CHALLENGES RELATING TO THE INTER-FACILITY TRANSPORT OF HIGH ACUITY PAEDIATRIC CASES


A Traffic Flow Simulation Framework for Learning Driver Heterogeneity from Naturalistic Driving Data using Autoencoders

This paper proposes a novel data-centric framework for microscopic traffic flow simulation with intra and inter driver heterogeneity.We utilized a naturalistic driving corpus of 46 different drivers to learn and Electric Food Pan Carriers model the behavior divergence of Japanese drivers.First, ego-driver behavior signals are used to extract unique

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