A composite transportation network design problem with land-air coordinated operations

• Published in: Transportation research. Part C, Emerging technologies Emerging technologies, 2025-02, Vol.171, p.104967, Article 104967
• Main Authors: Zhang, Honggang, Huo, Jinbiao, Chen, Churong, Liu, Zhiyuan
• Format: Article
• Language: English
• Subjects: Network planning; Urban aerial mobility; Vertiport location and capacity
• ISSN: 0968-090X
• DOI: 10.1016/j.trc.2024.104967

•A novel bi-level programming model is proposed to formulate the composite transportation network design with land-air coordinated operations.•Both the vertiports’ location and capacity are optimized to reduce total travel time.•A land-air collaboration network equilibrium model is developed to characterize the traveler’s behavior.•A customized mixed-integer Bayesian optimization (MI-BO) method is devised to solve the model.•Numerical experiments under different scenario settings are provided to validate the applicability of the proposed model. With the advent of electric vertical-takeoff-and-landing (eVTOL) vehicles, it becomes imperative to assess their impact on transportation network efficiency. Hence, this paper introduces a novel model for the composite transportation network design problem (CTNDP). Specifically, the model is designed to inform the planning of composite transportation networks by considering travel behaviors of land-air coordinated mobility. This innovative model is formulated as a bi-level programming problem, in which the upper-level model focuses on strategically planning vertiport locations and capacities, thereby reducing the total travel time within the transportation system. Upon determining decisions at the upper level, the composite transportation network can be established by constructing new links that interconnect the vertiports and existing road networks. The lower-level model addresses the land-air collaboration network equilibrium (LAC-NE) problem through mathematical programming. To solve the bi-level programming problem, a customized Bayesian optimization method, namely the mixed-integer Bayesian optimization (MI-BO) method, is proposed. Specifically, MI-BO is developed by incorporating the branch-and-bound algorithm into the Bayesian optimization framework. Additionally, an advanced path-based improved gradient projection (IGP) algorithm is developed to efficiently resolve the LAC-NE problem. The efficacy of the proposed model and solution algorithms are substantiated through numerical experiments, and the results illustrate the impact of land-air coordinated operations on the performance of the composite transportation network.