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Quantification of User Driving Behavior in Motorized Mobility Scooters using CNN-based Head Pose Estimation

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    Summary
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    Head movements can predict steering in Motorized Mobility Scooters (MMSs), offering insights into safer driving for elderly and mobility-impaired users. Quantifying head-steering lag helps identify risky driving patterns.

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    Area of Science:

    • Gerontology
    • Rehabilitation Engineering
    • Human Factors Engineering

    Background:

    • Growing concerns exist regarding the driving safety of Motorized Mobility Scooters (MMSs) among elderly and mobility-impaired populations.
    • Existing research primarily focuses on environmental hazard detection, with limited investigation into user behavior's impact on MMS driving safety.

    Purpose of the Study:

    • To develop and implement a Driving Status Logging (DSL) system for quantifying user behavior during MMS operation.
    • To analyze the temporal relationship between head movements and steering operations in MMS driving.
    • To explore the potential of head movement as a predictive index for steering actions and identify hazardous driving patterns.

    Main Methods:

    • Development of a novel Driving Status Logging (DSL) system to record user behavior.
    • Application of cross-correlation analysis to quantify the temporal relationship between head movements and steering operations.
    • Preliminary analysis of collected data to establish correlations and identify potential safety indicators.

    Main Results:

    • The developed DSL system successfully measured user behavior during MMS driving.
    • A significant temporal relationship was identified between head movement and steering operation.
    • Head movement was found to be a potential predictor of intended steering actions, with quantified head-steering lag time.

    Conclusions:

    • User behavior significantly impacts MMS driving safety, and quantitative measurement is feasible.
    • Head movement serves as a valuable index for predicting steering intentions in MMS users.
    • The quantified head-steering lag time offers a novel method for identifying and potentially mitigating hazardous driving patterns, enhancing overall MMS safety.