This paper deals with the problem of reducing fuel consumption and pollutant emissions of Heavy Duty Vehicles (HDVs). The overall objective of improving the efficiency of the HDVs can be obtained by employing additional information about road topography, altitude or slope, traffic and weather conditions. To this aim, a cloud computing architecture is proposed to support the fleet companies to manage the HDV route planning. The cloud system receives the transport mission data (departure, destination, waypoints, maximum mission duration time, etc.) and calculates the best eco route and the optimal velocity profiles minimizing fuel consumptions by a cloud-based optimizer. Some case studies show the efficiency (fuel consumption savings and travel times) of the proposed smart technology.

A Cloud Computing Architecture for Eco Route Planning of Heavy Duty Vehicles / Fanti, Maria Pia; Mangini, Agostino M.; Rotunno, Giuliana; Fiume, Giambattista; Favenza, Alfredo; Gaetani, Manuel. - ELETTRONICO. - (2018), pp. 8560498.730-8560498.735. (Intervento presentato al convegno 14th IEEE International Conference on Automation Science and Engineering, CASE 2018 tenutosi a Munich, Germany nel August 20-24, 2018) [10.1109/COASE.2018.8560498].

A Cloud Computing Architecture for Eco Route Planning of Heavy Duty Vehicles

Maria Pia Fanti;Agostino M. Mangini;Giuliana Rotunno;
2018-01-01

Abstract

This paper deals with the problem of reducing fuel consumption and pollutant emissions of Heavy Duty Vehicles (HDVs). The overall objective of improving the efficiency of the HDVs can be obtained by employing additional information about road topography, altitude or slope, traffic and weather conditions. To this aim, a cloud computing architecture is proposed to support the fleet companies to manage the HDV route planning. The cloud system receives the transport mission data (departure, destination, waypoints, maximum mission duration time, etc.) and calculates the best eco route and the optimal velocity profiles minimizing fuel consumptions by a cloud-based optimizer. Some case studies show the efficiency (fuel consumption savings and travel times) of the proposed smart technology.
2018
14th IEEE International Conference on Automation Science and Engineering, CASE 2018
978-1-5386-3593-3
A Cloud Computing Architecture for Eco Route Planning of Heavy Duty Vehicles / Fanti, Maria Pia; Mangini, Agostino M.; Rotunno, Giuliana; Fiume, Giambattista; Favenza, Alfredo; Gaetani, Manuel. - ELETTRONICO. - (2018), pp. 8560498.730-8560498.735. (Intervento presentato al convegno 14th IEEE International Conference on Automation Science and Engineering, CASE 2018 tenutosi a Munich, Germany nel August 20-24, 2018) [10.1109/COASE.2018.8560498].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/194430
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