Effect of monitoring system structure on short-term prediction of highway travel time

Satu Innamaa (Corresponding Author)

    Research output: Contribution to journalArticleScientificpeer-review

    6 Citations (Scopus)

    Abstract

    This article discusses how the structure of the measurement system affects the short-term forecasts of travel time based on it. The effects of section length and location of different measurement stations were investigated. The study used empirical data. The research was carried out on a 28-km long interurban two-lane highway section. The prediction models were made as feedforward multilayer perceptron neural networks. The main results showed that the division of long road sections into shorter sub-links in the travel time measurement system was important. Furthermore, it would be crucial to obtain information about traffic flow rates entering the section in order to time the start of congestion correctly. In conclusion, the structure of the monitoring system should be based on the analysis of a typical location and the development of congestion along the section.
    Original languageEnglish
    Pages (from-to)125-140
    Number of pages16
    JournalTransportation Planning and Technology
    Volume29
    Issue number2
    DOIs
    Publication statusPublished - 2006
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    system structure
    Travel time
    congestion
    monitoring system
    travel time
    travel
    monitoring
    road
    Monitoring
    Multilayer neural networks
    prediction
    Time measurement
    Flow rate
    Neural networks
    neural network
    traffic
    effect
    time
    forecast
    analysis

    Keywords

    • travel time
    • prediction
    • monitoring system
    • highway

    Cite this

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    title = "Effect of monitoring system structure on short-term prediction of highway travel time",
    abstract = "This article discusses how the structure of the measurement system affects the short-term forecasts of travel time based on it. The effects of section length and location of different measurement stations were investigated. The study used empirical data. The research was carried out on a 28-km long interurban two-lane highway section. The prediction models were made as feedforward multilayer perceptron neural networks. The main results showed that the division of long road sections into shorter sub-links in the travel time measurement system was important. Furthermore, it would be crucial to obtain information about traffic flow rates entering the section in order to time the start of congestion correctly. In conclusion, the structure of the monitoring system should be based on the analysis of a typical location and the development of congestion along the section.",
    keywords = "travel time, prediction, monitoring system, highway",
    author = "Satu Innamaa",
    year = "2006",
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    language = "English",
    volume = "29",
    pages = "125--140",
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    }

    Effect of monitoring system structure on short-term prediction of highway travel time. / Innamaa, Satu (Corresponding Author).

    In: Transportation Planning and Technology, Vol. 29, No. 2, 2006, p. 125-140.

    Research output: Contribution to journalArticleScientificpeer-review

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    T1 - Effect of monitoring system structure on short-term prediction of highway travel time

    AU - Innamaa, Satu

    PY - 2006

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    AB - This article discusses how the structure of the measurement system affects the short-term forecasts of travel time based on it. The effects of section length and location of different measurement stations were investigated. The study used empirical data. The research was carried out on a 28-km long interurban two-lane highway section. The prediction models were made as feedforward multilayer perceptron neural networks. The main results showed that the division of long road sections into shorter sub-links in the travel time measurement system was important. Furthermore, it would be crucial to obtain information about traffic flow rates entering the section in order to time the start of congestion correctly. In conclusion, the structure of the monitoring system should be based on the analysis of a typical location and the development of congestion along the section.

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    KW - prediction

    KW - monitoring system

    KW - highway

    U2 - 10.1080/03081060600753438

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