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| Mouftah, Hussein T. |
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| Dugay, Fabrice |
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| Rettenmeier, Max |
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| Tomasch, Ernst | Graz |
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| Cornaggia, Greta |
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| Palacios-Navarro, Guillermo |
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| Uspenskyi, Borys V. |
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| Khan, Baseem |
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| Fediai, Natalia |
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| Derakhshan, Shadi |
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| Somers, Bart | Eindhoven |
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| Anvari, B. |
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| Kraushaar, Sabine | Vienna |
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| Kehlbacher, Ariane |
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| Das, Raj |
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| Werbińska-Wojciechowska, Sylwia |
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| Brillinger, Markus |
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| Eskandari, Aref |
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| Gulliver, J. |
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| Loft, Shayne |
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| Kud, Bartosz |
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| Matijošius, Jonas | Vilnius |
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| Piontek, Dennis |
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| Kene, Raymond O. |
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| Barbosa, Juliana |
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Anvari, B.
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Publications (9/9 displayed)
- 2025Correlation between reaction time, multi-modal feedback and take-over requests for level 3 automated vehicles
- 2024Chapter Nine - Planning and operational considerations for a drone logistics futurecitations
- 2022Developing and evaluating a coordinated person-based signal control paradigm in a corridor network
- 2020Comparison of fleet size determination models for horizontal transportation of shipping containers using automated straddle carrierscitations
- 2019Evaluating the Impact of an Integrated Urban Design of Transport Infrastructure and Public Space on Human Behavior and Environmental Quality: A Case Study in Beijing
- 2017Simulating the impact of urban transport infrastructure design on local air quality in Beijing
- 2016A multi-objective GA-based optimisation for holistic Manufacturing, transportation and Assembly of precast constructioncitations
- 2016Calibration and Validation of a Shared Space Model Case Study
- 2014Shared space modeling based on social forces and distance potential fieldcitations
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article
Correlation between reaction time, multi-modal feedback and take-over requests for level 3 automated vehicles
Abstract
We are currently experiencing a paradigm shift towards fully automated vehicles (AVs). On the way towards fully AVs, we will experience an increase in numbers of automated vehicles on our roads, requiring the human driver to take back control in situations, which cannot be handled by the vehicle. These human-robot take-over requests (TORs) can lead to safety risks, in particular in scenarios when the driver fails to understand the TOR and, hence, lacks situational awareness (SA). In this paper, the correlation between reaction time, multimodal feedback, informing the human driver of a transition in automation level, and success of transfer of control has been investigated. Nineteen human drivers have participated in experiments in a full-sized driving simulator: First, the driver was engaged in a secondary reading task while the car was in self-driving mode. Then, a TOR indicated to the driver to take back control. Seven different feedback modalities for the TORs have been created consisting of an audio chime, a visual cue or a static mechano-tactile haptic feedback, or a combination of these. The mechano-tactile feedback is hereby given through soft pneumatic actuators embedded into a novel soft robotic driver’s seat. After the driver experienced the TOR, they were given seven seconds to regain SA, retake the driving task and react to a road incident ahead. Based on the results, it can be concluded that reaction times below 2.6 seconds and above 6 seconds result in an unsuccessful transfer of control. Additionally, we have found that haptic feedback results in a timely and safe transfer of control within a shorter time frame, when added to currently commercially available auditory and visual feedback.
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