Routing and scheduling optimization for urban air mobility fleet management using quantum annealing.

ABSTRACT: The growing integration of urban air mobility (UAM) for urban transportation and delivery has accelerated due to increasing traffic congestion and its environmental and economic repercussions. Efficiently managing the anticipated high-density air traffic in cities is critical to ensure safe and effective operations. In this study, we propose a routing and scheduling framework to address the needs of a large fleet of UAM vehicles operating in urban areas. Using mathematical optimization techniques, we plan efficient and deconflicted routes for a fleet of vehicles. Formulating route planning as a maximum weighted independent set problem enables us to utilize various algorithms and specialized optimization hardware, such as quantum annealers, which has seen substantial progress in recent year

SUBMITTER: Haba R 

PROVIDER: S-EPMC11799414 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature