Abstract: A system includes a processor configured to determine analogies between information associated with a new topic to be learned and information associated with existing knowledge of a user, identify terms associated with the new topic that appear similar to terms associated with the existing knowledge, and propose questions for the user to explore based on the new topic and the existing knowledge.

Abstract: A method for an augmented reality goal assistant is described. The method includes detecting an object associated with a behavioral goal of a user. The method also includes altering an appearance of the object based on the behavioral goal of the user. The method further includes displaying the altered appearance of a detected object on an augmented reality headset, such that the altered appearance of the detected object is modified based on the behavioral goal of the user.

Abstract: Systems and methods are provided for requirements engineering, and may include: receiving as input, time series data from at least one of a simulation of a vehicle run on a simulation system, or from the vehicle in operation; a requirements monitoring system checking to determine whether a plurality of requirements for operation of the vehicle are met, wherein the requirements are expressed in signal temporal logic form and a requirement includes at least an associated minimal sampling rate and a filtering policy applicable to the requirement; determining a quantitative conformance for each of selected requirements of the plurality of requirements; and add requirements to a verified requirements set based on the qualitative conformance of the requirements.

Abstract: A personalized notification method for a mobility as a service (MaaS) vehicle includes receiving conditional personalized notification features from a passenger of the MaaS vehicle. The method also includes monitoring current driving environment of the MaaS vehicle to determine whether a condition of the conditional personalized notification features is satisfied. The method further includes notifying the passenger when the condition is satisfied via at least one localized output device in a compartment of the MaaS vehicle.

Abstract: A driver monitor system and method for predicting impairment of a user of a vehicle. The system includes video cameras, an input device for inputting a list of medications being taken by the driver. Processing circuitry predicts side effects of the medications based on the half-life of the medication, detecting eye gaze movement, eye lid position, and facial expression of the user using images from the video camera, predicting whether the user is transitioning into an impaired physical state that is a side effect of the medications, verifying the side effect of the medications, determining whether the user is fit to drive using the verified side effects of the medications, and outputting to the vehicle an instruction to operate the vehicle in a level of automation that makes up for the at least one side effect or to perform a safe pull over operation of the vehicle.

Abstract: An object recognition determination produced by a perception system from data received from a ranging sensor system can be verified. A certificate can be produced that includes data for points of readings from the ranging sensor system. The points can have been segmented, by the perception system, into point sets that correspond to objects in an environment of a cyber-physical system. The certificate can also include lists of pairs of points in a point set and a velocity of the point set. A test of information in the certificate can be performed. Based on a result of the test: a rectification can be made to the perception system or the ranging sensor system or a communication can be transmitted to a control signal production module configured to produce, in response to the communication, a control signal to be transmitted to an actuator system configured to control the cyber-physical system.

Abstract: Systems and methods are provided for implementing soft model assertions (SMA) system and techniques designed to monitor and improve Machine Learning (ML) model quality by to detecting errors within the one or more ML models. SMA techniques and systems are distinctly designed to leverage: 1) a user's ability to specify features over data; and 2) large, existing datasets of organizations, in a manner that can improve the accuracy and quality of predicting potential errors in Machine Learning (ML) models. A SMA system can include a controller device receiving predictions generated based on the ML models and output from the SMA system. The controller performs autonomous operations of the system in response to determining that the one or more detected errors within the one or more ML models yield a high certainty of errors in the predictions. The SMA system also includes a domain specific language and a severity score module.

Abstract: Aspects of the disclosure provide a parking method and system for a vehicle. For example, the parking system can include a processor and an output circuit. As another example, the parking system can include the processor and a compelling unit. The processor can be configured to determine whether a first weather condition, such as snowing, raining, icing and hailing, at a first parking location meets a first criterion, and identify, when the first weather condition meets the first criterion, a second parking location at which a second weather condition meets a second criterion different from the first criterion. The output unit can be configured to output an alert to the vehicle parked at the first parking location indicating that the vehicle is to be moved to the second parking location. The compelling unit can be configured to compel the vehicle to move to the second parking location.

Abstract: Aspects of the disclosure provide a parking method and system for a vehicle. For example, the parking system can include a processor and an output circuit. As another example, the parking system can include the processor and a compelling unit. The processor can be configured to determine whether a first weather condition, such as snowing, raining, icing and hailing, at a first parking location meets a first criterion, and identify, when the first weather condition meets the first criterion, a second parking location at which a second weather condition meets a second criterion different from the first criterion. The output unit can be configured to output an alert to the vehicle parked at the first parking location indicating that the vehicle is to be moved to the second parking location. The compelling unit can be configured to compel the vehicle to move to the second parking location.

Abstract: A driver monitor system and method for predicting impairment of a user of a vehicle. The system includes video cameras, an input device for inputting a list of medications being taken by the driver. Processing circuitry predicts side effects of the medications based on the half-life of the medication, detecting eye gaze movement, eye lid position, and facial expression of the user using images from the video camera, predicting whether the user is transitioning into an impaired physical state that is a side effect of the medications, verifying the side effect of the medications, determining whether the user is fit to drive using the verified side effects of the medications, and outputting to the vehicle an instruction to operate the vehicle in a level of automation that makes up for the at least one side effect or to perform a safe pull over operation of the vehicle.

