Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
It has been shown that road geometry has a great impact on overall Energy consumption and emissions. Some roads connect traffic origins and destinations directly. On the other hand, some use winding, indirect routes. Indirect connections result in longer distances driven and increased fuel consumption. A similar effect is observed on congested roads and mountain roads with many changes in altitude. Therefore, we propose a framework to assess road networks based on energy consumption. This framework should take into consideration traffic volume, shares of vehicle classes, road geometry and energy needed for road operation and construction. It can be used to optimize energy consumption with efficient traffic management and to choose an optimum new road in the design phase. This is especially important as the Energy consumed by the vehicles soon supersedes the energy needed for road construction.
Czasopismo
Rocznik
Tom
Strony
77--87
Opis fizyczny
Bibliogr. 36 poz.
Twórcy
autor
- University of Ljubljana, Faculty of Maritime Studies and Transportation Pot pomorščakov 4, SI-6320 Portorož, Slovenia
autor
- University of Ljubljana, Faculty of Maritime Studies and Transportation Pot pomorščakov 4, SI-6320 Portorož, Slovenia
Bibliografia
- 1. European Commission. White paper, Roadmap to a single European Transport Area, Towards a competitive and resource efficient transport system. COM (2011). 2011.
- 2. Smarter, greener, more inclusive? Indicators to support the Europe 2020 strategy. Luxembourg: Publications Office of the European Union. 2015. ISBN 978-92-79-40079-7. Available from: http://ec.europa.eu/eurostat/documents/3217494/6655013/KS-EZ-14-001-EN-N.pdf
- 3. ODYSSEE – MURE 2012. Trends and policies for energy savings and emissions in transport [Internet]. 2015. Available from: http://www.odyssee-mure.eu/publications/br/energy-efficiencyin-transport.html
- 4. Ten Brink P. Mitigating CO2 Emissions from Cars in the EU (Regulation (EC) No. 443/2009). The new climate policies of the European Union: Internal legislation and climate diplomacy. 2010. (15):179.
- 5. Gambhir, A. & Tse, L.K.C. & Tong, D. & Martinez-Botas, R. Reducing China’s road transport sector CO2 emissions to 2050: Technologies, costs and decomposition analysis. Applied Energy. 2015 Nov. 1; 157. P. 905–917.
- 6. Bianco, N. & Litz, F. Reducing greenhouse gas emissions in the United States using existing federal authorities and state action. The World Resources Institute. 10 G Street. NE Suite 800 Washington, D. C. 20002 USA. 2010.
- 7. Metz, D. Peak Car in the Big City: Reducing London’s transport greenhouse gas emissions. Case Studies on Transport Policy. Available from: http://www.sciencedirect.com/science/article/pii/S2213624X15300018
- 8. Fritzsche, H-T, Ag D. Amodel for traffic simulation. Traffic Engineering and Control. 1994. Vol. 35. P. 317–321.
- 9. Wiedemann, R. Simulation des Strassenverkehrsflusses. 1974. Heft 8 (Vol. Band 8). Karlsruhe.
- 10. Kesting, A. & Treiber, M. & Helbing, D. General lane-changing model MOBIL for car-following models. Transportation Research Record: Journal of the Transportation Research Board. 2007.
- 11. Kesting, A. & Treiber, M. & Helbing, D. Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity. Philosophical Transactions of the Royal Society of London A. Mathematical, Physical and Engineering Sciences. 2010. 368(1928). P. 4585–4605.
- 12. Treiber, M. Traffic flow dynamics: data, models and simulation. Heidelberg; New York: Springer; 2013. 503 p.
- 13. Gipps, P.G. A behavioural car-following model for computer simulation. Transportation Research Part B: Methodological. 1981. 15(2) P. 105–111.
- 14. Kanagaraj, V. & Asaithambi, G. & Kumar, C.H.N. & Srinivasan, K.K. & Sivanandan, R. Evaluation of Different Vehicle Following Models under Mixed Traffic Conditions. Procedia -Social and Behavioral Sciences. 2013. Dec 2. 104. P. 390–401.
- 15. Sjödin, A. & Jerksjö, M. Evaluation of European road transport emission models against on-road emission data as measured by optical remote sensing. 2008. Available from: http://www20.vv.se/fudresultat/publikationer_000601_000700/publikation_000620/evaluation%20of%20european%20road%20transport%20emission.pdf.
- 16. Ahn, K. & Rakha, H. & Trani, A. & Van Aerde, M. Estimating Vehicle Fuel Consumption and Emissions based on Instantaneous Speed and Acceleration Levels. Journal of Transportation Engineering. 2002. 128(2). P. 182–190.
