The increasing traffic “big data” brings new challenges to traffic management innovation and puts forward new requirements for traffic management. Traffic information construction will inevitably step into the intelligent application stage brought by big data. Using big data to crack the bottleneck of urban traffic will become the only way for the future traffic industry. Big data technology can send accident information to nearby vehicles to prevent accidents from happening again, and encourage other vehicles to change their driving routes. It can effectively improve the operational capacity of traffic roads and maximize the traffic infrastructure. The intelligent traffic assistant decision system designed in this paper processes and analyzes the data, and finally forms a traffic state prediction method based on the dynamic reliability of multi-source traffic data to predict the traffic state of the whole road network. The main goal is to make use of the information, models, methods and rules provided by traffic data warehouse and information intelligent analysis module to solve reasonable answers to problems in an acceptable time, such as the optimal control parameters and control strategies for regional signal control, traffic allocation and route guidance, to make an optimal decision on the traffic command and guidance scheme.


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    Titel :

    Design of Intelligent Transportation Assistant Decision System Based on Traffic Big Data


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Kountchev, Roumen (Herausgeber:in) / Patnaik, Srikanta (Herausgeber:in) / Nakamatsu, Kazumi (Herausgeber:in) / Kountcheva, Roumiana (Herausgeber:in) / Sun, Min (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Communication Technology ; 2023 ; Shenzhen, China June 09, 2023 - June 11, 2023



    Erscheinungsdatum :

    21.03.2024


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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