The paper proposes a traffic speed prediction algorithm for urban road traffic networks. The motivation of the prediction is to provide short time forecast in order to support ITS (Intelligent Transport System) functionalities, such as traveler information systems, route guidance (navigation) systems, as well as adaptive traffic control systems. A potential and efficient solution to this problem is the application of a soft computing method. Namely, an artificial neural network (ANN) is used for the forecast by involving the measured speed patterns. The ANN is trained by using data produced by Vissim (a microscopic road traffic simulator) simulations. The proposed algorithm is developed and analyzed on a real-word test network (part of downtown in Budapest).


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Traffic speed prediction method for urban networks — an ANN approach




    Publication date :

    2015-06-01


    Size :

    380451 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Intelligent speed profile prediction on urban traffic networks with machine learning

    Park, Jungme / Murphey, Yi Lu / Kristinsson, Johannes et al. | IEEE | 2013


    Traffic speed prediction techniques in urban environments

    Alomari, Ahmad H. / Khedaywi, Taisir S. / Marian, Abdel Rahman O. et al. | Elsevier | 2022

    Free access

    Traffic speed prediction device and traffic speed prediction method

    KIM NAM-HYUK | European Patent Office | 2025

    Free access

    Traffic Speed Prediction with Neural Networks

    Çakmak, Umut Can / Apaydin, Mehmet Serkan / Çatay, Bülent | British Library Conference Proceedings | 2017