This paper presents a cloud system devoted to provide to Vehicles (HDVs) the route that guarantees the minimum fuel consumption by respecting the maximum travel time. To this aim, given a specified mission, the Cloud Optimizer builds a route network collecting the main possible routes from the assigned origin to the destination. Moreover, an updated HDV longitudinal model that integrates predictive traffic, weather conditions, road topography and load factor is presented in order to determine the optimized velocity and gear profiles. Finally, the cloud system finds the route the minimizes the fuel consumption and the travel time by finding the minimum path in the weighted route network.
A Cloud Optimizer for Eco Route Planning of Heavy Duty Vehicles / Difilippo, Gianvito; Fanti, Maria Pia; Fiume, Giambattista; Mangini, Agostino Marcello; Monsel, Nicolas. - ELETTRONICO. - 2018-:(2019), pp. 8619149.7142-8619149.7147. (Intervento presentato al convegno 57th IEEE Conference on Decision and Control, CDC 2018 tenutosi a Miami Beach, FL nel December 17-19, 2018) [10.1109/CDC.2018.8619149].
A Cloud Optimizer for Eco Route Planning of Heavy Duty Vehicles
Maria Pia Fanti;Agostino Marcello Mangini;
2019-01-01
Abstract
This paper presents a cloud system devoted to provide to Vehicles (HDVs) the route that guarantees the minimum fuel consumption by respecting the maximum travel time. To this aim, given a specified mission, the Cloud Optimizer builds a route network collecting the main possible routes from the assigned origin to the destination. Moreover, an updated HDV longitudinal model that integrates predictive traffic, weather conditions, road topography and load factor is presented in order to determine the optimized velocity and gear profiles. Finally, the cloud system finds the route the minimizes the fuel consumption and the travel time by finding the minimum path in the weighted route network.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
