Citation

Mao Y, Qin G, Ni P, Liu Q. Int. J. Urban Sci. 2022; 26(1): 87-107.

Copyright

(Copyright © 2022, University of Seoul, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/12265934.2021.1882331

PMID

unavailable

Abstract

Traffic operation quality of road network plays a vital role in urban planning and sustainable development. In this work, taking Kunming City, China as an example, the road traffic speed analysis method for plateau mountain area was developed combined with Python tools. Thereby, a one-stop analysis framework was proposed based on road traffic data of the downtown area of Kunming City. Specifically, a PSO-LSTM based model was developed to predict the whole and the dynamic time series of road traffic speed.. Then, the appearance of rush hour is discussed from the local and static heat map. Finally, the primary road traffic conditions of Kunming city were investigated, combined with the characteristics of the plateau mountain areas. The results show that the overall traffic situation in Kunming city is slow, and the partial traffic situation is congested in the east and west region. The crowding status is closely related to the peak working hours of Kunming residents, the geographical characteristics of plateau mountain areas, and the planning and distribution of residential land and working land.Highlights A Python-based one-stop framework is developed to analyse road speeds and visualize the results.A PSO-LSTM algorithm model is developed for road traffic speed prediction.This work provides a reference for traffic planning and road design in plateau mountain cities.

Language: en

Keywords

plateau mountain; Python; Road traffic speed; urban road; urban transport