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Inicio  /  Applied Sciences  /  Vol: 10 Par: 6 (2020)  /  Artículo
ARTÍCULO
TITULO

An Integrated Algorithm for Intersection Queue Length Estimation Based on IoT in a Mixed Traffic Scenario

Kai Gao    
Shuo Huang    
Farong Han    
Shuo Li    
Wenguang Wu and Ronghua Du    

Resumen

The proposed algorithm and architecture has the capability of estimating the queue length of waiting vehicles at a signalized intersection, where traffic cameras, edge server, and some connected vehicles are available. This method can resolve the queue length estimation problem in a mixed traffic scenario, especially when there are variable types of vehicles. It can provide key information for traffic lights control and improve the traffic efficiency.

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