Integrated Routing and Charging Scheduling for Autonomous Electric Aerial Vehicle System

Abstract

Autonomous electric aerial vehicles (EAVs) are expected to bring fundamental changes to city infrastructures and daily commutes. Currently, the EAVs, including the delivery drones and the electric vertical takeoff and landing (eVTOL) air taxi, are all under limited battery endurance and vertiport capacity, which is insufficient for long-range commutes. In this paper, we propose a joint scheduling methodology to handle the optimal routing and charging tasks for the Autonomous Electric Aerial Vehicle System. By considering the unique characteristics of on-demand EAVs, the joint optimization problem can effectively utilize the system's resources. The problem is formulated by integrating charging features into the classic vehicle routing problem with time windows. To make it easy to solve, we further transform the nonlinear problem to a mixed integer linear program. The problem formulation and the operational constraints are both well validated through comprehensive simulations.