With the fast advancements of the Autonomous Vehicle (AV) industry, detection of Vulnerable Road Users (VRUs) using smartphones is critical for safety applications of Cooperative Intelligent Transportation Systems (C-ITSs). This study explores the use of low-power smartphone sensors and the Recurrence Quantification Analysis (RQA) features for this task. These features are computed over a thresholded similarity matrix extracted from nine channels: accelerometer, gyroscope, and rotation vector in each direction (x, y, and z). Given the high-power consumption of GPS, GPS data is excluded. RQA features are added to traditional time domain features to investigate the classification accuracy when using binary, four-class, and five-class Random Forest classifiers. Experimental results show a promising performance when only using RQA features with a resulted accuracy of 98. 34% and a 98. 79% by adding time domain features. Results outperform previous reported accuracy, demonstrating that RQA features have high classifying capability with respect to VRU detection.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Vulnerable Road User Detection Using Smartphone Sensors and Recurrence Quantification Analysis




    Publication date :

    2019-10-01


    Size :

    509532 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    VULNERABLE ROAD USER IDENTIFICATION SYSTEM

    ALTEKAR NIRAJ / RYAN MICHAEL / RAO JAYANTHI | European Patent Office | 2025

    Free access

    Urban Vulnerable Road User Localization using GNSS, Inertial Sensors and Ultra-Wideband Ranging

    de Ponte Muller, Fabian / Diaz, Estefania Munoz / Perul, Johan et al. | IEEE | 2020


    Vulnerable road user safety in APROSYS

    Hardy, Roger | Tema Archive | 2007


    SYSTEM AND METHOD FOR VULNERABLE ROAD USER DETECTION USING WIRELESS SIGNALS

    SOLMAZ GUERKAN / GARCIA GALVAO ALMEIDA MIGUEL | European Patent Office | 2019

    Free access