Study of Data-Driven Traffic Congestion Level—Taking Yangzhou as an Example

Liu, Lu; Guo, Kai; Yang, Bin; Bian, Zhanglei

doi:10.1061/9780784482292.223

Cited by 1 publication

(1 citation statement)

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“…The internal traffic network information of high-speed railway stations was vectorized from the urban traffic map of 37 stations in the Yangtze River Economic Belt (2018). In addition, existing research found that the congestion index released by Amap is basically consistent with the results obtained from the construction of road traffic operation index model (Liu, 2018), which is of scientificity to measure urban traffic accessibility. Therefore, the traffic congestion data were obtained from the traffic analysis report of major Chinese cities in 2018 released by AutoNavi based on more than 700 million users.…”

Section: Data Collection and Processingsupporting

confidence: 78%

Spatial differentiation and influence mechanism of the connection-distribution performance of urban high-speed railway hub in the Yangtze River Economic Belt

De-gen

Zhao

2022

J. Geogr. Sci.

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A transportation hub is the key link in the construction of the comprehensive three-dimensional transportation corridor of the Yangtze River Economic Belt, and is the basic factor responsible for the promotion of this belt. A high-speed railway hub has the "last kilometer of time-space compression" effect and is the key to building an efficient, convenient, modern, and comprehensive transportation system. This study constructed a model for measuring the connection-distribution performance of the high-speed railway hub, determined the connection-distribution performance of the urban high-speed railway hub in the Yangtze River Economic Belt, and analyzed its spatial differentiation characteristics, further revealed the influencing mechanism of the connection-distribution performance of the high-speed railway hub. The main results are as follows: (1) The connection-distribution performance of the high-speed railway hub in the Yangtze River Economic Belt presented an "olive-shaped pattern" grade structure with two small ends and a large middle section, that is, the number of high-speed railway stations with high performance and average performance was small, and the number of high-speed railway stations with good performance and medium performance was large. (2) The connection-distribution performance of the high-speed railway hub in the Yangtze River Economic Belt showed a regional differentiation pattern of "high in the east and low in the west" and "high in the north and low in the south", and showed an urban agglomeration differentiation pattern of "high in the core areas but low in the marginal areas"; moreover, spatial differences were prominent in the distribution of nine evaluation indexes of the connection-distribution performance of the high-speed railway hub. (3) GDP, urbanization rate, city level, station passenger flow and frequency of shuttle bus were key driving factors affecting the connection-distribution performance of the high-speed railway hub. At the same time, there were significant differences in the key driving factors for the connection-distribution performance grades of high-quality, good, medium and average.

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Section: Data Collection and Processingsupporting

confidence: 78%