Scientific coordinator:

Partners:
CNR-STIIMA (IT)
CNR-ITB (IT)
IRCCS E. Medea – La Nostra Famiglia (IT)
UniverLecco (IT)

Type: INAIL

End date: 2023

Start date: 2020

Duration: 36

Overall budget: € 1.225.000,00

Funding: € 1.100.000,00

CNR cost: € 1.225.000,00

CNR funding: € 1.100.000,00

STIIMA budget: € 973.000,00

STIIMA funding: € 892.800,00

Coordinator: STIIMA-CNR

Simulatore di guida per assistere operatori nella valutazione delle capacità di guida dell’utente e nella scelta degli ausili di cui dotare l’automobile

The Rip@rto project aims to create a tool capable of supporting the staff of the INAIL Prosthesis Center in the process of assessing the driving skills of people with disabilities and defining the appropriate aids with which to adapt the vehicles. The result of Rip@rto may, in the future, become a tool to support the decision regarding the issue of the special driving license.

The project involves the construction of a driving simulator and a decision support system (DSS) that will allow: (1) to evaluate the user’s abilities in different driving situations, (2) to formalize the knowledge of expert operators regarding the aids and (3) to support the decision to use them, also thanks to the collection of objective data coming from the sensors integrated in the final system.

The Rip@rto simulator will allow the objective measurement of the actual abilities of the user in realistic scenarios, both ordinary and unforeseen. Thanks to the integrated sensor system on the dashboard and to the measurement of the EEG trace, the simulator will be able to objectively measure the user’s motor (reaction times, force exerted, etc.) and cognitive (cognitive load) parameters, providing a complete characterization of the capacity of the latter. The DSS will use this data and, thanks also to the formalization of the person’s state of health, will be able to assist the operator in identifying appropriate sets of aids and in choosing the changes to be made to the vehicle, with the aim of responding precisely to the specific needs of the patient.

Key research outcomes:

  • Rip@rto ontology – Turtle syntax (OWL file)
  • Spoladore, D., Cilsal, T., Mahroo, A., Trombetta, A., Sacco, M. (2022). Towards an Ontology-Based Decision Support System to Support Car-Reconfiguration for Novice Wheelchair Users. In: Miesenberger, K., Kouroupetroglou, G., Mavrou, K., Manduchi, R., Covarrubias Rodriguez, M., Penáz, P. (eds) Computers Helping People with Special Needs. ICCHP-AAATE 2022. Lecture Notes in Computer Science, vol 13342. Springer, Cham. https://doi.org/10.1007/978-3-031-08645-8_52
  • Mastropietro, A., Pirovano, I., Marciano, A., Porcelli, S., & Rizzo, G. (2023). Reliability of mental workload index assessed by eeg with different electrode configurations and signal pre-processing pipelines. Sensors23(3), 1367.
  • Mondellini, M., Pirovano, I., Colombo, V., Arlati, S., Sacco, M., Rizzo, G., & Mastropietro, A. (2023). A Multimodal Approach Exploiting EEG to Investigate the Effects of VR Environment on Mental Workload. International Journal of Human–Computer Interaction, 1-13.