mlsanityData to 7 Oct 2026

Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments

arXiv 1705.01693 ↗First posted 4 May 2017eess.SY cs.SYcited by 41

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Abstract (arXiv)

Traffic waves are phenomena that emerge when the vehicular density exceeds a critical threshold. Considering the presence of increasingly automated vehicles in the traffic stream, a number of research activities have focused on the influence of automated vehicles on the bulk traffic flow. In the present article, we demonstrate experimentally that intelligent control of an autonomous vehicle is able to dampen stop-and-go waves that can arise even in the absence of geometric or lane changing triggers. Precisely, our experiments on a circular track with more than 20 vehicles show that traffic waves emerge consistently, and that they can be dampened by controlling the velocity of a single vehicle in the flow. We compare metrics for velocity, braking events, and fuel economy across experiments. These experimental findings suggest a paradigm shift in traffic management: flow control will be possible via a few mobile actuators (less than 5%) long before a majority of vehicles have autonomous capabilities.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2017.

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Citing papers per year: 2021: 5; 2022: 6; 2023: 14; 2024: 10; 2025: 3; 2026: 3.

41 papers.

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  1. 2023I-24 MOTION: An instrument for freeway traffic sciencecited by 24
  2. 2022Unified Automatic Control of Vehicular Systems with Reinforcement Learningcited by 13
  3. 2021Scalable Multiagent Driving Policies For Reducing Traffic Congestioncited by 11
  4. 2024Automating Traffic Model Enhancement with AI Research Agentcited by 8
  5. 2022Automatic vehicle trajectory data reconstruction at scalecited by 7
  6. 2023Car-Following Models: A Multidisciplinary Reviewcited by 7
  7. 2023EnduRL: Enhancing Safety, Stability, and Efficiency of Mixed Traffic Under Real-World Perturbations Via Reinforcement Learningcited by 7
  8. 2023Parameterized Decision-making with Multi-modal Perception for Autonomous Drivingcited by 7
  9. 2024Traffic expertise meets residual RL: Knowledge-informed model-based residual reinforcement learning for CAV trajectory controlcited by 7
  10. 2023Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomycited by 6
  11. 2021Hybrid Car-Following Strategy based on Deep Deterministic Policy Gradient and Cooperative Adaptive Cruise Controlcited by 5
  12. 2022Offline Reinforcement Learning for Road Traffic Controlcited by 5
29 more
  1. 2022CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles using Deep Reinforcement Learningcited by 5
  2. 2021Learning a Robust Multiagent Driving Policy for Traffic Congestion Reductioncited by 4
  3. 2023PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory Systemscited by 4
  4. 2021Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomycited by 3
  5. 2023Cooperative Driving for Speed Harmonization in Mixed-Traffic Environmentscited by 3
  6. 2022Vessel-following model for inland waterways based on deep reinforcement learningcited by 2
  7. 2023Artificial Intelligence for Smart Transportationcited by 2
  8. 2023The Interstate-24 3D Dataset: a new benchmark for 3D multi-camera vehicle trackingcited by 2
  9. 2024Vehicle-group-based Crash Risk Prediction and Interpretation on Highwayscited by 2
  10. 2021Calibration of Human Driving Behavior and Preference Using Naturalistic Traffic Datacited by 1
  11. 2022Learning energy-efficient driving behaviors by imitating expertscited by 1
  12. 2023Learning "Look-Ahead" Nonlocal Traffic Dynamics in a Ring Roadcited by 1
  13. 2023RACER: Rational Artificial Intelligence Car-following-model Enhanced by Realitycited by 1
  14. 2024Cooperative Advisory Residual Policies for Congestion Mitigationcited by 1
  15. 2023Optimal Smoothing Distribution Exploration for Backdoor Neutralization in Deep Learning-based Traffic Systemscited by 0
  16. 2023Zero-shot Transfer Learning of Driving Policy via Socially Adversarial Traffic Flowcited by 0
  17. 2023Data-Driven Traffic Reconstruction and Kernel Methods for Identifying Stop-and-Go Congestioncited by 0
  18. 2024Traffic Smoothing Controllers for Autonomous Vehicles Using Deep Reinforcement Learning and Real-World Trajectory Datacited by 0
  19. 2024Mesoscale Traffic Forecasting for Real-Time Bottleneck and Shockwave Predictioncited by 0
  20. 2024Data/moment-driven approaches for fast predictive control of collective dynamicscited by 0
  21. 2024Lessons in Cooperation: A Qualitative Analysis of Driver Sentiments towards Real-Time Advisory Systems from a Driving Simulator User Studycited by 0
  22. 2024A Survey on Differential Privacy for SpatioTemporal Data in Transportation Researchcited by 0
  23. 2024Highway Congestion Reduction through Reinforcement Learning Based Eulerian Headway Controlcited by 0
  24. 2025Mitigating Traffic Oscillations in Mixed Traffic Flow with Scalable Deep Koopman Predictive Controlcited by 0
  25. 2025A phase-aware AI car-following model for electric vehicles with adaptive cruise control: Development and validation using real-world datacited by 0
  26. 2025Multi-Agent Coordination in Autonomous Vehicle Routing: A Simulation-Based Study of Communication, Memory, and Routing Loopscited by 0
  27. 2026GNN-based Multi-Agent Control of Traffic Shockwaves in Sparse Vehicular Ad-hoc Networkscited by 0
  28. 2026Simulating Cognitive Smart Freight Corridors with Agent-Based Models and Reinforcement Learningcited by 0
  29. 2026SSP-DMGTimeNet: Physics-Constrained Learning for Spatiotemporal Trajectory Prediction of Vehicle Platoonscited by 0