Abstract: Systems and methods for controlling a vehicle based on driver engagement are disclosed. In one embodiment, a method of controlling a vehicle includes determining, using driver data from one or more driver sensors, a driver state estimation of a driver of the vehicle, determining, using environment data from one or more environmental sensors, one or more environment anomalies within an environment of the vehicle, and determining an anomaly category for at least one of the one or more environment anomalies. The method further includes, based on the driver state estimation and one or more anomaly categories, selecting a failure mode, based on the failure mode, selecting at least one failsafe action, and determining an operation of the vehicle in accordance with the failure mode.

Abstract: Systems and methods for predicting and/or detecting cardiac events based on real-time biomedical signals are discussed herein. In various embodiments, a machine learning algorithm may be utilized to predict and/or detect one or more medical conditions based on obtained biomedical signals. For example, the systems and methods described herein may utilize ECG signals to predict and detect cardiac events. In various embodiments, patterns identified within a signal may be assigned letters (i.e., encoded as distributions of letters). Based on the known morphology of a signal, states within the signal may be identified based on the distribution of letters in the signal. When applied in the in-vehicle environment, drivers or passengers within the vehicle may be alerted when an individual within the vehicle is, or is about to, experience a cardiac event.

Abstract: Systems and methods for predicting and/or detecting cardiac events based on real-time biomedical signals are discussed herein. In various embodiments, a machine learning algorithm may be utilized to predict and/or detect one or more medical conditions based on obtained biomedical signals. For example, the systems and methods described herein may utilize ECG signals to predict and detect cardiac events. In various embodiments, patterns identified within a signal may be assigned letters (i.e., encoded as distributions of letters). Based on the known morphology of a signal, states within the signal may be identified based on the distribution of letters in the signal. When applied in the in-vehicle environment, drivers or passengers within the vehicle may be alerted when an individual within the vehicle is, or is about to, experience a cardiac event.

Abstract: Systems and methods for predicting and/or detecting cardiac events based on real-time biomedical signals are discussed herein. In various embodiments, a machine learning algorithm may be utilized to predict and/or detect one or more medical conditions based on obtained biomedical signals. For example, the systems and methods described herein may utilize ECG signals to predict and detect cardiac events. In various embodiments, patterns identified within a signal may be assigned letters (i.e., encoded as distributions of letters). Based on the known morphology of a signal, states within the signal may be identified based on the distribution of letters in the signal. When applied in the in-vehicle environment, drivers or passengers within the vehicle may be alerted when an individual within the vehicle is, or is about to, experience a cardiac event.

Abstract: Systems and methods for controlling a vehicle based on driver engagement are disclosed. In one embodiment, a method of controlling a vehicle includes determining, using driver data from one or more driver sensors, a driver state estimation of a driver of the vehicle, determining, using environment data from one or more environmental sensors, one or more environment anomalies within an environment of the vehicle, and determining an anomaly category for at least one of the one or more environment anomalies. The method further includes, based on the driver state estimation and one or more anomaly categories, selecting a failure mode, based on the failure mode, selecting at least one failsafe action, and determining an operation of the vehicle in accordance with the failure mode.

Abstract: Embodiments of the disclosure relate to systems and methods for detecting driver state based on glucose levels of a driver of the vehicle. In one embodiment, a method of detecting driver state based on glucose levels of a driver of the vehicle includes receiving measurements of glucose levels of the driver from a continuous glucose monitoring (CGM) device and determining a glycemic state of the driver based on the measurements and a driving performance parameter based on the glycemic state. The method further includes determining a degree of impairment of the driver based on whether the driving performance parameter satisfies a predetermined threshold and determining a level of driver state severity based on driver performance characteristics, features of the driving environment, and the degree of impairment of the driver. A response is then activated based on the driver state severity.

