Feb 6, 2020 · This paper aims at investigating the usage of smartphone sensor data and machine learning methods to monitor abnormal driver behavior.
This paper aims at investigating the usage of smartphone sensor data and machine learning methods to identify abnormal driver behavior.
Abstract—This paper aims at investigating the usage of smartphone sensor data and machine learning methods to monitor abnormal driver behavior.
This work proposes to collect data sensors using Carla Simulator available in smartphones in order to classify the driver behavior using speed, acceleration ...
Feb 1, 2022 · Selected results compare the different implemented methods and show an effective ability to detect the driving behavior using limited sensor ...
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Dynamic Temporal Warping (DTW), Threshold-based approaches, and machine learning methods [3] are the three basic approaches to Smartphone-based driver behavior ...
This study presents a novel analysis framework for classifying driving behavior based on data gathered from passengers' smartphones.
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In this article we described some of the inner workings of our driving behavior modelling algorithms, and showed several real-life examples and results. We ...
Aug 29, 2023 · The paper reviews smartphone-based approaches to distracted driving behaviour detection, the smartphone sensors and detection methods applied, and the results ...
Apr 25, 2022 · Findings indicate that the smartphone-based algorithms may accurately detect four distinct patterns (braking, acceleration, left cornering and ...