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Lawrence Frank Mark Bradley Sarah Kavage James Chapman T. Keith Lawton 《Transportation》2008,35(1):37-54
The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns
where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By
using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the
specific land use changes necessary to address different types of travel, and to develop a comparative framework by which
the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for
demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining
characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative
contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel.
Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice.
Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within
a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns
where respondents work predicted mode choice for mid day and journey to work travel.
Lawrence Frank is an Associate Professor and Bombardier Chair in Sustainable Transportation at the University of British Columbia and a Senior Non-Resident Fellow of the Brookings Institution and Principal of Lawrence Frank and Company. He has a PhD in Urban Design and Planning from the University of Washington. Mark Bradley is Principal, Mark Bradley Research & Consulting, Santa Barbara California. He has a Master of Science in Systems Simulation and Policy Design from the Dartmouth School of Engineering and designs forecasting and simulation models for assessment of market-based policies and strategies. Sarah Kavage is a Senior Transportation Planner and Special Projects Manager at Lawrence Frank and Company. She has a Masters in Urban Design and Planning from the University of Washington and is a writer and an artist based in Seattle. James Chapman is a Principal Transportation Planner and Analyst at Lawrence Frank and Company in Atlanta Georgia. He has a Masters in Engineering from the Georgia Institute of Technology. T. Keith Lawton transport modeling consultant and past Director of Technical services, Metro Planning Department, Portland, OR, has been active in model development for over 40 years. He has a BSc. in Civil Engineering from the University of Natal (South Africa), and an M.S. in Civil and Environmental Engineering from Duke University. He is a member and past Chair of the TRB Committee on Passenger Travel Demand Forecasting. 相似文献
T. Keith LawtonEmail: |
Lawrence Frank is an Associate Professor and Bombardier Chair in Sustainable Transportation at the University of British Columbia and a Senior Non-Resident Fellow of the Brookings Institution and Principal of Lawrence Frank and Company. He has a PhD in Urban Design and Planning from the University of Washington. Mark Bradley is Principal, Mark Bradley Research & Consulting, Santa Barbara California. He has a Master of Science in Systems Simulation and Policy Design from the Dartmouth School of Engineering and designs forecasting and simulation models for assessment of market-based policies and strategies. Sarah Kavage is a Senior Transportation Planner and Special Projects Manager at Lawrence Frank and Company. She has a Masters in Urban Design and Planning from the University of Washington and is a writer and an artist based in Seattle. James Chapman is a Principal Transportation Planner and Analyst at Lawrence Frank and Company in Atlanta Georgia. He has a Masters in Engineering from the Georgia Institute of Technology. T. Keith Lawton transport modeling consultant and past Director of Technical services, Metro Planning Department, Portland, OR, has been active in model development for over 40 years. He has a BSc. in Civil Engineering from the University of Natal (South Africa), and an M.S. in Civil and Environmental Engineering from Duke University. He is a member and past Chair of the TRB Committee on Passenger Travel Demand Forecasting. 相似文献
3.
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
4.
Residential location,vehicle ownership and travel in Asia: a comparative analysis of Kei-Han-Shin and Kuala Lumpur metropolitan areas 总被引:1,自引:1,他引:0
The study examines the relationships between residential location, vehicle ownership and mobility in two metropolitan areas
of Asia, Kei-Han-Shin area of Japan and Kuala Lumpur area of Malaysia. It shows that, behind apparent similarities of household
auto ownership and travel time expenditure per household member, there are many causal relationships that are distinct between
the areas. The similarities and differences between the two areas point to the conjecture that the evolution of a metropolitan
area may be unique and path dependent, being heavily influenced by the history and culture of the locale, spatial and geographical
constraints, and historical progression in infrastructure development.
Metin Senbil is an Associate Professor in City and Regional Planning Department at Gazi University in Ankara, Turkey. He obtained the degree of Doctor of Engineering from Kyoto University, Japan. His research interests cover different aspects of urban travel demand and its interactions with telecommunications, land use, and policies directed at controlling as well as managing travel demand. Ryuichi Kitamura is Professor of Civil Engineering Systems at Kyoto University, Japan. His past research effort spans in the area of travel behavior analysis and demand forecasting, in particular in activity-based analysis, and panel surveys and dynamic analysis of travel behavior. He is associate editor of Transportation. Dr Jamilah Mohamad is Professor and Head of the Department of Geography, University of Malaya, Kuala Lumpur. Her main fields of research interest are travel behavior, the relationship between transport and spatial development and urban growth management. 相似文献
Jamilah MohamadEmail: |
Metin Senbil is an Associate Professor in City and Regional Planning Department at Gazi University in Ankara, Turkey. He obtained the degree of Doctor of Engineering from Kyoto University, Japan. His research interests cover different aspects of urban travel demand and its interactions with telecommunications, land use, and policies directed at controlling as well as managing travel demand. Ryuichi Kitamura is Professor of Civil Engineering Systems at Kyoto University, Japan. His past research effort spans in the area of travel behavior analysis and demand forecasting, in particular in activity-based analysis, and panel surveys and dynamic analysis of travel behavior. He is associate editor of Transportation. Dr Jamilah Mohamad is Professor and Head of the Department of Geography, University of Malaya, Kuala Lumpur. Her main fields of research interest are travel behavior, the relationship between transport and spatial development and urban growth management. 相似文献
5.
