Analysis Method of Travel Mode Choice of Urban Residents Based on Spatial-temporal Heterogeneity

被引：0
|
作者：
Zhou, Kang [1 ]
Peng, Xiao [1 ]
Guo, Zhong [1 ]
机构：
[1] China Acad Transportat Sci, 240 Huixinli, Beijing 100029, Peoples R China
来源：
ICMLC 2019: 2019 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING | 2019年
基金：
中国国家自然科学基金;
关键词：
Urban traffic; travel mode choice; spatial-temporal heterogeneity; cross-classification selection model; Bayesian estimation method;
D O I：
10.1145/3318299.3318333
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Green travel, low-carbon travel, harmonious and livable have become the main objectives of urban development. Public transport-oriented urban development mode can effectively alleviate traffic congestion, reduce energy consumption, reduce environmental pollution. Considering the influence of spatial temporal heterogeneity on the choice of urban residents' travel modes, a cross-classification selection model is constructed based on hierarchical modeling theory to capture the spatial-temporal heterogeneity quantitatively. Bayesian estimation method is selected to estimate the model parameters, and then the influencing factors of urban residents' travel mode choice behavior are revealed. Combining with typical cases, this paper compares and analyzes the differences between the results of the model analysis under the two scenarios of neglecting spatial-temporal heterogeneity and considering spatial-temporal heterogeneity, so as to provide a scientific basis for public transport-oriented urban planning.
引用
收藏
页码：332 / 337
页数：6
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