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Traffic control at road intersections is based on traffic lights (TLs). The control mechanism typically used for traffic lights operates based on a periodic schedule to change the light (red/yellow/green). In many cases, a different schedule is used in late night/early morning hours. This fixed control mechanism does not adequately account for changing traffic conditions, and is unaware of/unresponsive to congestion. In this work, we propose a framework for dynamic traffic light control at intersections. The framework relies on a simple sensor network to collect traffic data and includes novel protocols for traffic flow control to handle congestion and facilitate flow. We show that our proposed algorithms have low overhead and are practical to employ in live traffic flow scenarios. Through extensive simulations, we demonstrate the benefits of our framework in optimizing traffic flow metrics, such as traffic throughput, average vehicle waiting time, and vehicle waiting line length.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 17 | |
| downloads | 14 |

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