# Simulating the Integration of Urban Air Mobility into Existing Transportation Systems: A Survey

arXiv: https://arxiv.org/abs/2301.12901 · HTML: https://mlsanity.com/paper/2301.12901/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 97 references that are in the map.
- First posted on arXiv 25 Jan 2023.

## Builds on (most cited first, 4 of 4)

- [Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities](https://mlsanity.com/paper/2103.01768/) (2021)
- [AAM-Gym: Artificial Intelligence Testbed for Advanced Air Mobility](https://mlsanity.com/paper/2206.04513/) (2022)
- [Trajectory-Based Urban Air Mobility (UAM) Operations Simulator (TUS)](https://mlsanity.com/paper/1908.08651/) (2019)
- [Microsimulation Analysis for Network Traffic Assignment (MANTA) at Metropolitan-Scale for Agile Transportation Planning](https://mlsanity.com/paper/2007.03614/) (2020)

## Built on by (most cited first, 1 of 1)

- [RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailing](https://mlsanity.com/paper/2512.13727/) (2025)

## Abstract (arXiv)

Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility. However, the integration of UAM into existing transportation systems is a complex task that requires a thorough understanding of its impact on traffic flow and capacity. In this paper, we conduct a survey to investigate the current state of research on UAM in metropolitan-scale traffic using simulation techniques. We identify key challenges and opportunities for the integration of UAM into urban transportation systems, including impacts on existing traffic patterns and congestion; safety analysis and risk assessment; potential economic and environmental benefits; and the development of shared infrastructure and routes for UAM and ground-based transportation. We also discuss the potential benefits of UAM, such as reduced travel times and improved accessibility for underserved areas. Our survey provides a comprehensive overview of the current state of research on UAM in metropolitan-scale traffic using simulation and highlights key areas for future research and development.