The invention discloses a multimode traffic distribution model construction method based on mobile phone signaling data. The method includes the steps of recognizing a parking point based on a space-time clustering algorithm, extracting travel base station track information of a user according to the mobile phone signaling data, completing the matching of a base station and a road network intersection in a travel chain through a probability decision-making method, and obtaining travel track information of the user in an urban road network; performing rule matching on the resident travel surveydata and the mobile phone signaling data to obtain mobile phone signaling track data with a traffic mode label; integrating multi-source data to extract characteristic parameters, screening the characteristic parameters by chi-square test, constructing a traffic mode division model by using a random forest classification algorithm, and completing full-sample multi-mode travel OD estimation through sample expansion; and quantifying the influence of land layout and traffic modes on traffic distribution, constructing a multi-mode traffic distribution model based on a gravity model, completing model parameter calibration through the full-sample multi-mode travel OD, and finally completing a multi-mode traffic distribution prediction work.
本发明公开了一种基于手机信令数据的多方式交通分布模型构建方法,基于时空聚类算法识别停驻点,根据手机信令数据提取用户出行的基站轨迹信息,通过概率决策方法完成出行链中基站与路网交叉口的匹配,获取用户在城市路网的出行轨迹信息。然后将居民出行调查数据与手机信令数据进行规则匹配,获取有交通方式标签的手机信令轨迹数据。融合多源数据提取特征参数,采用卡方检验筛选特征参数,运用随机森林分类算法构建交通方式划分模型,并通过扩样完成全样本的分方式出行OD估计。量化用地布局和交通方式对交通分布的影响,基于重力模型构建多方式交通分布模型,利用全样本分方式出行OD完成模型参数标定,最终完成多方式交通分布预测工作。
Multimode traffic distribution model construction method based on mobile phone signaling data
一种基于手机信令数据的多方式交通分布模型构建方法
2020-12-25
Patent
Elektronische Ressource
Chinesisch
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