Atmospheric and water pollution are two main sources of negative environmental externalities generated by shipping. This study recognizes the negative externalities in the production of port services in East Asia by explicitly incorporating environmental impacts of shipping. Programming techniques are used to analyze 156 Origin–Destination pairs between 13 major East Asian ports, to derive the externality-augmented measures of port productivity and efficiency at the waterside. The results suggest that the inclusion of externality mitigation strategies can exert a considerable influence on efficiency performance. 相似文献
Robust public transport networks are important, since disruptions decrease the public transport accessibility of areas. Despite this importance, the full passenger impacts of public transport network vulnerability have not yet been considered in science and practice. We have developed a methodology to identify the most vulnerable links in the total, multi-level public transport network and to quantify the societal costs of link vulnerability for these identified links. Contrary to traditional single-level network approaches, we consider the integrated, total multi-level PT network in the identification and quantification of link vulnerability, including PT services on other network levels which remain available once a disturbance occurs. We also incorporate both exposure to large, non-recurrent disturbances and the impacts of these disturbances explicitly when identifying and quantifying link vulnerability. This results in complete and realistic insights into the negative accessibility impacts of disturbances. Our methodology is applied to a case study in the Netherlands, using a dataset containing 2.5 years of disturbance information. Our results show that especially crowded links of the light rail/metro network are vulnerable, due to the combination of relatively high disruption exposure and relatively high passenger flows. The proposed methodology allows quantification of robustness benefits of measures, in addition to the costs of these measures. Showing the value of robustness, our work can support and rationalize the decision-making process of public transport operators and authorities regarding the implementation of robustness measures. 相似文献
This paper develops a mathematical model that is based on the absorbing Markov chain approach to describe taxi movements, taking into account the stochastic searching processes of taxis in a network. The local searching behavior of taxis is specified by a logit form, and the O‐D demand of passengers is estimated as a logit model with a choice of taxi meeting point. The relationship between customer and taxi waiting times is modeled by a double‐ended queuing system. The problem is solved with a set of non‐linear equations, and some interesting results are presented. The research provides a novel and potentially useful formulation for describing the urban taxi services in a network. 相似文献
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.
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
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.
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
Transportation planning continues to expand beyond traditional engineering and economic performance measures toward a broader scope of impacts across space and society. However, the attitudes of transportation planners as they balance their expert knowledge against public insights are not well-understood. We test a two-dimensional attitudinal framework using survey data from 311 U.S. and Canadian transportation planners. We reveal four attitudinal categories using principal component analysis, and hypothesis testing shows significant differences in personal and institutional attributes across these categories. We discuss what our results mean for training and regulatory measures striving to influence planner attitudes before proposing future directions for research.