AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
Not on the map. Why?
Cited by 54 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Developing and testing algorithms for autonomous vehicles in real world is an expensive and time consuming process. Also, in order to utilize recent advances in machine intelligence and deep learning we need to collect a large amount of annotated training data in a variety of conditions and environments. We present a new simulator built on Unreal Engine that offers physically and visually realistic simulations for both of these goals. Our simulator includes a physics engine that can operate at a high frequency for real-time hardware-in-the-loop (HITL) simulations with support for popular protocols (e.g. MavLink). The simulator is designed from the ground up to be extensible to accommodate new types of vehicles, hardware platforms and software protocols. In addition, the modular design enables various components to be easily usable independently in other projects. We demonstrate the simulator by first implementing a quadrotor as an autonomous vehicle and then experimentally comparing the software components with real-world flights.
Key facts. Cited by 517 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 May 2017.
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Citing papers per year: 2018: 3; 2019: 1; 2020: 1; 2021: 54; 2022: 79; 2023: 74; 2024: 104; 2025: 117; 2026: 84.
517 papers.
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