The invention discloses an emergency vehicle dynamic path planning method based on accident influence causal inference, which collects road network traffic flow information to train a causal inference model, and selects a shortest time-consuming path for an emergency vehicle to arrive at an accident scene. The method comprises the following steps: reading road network information, obtaining road network traffic flow data, setting a target node, a source node and other intersection nodes in a road network, determining the type, place and time of an accident, and generating corresponding accident information as input; obtaining an influence value of the space-time speed through a causal inference method, and obtaining new road section travel time updated in a time-varying period; and carrying out emergency vehicle optimal path selection through a global optimal path planning method of road network weight time-varying characteristics. According to the invention, a machine learning method is combined with a traditional causal effect model, dynamic path planning of the emergency vehicle is realized, and the traffic efficiency is improved.

    本发明公开了一种基于事故影响因果推断的应急车辆动态路径规划方法,本发明收集路网交通流信息进行因果推断模型训练,并为应急车辆选择耗时最短的路线到达事故现场。通过读取路网信息,获得路网交通流数据,设置目标节点、源节点与路网中其他交叉口节点,并确定事故发生的类型,地点与时间,生成相应的事故信息作为输入;通过因果推断方法获得时空速度的影响值,并得到时变周期下更新的新的路段行程时间;通过路网权值时变特性的全局最优路径规划方法进行应急车辆最优路径选择。本发明将机器学习方法与传统因果效应模型相结合,实现应急车辆的动态路径规划,提高通行效率。


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    Titel :

    Emergency vehicle dynamic path planning method based on accident influence causal inference


    Weitere Titelangaben:

    一种基于事故影响因果推断的应急车辆动态路径规划方法


    Beteiligte:
    WANG CHEN (Autor:in) / LU CHANG (Autor:in) / XU SIXUAN (Autor:in) / ZHANG JIYANG (Autor:in) / SHI MINGLIANG (Autor:in)

    Erscheinungsdatum :

    06.08.2024


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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