Lyft, Inc.

Devjit Chakravarti

Julien Van Hout

Alexander Wesley Contryman

Alya Abbott

Zhan Zhang

James Kevin Murphy

Michael Jonathan DiCarlo

Ashivni Shekhawat

Renee Hei-Kyung Park

Gautam Kedia

This disclosure describes a vehicle-motion-analysis system that can align axes for a provider device and a corresponding transportation vehicle based on the provider device's location and motion data as a basis for generating driving-event scores for particular driving events. In particular, the disclosed systems can generate axes-rotation parameters that align axes of a provider device with axes of a transportation vehicle. In addition, the disclosed systems can identify motion paths, motion patterns, or other driving behaviors that occur during particular driving events. Further, the disclosed systems can generate driving-event scores for such driving events and can customize a graphical user interface based on the driving-event scores to reflect a provider rating and/or a location rating.

Aligning provider-device axes with transportation-vehicle axes to generate driving-event scores

The present application discloses systems, methods, and computer-readable media that can utilize a handheld-movement-detection model to detect whether a computing device is moved by hand or otherwise by a person within a vehicle. For instance, the disclosed systems can receive movement data from a computing device and generate filtered signals. Subsequently, the disclosed systems can utilize the handheld-movement-detection model to convert the filtered signals into a binary movement-classification signal (based on a signal threshold) to indicate the presence of handheld movement of a device. Furthermore, the disclosed systems can also utilize movement data from a computing device to detect whether the computing device is mounted and/or to detect vehicular movements. Additionally, the disclosed systems can configure (or adjust) parameters of the handheld-movement-detection model by utilizing movement data from a computing device that is secured to a vehicle and movement data of a computing device that is moveable within the vehicle.

Detecting handheld device movements utilizing a handheld-movement-detection model

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Orinda, CA, United States of America

Devjit Chakravarti