POSCA: Path Optimization for Solar Cover Amelioration in Urban Air Mobility

Urban Air Mobility (UAM) encompasses both piloted and autonomous aerial vehicles, spanning from small unmanned aerial vehicles (UAVs) like drones to passenger-carrying personal air vehicles (PAVs), to revolutionize smart transportation in congested urban areas. This emerging paradigm is anticipated to offer disruptive solutions to the mobility challenges in congested cities. In this context, a pivotal concern centers on the sustainability of transitioning to this mode of transportation, especially with the focus on incorporating clean technology into developing innovative solutions from the ground up. Recent studies highlight that a significant portion of the total energy consumption in UAM can be attributed to the flight operations of the aircraft. To address this challenge, this paper introduces a framework POSCA aimed at meeting the energy requirements of UAM flights. It delves into a complex and dynamic route-planning problem. It introduces a novel concept called the Phototropic Index, calculated by considering the traversal distance and solar coverage along the route. To solve the path planning problem, we propose two solutions, S-POSCA and D-POSCA, catering to static and dynamic setups. Simulation results confirm an average increase of 8.81% in static conditions and 10.64% in the dynamic condition for the cumulative Global Horizontal Irradiance (GHI) compared to the baseline approaches.