5 results on '"RUPI, FEDERICO"'
Search Results
2. Unified, Low-Cost Analysis Framework for the Cycling Situation in Cities
- Author
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SCHWEIZER, JOERG, RUPI, FEDERICO, J. N. Meggs, N. R. Dehkordi, A. Pashkevich, J. Schweizer, J.N. Megg, N. R. Dehkordi, F. Rupi, and A. Pashkevich
- Subjects
BICYCLING ,MODAL SPLITS ,TRANSPORT POLICY ,DIRECT DEMAND ,SURVEYS - Abstract
We propose a low-cost uniform analysis framework allowing comparison of the strengths and weaknesses of the bicycling experience within and between cities. A primary component is an expedient, one-page mobility survey from which mode share is calculated. The bicycle mode share of many cities remains unknown, creating a serious barrier for both scientists and policy makers aiming to understand and increase rates of bicycling. Because of its low cost and expedience, this framework could be replicated widely, uniformly filling the data gap. The framework has been applied to 13 Central European cities with success. Data is collected on multiple modes with specific questions regarding both behavior and quality of travel experience. Individual preferences are also collected, examining the conditions under which respondents would change behavior to adopt more sustainable modes (bicycling or public transportation). A broad analysis opportunity results, intended to inform policy choices.
- Published
- 2012
3. Automobile, public transport and bike usage in West and Eastern Europe: a comparative survey
- Author
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N. R. Dehkordi, J. N. Meggs, A. Pashkevich, RUPI, FEDERICO, SCHWEIZER, JOERG, N. R. Dehkordi, J. N. Megg, A. Pashkevich, F. Rupi, and J. Schweizer
- Subjects
BICYCLING ,MODAL SPLITS ,TRANSPORT POLICY ,DIRECT DEMAND ,SURVEYS - Abstract
Public policy objectives frequently aim to increase the use of alternative transport and reduce the use of private automobiles. Utilising a low-cost analysis framework that allows comparison of transport behaviour and preferences across ten Central European cities, perspective is gained into the trade-offs between modes. Competition between cycling and public transport is considered. Preliminary results are presented.
- Published
- 2012
4. Updated Models of Passenger Transport Related Energy Consumption of Urban Areas.
- Author
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Dingil, Ali Enes, Schweizer, Joerg, Rupi, Federico, and Stasiskiene, Zaneta
- Abstract
Introduction: As the global warming threat has become more concrete in recent years, there is a need to update transport energy consumptions of cities and to understand how they relate to population density and transport infrastructure. Transportation is one of the major sources of global warming and this update is an important warning for urban planners and policy makers to take action in a more consistent way. Analysis: This paper estimates and analyzes the passenger transport energy per person per year with a large and diverse sample set based on comparable, directly observable open-source data of 57 cities, distributed over 33 countries. The freight transport energy consumption, which accounts for a large portion of urban transport energy, is not considered. The main focus of the analysis is to establish a quantitative relation between population density, transport infrastructure and transport energy consumption. Results: In a first step, significant linear relations have been found between road length per inhabitant, the road infrastructure accessibility (RIA) and private car mode share as well as between RIA and public transport mode share. Results show further relation between travel distance, population density and RIA. In a second step, a simplified model has been developed that explains the non-linear relation between the population density and RIA. Finally, based on this relation and the above findings, a hyperbolic function between population density and transport energy has been calibrated, which explains the rapid increase of transport energy consumption of cities with low population density. Conclusions: The result of the this study has clearly identified the high private car mode share as main cause for the high transport energy usage of such cities, while the longer average commute distance in low-population density cities has a more modest influence on their transport energy consumption. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
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5. Transport indicator analysis and comparison of 151 urban areas, based on open source data
- Author
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Zaneta Stasiskiene, Ali Enes Dingil, Joerg Schweizer, Federico Rupi, „Springer' grupė, Dingil, Ali Ene, Schweizer, Joerg, Rupi, Federico, and Stasiskiene, Zaneta
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Relation (database) ,Population ,0211 other engineering and technologies ,Transportation ,open source data ,02 engineering and technology ,infrastructure accessibility ,Transport engineering ,Qualitative analysis ,Open source data ,Kilometer ,0502 economics and business ,050207 economics ,education ,population density ,education.field_of_study ,OSM ,Mechanical Engineering ,congestion ,05 social sciences ,lcsh:TA1001-1280 ,021107 urban & regional planning ,Regression analysis ,lcsh:HE1-9990 ,Geography ,Sample size determination ,TomTom ,Automotive Engineering ,transport policy ,Performance indicator ,lcsh:Transportation engineering ,lcsh:Transportation and communications - Abstract
Introduction The accurate analysis and comparison of transport indicators from a large variety of urban areas can help to evaluate the performance of different adopted transport policies. This paper attempts to determine important transport and socio-economic indicators from 151 urban areas and 51 countries, based on comparable, directly observable open-source data such as OpenstreetMap (OSM) and the TomTom database. Analysis This is the first, systematic indicator-analysis using recent, open source data from different urban areas around the world. The indicator road kilometers per person, sometimes cited as infrastructure accessibility is calculated by processing OSM data. Information on congestion levels have been taken from the TomTom database and socio-economic data from various, publicly accessible databases. Relations between indicators are identified through correlations and regression models are calibrated, quantifying the relation between transport infrastructure and performance indicators. Three sub-categories of cities with different population sizes (small cities, large cities and metropolises) are defined and studied individually. In addition, a qualitative analysis is performed, putting five different indicators into relation. Results & Conclusions The main results reconfirm previous findings but with a larger sample size and more comparable data. Good correlation values between infrastructure accessibility, socio-economic indicators, and congestion levels are demonstrated. It is shown that cities with higher GDP have generally built more infrastructure which in turn reduces their congestion levels. In particular, for cities with low population density (above approximately 1500 inh. Per sq.km), more roads per inhabitant lead to lower congestion levels; cities with high population density have in general lower congestion levels if the rail infrastructure per person ratio is high. Furthermore, these cities increasing railways per person is more effective in reducing congestions than increasing road length per person.
- Published
- 2018
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