TY - GEN
T1 - Mixed hybrid and electric bus dynamic fleet management in urban networks
T2 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2019
AU - Rinaldi, Marco
AU - Picarelli, Erika
AU - Laskaris, Georgios
AU - D'Ariano, Andrea
AU - Viti, Francesco
PY - 2019/6
Y1 - 2019/6
N2 - Reducing pollutant emissions and promoting sustainable mobility solutions, including Public Transport, are increasingly becoming key objectives for policymakers worldwide. In order to jointly achieve these goals, careful consideration should be put on the operational cost and management of PT services, in order to promote the adoption of green mobility solutions and advanced management techniques by operators. In this work we develop a dynamic fleet management approach for next generation Public Transportation systems, considering the instance of mixed electric / hybrid fleet. Our objective is that of investigating to what extent electrification, coupled with optimal fleet management, can yield operational cost savings for PT operators, explicitly considering real-Time disturbances, including delays, service disruptions etc. We propose a Mixed Integer Linear Program to address the problem of optimal scheduling of a mixed fleet of electric and hybrid / non-electric buses, and employ it as predictor in a Model Predictive Control approach. Test results based upon a real-life scenario showcase how the proposed approach is indeed capable of yielding a sizable reduction in operational costs, even when considerable disturbances arise from the underlying system.
AB - Reducing pollutant emissions and promoting sustainable mobility solutions, including Public Transport, are increasingly becoming key objectives for policymakers worldwide. In order to jointly achieve these goals, careful consideration should be put on the operational cost and management of PT services, in order to promote the adoption of green mobility solutions and advanced management techniques by operators. In this work we develop a dynamic fleet management approach for next generation Public Transportation systems, considering the instance of mixed electric / hybrid fleet. Our objective is that of investigating to what extent electrification, coupled with optimal fleet management, can yield operational cost savings for PT operators, explicitly considering real-Time disturbances, including delays, service disruptions etc. We propose a Mixed Integer Linear Program to address the problem of optimal scheduling of a mixed fleet of electric and hybrid / non-electric buses, and employ it as predictor in a Model Predictive Control approach. Test results based upon a real-life scenario showcase how the proposed approach is indeed capable of yielding a sizable reduction in operational costs, even when considerable disturbances arise from the underlying system.
KW - Dynamic bus fleet management
KW - e-bus charging scheduling
KW - MILP
KW - MPC
UR - http://www.scopus.com/inward/record.url?scp=85074946857&partnerID=8YFLogxK
U2 - 10.1109/MTITS.2019.8883387
DO - 10.1109/MTITS.2019.8883387
M3 - Conference contribution
AN - SCOPUS:85074946857
T3 - MT-ITS 2019 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems
BT - MT-ITS 2019 - 6th International Conference on Models and Technologies for Intelligent Transportation Systems
PB - Institute of Electrical and Electronics Engineers (IEEE)
Y2 - 5 June 2019 through 7 June 2019
ER -