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Traffic emission mapping with toll system assistance

Autorzy
Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents a method of the traffic emission computing, mapping and its monitoring in relation o the system of the highway toll gates. The construction of an own mathematical model, built on secondarily used data variables of the toll gate system, is presented. The model construction allows describing a simple method for the estimation of traffic intensities and finally for modelling the emission load maps of the mobile sources.
Rocznik
Strony
8--12
Opis fizyczny
Bibliogr. 7 poz.
Twórcy
autor
autor
  • Faculty of Transportation Sciences, Czech Technical University in Prague, Konviktska 20, 110-00 Prague, Czech Republic, derbek@lss.fd.cvut.cz
Bibliografia
  • [1] CICERO-FERNANDEZ P., LONG J.R., Grades and Other Load Effects on On-Road Emissions: An On-Board Analyzer Study, Fifth Annual On-Road Vehicle Emissions Workshop, San Diego, California, 1995.
  • [2] GAMMARIELLO R., CARLOCK M., Development of Hourly Vehicle Activity for Estimating Vehicle Emissions, Seventh CRC On-Road Vehicle Emissions Workshop, San Diego, California, April 1997.
  • [3] HRUBEŠ P., KAZMAROVÁ H., KEDER J., HELMUT T., POTUŽNIKOVÁ D., The study Run limitation of selected trucks on weekends - an impact and benefits analysis, Research report LSS 337/08, part III., 33, 20-32, Czech Technical University in Prague, Prague 2008.
  • [4] HRUBEŠ P., VLČKOVÁ V., ČARSKÝ J., KUMPOŠT P., BRABEC M., PELIKÁN E., The study Weekend trip limitations of selected heavy trucks - an impact and benefits analysis, Research report LSS 337/08, part I., 129, 5-84, Czech Technical University in Prague, Prague 2008.
  • [5] SVITEK M., STÁREK T., HRUBEŠ P., KANTOR S., DERBEK P., Intelligent Transport Systems (ITS) and Their Impact on Sustainable Development, (IDOC194), Annual Report, 26, 15-18, Czech Technical University in Prague, Prague 2008.
  • [6] ZITO P., CHEN H., BELL M., Predicting real-Time Roadside CO and NO2 Concentrations Using Neural Networks, IEEE Transaction on Intelligent Transportation Systems, Vol. 9, No. 3, September 2008.
  • [7] http://www.env.cz/AIS/web-pub.nsf/$pid/MZPMSF437BOZ
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSL7-0047-0056
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