Several elements can affect the drivers' behaviour while they are performing driving activities. Ranging from visual to cognitive distractions, emotions and other drivers' conditions (that could emerge from biometric data, such as temperature, heartbeat, pressure, etc.) can play a significant role, performing as a factor that can increase drivers' response time. This could be crucial in avoiding dangerous situations and in deciding and performing actions that could influence the happening of car accidents. This paper introduces the concept of the "Fitness-to-Drive" index and aims to evaluate how the arousal effects can influence the drivers' status. The paper presents some experimental evaluations we have conducted on a driver simulator, discussing the obtained results.

Andruccioli, M., Mengozzi, M., Presta, R., Mirri, S., Girau, R. (2023). Arousal effects on Fitness-to-Drive assessment: algorithms and experiments. New York : IEEE [10.1109/CCNC51644.2023.10060261].

Arousal effects on Fitness-to-Drive assessment: algorithms and experiments

Mengozzi, M;Mirri, S;Girau, R
2023

Abstract

Several elements can affect the drivers' behaviour while they are performing driving activities. Ranging from visual to cognitive distractions, emotions and other drivers' conditions (that could emerge from biometric data, such as temperature, heartbeat, pressure, etc.) can play a significant role, performing as a factor that can increase drivers' response time. This could be crucial in avoiding dangerous situations and in deciding and performing actions that could influence the happening of car accidents. This paper introduces the concept of the "Fitness-to-Drive" index and aims to evaluate how the arousal effects can influence the drivers' status. The paper presents some experimental evaluations we have conducted on a driver simulator, discussing the obtained results.
2023
2023 IEEE 20th Consumer Communications & Networking Conference (CCNC)
366
371
Andruccioli, M., Mengozzi, M., Presta, R., Mirri, S., Girau, R. (2023). Arousal effects on Fitness-to-Drive assessment: algorithms and experiments. New York : IEEE [10.1109/CCNC51644.2023.10060261].
Andruccioli, M; Mengozzi, M; Presta, R; Mirri, S; Girau, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/942502
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