Abstract: Embodiments of the disclosure relate to systems and methods for detecting driver state based on glucose levels of a driver of the vehicle. In one embodiment, a method of detecting driver state based on glucose levels of a driver of the vehicle includes receiving measurements of glucose levels of the driver from a continuous glucose monitoring (CGM) device and determining a glycemic state of the driver based on the measurements and a driving performance parameter based on the glycemic state. The method further includes determining a degree of impairment of the driver based on whether the driving performance parameter satisfies a predetermined threshold and determining a level of driver state severity based on driver performance characteristics, features of the driving environment, and the degree of impairment of the driver. A response is then activated based on the driver state severity.

Abstract: Systems and methods for predicting and/or detecting cardiac events based on real-time biomedical signals are discussed herein. In various embodiments, a machine learning algorithm may be utilized to predict and/or detect one or more medical conditions based on obtained biomedical signals. For example, the systems and methods described herein may utilize ECG signals to predict and detect cardiac events. In various embodiments, patterns identified within a signal may be assigned letters (i.e., encoded as distributions of letters). Based on the known morphology of a signal, states within the signal may be identified based on the distribution of letters in the signal. When applied in the in-vehicle environment, drivers or passengers within the vehicle may be alerted when an individual within the vehicle is, or is about to, experience a cardiac event.

Abstract: Systems and methods for predicting and/or detecting cardiac events based on real-time biomedical signals are discussed herein. In various embodiments, a machine learning algorithm may be utilized to predict and/or detect one or more medical conditions based on obtained biomedical signals. For example, the systems and methods described herein may utilize ECG signals to predict and detect cardiac events. In various embodiments, patterns identified within a signal may be assigned letters (i.e., encoded as distributions of letters). Based on the known morphology of a signal, states within the signal may be identified based on the distribution of letters in the signal. When applied in the in-vehicle environment, drivers or passengers within the vehicle may be alerted when an individual within the vehicle is, or is about to, experience a cardiac event.

Abstract: A computing device for a vehicle hazard avoidance system. The device includes one or more processors for controlling operation of the computing device, and a memory storing computer-executable instructions which, when executed by the one or more processors, cause the computing device to receive hazard assessment information relating to a vehicle, perform an analysis of the hazard assessment information, and generate a hazard assessment based on the analysis.

Abstract: A host vehicle can be configured to monitor an external environment of the host vehicle using a sensor system. The host vehicle can detect an object in the external environment of the host vehicle. The object can be classified as a surrounding vehicle. The host vehicle can determine a driving behavior of the surrounding vehicle. The driving behavior can be based on any one of a predetermined vehicle characteristics and current driving characteristics of the surrounding vehicle. The predetermined vehicle characteristics can be based on a type of the surrounding vehicle. The current driving characteristics can be based on observations obtained by the sensor system. The host vehicle can predict a trajectory of the surrounding vehicle based on the determined driving behavior. The host vehicle can follow a safe path based on the predicted trajectory responsive to detecting one or more sensors in a failed state.

Abstract: A system for a vehicle that provides personal convenience reminders to a user of a vehicle. The system accesses an off board system such as a personal electronic device of the user to display the personal convenience reminders. The system can also access various off board applications in response to the personal electronic device of the user to further refine the personal convenience reminders in response to a user selection.

Abstract: A method and apparatus for determining an inattentive state of an operator of a vehicle and for providing information to the operator of the vehicle by obtaining face images of the operator of the vehicle, obtaining images of an environment of the vehicle, determining one or more areas of interest in the environment of the vehicle based on the images of the environment, obtaining, from a relevance and priority database, relevance and priority values corresponding to the one or more areas of interest, determining a probability of attention of the operator of the vehicle to the one or more areas of interest based on the images of the environment and the relevance and priority values, determining an attention deficiency based on the determined probability of attention and the face images, and providing the information to the operator of the vehicle based on the determined attention deficiency.

