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581.
This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents
a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the
base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are
then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed
algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The
algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination
of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision,
geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan
Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises
based on administrative units.
Luis M. Martínez is a Civil Engineer from the Instituto Superior Técnico, Technical University of Lisbon since 2004. After finishing his degree, he started his work as researcher in the CESUR (Civil Engineering & Architecture Department—Instituto Superior Técnico) where he has been working since. In 2006 he completed his Master Thesis at Instituto Superior Técnico on Traffic Analysis Zones modeling and started his PhD studies on the theme: Metropolitan Transportation Systems Financing Using the Value Capture Concept. José Manuel Viegas is Full Professor of Transportation at the Civil Engineering & Architecture Department of the Instituto Superior Técnico, Technical University of Lisbon. He has worked extensively in Modeling, Innovation and Policy in several types of Transport Systems. He was founder and first Director General of Transportnet, a group of eight leading European Universities with Advanced Studies in Transportation, and currently leads the Portuguese side of the Transportation Systems area in the MIT—Portugal program. Elisabete A. Silva is at the University of Cambridge (University Lecturer in Planning at the Department of Land Economy and a Fellow of Robinson College). With more than 100 contributions in peer review journals, books/books chapters, conference proceedings, and a research track record of approximately 16 years, (both at the public and private sector), her research interests are centred on the application of new technologies to spatial planning in particular city and metropolitan dynamic modelling through time. 相似文献
Elisabete A. SilvaEmail: |
Luis M. Martínez is a Civil Engineer from the Instituto Superior Técnico, Technical University of Lisbon since 2004. After finishing his degree, he started his work as researcher in the CESUR (Civil Engineering & Architecture Department—Instituto Superior Técnico) where he has been working since. In 2006 he completed his Master Thesis at Instituto Superior Técnico on Traffic Analysis Zones modeling and started his PhD studies on the theme: Metropolitan Transportation Systems Financing Using the Value Capture Concept. José Manuel Viegas is Full Professor of Transportation at the Civil Engineering & Architecture Department of the Instituto Superior Técnico, Technical University of Lisbon. He has worked extensively in Modeling, Innovation and Policy in several types of Transport Systems. He was founder and first Director General of Transportnet, a group of eight leading European Universities with Advanced Studies in Transportation, and currently leads the Portuguese side of the Transportation Systems area in the MIT—Portugal program. Elisabete A. Silva is at the University of Cambridge (University Lecturer in Planning at the Department of Land Economy and a Fellow of Robinson College). With more than 100 contributions in peer review journals, books/books chapters, conference proceedings, and a research track record of approximately 16 years, (both at the public and private sector), her research interests are centred on the application of new technologies to spatial planning in particular city and metropolitan dynamic modelling through time. 相似文献
582.
583.
Erika Spissu Abdul Rawoof Pinjari Ram M. Pendyala Chandra R. Bhat 《Transportation》2009,36(4):403-422
In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles
drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study
explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e.,
self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive
distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components.
The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation
approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling
in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at The University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from The University of Texas at Austin. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use-transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献
Chandra R. Bhat (Corresponding author)Email: |
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at The University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from The University of Texas at Austin. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use-transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. 相似文献
584.
Philippe Barla Bernard Lamonde Luis F. Miranda-Moreno Nathalie Boucher 《Transportation》2009,36(4):389-402
This paper presents estimates of the rebound effect and other elasticities for the Canadian light-duty vehicle fleet using
panel data at the provincial level from 1990 to 2004. We estimate a simultaneous three-equation model of aggregate demand
for vehicle kilometers traveled, vehicle stock and fuel efficiency. Price and income elasticities obtained are broadly consistent
with those reported in the literature. Among other results, an increase in the fuel price of 10% would reduce driving by ~2%
in the long term and by 1% the average fuel consumption rate. Estimates of the short- and long-term rebound effects are ~8
and 20%, respectively. We also find that an increase in the gross domestic product per capita of 10% would cause an increase
in driving distance of 2–3% and an increase of up to 4% in vehicle stock per adult. In terms of policy implications, our results
suggest that: (1) the effectiveness of new fuel efficiency standards will be somewhat mitigated by the rebound effect and
(2) fuel price increases have limited impacts on gasoline demand.
Philippe Barla is full professor at the economics department of Université Laval. He is currently the director of the research center GREEN and is a member of CDAT. He is conducting theoretical and empirical research on energy efficiency in the transportation sector. Bernard Lamonde obtained his MA in economics in 2007 working on this project. He is working as an economist for Agence de l’efficacité énergique du Québec. Luis Miranda-Moreno is professor at McGill Department of Civil Engineering and Applied Mechanics. He was post-doctoral student at CDAT when this research was carried out. His research interests include road safety, travel behaviour and demand modeling. Nathalie Boucher holds a PhD in economics from Queens’ University. She is the executive director the CDAT a research center dedicated to improving knowledge about energy use in the Canadian private and commercial transportation sector. 相似文献
Philippe BarlaEmail: |
Philippe Barla is full professor at the economics department of Université Laval. He is currently the director of the research center GREEN and is a member of CDAT. He is conducting theoretical and empirical research on energy efficiency in the transportation sector. Bernard Lamonde obtained his MA in economics in 2007 working on this project. He is working as an economist for Agence de l’efficacité énergique du Québec. Luis Miranda-Moreno is professor at McGill Department of Civil Engineering and Applied Mechanics. He was post-doctoral student at CDAT when this research was carried out. His research interests include road safety, travel behaviour and demand modeling. Nathalie Boucher holds a PhD in economics from Queens’ University. She is the executive director the CDAT a research center dedicated to improving knowledge about energy use in the Canadian private and commercial transportation sector. 相似文献
585.
