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Fuzzy System to Assess Dangerous Driving: A Multidisciplinary Approach.

Carlos Javier Ronquillo-Cana1, Pablo Pancardo1, Martha Silva1

  • 1Academic Division of Information Science and Technology, Juarez Autonomous University of Tabasco, Cunduacan 86690, Tabasco, Mexico.

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Summary

This study introduces a novel fuzzy system combining smartphone sensor data and questionnaires to assess dangerous driving behavior. The innovative approach enhances driver safety evaluations by integrating objective and subjective data for more accurate risk identification.

Keywords:
AHPDula dangerous driving indexdangerous drivingdriver behaviorfuzzy systemsintelligent transportation systems

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Area of Science:

  • Multidisciplinary approach integrating computer science and behavioral sciences for driver behavior analysis.

Background:

  • Dangerous driving poses significant risks, necessitating efficient assessment methods.
  • Existing methods rely on either objective sensor data or subjective questionnaire responses, each with limitations.
  • A holistic assessment requires combining both objective and subjective variables for a more realistic evaluation.

Purpose of the Study:

  • To propose a novel three-phase fuzzy system for evaluating driver behavior and social desirability.
  • To combine objective (sensor-based) and subjective (questionnaire-based) variables for a comprehensive driver assessment.
  • To mitigate the weaknesses of individual assessment approaches, such as sensor errors and respondent dishonesty.

Main Methods:

  • Development of a three-phase fuzzy system utilizing smartphone sensors and questionnaires.
  • Integration of objective variables (acceleration, turns, speed) and subjective variables (driving thoughts, perceptions).
  • Application of a combined fuzzy system to handle input vagueness and generate personalized driver assessments.

Main Results:

  • The proposed fuzzy system achieved an 84.21% efficiency in a real-world scenario.
  • Results were validated by mobility experts, confirming the system's reliability.
  • The system effectively combines objective and subjective data, overcoming individual discipline limitations.

Conclusions:

  • The developed fuzzy system offers a reliable and holistic method for assessing dangerous driving.
  • This approach can enhance driver safety, support intelligent transportation systems, and aid in personnel selection.
  • The integration of multidisciplinary data provides a more accurate and personalized driver behavior evaluation.