Robust optimisation for vertiport location problem considering travel mode choice behaviour in urban air mobility systems

With the rapid development of novel vehicle technologies, air taxis are becoming a new transport servicing model to achieve better urban air mobility (UAM) systems. The UAM system can mitigate severe traffic congestion problems on the ground in many metropolitan areas effectively. This research aims to design a robust UAM network to serve broader mobility needs in the future. In this study, we consider the two main competition transportation modes of air taxis (luxury ground taxis and ordinary ground taxis) and establish a travel mode choice behaviour model based on the multinomial logit choice approach to determine the aggregate air taxi demand flow. Furthermore, we account for the varying temporal preferences of different UAM passengers by incorporating different time values for heterogeneous passengers, such as leisure and business passengers, into the travel mode choice behaviour model. Additionally, to address uncertainties in user demand, we introduce a robust optimisation model for vertiport location under a budget uncertainty set. This model is then reformulated as a mixed-integer linear programming model to address computational challenges. Ultimately, we conduct a series of numerical experiments to showcase the effectiveness of our proposed mathematical model. The outcomes of this research offer valuable managerial insights and implications, aiding governments and UAM operators in scientifically designing UAM networks and making strategic decisions regarding infrastructure investments.