When a new public transport service is introduced it would be valuable for public authorities, financing organisations and
transport operators to know how long it will take for people to start to use the service and what factors influence this.
This paper presents results from research analysing the time taken for residents living close to a new guided bus service
to start to use (or adopt) the service. Data was obtained from a sample of residents on whether they used the new service
and the number of weeks after the service was introduced before they first used it. Duration modelling has been used to analyse
how the likelihood of starting to use the new service changes over time (after the introduction of the service) and to examine
what factors influence this. It is found that residents who have not used the new service are increasingly unlikely to use
it as time passes. Those residents gaining greater accessibility benefits from the new service are found to be quicker to
use the service, although the size of this effect is modest compared to that of other between-resident differences. Allowance
for the possibility that there existed a proportion of the sample that would never use the new service was tested using a
split population model (SPD) model. The SPD model indicates that 36% of residents will never use the new service and is informative
in differentiating factors that influence whether Route 20 is used and when it is used.
Kiron Chatterjee has been a Senior Lecturer at the University of the West of England, Bristol, since 2003 and previously was at the University of Southampton. Currently, a main focus of his research is on longitudinal analysis of travel behaviour to improve policy analysis. Kang-Rae Ma received a PhD in Planning from University College London. He worked at the University of the West of England, Bristol, and the Korea Transport Institute before he joined Chung-Ang University as an Assistant Professor. His research interests include modelling of travel behaviour and urban excess commuting. 相似文献
Kang-Rae MaEmail: |
Kiron Chatterjee has been a Senior Lecturer at the University of the West of England, Bristol, since 2003 and previously was at the University of Southampton. Currently, a main focus of his research is on longitudinal analysis of travel behaviour to improve policy analysis. Kang-Rae Ma received a PhD in Planning from University College London. He worked at the University of the West of England, Bristol, and the Korea Transport Institute before he joined Chung-Ang University as an Assistant Professor. His research interests include modelling of travel behaviour and urban excess commuting. 相似文献
6.
Using latent class cluster analysis, this paper investigates the spatial, social, demographic, and economic determinants of
immigrants’ joint distribution among travel time, mode choice, and departure time for work using the 2000 Census long form
data. Through a latent tree structure analysis, age, residential location, immigration stage, gender, personal income, and
race are found to be the primary determinants in the workplace commute decision-making process. By defining several relatively
homogeneous population segments, the likelihood of falling into each segment is found to differ across age groups and geography,
with different indicators affecting each group differentially. This analysis complements past studies that used regression
models to investigate socio-demographic indicators and their impact on travel behavior in two distinct ways: (a) analysis
is done by considering travel time, mode choice, and departure time for work simultaneously, and (b) heterogeneity in behavior
is accounted for using methods that identify different groups of behavior and then their determinants. Conclusively the method
here is richer than many other methods used to study the ethnically diverse population of California and shows the addition
of geographic location and latent segment identification to greatly improve our understanding of specific behaviors. It also
provides evidence that immigrants are as diverse as the non-immigrant population and transportation policies need to be defined
accordingly.
相似文献
Konstadinos G. GouliasEmail: |
7.
Mintesnot G. Woldeamanuel Rita Cyganski Angelika Schulz Andreas Justen 《Transportation》2009,36(4):371-387
For economic and environmental policy formulation and with the effort of creating less car dependent societies, it is important
to study the changing characteristics of car ownership in a household through time as well as factors responsible of these
variations. There is a vast body of literature on empirical studies of car ownership and use. These studies have investigated
the socio-economic background of the decision maker, the built environment and the perception associated with owning a car
as determinant factors of car ownership and use. In most cases, these analyses have been carried out using cross-sectional
data sets. However, the analysis of factors determining changes in travel behavior of an individual or household requires
information on their behavior over time (longitudinal data set). In this study, the German Mobility Panel (1996–2006) is used
to examine variation of car ownership through time and across households. The panel data modeling results showed that there
are variations of car ownership between households whereas changes in car ownership of a given household over time (within
household variations) are insignificant. The influence of other factors such as the households’ socio-economic background,
the availability of public transportation and shopping/leisure facilities, perception on parking difficulties and satisfaction
with existing public transportation services on the car owning characteristics of households is also presented and discussed
in this paper.
相似文献
Andreas JustenEmail: |
8.
