On Determinism of Game Engines used for Simulation-based Autonomous Vehicle Verification
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Abstract (arXiv)
Game engines are increasingly used as simulation platforms by the autonomous vehicle (AV) community to develop vehicle control systems and test environments. A key requirement for simulation-based development and verification is determinism, since a deterministic process will always produce the same output given the same initial conditions and event history. Thus, in a deterministic simulation environment, tests are rendered repeatable and yield simulation results that are trustworthy and straightforward to debug. However, game engines are seldom deterministic. This paper reviews and identifies the potential causes of non-deterministic behaviours in game engines. A case study using CARLA, an open-source autonomous driving simulation environment powered by Unreal Engine, is presented to highlight its inherent shortcomings in providing sufficient precision in experimental results. Different configurations and utilisations of the software and hardware are explored to determine an operational domain where the simulation precision is sufficiently low i.e. variance between repeated executions becomes negligible for development and testing work. Finally, a method of a general nature is proposed, that can be used to find the domains of permissible variance in game engine simulations for any given system configuration.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Apr 2021.
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Citing papers per year: 2023: 3; 2024: 0; 2025: 2; 2026: 1.
6 papers.
- 2023Attacking Motion Planners Using Adversarial Perception Errorscited by 1
- 2025SimClass: A Classroom Speech Dataset Generated via Game Engine Simulation For Automatic Speech Recognition Researchcited by 1
- 2023Evaluation Metrics for DNNs Compressioncited by 0
- 2023Traffic Flow Simulation for Autonomous Drivingcited by 0
- 2025Assessing behaviour coverage in a multi-agent system simulation for autonomous vehicle testingcited by 0
- 2026AD2: Analysis and Detection of Adversarial Threats in Visual Perception for End-to-End Autonomous Driving Systemscited by 0
- 2026AD2: Analysis and Detection of Adversarial Threats in Visual Perception for End-to-End Autonomous Driving Systems10 Feb 2026
- 2025Assessing behaviour coverage in a multi-agent system simulation for autonomous vehicle testing29 Dec 2025
- 2025SimClass: A Classroom Speech Dataset Generated via Game Engine Simulation For Automatic Speech Recognition Research10 Jun 2025
- 2023Attacking Motion Planners Using Adversarial Perception Errors21 Nov 2023
- 2023Traffic Flow Simulation for Autonomous Driving23 Jul 2023
- 2023Evaluation Metrics for DNNs Compression18 May 2023