Skip to main content

My TRAvel Companion

Deliverables

Continued assessment and improvement of the Human-Machine Interface

The report will expound on the changes performed on the HMI based on the feedback received from the pilots. Feedback concerning the HMI will be collected during the first months of pilot execution ensuring that at least half the time given for pilot execution is performed with a finalized version of the app.

Analytics Framework algorithms calibration

Settings and report of the fine-tuning of the model and algorithms for situation analysis and prediction factors both long-term data based advice, and short-term advice using sample data sets.

Elicitation of requirements document for My-TRAC

This will provide a requirements document for the rest of the tasks of this WP.

Final Summary Report of the Project

Will provide a full review of the project and conclusions to the achievements obtained. The report aims to address the scientific and technical findings of the project and provide a lookback on the methodologies, models etc. while articulating paths for future research and next steps for commercialization/implementation of the produce.

Model for analysing a user’s trip purpose (activities)

The model, based on a social machine, will predict activities of users and provide results to the model framework developed in T2.3. Furthermore, it will analyse user’s activities in trip sequences.

Lifelong training schemes for My-TRAC users

Training curriculum for all relevant stakeholders reported.

Continued assessment and improvement of the modelling framework

The report will expound on the changes performed on the modelling framework based on the feedback received from the pilots. Feedback concerning the modelling framework will be collected during the first months of pilot execution.

Continued assessment and improvement of the user-service algorithm

The report will expound on the changes performed on the user-service algorithm based on the feedback received from the pilots. Feedback concerning the user-service algorithm will be collected during the first months of pilot execution ensuring that at least half the time given for pilot execution is performed with a finalized version of the app.

Affective and Persuasive HMI concepts and models

Report for the unique “look and feel” UI concept of My-TRAC accompanied by a relevant style guide and UI libraries for mobile apps.

Roadmap for application improvements and extension

Based on D6.2 and D6.3, comments about enhancements to the application and improvements to the applications’ operation and models that are beyond the scope of the My-TRAC project, will arise. The comments will be used to create a roadmap to improve the application demonstrating the commitment of the consortium partners to further the work performed beyond the end of the My-TRAC project.

Final version of My-TRAC application

This will provide the final version of the mobile application that will take into account the assessment of the second version of the application obtained from T5.1 and the work done in T5.3 and T5.4, the anonymity obtained will be assessed in the report.

Operators’ platform

The operators’ platform will be a web-based interface and gateway for operators to communicate with My-TRAC’s data and services.

Project brochure (first version)

The project brochure will contain key information on the project targeted to the public and stakeholders. Two versions will be created in M12 and M24 respectively.

Project leaflet

Project leaflet.

Project brochure (second version)

The project brochure will contain key information on the project targeted to the public and stakeholders. Two versions will be created in M12 and M24 respectively.

Modelling framework for analysing user’s choices

The framework will utilize the factors determined in T2.1 and incorporate the model developed in T2.2. A model for predicting users’ mode, station, route and departure-time choices will be also formulated, estimated and incorporated in the framework. D2.3 will be extended in WP3.

Searching for OpenAIRE data...

Publications

Urban Travel Behaviour: A Cross-country Comparison

Author(s): Eleni Mantouka, Alexandros E. Papacharalampous, Ismini Stroumpou, Léonie Heydenrijk, Sanmay Shelat, Pablo Chamoso Santos, Joan Guisado-Gámez5, Evangelos Mitsakis, Viktoriya Degeler, Eleni I. Vlahogianni, Josep Lluís Larriba-Pey
Published in: hEART 2018: 7th Symposium of the European Association for Research in Transportation, 2018
Publisher: European Association for Research in Transportation

What does smart card data reveal about subjective beliefs regarding waiting time uncertainty?

Author(s): Sanmay Shelat, Malvika Dixit, Oded Cats, Niels van Oort, Hans van Lint
Published in: 8th International Conference on Transport Network Reliability, 2019
Publisher: INSTR 2021

Affective interfaces: a conceptual framework of emotional design at mobile routing applications

Author(s): Eleni Chalkia, Evangelos Bekiaris, George Yiannis
Published in: Proceedings of 8th Transport Research Arena TRA 2020, 2020
Publisher: TRA 2020
DOI: 10.26226/morressier.5e4fe9bd6bc493207536f88f

Unsupervised approach to bunching swings phenomenon analysis

Author(s): Viktoriya Degeler · Léonie Heydenrijk-Ottens · Ding Luo · Niels van Oort · Hans van Lint
Published in: CASPT 2018, 2018
Publisher: CASPT 2018

Supervised learning: Predicting passenger load in public transport

Author(s): Léonie Heydenrijk-Ottens · Viktoriya Degeler · Ding Luo · Niels van Oort · Hans van Lint
Published in: CASPT 2018, 2018
Publisher: CASPT 2018

Calibrating Route Choice Sets for an Urban Public Transport Network using Smart Card Data

Author(s): Sanmay Shelat, Oded Cats, Niels van Oort, Hans van Lint
Published in: 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 2019, Page(s) 1-8, ISBN 978-1-5386-9484-8
Publisher: IEEE
DOI: 10.1109/mtits.2019.8883366

Reputation Algorithm for Users and Activities in a Public Transport Oriented Application

Author(s): D. García-RetuertaA. RivasJoan Guisado-GámezE. AntoniouP. Chamoso
Published in: book: Ambient Intelligence – Software and Applications, 11th International Symposium on Ambient Intelligence, 2020, Page(s) 213-223
Publisher: Springer Nature Switzerland AG
DOI: 10.1007/978-3-030-58356-9_21

Extraction of Travellers’ Preferences Using Their Tweets

Author(s): Juan J. Cea-Morán, Alfonso González-Briones, Fernando De La Prieta, Arnau Prat-Pérez, Javier Prieto
Published in: Ambient Intelligence – Software and Applications - 11th International Symposium on Ambient Intelligence, 1239, 2021, Page(s) 224-235, ISBN 978-3-030-58355-2
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-58356-9_22

Unsupervised approach towards analysing the public transport bunching swings formation phenomenon

Author(s): Viktoriya Degeler, Léonie Heydenrijk-Ottens, Ding Luo, Niels van Oort, Hans van Lint
Published in: Public Transport, 2020, ISSN 1613-7159
Publisher: Springer Verlag
DOI: 10.1007/s12469-020-00251-z

Understanding Travel Behavior through Travel Happiness

Author(s): Eleni G. Mantouka, Eleni I. Vlahogianni, Alexandros E. Papacharalampous, Léonie Heydenrijk-Ottens, Sanmay Shelat, Viktoriya Degeler, Hans van Lint
Published in: Transportation Research Record: Journal of the Transportation Research Board, 2019, Page(s) 036119811983676, ISSN 0361-1981
Publisher: US National Research Council
DOI: 10.1177/0361198119836761

Integrating network science and public transport accessibility analysis for comparative assessment

Author(s): Ding Luo, Oded Cats, Hans van Lint, Graham Currie
Published in: Journal of Transport Geography, 80, 2019, Page(s) 102505, ISSN 0966-6923
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.jtrangeo.2019.102505