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Smart Mobility: Driver State Estimation and Advanced Driver-Vehicle Interfaces

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Mobility Engineering

Abstract

With increasingly complex user interfaces and advancing automation, measuring the state of the driver has never been more important. By using sensor fusion techniques we combine information from multiple sources to accurately and robustly measure the driver’s state—drowsiness and attention, workload and cognitive load, pleasure and anxiety. Only by integrating and synchronizing all the data streams can we properly understand the interaction of the driver and the vehicle.

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References

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Acknowledgments

DriveLab has been developed in the project ADVICE (Advanced Driver Vehicle Interface in a Complex Environment) [12], which is funded by the Dutch Ministry of Economic Affairs and will finish in December 2015. The partners in the project are: HAN University of Applied Sciences (www.han.nl/international/english/), Delft University of Technology (www.tudelft.nl/en/), Noldus Information Technology (www.noldus.com), TNO (www.tno.nl/en/), and TomTom (www.tomtom.com).

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Correspondence to Lucas P. J. J. Noldus .

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© 2017 Springer Nature Singapore Pte Ltd.

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Noldus, L.P.J.J., Spink, A.J., Bollen, R., Heffelaar, T. (2017). Smart Mobility: Driver State Estimation and Advanced Driver-Vehicle Interfaces. In: Tandon, M., Ghosh, P. (eds) Mobility Engineering . Springer, Singapore. https://doi.org/10.1007/978-981-10-3099-4_2

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  • DOI: https://doi.org/10.1007/978-981-10-3099-4_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3098-7

  • Online ISBN: 978-981-10-3099-4

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