# Traffic smoothing using explicit local controllers

arXiv: https://arxiv.org/abs/2310.18151 · HTML: https://mlsanity.com/paper/2310.18151/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Oct 2023.

## Built on by (most cited first, 2 of 2)

- [Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test](https://mlsanity.com/paper/2402.17050/) (2024)
- [A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research](https://mlsanity.com/paper/2407.15868/) (2024)

## Abstract (arXiv)

The dissipation of stop-and-go waves attracted recent attention as a traffic management problem, which can be efficiently addressed by automated driving. As part of the 100 automated vehicles experiment named MegaVanderTest, feedback controls were used to induce strong dissipation via velocity smoothing. More precisely, a single vehicle driving differently in one of the four lanes of I-24 in the Nashville area was able to regularize the velocity profile by reducing oscillations in time and velocity differences among vehicles. Quantitative measures of this effect were possible due to the innovative I-24 MOTION system capable of monitoring the traffic conditions for all vehicles on the roadway. This paper presents the control design, the technological aspects involved in its deployment, and, finally, the results achieved by the experiment.