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Open AccessProceedings ArticleDOI

Listen To Your Drive: Sonification Architecture and Strategies for Driver State and Performance

TLDR
An in-vehicle interactive sonification system intended to integrate driving performance data and driver affective state data in real-time is developed using the medium-fidelity simulator and neurophysiological devices.
Abstract
Driving is mainly a visual task, leaving other sensory channels open for additional information communication. As the level of automation increases in vehicles, monitoring the state and performance of the driver and vehicle shifts from the secondary to primary task. Auditory channels provide the flexibility to display a wide variety of information to the driver without increasing the workload of driving task. It is important to identify types of auditory displays and sonification strategies that provide integral information necessary for the driving task, and not overload the driver with unnecessary or intrusive data. To this end, we have developed an in-vehicle interactive sonification system using the medium-fidelity simulator and neurophysiological devices. The system is intended to integrate driving performance data and driver affective state data in real-time. The present paper introduces the architecture of our invehicle interactive sonification system and potential sonification strategies for providing feedback to the driver in an intuitive and non-intrusive manner.

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Proceedings ArticleDOI

Tutorial on In-vehicle Auditory Interactions: Design and Application of Auditory Displays, Speech, Sonification, & Music

TL;DR: This tutorial aims to inspire practitioners as well as researchers to appropriately apply auditory displays and sonification to in-vehicle technologies, and thus, facilitate necessary multi-tasking processes in automotive user interfaces.
Proceedings ArticleDOI

Designing Adaptive Audio for Autonomous Driving: An Industrial and Academic-Led Design Challenge

TL;DR: The paper outlines a collaboration that is currently being established between Researchers at Swansea university and a major OEM that is set to examine user-centred approaches to designing audio that enhance and enrich human-experience with driving.
Proceedings ArticleDOI

The development of a dance-musification model with the use of machine learning techniques under COVID-19 restrictions

TL;DR: In this paper, the authors present the design and development of a model which takes as input a dancer's movement and outputs music, structurally related to dance, with the use of machine learning techniques.
References
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Multiple resources and performance prediction

TL;DR: One particular application of the theory, the 4-dimensional multiple resources model, is described in detail, positing that there will be greater interference between two tasks to the extent that they share stages, sensory modalities, codes and channels of visual information.
Journal ArticleDOI

Auditory Display: Sonification, Audification and Auditory Interfaces

TL;DR: This book presents a meta-modelling framework for automating the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and reconstructing musical structures in data from Chaotic Attraction.
Journal ArticleDOI

Fifty Years of Driving Safety Research

TL;DR: Improved crashworthiness has contributed to substantial improvements in driving safety over the past 50 years, but future improvements will depend on enhancing driver performance and perhaps, more important, improving driver behavior.
Journal ArticleDOI

Improvement of Road Safety Using Passive and Active Intelligent Vehicle Safety Systems

TL;DR: Some of the most promising and the most used intelligent vehicle safety systems, that enable to raise the level of road safety, are analised and possible solutions to deploying intelligent transport systems in Lithuania are introduced.
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