The invention discloses an urban center roadside parking characteristic influence analysis and demand prediction method. Comprising the following steps: S1, analyzing urban center roadside parking demand space-time characteristics; s2, establishing a gradient lifting decision tree nonlinear model to perform roadside parking demand nonlinear influence mechanism analysis; and S3, establishing a ConvLSTM space-time sequence prediction model to carry out roadside parking demand short-time prediction. According to the invention, research finds that the roadside parking demand has strong spatial-temporal correlation, and the hierarchical clustering method is utilized to analyze the time sequence characteristics of the roadside parking demand. Then, explanatory variables are selected from three dimensions of land utilization attributes, traffic facility attributes and social economic attributes, a gradient boosting decision tree nonlinear model is established, and the relationship between the explanatory variables and roadside parking demands is analyzed in combination with an SHAP algorithm; and finally, proposing a ConvLSTM space-time sequence prediction model based on the roadside parking demand space-time characteristics and the influence mechanism analysis result, and carrying out regional roadside parking demand short-time prediction.

    本发明公开了一种城市中心区路侧停车特性影响分析及需求预测方法。包括:S1、城市中心区路侧停车需求时空特性分析;S2、建立梯度提升决策树非线性模型进行路侧停车需求非线性影响机理分析;S3、建立ConvLSTM时空序列预测模型进行路侧停车需求短时预测。本发明通过研究发现路侧停车需求具有较强的时空相关性,利用层次聚类法对路侧停车需求的时序特征进行分析。然后分别从土地利用属性、交通设施属性和社会经济属性三个维度选取解释变量,建立梯度提升决策树非线性模型,结合SHAP算法分析了解释变量与路侧停车需求之间的关系。最后基于路侧停车需求时空特性和影响机理分析结果,提出了ConvLSTM时空序列预测模型,进行区域路侧停车需求短时预测。


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    Titel :

    Urban center roadside parking characteristic influence analysis and demand prediction method


    Weitere Titelangaben:

    一种城市中心区路侧停车特性影响分析及需求预测方法


    Beteiligte:
    MEI ZHENYU (Autor:in) / WANG DONG (Autor:in) / TANG WEI (Autor:in) / XU YIFAN (Autor:in) / GONG JINRUI (Autor:in) / ZHANG HONGYANG (Autor:in) / YANG JIAYI (Autor:in) / ZHANG XUJIE (Autor:in)

    Erscheinungsdatum :

    20.09.2024


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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