A data recording mobile application to create datasets of vehicle users’ routines

One of today's automotive research focus is the development of vehicles for the future, with their own intelligence, aware of their occupants, able to give support to its users, striving for natural and efficient interaction, and giving rise to the concept of the cognitive vehicle. Furthermore, truly adaptive intelligence can be achieved with assistance systems capable of adapting to different drivers. Vehicles with the potential to learn users' routines and preferences, and make decisions to prepare the next trip (e.g., manage comfort; check if the usual objects are being transported), is a concrete example that has started gaining attention. To accomplish such a challenge, data-driven approaches are required. Hence, datasets that include information on the habits of different vehicle occupants and their preferences are essential for building cognitive computational models. To the best of our knowledge, there is no tool capable of obtaining these data in a real-world situation. Thus, this work proposes a mobile application capable of collecting real data and creating datasets about: (1) where and when the driver and passengers get in and out of the vehicle; (2) objects brought/taken by the occupants; and (3) vehicle settings preferences. Collected data are internally structured in files that can be uploaded at any time. The developed mobile application can be described as an easy-to-use, flexible, and free of charge solution for collecting data on the travel routines of vehicle occupants, to support the development of personalized assistance systems.This work received financial support from European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) and national funds, through ADI (Project “Easy Ride: Experience iseverything", ref POCI-01-0247-FEDER-039334), FCT – Fundação para a Ciência e Tecnologia and Bosch Car Multimedia Ph.D. fellowship PD/BDE/150498/2019, and R&D Units Project Scope: UIDB/00319/2020 and UIDB/00013/2020