Highway Truck Parking Prediction System and Statistical Modeling Underlying its Development

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F14%3A00442563" target="_blank" >RIV/67985807:_____/14:00442563 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Highway Truck Parking Prediction System and Statistical Modeling Underlying its Development

Popis výsledku v původním jazyce

In this paper, we will describe a system for on-line prediction of truck parking demand along highway system in the Czech Republic. We will describe structure of the system developed during the TACR TA02031411 project and mention some of its specific functionalities. Further, we will explain in detail statistical modeling methodology which underlies the forecasting model in the core of the prediction procedure. Whole system relies on the use of indirect but very precise and relatively cheap to obtain toll transaction data (accessible through a cooperation with Kapsch Telematic Services, Inc.). Our statistical modeling starts with a recognition of the fact that the number of trucks parking at a given lot and given time is a latent variable to be estimated from the observable toll transaction data (which are available in the form of times when individual truck pass toll gates). After constructing appropriate proxy variable, we formulate a flexible class of statistical semi-parametric mod

Název v anglickém jazyce

Highway Truck Parking Prediction System and Statistical Modeling Underlying its Development

Popis výsledku anglicky

In this paper, we will describe a system for on-line prediction of truck parking demand along highway system in the Czech Republic. We will describe structure of the system developed during the TACR TA02031411 project and mention some of its specific functionalities. Further, we will explain in detail statistical modeling methodology which underlies the forecasting model in the core of the prediction procedure. Whole system relies on the use of indirect but very precise and relatively cheap to obtain toll transaction data (accessible through a cooperation with Kapsch Telematic Services, Inc.). Our statistical modeling starts with a recognition of the fact that the number of trucks parking at a given lot and given time is a latent variable to be estimated from the observable toll transaction data (which are available in the form of times when individual truck pass toll gates). After constructing appropriate proxy variable, we formulate a flexible class of statistical semi-parametric mod

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/TA02031411" target="_blank" >TA02031411: Zvýšení využití parkovací kapacity na dálnicích za pomoci predikčních modelů</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Second International Conference on Traffic and Transport Engineering

ISBN

978-86-916153-2-1

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

164-170

Název nakladatele

City Net Scientific Research Center

Místo vydání

Belgrade

Místo konání akce

Belgrade

Datum konání akce

27. 11. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000348569200021