Izvorni znanstveni članak

https://doi.org/10.17559/TV-20240227001353

Research on Intelligent Traffic Congestion Degree Collaborative Algorithm and Path Planning Based on Sensor Data

Hanzheng Sun ; School of Civil Engineering and Transportation Engineering, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China
Xuejing Zhang ; School of Water Conservancy Engineering, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China
Dan Li ; School of Civil Engineering and Transportation Engineering, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China
Jianling Tan ; School of Water Conservancy Engineering, Yellow River Conservancy Technical Institute, Kaifeng, 475004, China

Sažetak

Urban road traffic congestion has become a major problem that hinders the rapid and healthy development of cities. In this paper, the heterogeneous congestion network is divided into multiple congestion proton regions and boundary subregions by the double-layer partition method, and the traffic flow balance model of multi-regional network is established based on the macro basic map. A layered traffic management architecture based on multi-agent is designed, which provides a new method to improve the efficiency of urban traffic signal control. The wireless sensor network is deeply studied, and the path of the most critical factor affecting the transportation cost in the site construction model is studied in detail by tabu algorithm. According to the traffic network and real-time road condition information, the road network is abstracted as a graph based on the principle of graph theory, and the shortest path algorithm in graph theory is used to avoid obstacles and search for the optimal path, which can make drivers understand the road condition information in real time and make route decisions.

Ključne riječi

intelligent transportation; path planning; sensor; traffic congestion coordination

Hrčak ID:

318467

URI

https://hrcak.srce.hr/318467

Datum izdavanja:

27.6.2024.

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