Toyota Motor Engineering & Manufacturing North America, Inc.

University of Michigan

Toyota Jidosha Kabushiki Kaisha

Central Michigan University

Toyota Motor Sales, U.s.a., Inc.

Pujitha Gunaratne

Kayvan Najarian

Jonathan Gryak

Hendrikus Derksen

Zhi Li

Richard W Backs

James T Pisz

Kazutoshi Ebe

Warren Jing Po Chou

Jason A Schulz

Yifan Jiang

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.

Systems and methods for controlling a vehicle based on driver engagement

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.

Systems and methods for predicting and detecting a cardiac event

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.

Driver state detection based on glycemic condition

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.

System and method for driving hazard estimation using vehicle-to-vehicle communication

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.

Surrounding vehicle classification and path prediction

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.

Interactive vehicle window display system with personal convenience reminders

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.

Method and apparatus for early detection of dynamic attentive states for providing an inattentive warning

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.

Method and apparatus for generating and using driver specific vehicle controls

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.

Environment-based function lock system for a vehicle

A method, system, device and computer readable medium for adaptively warning a driver includes detecting a behavior of the driver, the behavior including engagement in a secondary activity, which is an activity other than driving a vehicle. Based on the detected behavior, a level of engagement in the secondary activity is estimated, and, based on the estimated level of engagement in the secondary activity, the driver's level of perception of an external hazard is determined. A warning alert for the driver, when the level of perception is below a threshold is actuated. A reaction of the driver to the actuated warning alert is determined. Based on the reaction of the driver to the actuated warning alert, the warning alert is adjusted, and the warning alert is terminated when the level of perception becomes above the threshold because of the reaction of the driver to the actuated warning alert.

Adaptive Actuator interface for active driver warning

A method and system for risk prediction for a support actuation system. The system includes a support actuation system for an automobile having a support actuation module and/or a risk prediction system. The risk prediction system includes a sensor, a processor, and/or a memory. The sensor detects images corresponding to identity data, environment data, event data, and/or behavior data, which are stored in the memory. The memory also stores a database including identities of users, environment risk values, event risk values, and/or behavior risk values. Using the identity data, the environment data, the event data, and/or the behavior data, the processor determines the environment risk value, the event risk value, the behavior risk value, and/or the total risk value for a user. When the total risk value is above a predetermined risk threshold, the support actuation module performs support actuation.

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Windsor, CA, United States of America

Pujitha Gunaratne