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 an electric vehicle trip simulator is described. The method includes determining parameters for an upcoming trip of an electric vehicle, including at least a start location and a destination location. The method also includes analyzing data associated with a plurality of points of interest between the start location and the destination location. The method further includes selecting a set of locations from the plurality of points of interest for the upcoming trip of the electric vehicle, according to the analyzing of the data. The method also includes displaying a travel order recommendation associated with the set of locations selected for the upcoming trip of the electric vehicle, including at least one charging station location according to a current charge capacity of the electric vehicle.

Abstract: Systems and methods for generating predicted preferences are disclosed. The method includes implementing, with a computing device having a processor and a non-transitory computer-readable memory, a conjoint architecture comprising: an autoencoder trained to transform input data including one or more choices and one or more features into a latent representation, and a choice classification network trained to predict one or more predicted preferences from the latent representation extracted by the autoencoder. The method further includes outputting, from the choice classification network, the one or more predicted preferences.

Abstract: Systems and methods for generating and evaluating driving scenarios with varying difficulty levels is provided. The disclosed systems and methods may be used to develop a suite of regression tests that track the progress of an autonomous driving stack. A robustness trace of a temporal logic formula may be computed from an always-eventually fragment using a computation graph. The robustness trace may be approximated by a smoothly differentiable computation graph, which can be implemented in existing machine learning programming frameworks. The systems and methods provided herein may be useful in automatic test case generation for autonomous or semi-autonomous vehicles.

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: Systems, methods, and other embodiments described herein relate to informing a user how a hypothetical electric vehicle would perform based on the driving habits of the user in a non-electric vehicle. In one embodiment, a method includes identifying an origin and a destination of a non-electric vehicle after the non-electric vehicle has arrived at the destination. The method includes determining energy information for a hypothetical electric vehicle traveling from the origin to the destination and outputting the energy information to the user.

Abstract: A method for use of elicited factors to inform intervention suggestions is described. The method includes identifying a demographic of a user according to a background of the user. The method also includes predicting factors including an associated set of barriers and/or motivators regarding a preference according to the demographic of the user. The method further includes predicting a plurality of interventions to shift the preference of the user according to the associated set of barriers and/or motivators. The method also includes presenting a selected one of the plurality of determined interventions to the user.

Abstract: Systems, methods, and other embodiments described herein relate to informing a user how a hypothetical electric vehicle would perform based on the driving habits of the user in a non-electric vehicle. In one embodiment, a method includes identifying an origin and a destination of a non-electric vehicle after the non-electric vehicle has arrived at the destination. The method includes determining energy information for a hypothetical electric vehicle traveling from the origin to the destination and outputting the energy information to the user.

Abstract: System, methods, and other embodiments described herein relate to a manner of determining an interpretable model from experimental data using tokenization in a prediction model. In one embodiment, a method includes outputting a bit pattern of probable tokens generated from raw data using a model. The method also includes converting, using the model, the bit pattern into output tokens and parsing the output tokens into a symbolic expression. The method also includes fitting symbolic parameters from the symbolic expression into an interpretable model for accuracy. The method also includes estimating an operational behavior and signal output of a vehicle system according to the interpretable model.

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.