- 17. Joumard, R. & Rapone, M. & Andre, M. and others. Analysis of the cars pollutant emissions as regards driving cycles and kinematic parameters. 2006. Available from: http://hal.archivesouvertes. fr/hal-00545918/
- 18. André, M. & Keller, M. & Sjödin, A. Ake & Gadrat, M. & Crae, I.M. The ARTEMIS European tools for estimating the pollutant emissions from road transport and their application in Sweden and France. 2008. Available from: http://inrets.fr/ur/lte/publiautresactions/fichesresultats/ficheartemis/report2/ARTEMIS_paper_M_ANDRE_et_Al.pdf.
- 19. Franzese, O. & Davidson, D. Effect of weight and roadway grade on the fuel economy of class-8 freight trucks. Oak Ridge National Laboratory, Tennessee, USA. 2011. Available from: http://info.ornl.gov/sites/publications/files/Pub33386.pdf.
- 20. Sadri, A. & Ardehali, M.M. & Amirnekooei, K. General procedure for long-term energyenvironmental planning for transportation sector of developing countries with limited data based on LEAP (long-range energy alternative planning) and EnergyPLAN. Energy. 2014. Vol. 77. Issue C. P. 831–843.
- 21. Smit, R. & Smokers, R. & Rabé, E. A new modelling approach for road traffic emissions: VERSIT+. Transportation Research Part D: Transport and Environment. 2007. 12(6) P. 414–422.
- 22. Hidas P. A functional evaluation of the AIMSUN, PARAMICS and VISSIM microsimulation models. Road and Transport Research. 2005. 14(4). P. 45-59.
- 23. Behrisch, M. & Bieker, L. & Erdmann, J. & Krajzewicz, D. Sumo–simulation of urban mobility. In: The Third International Conference on Advances in System Simulation (SIMUL 2011). Barcelona, Spain. 2011.
- 24. Krajzewicz, D. & Behrisch, M. & Wagner. P. & Luz, R. & Krumnow, M. Second Generation of Pollutant Emission Models for SUMO. Modeling Mobility with Open Data. Springer. 2015.
- 25. Jimenez-Palacios, J.L. Understanding and quantifying motor vehicle emissions with vehicle specific power and TILDAS remote sensing. Massachusetts Institute of Technology. 1998.
- 26. Zhai, H. & Frey, H.C. & Rouphail, N.M. A Vehicle-Specific Power Approach to Speed and Facility-Specific Emissions Estimates for Diesel Transit Buses. Environ Sci Technol. 2008 Nov 1; 42(21). P. 7985–7991.
- 27. Frey, H.C. & Unal, A. & Rouphail, N.M. & Colyar, J.D. On-Road Measurement of Vehicle Tailpipe Emissions Using a Portable Instrument. Journal of the Air & Waste Management Association. 2003 Aug 1. 53(8). P. 992–1002.
- 28. Rahman, S.M.A. & Masjuki, H.H. & Kalam, M.A. & Abedin, M.J. & Sanjid, A. & Imtenan, S. Effect of idling on fuel consumption and emissions of a diesel engine fueled by Jatropha biodiesel blends. Journal of Cleaner Production. 2014. Apr 15; 69. P. 208–215.
- 29. Song, G. & Yu, L. Estimation of fuel efficiency of road traffic by characterization of vehiclespecific power and speed based on floating car data. Transportation Research Record: Journal of the Transportation Research Board. 2009. (2139). P.11–20.
- 30. Song, G. & Yu, L. Characteristics of Low-Speed Vehicle-Specific Power Distributions on Urban Restricted-Access Roadways in Beijing. Transportation Research Record: Journal of the Transportation Research Board. 2011. (2233). P. 90–98.
- 31. Åhman, M. Primary energy efficiency of alternative powertrains in vehicles. Energy. 2001 Nov; 26(11). P. 973–989.
- 32. Haklay, M. & Weber, P. Openstreetmap: User-generated street maps. Pervasive Computing, IEEE. 2008. 7(4). P. 12–18.
- 33. Danielson, J.J. & Gesch, D.B. Global multi-resolution terrain elevation data 2010 (GMTED2010). US Geological Survey; 2011.
- 34. Krajzewicz, D. & Erdmann, J. & Behrisch, M. & Bieker, L. Recent development and applications of SUMO-Simulation of Urban MObility. International Journal on Advances in Systems and Measurements. 2012. 5 (3&4) P. 128-138.
- 35. Jones, C.I. & Hammond, G.P. Embodied energy and carbon in construction materials. Proceedings of the ICE - Energy 161. 2008. P. 87–98.
- 36. Luin, B. & Petelin, S. & Dimc, F. Energy Labeling of Road Network. Maritime, transport and logistics science: conference proceedings. Portorož: Fakulteta za pomorstvo in promet. 2015. P. 232-239.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-484b68c8-9633-4f7f-b2ed-aca126f80397