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  • Open Access

    ARTICLE

    Time-Series Data and Analysis Software of Connected Vehicles

    Jaekyu Lee1,2, Sangyub Lee1, Hyosub Choi1, Hyeonjoong Cho2,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2709-2727, 2021, DOI:10.32604/cmc.2021.015174

    Abstract In this study, we developed software for vehicle big data analysis to analyze the time-series data of connected vehicles. We designed two software modules: The first to derive the Pearson correlation coefficients to analyze the collected data and the second to conduct exploratory data analysis of the collected vehicle data. In particular, we analyzed the dangerous driving patterns of motorists based on the safety standards of the Korea Transportation Safety Authority. We also analyzed seasonal fuel efficiency (four seasons) and mileage of vehicles, and identified rapid acceleration, rapid deceleration, sudden stopping (harsh braking), quick starting, sudden left turn, sudden right… More >

  • Open Access

    ARTICLE

    NARX Network Based Driver Behavior Analysis and Prediction Using Time-series Modeling

    Ling Wu1, Haoxue Liu2, Tong Zhu2, Yueqi Hu3

    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 633-642, 2018, DOI:10.31209/2018.100000030

    Abstract The objective of the current study was to examine how experienced and inexperienced driver behaviour changed (including heart rate and longitudinal speeds) when approaching and exiting highway tunnels. Simultaneously, the NARX neural network was used to predict real-time speed with the heart rate regarded as the input variable. The results indicated that familiarity with the experimental route did decrease drivers’ mental stress but resulted in higher speed. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern how to establish the automated driver model in the simulation environment. More >

  • Open Access

    ARTICLE

    Unsupervised Time-series Fatigue Damage State Estimation of Complex Structure Using Ultrasound Based Narrowband and Broadband Active Sensing

    S.Mohanty1, A. Chattopadhyay2, J. Wei3, P. Peralta4

    Structural Durability & Health Monitoring, Vol.5, No.3, pp. 227-250, 2009, DOI:10.3970/sdhm.2009.005.227

    Abstract This paper proposes unsupervised system identification based methods to estimate time-series fatigue damage states in real-time. Ultrasound broadband input is used for active damage interrogation. Novel damage index estimation techniques based on dual sensor signals are proposed. The dual sensor configuration is used to remove electrical noise, as well as to improve spatial resolution in damage state estimation. The scalar damage index at any particular damage condition is evaluated using nonparametric system identification techniques, which includes an empirical transfer function estimation approach and a correlation analysis approach. In addition, the effectiveness of two sensor configurations (configuration 1: sensors placed near… More >

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