The ability to generate a meaningful big-data through social media opens many possibilities that never existed before. In traffic management system, there are systems that use user generated contents to brings information about real-time traffic condition, such as waze (www.waze.com). However, those applications do not utilize the available traffic camera network. Second, they do not also utilize all that information to predict the future traffic condition through simulation and use it to gives user traffic suggestions that potentially balances the traffic load. The paper describes the project to develop the integration of traffic camera network & user proximity device's generated content to bring more robust traffic information. Furthermore, by using those information to calibrate traffic microsimulation in real-time, the system has prediction capability to generate better sugestion for the user and even optimally balance the traffic load.


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    Title :

    Integration of traffic camera network & user generated content for traffic load balancing system




    Publication date :

    2013-11-01


    Size :

    640834 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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