Pavan Yedavalli | Searcharxiv

arXiv2026

Aircraft and Fleet Sizing for Regional Air Mobility: College Town Case Studies

We examine how aircraft seat configuration interacts with daily operation in Regional Air Mobility by applying a joint supply-demand optimization framework that simultaneously determines market share, fare, and flight schedule. The framework integrates a binary logit discrete choice model into a task assignment formulation, capturing passengers' mode choice between Regional Air Mobility and driving across spatiotemporal origin-destination pairs. We evaluate three U.S. college town corridors under 4-, 6-, and 8-seat configurations across cost scales from 0.4 to 1.0 and fleet sizes from 12 to 30 aircraft. Profitability and throughput serve as primary performance metrics, and we analyze pricing power, operating cost, and revenue to explain performance variation across markets. We find that larger aircraft configurations and fleet sizes do not improve profitability universally. Larger aircraft are preferred where economies of scale are favorable and demand is sufficient and directionally balanced. The best configuration in these case studies is the 4-seat in imbalanced markets and the 6-seat in balanced or dense markets.

eess.SY↗

arXiv2021

Microsimulation Analysis for Network Traffic Assignment (MANTA) at Metropolitan-Scale for Agile Transportation Planning

Abrupt changes in the environment, such as unforeseen events due to climate change, have triggered massive and precipitous changes in human mobility. The ability to quickly predict traffic patterns in different scenarios has become more urgent to support short-term operations and long-term transportation planning. This requires modeling entire metropolitan areas to recognize the upstream and downstream effects on the network. However, there is a well-known trade-off between increasing the level of detail of a model and decreasing computational performance. To achieve the level of detail required for traffic microsimulation, current implementations often compromise by simulating small spatial scales, and those that operate at larger scales often require access to expensive high-performance computing systems or have computation times on the order of days or weeks that discourage productive research and real-time planning. This paper addresses the performance shortcomings by introducing a new platform, MANTA (Microsimulation Analysis for Network Traffic Assignment), for traffic microsimulation at the metropolitan-scale. MANTA employs a highly parallelized GPU implementation that is capable of running metropolitan-scale simulations within a few minutes. The runtime to simulate all morning trips, using half-second timesteps, for the nine-county San Francisco Bay Area is just over four minutes, not including routing and initialization. This computational performance significantly improves the state of the art in large-scale traffic microsimulation. MANTA expands the capacity to analyze detailed travel patterns and travel choices of individuals for infrastructure planning.

physics.soc-ph↗