In this paper an approach to the many-to-many carpooling problem with automated passenger aggregation is presented. The proposed solution allows to optimally solve the related routing problem, by relying on a constrained shortest path algorithm, for users travelling within multiple transportation networks, thus enabling multi-modality, and exploits the users' availability to be aggregated into carpools. The mathematical model behind the proposed approach is illustrated. Then, an algorithmic procedure capable of reasonably coping with the complexity that arises in real-sized scenarios, often characterized by multiple heterogeneous data sources, is discussed. Finally, simulations are reported in order to evaluate the effectiveness and the performance of the proposed approach.

On the many-to-many carpooling problem in the context of multi-modal trip planning

Lorenzo Ricciardi Celsi;
2017-01-01

Abstract

In this paper an approach to the many-to-many carpooling problem with automated passenger aggregation is presented. The proposed solution allows to optimally solve the related routing problem, by relying on a constrained shortest path algorithm, for users travelling within multiple transportation networks, thus enabling multi-modality, and exploits the users' availability to be aggregated into carpools. The mathematical model behind the proposed approach is illustrated. Then, an algorithmic procedure capable of reasonably coping with the complexity that arises in real-sized scenarios, often characterized by multiple heterogeneous data sources, is discussed. Finally, simulations are reported in order to evaluate the effectiveness and the performance of the proposed approach.
2017
978-1-5090-4533-4
future internet networks
learning based approach
car pooling problem
experience control
quality
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12606/23777
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