# Scalable Adaptive Traffic Light Control Over a Traffic Network Including Turns, Transit Delays, and Blocking

arXiv: https://arxiv.org/abs/2404.17479 · HTML: https://mlsanity.com/paper/2404.17479/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Apr 2024.

## Built on by (most cited first, 1 of 1)

- [Independent policy gradient-based reinforcement learning for economic and reliable energy management of multi-microgrid systems](https://mlsanity.com/paper/2511.20977/) (2025)

## Abstract (arXiv)

We develop adaptive data-driven traffic light controllers for a grid-like traffic network considering straight, left-turn, and right-turn traffic flows. The analysis incorporates transit delays and blocking effects on vehicle movements between neighboring intersections. Using a stochastic hybrid system model with parametric traffic light controllers, we use Infinitesimal Perturbation Analysis (IPA) to derive a data-driven cost gradient estimator with respect to controllable parameters. We then iteratively adjust them through an online gradient-based algorithm to improve performance metrics. By integrating a flexible modeling framework to represent diverse intersection and traffic network configurations with event-driven IPA-based adaptive controllers, we develop a general scalable, adaptive framework for real-time traffic light control in multi-intersection traffic networks.