Castellano, AndreaCarbonara, GiuseppeDiaz, SergioMarcano, MauricioTango, FabioMontanari, RobertoStephanidis, ConstantineAntona, MargheritaNtoa, Stavroula2024-07-242024-07-242020Castellano , A , Carbonara , G , Diaz , S , Marcano , M , Tango , F & Montanari , R 2020 , Development of a Driver-State Adaptive Co-Driver as Enabler for Shared Control and Arbitration . in C Stephanidis , M Antona & S Ntoa (eds) , HCI International 2020 – Late Breaking Posters - 22nd International Conference, HCII 2020, Proceedings . Communications in Computer and Information Science , vol. 1294 , Springer Science and Business Media Deutschland GmbH , pp. 538-544 , 22nd International Conference on Human-Computer Interaction, HCI International 2020 , Copenhagen , Denmark , 19/07/20 . https://doi.org/10.1007/978-3-030-60703-6_69conference97830306070291865-0929https://hdl.handle.net/11556/2410Publisher Copyright: © 2020, Springer Nature Switzerland AG.For automated and partially automated cars, there are new crucial questions to answer: “When should the driver or the automated system take control of the vehicle?" ; and also: “Can both control the vehicle together at the same time, or can this create potential conflicts?". These are non-trivial issues because they depend on different conditions, such as the environment, driver’s state, vehicle capabilities, and fault tolerance, among others. This paper will describe a human-machine cooperation approach for collaborative driving maneuvers, developed in the EU funded project PRYSTINE. In particular, this study presents the work-in-progress and will focus attention on the proposed architecture design and the corresponding use case for testing.7enginfo:eu-repo/semantics/restrictedAccessconference output10.1007/978-3-030-60703-6_69ArbitrationHighly automated vehiclesHuman-machine cooperationShared controlGeneral Computer ScienceGeneral Mathematicshttp://www.scopus.com/inward/record.url?scp=85097232970&partnerID=8YFLogxK