Abstract: A method and system presents a sensory trait to a person for providing a human-sense perceivable representation of an aspect of an event. Information associated with an event can be received which has a first aspect being perceivable by a human via a first human sense at a distance from the event. A second aspect of the event is imperceivable by the human via a second human sense at the distance from the event. A query can be sent to a database for a representation of the first aspect of the event. A response to the query can be received which identifies the representation of the second aspect. The representation of the second aspect can be outputted in a manner that is perceivable by the human via the second human sense, while the human perceives the first aspect via the first human sense at the distance from the event.

Abstract: A self-driving vehicle (SDV) ameliorates a vehicular mishap incurred by a second vehicle. At least one sensor on a first SDV detects a second vehicle that has been involved in a vehicular mishap. One or more processors determine a confidence level L, which is a confidence level of a mishap assessment accuracy of determining that the second vehicle has been involved in the vehicular mishap. In response to the confidence level L exceeding a predetermined value, the SDV executes an amelioration action to ameliorate a condition of the second vehicle that has been involved in the vehicular mishap.

Abstract: A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.

Abstract: A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of the on-board SDV control processor that autonomously controls the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV experiences the current operational anomaly. One or more processors then selectively assign control of the SDV to the on-board SDV control processor or to the human driver while the SDV experiences the current operational anomaly based on which of the control processor competence level and the human driver competence level is relatively higher to the other.

Abstract: Various embodiments provide systems, computer program products and computer implemented methods. In some embodiments, a system includes a method of providing a confidence-estimation-based inference, the method includes receiving a query concerning a patient from a user, accessing an electronic health record (EHR) for the patient, the EHR including a first component regarding the patient, querying the user, using a conversational interface, for a second component regarding the patient, receiving the second component regarding the patient in response to the query, calculating a first probability density function using the first component, and a second probability density function using the second component, combining the first and second probability density functions using a Gaussian mixture model, calculating at least one conditional probability table using the Gaussian mixture model and providing the confidence-estimation-based inference based on the at least one conditional probability table.

Abstract: Detecting user input based on multiple gestures is provided. One or more interactions are received from a user via a user interface. An inferred interaction is determined based, at least in part, on a geometric operation, wherein the geometric operation is based on the one or more interactions. The inferred interaction is presented via the user interface. Whether a confirmation has been received for the inferred interaction is determined.

Abstract: A possible failure of a first device may be identified. Whether a user of the first device has a scheduled meeting to be held within a time range of the possible failure, may be determined by accessing calendar information. Responsive to determining that the user has the scheduled meeting to be held within the time range of the possible failure, at least one other participant of the scheduled meeting may be determined by accessing the calendar information, a contact address for said at least one other participant may be determined, and information may be transferred to the at least one other participant via the contact address.

Abstract: A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV) when a driver receives a telecommunication message on a telecommunication device. An SDV on-board computer within the SDV detects that the SDV is currently being operated in manual mode by a human driver. The SDV on-board computer detects that a telecommunication device located within the SDV is receiving a telecommunication message. In response to detecting that the telecommunication device within the SDV is receiving the telecommunication message, the SDV on-board computer transfers control of the SDV to the SDV on-board computer in order to place the SDV in autonomous mode, where the SDV is in the autonomous mode when steering, braking, throttle control, and obstacle avoidance by the SDV are all controlled by the SDV on-board computer.

Abstract: Content of a web-based application is displayed in a window of a web browser application. A selection of the display region is received from a user or a computer implemented system. A locked region is defined based on the selection. When instructions to modify the content of web-based application is received, the instructions are executed except those to modify the locked region.

Abstract: A method and/or computer program product controls an operational mode of a self-driving vehicle (SDV) that is initially being operated in a nominal autonomous mode. Detectors on an SDV detect an erratically driven vehicle (EDV) that is being operated in an unsafe manner within a predetermined distance of an SDV. In response to detecting the EDV, a driving mode device in the SDV changes an operational mode of the SDV from the nominal autonomous mode to an evasive autonomous mode.

Abstract: A method controls an operational mode of a self-driving vehicle (SDV). One or more physical detectors detect an erratically driven vehicle (EDV) that is being operated in an unsafe manner within a predetermined distance of an SDV that is initially being operated in an evasive autonomous mode. One or more processors retrieve traffic pattern data for other SDVs, and examine the traffic pattern data to 1) determine a first traffic flow of the other SDVs while operating in the evasive autonomous mode, and 2) determine a second traffic flow of the other SDVs while operating in a manual mode. In response to determining that the first traffic flow has a higher accident rate than the second traffic flow, an operational mode device changes the operational mode of the SDV from the evasive autonomous mode to the manual mode.

Abstract: Aspects generate customized routes by automatically selecting between human-powered and motorized transport option segments, by determining a well-being objective of a traveler and an amount of the human-powered transport option for the traveler to perform to meet requirements of the well-being objective. Aspects generate recommended routes to a destination from a current location of the traveler that meets the well-being objective by selecting between route segment portions of usage of a human-powered option and of a motorized transport option, and include a first segment of usage of the human-powered transport option in response to determining that said included first segment requires an amount of effort that meets the well-being objective and does not exceed an amount of the human-powered transport option that the traveler is currently able to perform.

