This project received funding from the Shit2Rail Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement number No. 77640.
My-TRAC project aim was to deliver an innovative application for seamless transport and an ecosystem of models and algorithms for Public Transport – PT user choice simulation, data analytics and affective computing.
My-TRAC stand out from other technologies due to three main reasons. First, My-TRAC fostered unprecedented involvement of users during, before and after a trip through a smart Human-Machine interface and numerous functionalities such as crowdsourcing, group recommendations, data exchange. Second, the application implemented a vast array of technologies, such as affective computing, Artificial Intelligence and user choice simulation, that fuse expertise from multiple fields. Third, My-TRAC facilitated engagement of multiple stakeholders by seamlessly integrating services and creating connections between Rail operators, Mobility as a Service and other PT providers.
My-TRAC was designed as a traveller focused application with a mobile app front-end that connected information from various sources: (i) Public Transport (PT) operators for schedules and actual information (i.e., disruptions), (ii) MaaS providers/booking options (i.e., carsharing, bike-sharing, taxi services), (iii) Datasets related to the service and trip (i.e., crowd density at stations, accessibility) and relate this information with users’ preferences and state-of-mind.
My-TRAC app had two modes of operation: as a “common” travel companion or either as personal travel companion providing recommendations, either routes or activities personalized according to the specific characteristics of the traveller and the specific trip the person was doing. It was also the application in charge of collecting the data that were used to feed the models running at the backend and that were responsible for the personalized recommendations. Thus, My-TRAC clearly extended existing companion concepts through the introduction of human-like behaviour (Artificial Intelligence). To that extent, the application acted like a real ‘companion’ that would take the strain of organising travel under all circumstances, thus improving a traveller’s travel comfort and ease of travel.
