The invention discloses an intersection pedestrian-left-turn vehicle conflict risk factor quantification method based on causal machine learning. The method specifically comprises the following steps: 1, extracting pedestrian-left-turn vehicle conflict data; 2, matching the pedestrian-left turning vehicle conflict data with a signal control type Ttype and a safety influence factor; 3, constructing a directed acyclic graph; 4, on the basis of a directed acyclic graph, using a dual robust learning algorithm to construct causal inference models under different signal control types, and mining factors related to pedestrian-left turn vehicle conflicts from safety influence factors as conflict risk factors; and the heterogeneity causal effect of different signal control types on the pedestrian-left turn vehicle conflict risk is estimated. According to the method, confusion factors can be effectively identified and processed, and the robustness and generalization ability of the model facing real world data are improved.
本发明公开了一种基于因果机器学习的交叉口行人‑左转车辆冲突风险因素量化方法,具体为:1:提取行人‑左转车辆冲突数据;2:将行人‑左转车辆冲突数据与信号控制类型Ttype以及安全影响因素匹配;3:构建有向无环图;4:基于有向无环图,利用双重鲁棒学习算法构建了不同信号控制类型下的因果推断模型,在安全影响因素中挖掘与对行人‑左转车辆冲突相关的因素作为冲突风险因素,并估计不同信号控制类型对行人‑左转车辆冲突风险的异质性因果效应。本发明能够有效地识别并处理混淆因素,提高了模型在面对真实世界数据时的鲁棒性和泛化能力。
Intersection pedestrian-left turning vehicle conflict risk factor quantification method based on causal machine learning
基于因果机器学习的交叉口行人-左转车辆冲突风险因素量化方法
28.03.2025
Patent
Elektronische Ressource
Chinesisch
IPC: | G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES |
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