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    Wyświetlanie 1-2 z 2
    Tytuł:
    Effect of Vehicle Composition and Delay on Roundabout Capacity under Mixed Traffic Conditions
    Autorzy:
    Abhigna, D.
    Kondreddy, S.
    Ravi Shankar, K. V. R.
    Powiązania:
    https://bibliotekanauki.pl/articles/223955.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    critical gap
    vehicle type
    delay
    capacity
    simulation
    circulation flow
    pojazd
    opóźnienie
    pojemność
    symulacja
    Opis:
    Roundabouts are replacing conventional unsignalized intersections in many parts of the world (Polus and Shmueli, 1997). Capacity estimation is necessary for designing a new roundabout, to analyze and improve the existing roundabout facilities. There are several methods to estimate the capacity of the roundabout, but most of them are for homogeneous lane based traffic conditions and not applicable for mixed traffic conditions. This study tries to find out the applicability of the existing methods to mixed traffic conditions, identify the effect of vehicle composition, travel time and delay on capacity. In this study, data was collected from two roundabouts located in Mysore, Karnataka and Rajahmundry, Andhra Pradesh in India. Capacities for both the roundabouts are calculated using the existing methods and compared. VISSIM simulation model has been developed and analyzed for different vehicle compositions scenarios. It was observed that vehicle composition of the traffic influences the roundabout capacity. Since the entry capacity of a roundabout varies significantly with the vehicle composition of the traffic at the roundabout, it is necessary to incorporate this factor into the existing capacity estimation models.
    Źródło:
    Archives of Transport; 2016, 40, 4; 7-14
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Estimation of stochastic traffic capacity using extreme value theory and censoring: a case study in Salem, New Hampshire
    Autorzy:
    Laflamme, E. M.
    Ossenbruggen, P. J.
    Powiązania:
    https://bibliotekanauki.pl/articles/224150.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    stochastic capacity
    estimation of traffic
    daily flow maxima
    capacity distribution function
    censoring
    computational Bayesian method
    przepustowość ruchu
    szacowanie ruchu
    metoda bayesowska
    Opis:
    In this work, we introduce a method of estimating stochastic freeway capacity using elements of both extreme value theory and survival analysis. First, we define capacity data, or estimates of the capacity of the roadway, as the daily maximum flow values. Then, under a survival analysis premise, we introduce censoring into our definition. That is, on days when flows are sufficiently high and congestion occurs, corresponding flow maxima are considered true estimates of capacity; otherwise, for those days that do not observe high flows or congestion, flow maxima are deemed censored observations and capacities must be higher than the observations. By extreme value theory, the collection of flow maxima (block maxima) can be appropriately approximated with a generalized extreme value (GEV) distribution. Because of small sample sizes and the presence of censoring, a Bayesian framework is pursued for model fitting and parameter estimation. To lend credence to our proposed methodology, the procedure is applied to real-world traffic stream data collected by the New Hampshire Department of Transportation (NHDOT) at a busy location on Interstate I-93 near Salem, New Hampshire. Data were collected over a period of 11 months and raw data were aggregated into 15-minute intervals. To assess our procedure, and to provide proof of concept, several validation procedures are presented. First, using distinct training and validation subsets of our data, the procedure yields accurate predictions of highway capacity. Next, our procedure is applied to a training set to yield random capacities which are then used to predict breakdown in the validation set. The frequency of these predicted breakdowns is found to be statistically similar to observed breakdowns observed in our validation set. Lastly, after comparing our methodology to other methods of stochastic capacity estimation, we find our procedure to be highly successful.
    Źródło:
    Archives of Transport; 2018, 48, 4; 61-75
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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