ODySSEUS is a data management and simulation software for mobility data, focused mostly on shared fleets in urban environments.
Its goal is to provide a general, easy-to-use framework to simulate shared mobility scenarios across different cities using real-world data.
At the following link you can find a User Guide and the API reference: https://odysseus-dev.readthedocs.io/en/latest/index.html
Below a list of publications concerning the development and the use of ODySSEUS:
[1] - Alessandro Ciociola, Michele Cocca, Danilo Giordano, Luca Vassio, Marco Mellia (2020) E-Scooter Sharing: Leveraging Open Data for System Design, In: 2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT), pages 1-8, ISBN: 978-1-7281-7343-6
[2] - Michelangelo Barulli, Alessandro Ciociola, Michele Cocca, Luca Vassio, Danilo Giordano, Marco Mellia (2020) On Scalability of Electric Car Sharing in Smart Cities, In: 2020 IEEE International Smart Cities Conference (ISC2), pages 1-8, ISBN: 978-1-7281-8294-0
[3] - Alessandro Ciociola, Dena Markudova, Luca Vassio, Danilo Giordano, Marco Mellia, Michela Meo (2020) Impact of Charging Infrastructure and Policies on Electric Car Sharing Systems, In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), pages 1-6, ISBN: 978-1-7281-4149-7
[4] - Alessandro Ciociola, Michele Cocca, Danilo Giordano, Marco Mellia, Andrea Morichetta, Andrian Putina, Flavia Salutari (2017) UMAP: Urban Mobility Analysis Platform to Harvest Car Sharing Data, In: Proceedings of the IEEE Conference on Smart City Innovations, ISBN: 978-1-5386-0435-9
[5] - Luca Pappalardo, Filippo Simini, Gianni Barlacchi and Roberto Pellungrini (2019). scikit-mobility: a Python library for the analysis, generation and risk assessment of mobility data, https://arxiv.org/abs/1907.07062
[6] - S. Fiorini, G. Pilotti, M. Ciavotta, and A. Maurino, (2020) “3D-CLoST: A CNN-LSTM Approach for Mobility Dynamics Prediction in SmartCities,” In: 2020 IEEE Big Data.