Impact of Autonomous Solutions on Electric Earthmoving Design Using Machine Learning: Case Study

Abstract

The increased development in automated driving systems (ADS) has opened up significant opportunities to revolutionize mobility and to set the path for technologies, such as electrification. The proposed methodology is a simulation model backed by a multi-objective optimization algorithm. This research investigates the adoption of future technologies in earthmoving application and explores its implications on the design of future machine concepts in terms of equipment size. The shift from “elephant to ants” in the machine selection, resulted in improved feasibility.