 | Up a level |
Meteier, Quentin; Capallera, Marine; de Salis, Emmanuel; Angelini, Leonardo; Carrino, Stefano; Widmer, Marino; Khaled, Omar Abou; Mugellini, Elena; Sonderegger, Andreas (2023). A dataset on the physiological state and behavior of drivers in conditionally automated driving Data in Brief, 47, p. 109027. Elsevier, Science Direkt 10.1016/j.dib.2023.109027
de Salis, Emmanuel; Meteier, Quentin; Capallera, Marine; Angelini, Leonardo; Andreas, Sonderegger; Abou Khaled, Omar; Mugellini, Elena; Widmer, Marino; Carrino, Stefano (2021). Predicting Takeover Quality in Conditionally Automated Vehicles Using Machine Learning and Genetic Algorithms In: Russo, Dario; Ahram, Tareq; Karwowski, Waldemar; Di Bucchianico, Giuseppe; Taiar, Redh (eds.) Intelligent Human Systems Integration 2021. Proceedings of the 4th International Conference on Intelligent Human Systems Integration (IHSI 2021): Integrating People and Intelligent Systems. February 22-24, 2021, Palermo, Italy. Advances in Intelligent Systems and Computing: Vol. 1322 (pp. 84-89). Cham: Springer 10.1007/978-3-030-68017-6_13
de Salis, Emmanuel; Meteier, Quentin; Pelletier, Colin; Capallera, Marine; Angelini, Leonardo; Sonderegger, Andreas; Khaled, Omar Abou; Mugellini, Elena; Widmer, Marino; Carrino, Stefano (2021). Clustering of drivers’ state before takeover situations based on physiological features using unsupervised machine learning In: Tareq Ahram, Redha Taiar (ed.) Human Interaction, Emerging Technologies and Future Systems V. Lecture Notes in Networks and Systems: Vol. 319 (pp. 550-555). Cham: Springer 10.1007/978-3-030-85540-6_69
Meteier, Quentin; Capallera, Marine; de Salis, Emmanuel; Sonderegger, Andreas; Angelini, Leonardo; Carrino, Stefano; Abou Khaled, Omar; Mugellini, Elena (2020). The Effect of Instructions and Context-Related Information about Limitations of Conditionally Automated Vehicles on Situation Awareness In: AutomotiveUI '20: 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 241-251). New York, NY, USA: ACM 10.1145/3409120.3410649
