Abstract: 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.

Abstract: System, 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.

Abstract: 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.

Abstract: In an embodiment, a driver-scoring device detects harsh events performed by an operator of a vehicle driven a number of distance units by the operator during a first period of time. Each of the detected harsh events has a respective g-force exceeding a threshold g-force. The driver-scoring device determines a penalty score including a ratio of a harsh-event score added to a sum of respective event-penalty scores for each of the detected harsh events to a metric score parameter. The harsh-event score includes a ratio of a number of the detected harsh events to the number of distance units driven by the operator during the first period of time. The respective event-penalty score for each of the detected harsh events includes a respective ratio of a penalty factor associated with the detected harsh event to the number of distance units driven by the operator during the first period of time.

Abstract: 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.