This article describes an open-source platform for collecting multi-modal driver behavior data. The presented platform encompasses all essential components for efficient data collection, including hardware, software, and a rigorous simulation protocol. The hardware aspect involves the creation of a simulated driver environment including a realistic driving cockpit and position with a real seat, and non-invasive sensors to ensure non-intrusive data collection. The software component of our platform leverages the power of the Internet of Things (IoT) to enable seamless communication between various sensors in an atomic and scalable manner. Through the implementation of a thoughtfully designed simulation protocol, driver data is systematically gathered in controlled and replicable scenarios featuring varying stress levels. The presented work therefore offers a comprehensive and effective solution for gathering essential data to advance the development of Drive Status Monitoring (DSM) systems.

Bianco, S., Celona, L., Gallo, G., Napoletano, P. (2023). A Platform for Multi-Modal Driver Behaviour Data Collection. In 2023 IEEE 13th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) (pp.112-116) [10.1109/ICCE-Berlin58801.2023.10375673].

A Platform for Multi-Modal Driver Behaviour Data Collection

Bianco, Simone;Celona, Luigi
;
Gallo, Giovanni Donato;Napoletano, Paolo
2023

Abstract

This article describes an open-source platform for collecting multi-modal driver behavior data. The presented platform encompasses all essential components for efficient data collection, including hardware, software, and a rigorous simulation protocol. The hardware aspect involves the creation of a simulated driver environment including a realistic driving cockpit and position with a real seat, and non-invasive sensors to ensure non-intrusive data collection. The software component of our platform leverages the power of the Internet of Things (IoT) to enable seamless communication between various sensors in an atomic and scalable manner. Through the implementation of a thoughtfully designed simulation protocol, driver data is systematically gathered in controlled and replicable scenarios featuring varying stress levels. The presented work therefore offers a comprehensive and effective solution for gathering essential data to advance the development of Drive Status Monitoring (DSM) systems.
slide + paper
Driver behaviour,driver monitoring,framework,multi-modal signals,data collection
English
IEEE 13th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) - 03-05 September 2023
2023
2023 IEEE 13th International Conference on Consumer Electronics - Berlin (ICCE-Berlin)
9798350324150
2023
112
116
none
Bianco, S., Celona, L., Gallo, G., Napoletano, P. (2023). A Platform for Multi-Modal Driver Behaviour Data Collection. In 2023 IEEE 13th International Conference on Consumer Electronics - Berlin (ICCE-Berlin) (pp.112-116) [10.1109/ICCE-Berlin58801.2023.10375673].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/455219
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