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14 March 2022 Analysis of intercity highway traffic trip based on spatial autocorrelation model: an empirical study using mobile signaling data
Yi Liu, Di Wu, Jun Ma, Yingping Wang
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Proceedings Volume 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021); 121651K (2022) https://doi.org/10.1117/12.2627926
Event: 2021 International Conference on Intelligent Traffic Systems and Smart City, 2021, Zhengzhou, China
Abstract
Intercity transportation in urban agglomerations has the characteristics of large travel scale, diversified travel modes, diversified travel purposes, unbalanced temporal and spatial distribution and so on. Based on the mobile signaling data, this paper calculates the intercity travel volume and external traffic travel volume of the Beijing-Tianjin-Hebei urban agglomeration through data cleaning, processing, fusion and mining. Using the spatial autocorrelation analysis method, the spatial effect of intercity highway traffic travel is analyzed. The results indicate that the intercity highway travel volume of adjacent cities shows a significant positive correlation, and intercity highway travel is positively correlated with population, economic development level, urbanization development level and residents' income level.
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Yi Liu, Di Wu, Jun Ma, and Yingping Wang "Analysis of intercity highway traffic trip based on spatial autocorrelation model: an empirical study using mobile signaling data", Proc. SPIE 12165, International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2021), 121651K (14 March 2022); https://doi.org/10.1117/12.2627926
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KEYWORDS
Data modeling
Roads
Analytical research
Signal attenuation
Data fusion
Signal processing
Standards development
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