Aerial vehicle path planning model considering ridesharing fairness

REN Xinhui; WANG Mengde; YU Fang

doi:10.11860/j.issn.1673-0291.20230097

Abstract：The use of electric Vertical Take-off and Landing(eVTOL)aircraft for low-altitude urban air transportation presents an effective solution to alleviate ground traffic congestion.This study addresses the path planning problem in future eVTOL ridesharing operations.First,a static eVTOL path planning mathematical model is developed,aiming to maximize the benefits for both eVTOL operators and passengers.The model considers constraints such as eVTOL vertiport capacity,aircraft load,and battery limitations.Ridesharing fairness is also taken into account,including passenger charging fair-ness and the equitable distribution of shared trip revenue between passengers and operators.Next,based on the problem's characteristics,an Improved Adaptive Genetic Algorithm(IAGA)is pro-posed,incorporating customized crossover and mutation operations with adaptive probability adjust-ments.Finally,numerical experiments are conducted to solve the model,followed by a sensitivity analysis.The results show that,compared to non-ridesharing scenarios,ridesharing reduces total eV-TOL flight distance by 16.52%,increases operator revenue by 9%,and decreases passenger expendi-ture by 9.01%.These findings confirm that the proposed ridesharing model ensures a fair distribution of benefits between passengers and operators.Both the enumeration algorithm and the IAGA achieve optimal solutions for small-scale cases.Compared to the Improved Genetic Algorithm(IGA),the IAGA reduces computation time by 51.47%.This proves that the IAGA can effectively solve rideshar-ing problems of various scales.The research results provide valuable insights for future eVTOL ride-sharing pricing strategies.