The present invention discloses an urban traffic velocity estimation method based on multi-source crowd sensing data. This method, based on roadside pedestrian data and road navigation data collected by smart phones, obtains a final estimated velocity through the steps of missing data filling, self-view velocity aggregation and multi-view velocity fusion. This fine-grained large-scale urban traffic velocity estimation method can achieve velocity estimation on all types of roads, including suburban road sections and paths, instead of just focusing on main roads in a city center. According to the present invention, based on data driving, the urban traffic velocity estimation method does not need to install additional devices on roads, and is low in cost and high in universality. Compared with the prior art, the urban traffic velocity estimation method has higher practicability, theoretical property and applicability, and is of great significance for improving traffic management and planning.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    URBAN TRAFFIC VELOCITY ESTIMATION METHOD BASED ON MULTI-SOURCE CROWD SENSING DATA


    Beteiligte:
    LI CHAO (Autor:in) / ZHANG YINGQIAN (Autor:in) / HE SHIBO (Autor:in) / CHEN JIMING (Autor:in) / FANG YI (Autor:in) / YANG QINMIN (Autor:in) / CHENG PENG (Autor:in)

    Erscheinungsdatum :

    27.03.2025


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G01C Messen von Entfernungen, Höhen, Neigungen oder Richtungen , MEASURING DISTANCES, LEVELS OR BEARINGS / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



    Urban traffic speed estimation method based on multi-source crowd sensing data

    HE SHIBO / ZHANG YINGQIAN / LI CHAO et al. | Europäisches Patentamt | 2023

    Freier Zugriff


    Mining Urban Traffic Condition from Crowd-Sourced Data

    Mai-Tan, Ha / Pham-Nguyen, Hoang-Nam / Long, Nguyen Xuan et al. | Springer Verlag | 2020


    Urban expressway traffic state estimation method based on multi-source data fusion

    LONG KEJUN / LIU YANG / WU WEI et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    Using crowd-sourced traffic data and open-source tools for urban congestion analysis

    Khaula Alkaabi / Mohsin Raza / Esra Qasemi et al. | DOAJ | 2024

    Freier Zugriff