Scalable Adaptive Traffic Light Control Over a Traffic Network Including Turns, Transit Delays, and Blocking
<|reference_start|>Scalable Adaptive Traffic Light Control Over a Traffic Network Including Turns, Transit Delays, and Blocking: 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.<|reference_end|>
@article{chen2024scalable,
    title={Scalable Adaptive Traffic Light Control Over a Traffic Network Including
  Turns, Transit Delays, and Blocking},
    author={Yingqing Chen and Christos G. Cassandras},
    journal={arXiv preprint arXiv:2404.17479},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.17479},
    primaryClass={eess.SY cs.SY}
}