# RoboCar: A Rapidly Deployable Open-Source Platform for Autonomous Driving Research

arXiv: https://arxiv.org/abs/2405.03572 · HTML: https://mlsanity.com/paper/2405.03572/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 May 2024.

## Built on by (most cited first, 6 of 6)

- [LLM4AD: Large Language Models for Autonomous Driving -- Concept, Review, Benchmark, Experiments, and Future Trends](https://mlsanity.com/paper/2410.15281/) (2024)
- [SUMO-MCP: Leveraging the Model Context Protocol for Autonomous Traffic Simulation and Optimization](https://mlsanity.com/paper/2506.03548/) (2025)
- [TrafficSimAgent: A Hierarchical Agent Framework for Autonomous Traffic Simulation with MCP Control](https://mlsanity.com/paper/2512.20996/) (2025)
- [Leveraging V2X for Collaborative HD Maps Construction Using Scene Graph Generation](https://mlsanity.com/paper/2502.10127/) (2025)
- [Bandwidth-adaptive Cloud-Assisted 360-Degree 3D Perception for Autonomous Vehicles](https://mlsanity.com/paper/2602.23871/) (2026)
- [nuTruck: Benchmarking Autonomous Driving Planning for Distributed Electric-drive Trucks](https://mlsanity.com/paper/2607.13704/) (2026)

## Abstract (arXiv)

This paper introduces RoboCar, an open-source research platform for autonomous driving developed at the University of Luxembourg. RoboCar provides a modular, cost-effective framework for the development of experimental Autonomous Driving Systems (ADS), utilizing the 2018 KIA Soul EV. The platform integrates a robust hardware and software architecture that aligns with the vehicle's existing systems, minimizing the need for extensive modifications. It supports various autonomous driving functions and has undergone real-world testing on public roads in Luxembourg City. This paper outlines the platform's architecture, integration challenges, and initial test results, offering insights into its application in advancing autonomous driving research. RoboCar is available to anyone at https://github.com/sntubix/robocar and is released under an open-source MIT license.