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Smartphone Sensor Dataset for Driver Behavior Analysis.

Pawan Wawage1, Yogesh Deshpande1

  • 1Vishwakarma University, India.

Data in Brief
|March 14, 2022
PubMed
Summary

Researchers created a new smartphone sensor dataset for Indian drivers to improve machine learning models. This dataset captures key driving parameters to better understand and classify driver behavior.

Keywords:
DB classificationDriver behavior analysisMachine learningSmartphone sensor dataset

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Area of Science:

  • Computer Science
  • Transportation Engineering
  • Human-Computer Interaction

Background:

  • Driving requires significant cognitive load, with drivers often performing secondary tasks.
  • Accurately modeling realistic driver behavior presents a persistent challenge for researchers.
  • Existing datasets may not fully capture the nuances of diverse driving conditions and behaviors.

Purpose of the Study:

  • To develop a comprehensive dataset of driving behavior using smartphone sensors.
  • To facilitate the training and validation of machine learning models for driver behavior analysis.
  • To provide a valuable resource for understanding the impact of various driving parameters on driver actions.

Main Methods:

  • Utilized smartphone sensors, specifically accelerometers and gyroscopes, to collect driving data.
  • Collected data from Indian drivers across various driving scenarios.
  • Organized the dataset into a structured format with day-by-day folders and subfolders for accessibility.

Main Results:

  • Successfully constructed a novel dataset of smartphone sensor readings from Indian drivers.
  • The dataset includes critical driving parameters influencing driver behavior.
  • The data is organized for efficient use in machine learning model development.

Conclusions:

  • The developed dataset is expected to significantly aid in the training and testing of machine learning models.
  • This resource will support advancements in driver behavior classification and recognition.
  • The dataset offers a foundation for future research into intelligent driver assistance systems.