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Study on dwell time optimization for Copenhagen metro

Giulia Terzolo

Study on dwell time optimization for Copenhagen metro.

Rel. Cristina Pronello. Politecnico di Torino, Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro), 2022


Both energy consumption and travel time are important indices to evaluate the efficiency of operations of metro rail systems. In the case of Copenhagen driverless metro, object of this study, optimization of trains' management during the trip is even more important because the automation in the system can bring to more satisfactory results than manually operated technologies. Little but significant changes can bring to very good improvements in the long run. This study proposes an optimization method to manage the time duration at each train stop during the trips, depending on the number of expected passengers willing to board at each station. This optimization procedure should maintain the service availability (SA) index constant but give the chance to the system to regulate the speed and trip dynamics of the vehicle in order to save energy. The methodology is structured according to four steps: 1) data generation; 2) database organization; 3) implementation of algorithms; and 4) REST APIs and dashboard design. The first step, data generation, consists in the creation of a people flow data simulator, used to deal with real information being temporarily unavailable. Data is then stored in a database (second step). The third step provides two algorithms: one in charge of providing information on the expected number of people in each station for the next hour and the other computing and suggesting the optimal dwell time for each stop at any time. This information is dynamically changed over time and new predictions are provided. Finally, since Hitachi is working on an integration directly on the system but the needed time to implement it in the real context is not compatible with this study, a dashboard reporting all the real time predictions and suggestions for the system is designed (fourth step). All the outcomes of this research activity, from the simulated data to the dwell optimization proposal, are displayed in the visualization tool (the dashboard) that is a strategic tool allowing the operators to use the described system as an "advisor", meanwhile the existent technology and new proposals are blended into one.

Relators: Cristina Pronello
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 69
Additional Information: Tesi secretata. Fulltext non presente
Corso di laurea: Corso di laurea magistrale in Ict For Smart Societies (Ict Per La Società Del Futuro)
Classe di laurea: New organization > Master science > LM-27 - TELECOMMUNICATIONS ENGINEERING
Aziende collaboratrici: HITACHI RAIL STS SPA
URI: http://webthesis.biblio.polito.it/id/eprint/24564
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