Abstract

This paper is an extension of work originally reported in SESAR Innovation Days 2018 : Zhengyi Wang, Man Liang, Daniel Delahaye. Automated Data-Driven Prediction on Aircraft Estimated Time of Arrival. SID 2018, 8th Sesar Innovations Days, Dec 2018, Salzburg, Austria. ⟨hal-01944608⟩; [...]

Abstract

This paper explores the potential of machine learning (ML) systems which use data from in-vehicle sensors as well as external IoT data sources to enhance autonomous driving for efficiency and safety in urban environments. We propose a system which combines sensor data from autonomous [...]

Abstract

A deep neural network-based approach of energy demand modeling of electric vehicles (EV) is proposed in this paper. The model-based prediction of energy demand is based on driving cycle time series used as a model input, which is properly preprocessed and transformed into 1D or 2D [...]