Scalable Adaptive Traffic Light Control Over a Traffic Network Including Turns, Transit Delays, and Blocking
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917651739049984 |
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| author | Chen, Yingqing Cassandras, Christos G. |
| author_facet | Chen, Yingqing Cassandras, Christos G. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_17479 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Scalable Adaptive Traffic Light Control Over a Traffic Network Including Turns, Transit Delays, and Blocking Chen, Yingqing Cassandras, Christos G. Systems and Control 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. |
| title | Scalable Adaptive Traffic Light Control Over a Traffic Network Including Turns, Transit Delays, and Blocking |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2404.17479 |