Summary
Despite technological breakthroughs in connected and automated transport, the total transformation of existing transportation into a fully autonomous system is still decades away. In the meantime, mixed traffic environments with semi-autonomous vehicles proactively passing the dynamic driving task back to the human driver, whenever system limits are approached, is expected to become the norm. Such a Request to Intervene (RtI) can only be successful and met with trust by end-users if the driver state is continuously monitored and his/her availability properly evaluated and sufficiently triggered (through tailored human-machine interfaces - HMIs). In parallel, driver training has to evolve to account for the safe and sensible usage of semi-automated driving, whereas driver intervention performance has to be made an integral part of both driver and technology assessment. Besides, the ethical implications of automated decision-making need to be properly assessed, giving rise to novel risk and liability analysis models.
The vision of Trustonomy (a neologism from the combination of trust + autonomy) is to maximise the safety, trust and acceptance of automated vehicles by helping to address the aforementioned technical and non-technical challenges through a well-integrated and inter-disciplinary approach, bringing domain experts and ordinary citizens to work closely together. Trustonomy will investigate, setup, test and comparatively assess, in terms of performance, ethics, acceptability and trust, different relevant technologies and approaches, including driver state monitoring systems, HMI designs, risk models, and driver training methods. This will be done through both simulator and field based studies, in a variety of autonomous driving and RtI scenarios, covering different types of users (in terms of age, gender, driving experience, etc.), road transport modes (private cars, trucks, buses), levels of automation (L3 - L5) and driving conditions.
The vision of Trustonomy (a neologism from the combination of trust + autonomy) is to maximise the safety, trust and acceptance of automated vehicles by helping to address the aforementioned technical and non-technical challenges through a well-integrated and inter-disciplinary approach, bringing domain experts and ordinary citizens to work closely together. Trustonomy will investigate, setup, test and comparatively assess, in terms of performance, ethics, acceptability and trust, different relevant technologies and approaches, including driver state monitoring systems, HMI designs, risk models, and driver training methods. This will be done through both simulator and field based studies, in a variety of autonomous driving and RtI scenarios, covering different types of users (in terms of age, gender, driving experience, etc.), road transport modes (private cars, trucks, buses), levels of automation (L3 - L5) and driving conditions.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/815003 |
| Start date: | 01-05-2019 |
| End date: | 31-07-2022 |
| Total budget - Public funding: | 3 920 000,00 Euro - 3 920 000,00 Euro |
Cordis data
Original description
Despite technological breakthroughs in connected and automated transport, the total transformation of existing transportation into a fully autonomous system is still decades away. In the meantime, mixed traffic environments with semi-autonomous vehicles proactively passing the dynamic driving task back to the human driver, whenever system limits are approached, is expected to become the norm. Such a Request to Intervene (RtI) can only be successful and met with trust by end-users if the driver state is continuously monitored and his/her availability properly evaluated and sufficiently triggered (through tailored human-machine interfaces - HMIs). In parallel, driver training has to evolve to account for the safe and sensible usage of semi-automated driving, whereas driver intervention performance has to be made an integral part of both driver and technology assessment. Besides, the ethical implications of automated decision-making need to be properly assessed, giving rise to novel risk and liability analysis models.The vision of Trustonomy (a neologism from the combination of trust + autonomy) is to maximise the safety, trust and acceptance of automated vehicles by helping to address the aforementioned technical and non-technical challenges through a well-integrated and inter-disciplinary approach, bringing domain experts and ordinary citizens to work closely together. Trustonomy will investigate, setup, test and comparatively assess, in terms of performance, ethics, acceptability and trust, different relevant technologies and approaches, including driver state monitoring systems, HMI designs, risk models, and driver training methods. This will be done through both simulator and field based studies, in a variety of autonomous driving and RtI scenarios, covering different types of users (in terms of age, gender, driving experience, etc.), road transport modes (private cars, trucks, buses), levels of automation (L3 - L5) and driving conditions.
Status
CLOSEDCall topic
MG-3-3-2018Update Date
26-10-2022
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Organisations
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| algoWatt SpA (Coördinator)
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| AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
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| AITEK SPA (AITEK)
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| AUTOKLUB POZNANSKI OCTAVIUS
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| CATALINK LIMITED
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| INSTYTUT TRANSPORTU SAMOCHODOWEGO
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| INTRASOFT INTERNATIONAL SA
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| ITALSCANIA SPA
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| ROBOCAR TECHNOLOGIES SPOLKA Z OGRANICZONA ODPOWIEDZIALNOSCIA
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| SOLARIS BUS & COACH SPOLKA Z OGRANICZONA ODPOWIEDZIALNOSCIA
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| TTS Italia
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| TYOTEHOSEURA RY
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| UNIVERSITE GUSTAVE EIFFEL
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| UNIVERSITY OF LEEDS
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| University of Patras - PANEPISTIMIO PATRON