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| Seuring, Stefan |
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| Nor Azizi, S. |
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| Pato, Margarida Vaz |
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| Kölker, Katrin |
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| Huber, Oliver |
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| Király, Tamás |
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| Spengler, Thomas Stefan |
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| Al-Ammar, Essam A. |
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| Dargahi, Fatemeh |
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| Mota, Rui |
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| Mazalan, Nurul Aliah Amirah |
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| Macharis, Cathy | Brussels |
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| Arunasari, Yova Tri |
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| Nunez, Alfredo | Delft |
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| Bouhorma, Mohammed |
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| Bonato, Matteo |
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| Fitriani, Ira |
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| Autor Correspondente Coelho, Sílvia. |
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| Pond, Stephen |
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| Okwara, Ukoha Kalu |
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| Toufigh, Vahid |
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| Campisi, Tiziana | Enna |
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| Ermolieva, Tatiana |
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| Sánchez-Cambronero, Santos |
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| Agzamov, Akhror |
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Filtness, Ashleigh
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (20/20 displayed)
- 2023Framework for behaviour change implemented in real-time and post-trip interventions of the H2020 i-DREAMS naturalistic driving project
- 2023State-of-the-art Technologies for Post-Trip Safety Interventions
- 2023Effectiveness of real-time and post-trip interventions from the H2020 i-DREAMS naturalistic driving project: A Sneak Preview
- 2022Investigating the effects of sleepiness in truck drivers on their headway: an instrumental variable model with grouped random parameters and heterogeneity in their meanscitations
- 2022Methodology for the Evaluation of Safety Interventions
- 2022Investigating the effects of sleepiness in truck drivers on their headway: An instrumental variable model with grouped random parameters and heterogeneity in their meanscitations
- 2021Autonomous Vehicles and Vulnerable Road-Users—Important Considerations and Requirements Based on Crash Data from Two Countriescitations
- 2021The i-DREAMS intervention strategies to reduce driver fatigue and sleepiness for different transport modescitations
- 2021Post-trip safety interventions: State-of-the-art, challenges, and practical implicationscitations
- 2021Modelling driver decision-making at railway level crossings using the abstraction decomposition spacecitations
- 2019Riding the emotional roller-coaster: Using the circumplex model of affect to model motorcycle riders’ emotional state-changes at intersectionscitations
- 2019What do driver educators and young drivers think about driving simulators? A qualitative draw-and-talk studycitations
- 2019Riding the emotional roller-coastercitations
- 2019The effect of psychosocial factors on perceptions of driver education using the goals for driver education frameworkcitations
- 2019Review and ranking of crash risk factors related to the road infrastructurecitations
- 2018A mixed-methods study of driver education informed by the Goals for Driver Education: Do young drivers and educators agree on what was taught?citations
- 2018Serious Road Traffic Injuries in Europe, Lessons from the EU Research Project SafetyCubecitations
- 2018Burden of injury of serious road injuries in six EU countriescitations
- 2016Identification of Road User related Risk Factors. SAfetyCube Deliverable 4.1
- 2016Identification of Road User related Risk Factors. SAfetyCube Deliverable 4.1
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document
The i-DREAMS intervention strategies to reduce driver fatigue and sleepiness for different transport modes
Abstract
Driver sleepiness and fatigue are important contributors to many transport incidents and significantly increase crash risk. Recently, detection systems have been developed which aim to monitor the state of the driver and detect increasing levels of fatigue. However, there has been less focus on appropriate intervention strategies for drivers once fatigue and sleepiness have been detected. This paper describes the i-DREAMS fatigue intervention strategies, which aim to keep drivers within a safe driving zone. Interventions will be provided both in real-time and post-trip and can be customized to be used with a variety of transport modes. Real-time interventions will measure fatigue through trip duration, and driver sleepiness through heart-rate variability (HRV) information, obtained by means of sensors in the steering wheel or a wearable device, and attributed to Karolinska Sleepiness Score (KSS) bands. Thresholds for warnings will map onto phases of a ‘Safety Tolerance Zone’ and will be dynamic – changing as the driver state and driving situation develops. Post-trip interventions will aggregate data throughout the duration of the drive and aim to provide customized feedback and coping tips related to driver levels of fatigue and sleepiness, to improve driving behavior. Goals and challenges will add a gamified aspect to the post-trip interventions. The next stage of the development of the i-DREAMS fatigue intervention strategy is to test the concept in a series of simulator and field trials. Future research should explore acceptance and compliance of interventions and frequency of alerts.
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