A Survey on Small-Scale Testbeds for Connected and Automated Vehicles and Robot Swarms
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Abstract (arXiv)
Connected and automated vehicles and robot swarms hold transformative potential for enhancing safety, efficiency, and sustainability in the transportation and manufacturing sectors. Extensive testing and validation of these technologies is crucial for their deployment in the real world. While simulations are essential for initial testing, they often have limitations in capturing the complex dynamics of real-world interactions. This limitation underscores the importance of small-scale testbeds. These testbeds provide a realistic, cost-effective, and controlled environment for testing and validating algorithms, acting as an essential intermediary between simulation and full-scale experiments. This work serves to facilitate researchers' efforts in identifying existing small-scale testbeds suitable for their experiments and provide insights for those who want to build their own. In addition, it delivers a comprehensive survey of the current landscape of these testbeds. We derive 62 characteristics of testbeds based on the well-known sense-plan-act paradigm and offer an online table comparing 23 small-scale testbeds based on these characteristics. The online table is hosted on our designated public webpage https://bassamlab.github.io/testbeds-survey, and we invite testbed creators and developers to contribute to it. We closely examine nine testbeds in this paper, demonstrating how the derived characteristics can be used to present testbeds. Furthermore, we discuss three ongoing challenges concerning small-scale testbeds that we identified, i.e., small-scale to full-scale transition, sustainability, and power and resource management.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Aug 2024.
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Citing papers per year: 2025: 3; 2026: 1.
4 papers.
- 2025Simulator Ensembles for Trustworthy Autonomous Driving Systems Testingcited by 1
- 2025A Multi-Modality Evaluation of the Reality Gap in Autonomous Driving Systemscited by 1
- 2025Robust and Safe Multi-Agent Reinforcement Learning with Communication for Autonomous Vehicles: From Simulation to Hardwarecited by 0
- 2026Adversarial Robustness Analysis of Cloud-Assisted Autonomous Driving Systemscited by 0
- 2026Adversarial Robustness Analysis of Cloud-Assisted Autonomous Driving Systems6 Apr 2026
- 2025A Multi-Modality Evaluation of the Reality Gap in Autonomous Driving Systems26 Sep 2025
- 2025Robust and Safe Multi-Agent Reinforcement Learning with Communication for Autonomous Vehicles: From Simulation to Hardware1 Jun 2025
- 2025Simulator Ensembles for Trustworthy Autonomous Driving Systems Testing11 Mar 2025