Optimization of dispatch in urban aerial taxi sharing systems

In the context of increasing urban traffic congestion and the swift development of cutting-edge technologies, notably the latest advancements in information technology, urban aerial transportation is poised to become a pivotal trend in future mobility solutions, offering a viable means to mitigate ground traffic congestion. Air taxis, especially those utilizing Electric Vertical Take-Off and Landing (eVTOL) vehicles, have emerged as a focal point of interest among transportation industry professionals and researchers, owing to their potential to revolutionize urban mobility. This paper explores the optimization of pooled scheduling for eVTOL-based air taxis operating between simulated take-off and landing sites within the Guangdong-Hong Kong-Macao Greater Bay Area. It accounts for various factors, including meteorological conditions such as wind, as well as scenarios involving the replacement of batteries in aerial vehicles. A multi-objective model for the shared dispatch of air taxis is proposed alongside an effective multi-objective optimization algorithm that seeks to enhance the diversity of solutions through the adaptive adjustment of weight vectors. The Guangdong-Hong Kong-Macao Greater Bay Area simulation results substantiate the algorithm's exceptional diversity and convergence capabilities. These outcomes provide novel perspectives on solving urban aerial taxi sharing and dispatch challenges, offering significant theoretical and practical insights for optimizing scheduling in real-world scenarios.