Public transport experience

In getting from A to B by public transport, citizens are generally left to their own experience, devices, applications, and discovery. There is a broad range of different transport services, such as trams, trains, busses, car-sharing, ride-sharing, etc. But travelers have limited access to integrated door-to-door information on a given journey.

My-TRAC – “My Travel Companion” researches and develops user-centric services platform designed for users as well as public and private transport operators. This improves the passenger experience by developing and applying advanced behavioral transport analytics and artificial intelligence (AI) algorithms. It develops a smartphone application to connect information from public transport operators, MaaS providers and datasets related to the service and journey.

From a traveler’s perspective it helps you develop greater confidence in, and adhesion to, multimodal transport services. My-TRAC is a software application that functions as a travel companion. It is designed to operate like a human companion, who understands attributes and state-of-mind of the traveler to derive conclusions from vague information - similar to how human companions do this. My-TRAC is designed to function also as a traveller’s gateway to various services that are related to public transport with rail travel at its core. The application would thus provide predictive information about potential disruptions and disturbances, for instance, and display and analyze data with innovative algorithms that recommend best solutions.

The My-TRAC application also involves operators of public transport. The operators can retrieve and visualize aggregated data on users’ movements and state-of-mind, to make better strategic and dynamic operational decisions. The data that is retrieved by the operators is aggregated and anonymized and thereby integrating the “privacy-by-design” concept. And lastly, all models and algorithms are applied on the mobile device of the user itself.

The My-TRAC application will be tested in four pilot locations in cooperation with local operators including NS (Dutch Railways), Attiko Metro, the metro and train operator in Athens, Greece, Ferrocarrils de la Generalitat de Catalunya, rail operator in Catalonia, Spain, and Fertagus, commuter rail operator in Lisbon, Portugal.

The project team will rely on collaboration with NS and GVB (Gemeentelijk Vervoerbedrijf) for collecting data about long distance public transportation activities in the Netherlands.

What is unique about the project?
The My-TRAC application stands out from other technologies for three reasons: 1) My-TRAC fosters unprecedented involvement of users before, during and after a trip by using a human-machine interface and various functionalities like crowdsourcing, group recommendations and data exchange. 2) My-TRAC implements a technologies such as affective computing, AI (artificial intelligence) and user choice simulation which fuse expertise interdisciplinary. 3) My-TRAC connects multiple stakeholders by integrating services from rail operators, mobility-as-a-service and other public transport providers.

This project is integral to AMS Institute’s original Urban Mobility Lab in 2014 and the lab’s original series of projects. Thus, all developments and projects which enabled rich collection of both derived and acquired data are to be implemented in the My-TRAC project. In sum, My TRAC’s is then the first full-scale integration of public transport data that allows for multi-scale, multi-modal and analytical tooling which opens new developments in the years following 2018.

My-TRAC is co-funded by the European Union under Horizon 2020, Research and Innovation Directorate General under Grant Agreement n° 777640.

  • September 2017 - September 2020
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Delft University of Technology (TU Delft)