Predicting Traffic Congestion in the Construction of Smart Cities in the Northwest Industrial Center: A Case Study in Lanzhou of China

Li Ma, Xiaoshi Lv, Wude Xu, Lixia Chang, Yongshun Wang, Lei Pan

Advances in Information Management and Economic Development Research Vol. 1 / No. 1 / pp. 58-67 / September 23, 2024

DOI 10.70114/aimedr.2024.1.1.P58

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Abstract

Intelligent transportation is a crucial component in the construction of smart cities. This paper conducts a case study on the traffic conditions at the intersection of Fuli East Road in Xigu District, Lanzhou, an industrial hub in northwest China, during the evening peak hours from 17:30 to 19:00 in June 2022, and discusses the traffic situation in the city. The paper describes the geographical location of the intersection, presents the data sources, and ensures the robustness of the data. Based on 30 days of evening rush hour traffic data, conclusions are drawn about the actual traffic conditions in the area. Using the Random Forest prediction method, the traffic speed and volume for future time periods are forecasted, and the level of traffic congestion during the evening rush hour in the area is assessed. The paper also proposes solutions to alleviate traffic congestion in the construction of smart cities. This paper provides a theoretical foundation for strategy formulation for urban planning and smart transportation development in the region

Keywords

Smart City / Intelligent transportation / Traffic flow prediction / Random Forest

2024 International Conference on Economic Management and Information Technology

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