Optimizing land-air collaborative operations with environmental considerations

Urban air mobility (UAM) is an emerging transportation concept with the potential to transform urban commuting. By utilizing low-altitude airspace, novel aerial vehicles can provide faster transportation between vertiports in urban and suburban areas, offering a more efficient alternative than traditional surface transport. To successfully integrate UAM into urban environments, it is crucial to effectively connect it with existing road transportation systems, particularly in terms of constructing essential ground infrastructure, such as vertiports. This paper proposes a land-air collaborative network design model that incorporates environmental considerations. Specifically, we develop a bi-objective bi-level programming model to optimize the land-air integrated operations. The upper-level authority aims to minimize both the total travel time of the system and airborne pollutant emissions during UAM operations by selecting the locations and capacities of vertiports. The lower-level model determines the route choices of the multi-class commuters based on the user equilibrium condition. To solve this model, we propose a mixed-integer Bayesian optimization approach, incorporating a path-based solution algorithm using the partial linearization descent method to address the lower-level model. Numerical experiments demonstrate that incorporating environmental considerations significantly influences the design of the land-air collaborative network. In particular, environmental factors play a critical role in shaping commuters’ route choice, which in turn substantially affects key system metrics such as vertiport capacity, total travel time, and air pollutant emissions. This study offers valuable insights into optimizing land-air collaborative operations, maximizing the operational benefits of UAM while minimizing its environmental impact.