<Emphasis Type="Italic">Not</Emphasis> driving alone? American commuting in the twenty-first century
This paper investigates recent commuting trends by American workers. Unlike most studies of commuting that rely on data from
the American Community Survey this study utilizes the American Time Use Survey to detail the complex commuting patterns of
modern-day workers. Changes in the price of gasoline in recent years suggest that the incidence of “driving alone” should
be on the decline. Indeed, results show that the sensitivity of modal commuting with respect to changes in gasoline prices
appears to be relatively large. We estimate the gasoline-price elasticity of driving alone to be 0.057 and the gasoline-price
elasticity of carpooling to be 0.502. Additional factors also affect commuting, including socio-economic characteristics and
social desires. However, it is changes in gasoline prices that appear to account for nearly all of the recent variation in
the mode chosen for commuting. 相似文献
586.
This study presents a unified framework to understand the weekday recreational activity participation time-use of adults,
with an emphasis on the time expended in physically active recreation pursuits by location and by time-of-day. Such an analysis
is important for a better understanding of how individuals incorporate physical activity into their daily activities on a
typical weekday, and can inform the development of effective policy interventions to facilitate physical activity. Furthermore,
such a study of participation and time use in recreational activity episodes contributes to activity-based travel demand modeling,
since recreational activity participation comprises a substantial share of individuals’ total non-work activity participation.
The methodology employed here is the multiple discrete continuous extreme value (MDCEV) model, which provides a unified framework
to explicitly and endogenously examine time use by type, location, and timing. The data for the empirical analysis is drawn
from the 2000 Bay Area Travel Survey (BATS), supplemented with other secondary sources that provide information on physical
environment variables. To our knowledge, this is the first study to jointly address the issues of ‘where’, ‘when’ and ‘how
much’ individuals choose to participate in ‘what type of (recreational) activity’. 相似文献
587.
Agent-based microsimulation models of transportation, land use or other socioeconomic processes require an initial synthetic
population derived from census data, conventionally created using the iterative proportional fitting (IPF) procedure. This
paper introduces a novel computational method that allows the synthesis of many more attributes and finer attribute categories
than previous approaches, both of which are long-standing limitations discussed in the literature. Additionally, a new approach
is used to fit household and person zonal attribute distributions simultaneously. This technique was first adopted to address
limitations specific to Canadian census data, but could also be useful in U.S. and other applications. The results of each
new method are evaluated empirically in terms of goodness-of-fit. 相似文献
588.
It is possible for a twin-screw ship that one screw failure occurs during navigation, and the maneuverability in this case should be noticed by ship designers and operators. It is of great significance to evaluate the related risk. Firstly, a mathematical model for the twin-screw ship maneuvering motion with one failed screw is developed based on the maneuvering model group (MMG) equations, and verified by the model test results. Secondly, the maneuvering motions of a twin-screw liquefied natural gas (LNG) ship with one free rotating failure screw or with one locked failure screw are simulated and compared by using the mathematical model. It is shown that the numerical modeling results are in agreement with the model test results. Compared with those of normal navigation, the port turning ability of the ship with one failed port screw is better, but the starboard turning ability and yaw checking ability become worse. The maneuverability of the ship with locked failure screw is better than that with free failure screw, although the ship speed drops obviously. 相似文献
589.
This paper investigates the gap between qualitative and quantitative constraints in spare parts stock control, with specific reference to warship spare parts support projects. A critical literature review of theoretical contributions about qualitative or quantitative factors for warship spare parts warehouse management is firstly provided, which allows to analyze the reasons for this qualitative-quantitative gap by addressing the limitations of spare parts models developed in the literature. Therefore a model including cloud model, marginal analysis and Lagrange multiplier method (CML) for study is proposed in this paper to bridge the gap. The model is used to solve the mix-constraints (both qualitative and quantitative constraints are considered) problem in a logic decision diagram particularly at the different decision nodes of the diagram. Finally, verifying test results show that the algorithm is feasible and its optimal support project meets the needs of engineering practices. 相似文献
590.
The rate equations and power evolution equations of erbium-doped telluride glass fiber amplifier for both 1.530 and 2.700 μm lasers are solved numerically, the dependences of gain spectra on fiber length, dopant concentration and pump power are analyzed, and the gain of 2.700 μm laser is calculated and compared with the experimental result from reference. The numerical analysis shows that with 8 × 1024 ion/m3 erbium ion concentration, 5m fiber length and 600mW pump power, the gains at 1.530 and 2.700 μm may achieve 23dB or so. With larger power pump and higher dopant concentration, a net gain of 17 dB is obtained from the Er3+-doped telluride glass fiber amplifier for 110mW input signal. This fiber amplifier is promising for both 1.530 μm signal amplification and 2.700 μm laser amplification. 相似文献