Matteo Pezzetta
Optimal Vehicle Assignment for a Dynamic Ride-Sharing Service and Spatiotemporal Taxi Demand Forecasting.
Rel. Giuseppe Carlo Calafiore, Marina Mondin. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2020
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Abstract
During the recent years, the transportation of persons and items is changing drastically. Shared mobility systems are providing flexible public travel modes comparable to private transportation systems at accessible prices. Companies like Uber, Lyft, Postmates are developing algorithms for managing their fleets of vehicles to accommodate ever-growing demands. In 2014 Uber announced UberPool, a ride-sharing service that nowadays accounts for 20% of the total Uber rides. Ride-sharing was born to fit the requests of more customers in one single vehicle ride, so that to decrease the service costs both for the providers and the customers. The complexity of the problem derives from the number of constraints influencing the system.
The goal is to efficiently manage the fleet, by reducing transportation costs and increasing the occupancy ratio of vehicles, while at the same time satisfying the most customers
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