Toyota Connected North America, Inc.

Akshata Dundi Mohan

Raja Shekar Kilaru

Christian Gilles Claudel

Nimish Kumar Amlathe

Brian M Kursar

Toshikazu Tanaka

Systems, methods, and other embodiments described herein relate to improving crash prediction through correlating an observed response and a predicted response of a vehicle. In one embodiment, a method includes generating the predicted response for the vehicle as a function of a response model and according to current vehicle inputs that are control inputs associated with steering, braking, and accelerating the vehicle. The response model is a learning model that predicts behaviors of the vehicle. The method includes computing a residual indicating an extent of correlation between the predicted response and the observed response. The method includes, in response to determining the residual satisfies a crash threshold that indicates an anomaly between the predicted response and the observed response, providing an alert indicating the vehicle has likely crashed.

Systems and methods for real-time crash detection using telematics data

System, methods, and other embodiments described herein relate to determining a location of a vehicle within a structure. In one embodiment, a method includes collecting, from at least one sensor in the vehicle, sensor data that indicates information associated with control of the vehicle in the structure. The method includes classifying gradients along a path of the vehicle through the structure according to the sensor data. The method includes identifying traversed levels of the structure along the path according to the gradients. The method includes providing the location including at least an indicator of the traversed levels as an electronic output.

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Addison, TX, United States of America

Akshata Dundi Mohan