Abstract
A safe and smooth driving experience is one devoid of stressful events. To improve overall trip smoothness and driver safety, with user permission, the techniques of this disclosure utilize environmental factors (e.g., road geometry, weather, narrow lanes, etc.) and identify risky driver actions (e.g., speeding, sharp deceleration, etc.) to predict the likelihood of an unfavorable driving outcome. With user permission, dangerous driving maneuvers are identified using data from smartphone sensors such as GPS and inertial sensors such as the accelerometer, gyroscope, and magnetometer, e.g., on a smartphone or other device in the vehicle. A machine learning model, provided as part of a smartphone application, such as a mapping and navigation application, is utilized to analyze the data obtained from the inertial sensors. Results from the machine learning model are used for mitigation strategies such as routing advisories, dynamic UI alerts, refinement of driver assistance features, etc., designed to reduce or eliminate unfavorable driving outcomes.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
N/A, "Driver Safety Improvements Using Data From Smartphone Sensors", Technical Disclosure Commons, (July 01, 2020)
https://www.tdcommons.org/dpubs_series/3391