Abstract: A computer-implemented method, system, and/or computer program product controls self-driving vehicles (SDVs). An emergency message is transmitted to a receiver within a self-driving vehicle (SDV). The emergency message describes an emergency state of an emergency vehicle and an identified future route of the emergency vehicle, where the identified future route is a planned route to an emergency destination for the emergency vehicle that includes a first pathway. In response to the SDV receiving the emergency message, the SDV is redirected, via an auto-control hardware system on the SDV, to drive to a second pathway that does not conflict with the identified future route of the emergency vehicle.

Abstract: Aspects generate customized routes that select between human-powered and motorized transport option segments to maximize well-being objective in navigating a traveler to a destination. Amounts of human-powered transport options that a traveler is willing, able or recommended to perform via the traveler's own physical exertions in reaching a destination are determined as a function of well-being or cost objectives and performance limits. Recommended routes to the destination having human-powered and/or motorized transport option segments are generated that meet well-being objectives without exceeding amounts that the traveler is currently able to perform, and excluding segments that require efforts that do not meet the well-being objective or exceed the amounts that the traveler is currently able to perform.

Abstract: A computer-implemented method, system, and/or computer program product automatically provides spatial separation between a self-driving vehicle (SDV) operating in an autonomous mode and another vehicle on a roadway. One or more processors receive an emotional state descriptor for at least one occupant of the SDV and determine an emotional state of the occupant(s) of the SDV. A vehicle detector on the SDV detects another vehicle within a predefined proximity of the SDV. The processor(s) determine the braking abilities of the SDV and issue spatial separation instructions to a control mechanisms controller on the SDV to adjust a spacing between the SDV and the other vehicle based on the emotional state of the occupant(s) in the SDV.

Abstract: A computer-implemented method, system, and/or computer program product automatically provides spatial separation between a self-driving vehicle (SDV) operating in an autonomous mode and another vehicle on a roadway. One or more processors receive an emotional state descriptor for at least one occupant of the SDV and determine an emotional state of the occupant(s) of the SDV. A vehicle detector on the SDV detects another vehicle and the size of the other vehicle within a predefined proximity of the SDV. A control mechanisms controller determines that a field of view for the occupants in the SDV is blocked by the size of the other vehicle. The processor(s) issue spatial separation instructions to the control mechanisms controller on the SDV to adjust a spacing between the SDV and the other vehicle based on the emotional state descriptor for the occupant(s) in the SDV and the field of view for the occupant(s) in the SDV that is blocked by the size of the other vehicle.

Abstract: A processor-implemented method and/or computer program product selectively blocks a self-driving vehicle's access to a roadway. A vehicle interrogation hardware device receives an autonomous capability signal from an approaching self-driving vehicle. One or more processors compare the predefined roadway conditions to current roadway conditions of the access-controlled roadway. In response to the predefined roadway conditions matching the current roadway conditions of the access-controlled roadway within a predetermined range, the processor(s) determine whether the level of autonomous capability of the approaching self-driving vehicle is adequate to safely maneuver the approaching self-driving vehicle through the current roadway conditions of the access-controlled roadway.

Abstract: A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV) when a driver receives a telecommunication message on a telecommunication device. An SDV on-board computer within the SDV detects that the SDV is currently being operated in manual mode by a human driver. The SDV on-board computer detects that a telecommunication device located within the SDV is receiving a telecommunication message. In response to detecting that the telecommunication device within the SDV is receiving the telecommunication message, the SDV on-board computer transfers control of the SDV to the SDV on-board computer in order to place the SDV in autonomous mode, where the SDV is in the autonomous mode when steering, braking, throttle control, and obstacle avoidance by the SDV are all controlled by the SDV on-board computer.

Abstract: A computer-implemented method, system, and/or computer program product automatically provides spatial separation between a self-driving vehicle (SDV) operating in an autonomous mode and another vehicle on a roadway based on an emotional state of at least one occupant of the SDV. One or more processors receive an emotional state descriptor for at least one occupant of the SDV. A vehicle detector on the SDV detects another vehicle within a predefined proximity of the SDV. The processor(s) issue spatial separation instructions to a control mechanisms controller on the SDV to adjust a spacing between the SDV and the other vehicle based on the emotional state descriptor for the occupant(s) in the SDV.

Abstract: A computer-implemented method, system, and/or computer program product redirects a self-driving vehicle (SDV) to a physical location of a product provider. A self-driving vehicle (SDV) on-board computer on an SDV receives a current location and a planned route to an initial destination of the SDV. The SDV on-board computer receives information describing real-time physiological states of one or more occupants of the SDV, and then identifies a physical location of a product provider that provides a solution to ameliorate the real-time physiological states of the one or more occupants of the SDV. The SDV on-board computer then alters the planned route of the SDV to redirect the SDV on-board computer to autonomously drive the SDV to the physical location of the product provider.