Intelligent transportation systems (ITS) typically rely on massive sources of data to monitor the transportation system, estimate its current state, forecast its future state, and react with a set of control and management strategies in real time. This requires the prompt processing of a variety of data sources that is consistently changing with time and typically challenging to combine (and make sense of) in real time. This paper presents thoroughly the studies related to big data applications in ITS and its associated challenges.


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    Title :

    Big Data in ITS: Concept, Case Studies, Opportunities, and Challenges


    Contributors:


    Publication date :

    2019-08-01


    Size :

    206765 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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