openACC. An open database of car-following experiments to study the properties of commercial ACC systems
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Abstract (arXiv)
Commercial Adaptive Cruise Control (ACC) systems are increasingly available as standard options in modern vehicles. At the same time, still little information is openly available on how these systems actually operate and how different is their behavior, depending on the vehicle manufacturer or model.T o reduce this gap, the present paper summarizes the main features of the openACC, an open-access database of different car-following experiments involving a total of 16 vehicles, 11 of which equipped with state-of-the-art commercial ACC systems. As more test campaigns will be carried out by the authors, OpenACC will evolve accordingly. The activity is performed within the framework of the openData policy of the European Commission Joint Research Centre with the objective to engage the whole scientific community towards a better understanding of the properties of ACC vehicles in view of anticipating their possible impacts on traffic flow and prevent possible problems connected to their widespread. A first preliminary analysis on the properties of the 11 ACC systems is conducted in order to showcase the different research topics that can be studied within this open science initiative.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Apr 2020.
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Citing papers per year: 2022: 2; 2023: 3; 2024: 2; 2025: 4; 2026: 2.
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- 2022Automatic vehicle trajectory data reconstruction at scalecited by 8
- 2023Car-Following Models: A Multidisciplinary Reviewcited by 8
- 2023A Generic Stochastic Hybrid Car-following Model Based on Approximate Bayesian Computationcited by 3
- 2026A knowledge-augmented dataset of high-risk driving scenarios with LLM annotations for autonomous drivingcited by 3
- 2025Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signscited by 2
- 2022Bayesian Methods in Automated Vehicle's Car-following Uncertainties: Enabling Strategic Decision Makingcited by 1
- 2024Towards Robust Car Following Dynamics Modeling via Blackbox Models: Methodology, Analysis, and Recommendationscited by 1
- 2024Evidence and quantification of cooperation of driving agents in mixed traffic flowcited by 1
- 2023Physics-inspired Neural Networks for Parameter Learning of Adaptive Cruise Control Systemscited by 0
- 2025Knowledge-data fusion dominated vehicle platoon dynamics modeling and analysis: A physics-encoded deep learning approachcited by 0
- 2025Learn2Drive: A neural network-based framework for socially compliant automated vehicle controlcited by 0
- 2025Benchmarking Tesla's Traffic Light and Stop Sign Control: Field Dataset and Behavior Insightscited by 0
- 2026SSP-DMGTimeNet: Physics-Constrained Learning for Spatiotemporal Trajectory Prediction of Vehicle Platoons7 Sep 2026
- 2026A knowledge-augmented dataset of high-risk driving scenarios with LLM annotations for autonomous driving8 Jul 2026
- 2025Benchmarking Tesla's Traffic Light and Stop Sign Control: Field Dataset and Behavior Insights31 Oct 2025
- 2025Learn2Drive: A neural network-based framework for socially compliant automated vehicle control30 Sep 2025
- 2025Knowledge-data fusion dominated vehicle platoon dynamics modeling and analysis: A physics-encoded deep learning approach9 Feb 2025
- 2025Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs21 Jan 2025
- 2024Evidence and quantification of cooperation of driving agents in mixed traffic flow31 Jul 2024
- 2024Towards Robust Car Following Dynamics Modeling via Blackbox Models: Methodology, Analysis, and Recommendations11 Feb 2024
- 2023A Generic Stochastic Hybrid Car-following Model Based on Approximate Bayesian Computation27 Nov 2023
- 2023Physics-inspired Neural Networks for Parameter Learning of Adaptive Cruise Control Systems3 Sep 2023
- 2023Car-Following Models: A Multidisciplinary Review14 Apr 2023
- 2022Automatic vehicle trajectory data reconstruction at scale15 Dec 2022
- 2022Automatic vehicle trajectory data reconstruction at scalecited by 8
- 2023Car-Following Models: A Multidisciplinary Reviewcited by 8
- 2023A Generic Stochastic Hybrid Car-following Model Based on Approximate Bayesian Computationcited by 3
- 2025Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signscited by 2
- 2022Bayesian Methods in Automated Vehicle's Car-following Uncertainties: Enabling Strategic Decision Makingcited by 1
- 2024Towards Robust Car Following Dynamics Modeling via Blackbox Models: Methodology, Analysis, and Recommendationscited by 1
- 2024Evidence and quantification of cooperation of driving agents in mixed traffic flowcited by 1
- 2023Physics-inspired Neural Networks for Parameter Learning of Adaptive Cruise Control Systemscited by 0
- 2025Knowledge-data fusion dominated vehicle platoon dynamics modeling and analysis: A physics-encoded deep learning approachcited by 0
- 2025Learn2Drive: A neural network-based framework for socially compliant automated vehicle controlcited by 0
- 2025Benchmarking Tesla's Traffic Light and Stop Sign Control: Field Dataset and Behavior Insightscited by 0
- 2026SSP-DMGTimeNet: Physics-Constrained Learning for Spatiotemporal Trajectory Prediction of Vehicle Platoonscited by 0
- 2026SSP-DMGTimeNet: Physics-Constrained Learning for Spatiotemporal Trajectory Prediction of Vehicle Platoons7 Sep 2026
- 2025Benchmarking Tesla's Traffic Light and Stop Sign Control: Field Dataset and Behavior Insights31 Oct 2025
- 2025Learn2Drive: A neural network-based framework for socially compliant automated vehicle control30 Sep 2025
- 2025Knowledge-data fusion dominated vehicle platoon dynamics modeling and analysis: A physics-encoded deep learning approach9 Feb 2025
- 2025Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs21 Jan 2025
- 2024Evidence and quantification of cooperation of driving agents in mixed traffic flow31 Jul 2024
- 2024Towards Robust Car Following Dynamics Modeling via Blackbox Models: Methodology, Analysis, and Recommendations11 Feb 2024
- 2023A Generic Stochastic Hybrid Car-following Model Based on Approximate Bayesian Computation27 Nov 2023
- 2023Physics-inspired Neural Networks for Parameter Learning of Adaptive Cruise Control Systems3 Sep 2023
- 2023Car-Following Models: A Multidisciplinary Review14 Apr 2023
- 2022Automatic vehicle trajectory data reconstruction at scale15 Dec 2022
- 2022Bayesian Methods in Automated Vehicle's Car-following Uncertainties: Enabling Strategic Decision Making25 Oct 2022