Abstract: Systems and methods are provided for requirements engineering, and may include: receiving as input, time series data from at least one of a simulation of a vehicle run on a simulation system, or from the vehicle in operation; a requirements monitoring system checking to determine whether a plurality of requirements for operation of the vehicle are met, wherein the requirements are expressed in signal temporal logic form and a requirement includes at least an associated minimal sampling rate and a filtering policy applicable to the requirement; determining a quantitative conformance for each of selected requirements of the plurality of requirements; and add requirements to a verified requirements set based on the qualitative conformance of the requirements.

Abstract: A method for synthesizing parameters for control of a closed loop system based on a differentiable simulation model of the closed loop system includes determining requirements/specifications for the closed loop system in signal temporal logic (STL). The method also includes selecting a parametric control law having a differentiable parameter control function. The method also includes converting the requirements in signal temporal logic into differentiable computational graph. The method further includes building the differentiable simulation model as a differentiable computational graph. Furthermore, the method includes automatically learning values of parameters for the differentiable parameter control function of the closed loop system by backpropagating an error.

Abstract: An artificial intelligence perception system for detecting one or more objects includes one or more processors, at least one sensor, and a memory device. The memory device includes an image capture module, an object identifying module, and a logical scaffold module. The image capture module and the object identifying module cause the one or more processors to obtain sensor information of a field of view from a sensor, identify an object within the sensor information, and determine at least one property of the object. The logical scaffold module causes the one or more processors to determine, by a logical scaffold, when the at least one property of the object as determined by the object identifying module is one of a true condition or a false condition.

Abstract: A method performed by an autonomous vehicle includes identifying a condition preventing the autonomous vehicle from proceeding along an intended route. The method also includes prompting a passenger of the autonomous vehicle to interact with a driver of a first vehicle in response to identifying the condition. The method further includes receiving, from the passenger, an input at an interface of the autonomous vehicle indicating a successful interaction or an unsuccessful interaction with the driver. The method also includes controlling the autonomous vehicle to proceed along the intended route based on the input indicating the successful interaction with the driver.

Abstract: Systems and methods for a powered, robotic exoskeleton, or exosuit, for a user's limbs and body are provided. The exosuit may be equipped with airbag devices mounted at various locations on the suit. The exosuit may include on-board computing equipment that can sense, compute control commands in real-time, and actuate limbs and airbags to restore stability (fall prevention) and minimize injuries due to falls, should they happen (fall protection).

Abstract: A method for controlling an autonomous vehicle includes navigating the autonomous vehicle based on a set of rules. The method also includes identifying an abnormality in a current driving situation. The method further includes prompting a passenger of the autonomous vehicle to interact with a driver of a first vehicle in response to identifying the abnormality. The method still further includes controlling the autonomous vehicle to violate one or more rules of the set of rules in response to an indication of a successful interaction with the driver.

Abstract: An artificial intelligence perception system for detecting one or more objects includes one or more processors, at least one sensor, and a memory device. The memory device includes an image capture module, an object identifying module, and a logical scaffold module. The image capture module and the object identifying module cause the one or more processors to obtain sensor information of a field of view from a sensor, identify an object within the sensor information, and determine at least one property of the object. The logical scaffold module causes the one or more processors to determine, by a logical scaffold, when the at least one property of the object as determined by the object identifying module is one of a true condition or a false condition.

Abstract: A method for certified control of a self-driving ego vehicle is described. The method includes analyzing a safety situation of the self-driving ego vehicle to determine a proposed vehicle control action using a main controller of the self-driving ego vehicle. The method also includes presenting, by the main controller, the proposed vehicle control action to an interlock controller, including a certificate of the proposed vehicle control action. The method further includes checking a safety certification evidence from the certificate by the interlock controller using a predefined safety argument to verify the safety certification evidence of the certificate. The method also includes directing, by a low-level controller, the self-driving ego vehicle to perform a certified vehicle control action.

Abstract: System, methods, and other embodiments described herein relate to modeling dynamic agents in a surrounding environment of an ego vehicle. In one embodiment, a method includes, in response to receiving sensor data including present observations of a road agent of the dynamic agents in the surrounding environment, identifying previous observations of the road agent from an electronic data store. The method includes estimating a future state of the road agent using at least the present observations and the previous observations of the road agent to compute the future state according to a probabilistic model comprised of a transition model that accounts for dynamic behaviors of the road agent to characterize transitions between states, and an agent model that accounts for actions of the road agent. The method includes controlling one or more vehicle systems of the ego vehicle according to the future state of the road agent.

Abstract: A method for synthesizing parameters for control of a closed loop system based on a differentiable simulation model of the closed loop system includes determining requirements/specifications for the closed loop system in signal temporal logic (STL). The method also includes selecting a parametric control law having a differentiable parameter control function. The method also includes converting the requirements in signal temporal logic into differentiable computational graph. The method further includes building the differentiable simulation model as a differentiable computational graph. Furthermore, the method includes automatically learning values of parameters for the differentiable parameter control function of the closed loop system by backpropagating an error.