negative acceleration time segment into a model positive and negative acceleration pair curve such that a cumulative velocity value of the model positive and negative acceleration pair curves is equal to zero. Finally, the method (100) double integrates (120) the model positive and negative acceleration pair curves to obtain the displacement corresponding to the acceleration data.

Abstract: A method uses a computing device that includes a first processor in a first, inactive state operatively coupled to a second processor in an active state. While the first processor is in the first state (301) the second processor uses sensors to determine (303) that a first condition occurred. In response to determining that the first condition has occurred, the first processor initializes (305) to a second, active state. If the first or second processor determines (311) that a second condition has occurred within a given time period (307 and 309) after the first condition occurred, the first processor performs (315) a first action such as launching a software application, capturing a digital photograph, or placing a phone call.

Abstract: A method uses a computing device that includes a first processor in a first, inactive state operatively coupled to a second processor in an active state. While the first processor is in the first state (301) the second processor uses sensors to determine (303) that a first condition occurred. In response to determining that the first condition has occurred, the first processor initializes (305) to a second, active state. If the first or second processor determines (311) that a second condition has occurred within a given time period (307 and 309) after the first condition occurred, the first processor performs (315) a first action such as launching a software application, capturing a digital photograph, or placing a phone call.

Abstract: Systems and methods for speed estimation based on stride data using predictive modeling relate to portable wireless devices (202) that contain GPS or other location resources to generate position and speed data. The device (202) also incorporates an accelerometer (212) or other motion sensor. When GPS signals are interrupted, an estimation module (216) and associated logic generates a speed estimate based solely on stride frequency data from the accelerometer (212). Unlike conventional estimators, the estimation module (216) operates on a non-deterministic basis, generating an estimated speed using a joint probability distribution derived from previous speed and stride data captured while positioning signals are available. The estimation module (216) can continue to operate when GPS signals are available, and either filter the GPS speed measures for spurious signals, or further train the estimation module (216) with new position data.

Abstract: A pedometer or other stride-detection device (304) can record the number of strides, and the frequencies of those strides, during a running or other session using a detector (306). The device (304) can report an estimated total elapsed distance (318) at the end of the session, based on the number and estimated lengths of each stride. The reported distance can be calculated using estimates for stride lengths at various frequencies based on a user profile (210), as well as a correction value table (308) and a frequency count table (202). At the end of each session, a corrected distance can be received by user input based on a treadmill display, or other means. A frequency-based correction factor can be updated based on an error ratio of the corrected and reported distances, which can be limited by a correction factor limit and distributed based on a stride frequency probability distribution.

Abstract: Implementations relate to systems and methods for generating compensated speed values for a Doppler-enabled device. A portable wireless device can contain a GPS navigation engine (110) to capture position data (120) and Doppler speed data (118) from positioning satellites. The device can also generate position-based speed values from successive position readings and time intervals, to determine the current speed independently of the Doppler-based speed values. During degraded signal conditions, the Doppler-based speed values can drop to invalid levels. The device incorporates a combiner module (450) which compares the position-based and Doppler-based speed values and performs combination operations on those quantities to produce a compensated speed value (490). By selecting the maximum or otherwise combining those values, extreme excursions in speed values are avoided and accuracy promoted.

Abstract: A method and apparatus for determining a range within a wireless communication system is provided herein. The range information can then be used to locate a node (e.g., an asset tag). During operation, the minimum transmission power of a source transceiver (e.g., an RFID reader) that enables a tag to be detected will be used to indicate distance. Changes in transmit power will be used to indicate relative changes in distance to a particular node. The reader will be configured to always operate at a transmission power that will result in a certain percentage (e.g., 50%) detection rate for a target transceiver (e.g., an RFID asset tag). As the reader moves closer to the tag, the minimum detection power will decrease; as it moves farther from the tag, the minimum detection power will increase. This information is displayed to give a general change in range information between the RFID reader and the asset tag (e.g., increasing range or decreasing range).

Abstract: A method and apparatus is provided for easily creating virtual graffiti that will be left for a particular device to view. During operation a device will be placed near a first point that is used to define a boundary for the virtual graffiti. The device will locate the first point, and use the point to define the boundary. The device will receive an image that is to be used as virtual graffiti, and will fit the image within the boundary of the virtual graffiti. For example, the device may be consecutively placed near four points that will define a polygon to be used as the boundary for the virtual graffiti. An image will then be received, and the image will be fit within the polygon.

Abstract: A method and system is provided for easily creating virtual graffiti that will be left for a particular device to view. During operation a device will be placed near a first point that is used to define a boundary for the virtual graffiti. The device will locate the first point, and use the point to define the boundary. The device will receive an image that is to be used as virtual graffiti, and will fit the image within or upon the boundary of the virtual graffiti. For example, the device may be consecutively placed near four points that will define a polygon to be used as the boundary for the virtual graffiti. An image will then be received, and the image will be fit within the polygon. Additionally, a device may create virtual graffiti from an image and a boundary.