Abstract: A computing device for a vehicle hazard avoidance system. The device includes one or more processors for controlling operation of the computing device, and a memory storing computer-executable instructions which, when executed by the one or more processors, cause the computing device to receive hazard assessment information relating to a vehicle, perform an analysis of the hazard assessment information, and generate a hazard assessment based on the analysis.

Abstract: A host vehicle can be configured to monitor an external environment of the host vehicle using a sensor system. The host vehicle can detect an object in the external environment of the host vehicle. The object can be classified as a surrounding vehicle. The host vehicle can determine a driving behavior of the surrounding vehicle. The driving behavior can be based on any one of a predetermined vehicle characteristics and current driving characteristics of the surrounding vehicle. The predetermined vehicle characteristics can be based on a type of the surrounding vehicle. The current driving characteristics can be based on observations obtained by the sensor system. The host vehicle can predict a trajectory of the surrounding vehicle based on the determined driving behavior. The host vehicle can follow a safe path based on the predicted trajectory responsive to detecting one or more sensors in a failed state.

Abstract: A driver-specific vehicle control method is provided that can adjust one or more vehicle control systems in response to a difference in current driver driving characteristics with respect to safe driver driving characteristics on the same roadway type and vehicle operating conditions. The method maintains a driver score for each driver of a vehicle, in the form of a set of the driver's driving characteristics scores for each different roadway type. The method, via a control apparatus, determines a current position of the vehicle on a roadway and the roadway features to select the appropriate driver score for comparison. When the driver's score exceeds a threshold difference from a safe driver score on the same roadway type, the method can adjust a control system parameter.

Abstract: A driver specific vehicle control method and apparatus which can adjust one or more vehicle control systems in response to a difference of current driver driving characteristics with respect to safe driver driving characteristics on the same roadway features and vehicle operating conditions. The apparatus and method maintains a driver score for each driver of a vehicle, in the form of a set of the driver's driving characteristics scores for each different roadway feature. The method and control apparatus determine the current position of the vehicle on a roadway and the roadway features to select the appropriate driver score for comparison. When the driver's score exceeds a threshold difference from a safe driver score on the same roadway feature, the apparatus can adjust a control system parameter.

Abstract: A method and apparatus for determining an inattentive state of an operator of a vehicle and for providing information to the operator of the vehicle by obtaining face images of the operator of the vehicle, obtaining images of an environment of the vehicle, determining one or more areas of interest in the environment of the vehicle based on the images of the environment, obtaining, from a relevance and priority database, relevance and priority values corresponding to the one or more areas of interest, determining a probability of attention of the operator of the vehicle to the one or more areas of interest based on the images of the environment and the relevance and priority values, determining an attention deficiency based on the determined probability of attention and the face images, and providing the information to the operator of the vehicle based on the determined attention deficiency.

Abstract: A method and apparatus for determining an inattentive state of an operator of a vehicle and for providing information to the operator of the vehicle by obtaining face images of the operator of the vehicle, obtaining images of an environment of the vehicle, determining one or more areas of interest in the environment of the vehicle based on the images of the environment, obtaining, from a relevance and priority database, relevance and priority values corresponding to the one or more areas of interest, determining a probability of attention of the operator of the vehicle to the one or more areas of interest based on the images of the environment and the relevance and priority values, determining an attention deficiency based on the determined probability of attention and the face images, and providing the information to the operator of the vehicle based on the determined attention deficiency.

Abstract: A computing device and methods for restricting driver interactions with vehicle functions based on a challenging driving environment are disclosed. One example method for restricting driver interactions with vehicle functions based on a challenging driving environment includes identifying a challenging driving environment based at least in part on information regarding a driving condition; and preventing a driver from accessing one or more vehicle functions based on the challenging driving environment exists. Example implementations include identifying a challenging driving environment based on information received from on-vehicle sensors and/or external communication links; identifying a driver's skill level; and selectively blocking vehicle functionality, selectively presenting information to a driver, and selecting available driver interactions based on the driving environment.