# A Workflow for Map Creation in Autonomous Vehicle Simulations

arXiv: https://arxiv.org/abs/2508.16856 · HTML: https://mlsanity.com/paper/2508.16856/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 12 references that are in the map.
- First posted on arXiv 23 Aug 2025.

## Builds on (most cited first, 1 of 1)

- [HDMapNet: An Online HD Map Construction and Evaluation Framework](https://mlsanity.com/paper/2107.06307/) (2021)

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

- [DMAVA: Distributed Multi-Autonomous Vehicle Architecture Using Autoware](https://mlsanity.com/paper/2601.16336/) (2026)

## Abstract (arXiv)

The fast development of technology and artificial intelligence has significantly advanced Autonomous Vehicle (AV) research, emphasizing the need for extensive simulation testing. Accurate and adaptable maps are critical in AV development, serving as the foundation for localization, path planning, and scenario testing. However, creating simulation-ready maps is often difficult and resource-intensive, especially with simulators like CARLA (CAR Learning to Act). Many existing workflows require significant computational resources or rely on specific simulators, limiting flexibility for developers. This paper presents a custom workflow to streamline map creation for AV development, demonstrated through the generation of a 3D map of a parking lot at Ontario Tech University. Future work will focus on incorporating SLAM technologies, optimizing the workflow for broader simulator compatibility, and exploring more flexible handling of latitude and longitude values to enhance map generation accuracy.