Studying travel-related individual assessments and desires by combining hierarchically structured ordinal variables 总被引:1,自引:1,他引:0
Ordinal measures are frequently encountered in travel behavior research. This paper presents a new method for combining them
when a hierarchical structure of the data can be presumed. This method is applied to study the subjective assessment of the
amount of travel by different transportation modes among a group of French clerical workers, along with the desire to increase
or decrease the use of such modes. Some advantages of this approach over traditional data reduction technique such as factor
analysis when applied to ordinal data are then illustrated. In this study, combining evidence from several variables sheds
light on the observed moderately negative relationship between the personal assessment of the amount of travel and the desire
to increase or decrease it, thus integrating previous partial (univariate) results. We find a latent demand for travel, thus
contributing to clarify the behavioral mechanisms behind the induced traffic phenomenon. Categorizing the above relationship
by transportation mode shows a desire for a less environmental-friendly mix of modes (i.e., a greater desire to use heavy
motorized modes and a lower desire to use two-wheeled modes), whenever the respondents do not feel to travel extensively.
This result, combined with previous theoretical investigations concerning the determinants of the desire to alter trips consumption
levels, shows the importance of making people aware of how much they travel.
Marco Diana is a permanent researcher working at the Department of Hydraulics, Transport and Civil Infrastructures of Politecnico di Torino, Italy. His research interests include the study of innovative forms of public transport services and the analysis of multimodality behaviors. Tingting Song is a Scientific Programmer at The Rockefeller University, Center for Clinical and Translational Science, Biostatistics, Epidemiology, and Research Design Core, New York, NY, USA. She works on algorithms for non-parametric methods and their applications in medical research. She maintains the muStat package on CRAN.r-project.org and the Web server on muStat.rockefeller.edu. Knut M. Wittkowski is a Senior Research Associate at The Rockefeller University and Head of Biostatistics, Epidemiology, and Research Design at its Center for Clinical and Translational Science, New York, NY, USA. His research focuses on methods, meta data, and user interfaces to integrate nonparametric statistics into research and decision support systems. 相似文献
Knut M. WittkowskiEmail: |
Marco Diana is a permanent researcher working at the Department of Hydraulics, Transport and Civil Infrastructures of Politecnico di Torino, Italy. His research interests include the study of innovative forms of public transport services and the analysis of multimodality behaviors. Tingting Song is a Scientific Programmer at The Rockefeller University, Center for Clinical and Translational Science, Biostatistics, Epidemiology, and Research Design Core, New York, NY, USA. She works on algorithms for non-parametric methods and their applications in medical research. She maintains the muStat package on CRAN.r-project.org and the Web server on muStat.rockefeller.edu. Knut M. Wittkowski is a Senior Research Associate at The Rockefeller University and Head of Biostatistics, Epidemiology, and Research Design at its Center for Clinical and Translational Science, New York, NY, USA. His research focuses on methods, meta data, and user interfaces to integrate nonparametric statistics into research and decision support systems. 相似文献
9.
In this paper, we used the 10-wave Puget Sound Panel Dataset to investigate the response lag of a significant change in discretionary
time use. In particular, we want to quantify the relative magnitude of the following factors: the built environment, family
and social obligations, temporal constraints, or a psychological delay factor (people delay a behavioral change until the
next life shock). To answer this question, we developed a survival model to treat (1) left-censoring, (2) partial observation,
and (3) multi-type exits. The results suggest that family and social obligations, as well as temporal constraints, appear
to play a more important role than the built environment. Support for the psychological delay factor is not evident. We also
found that the probability of having a significant change in discretionary time use is negatively related to time progression,
supporting the human adaptivity hypothesis.
Cynthia Chen is an assistant professor of Civil Engineering at the City College of New York. Her recent research interests have been in travel behavior dynamics and residential search and location process. Jason Chen is a Ph.D. candidate in the department of civil engineering at the City University of New York. His research interests include travel behavior analysis, travel demand modeling, and residential location analysis. 相似文献
Jason ChenEmail: |
Cynthia Chen is an assistant professor of Civil Engineering at the City College of New York. Her recent research interests have been in travel behavior dynamics and residential search and location process. Jason Chen is a Ph.D. candidate in the department of civil engineering at the City University of New York. His research interests include travel behavior analysis, travel demand modeling, and residential location analysis. 相似文献
10.
Robert Bain 《Transportation》2009,36(5):469-482
Traffic forecasts are employed in the toll road sector, inter alia, by private sector investors to gauge the bankability of
candidate investment projects. Although much is written in the literature about the theory and practice of traffic forecasting,
surprisingly little attention has been paid to the predictive accuracy of traffic forecasting models. This paper addresses
that shortcoming by reporting the results from the largest study of toll road forecasting performance ever conducted. The
author had access to commercial-in-confidence documentation released to project financiers and, over a 4-year period, compiled
a database of predicted and actual traffic usage for over 100 international, privately financed toll road projects. The findings
suggest that toll road traffic forecasts are characterised by large errors and considerable optimism bias. As a result, financial
engineers need to ensure that transaction structuring remains flexible and retains liquidity such that material departures
from traffic expectations can be accommodated.
Robert Bain spent the first 15 years of his career as a traffic and transportation consultant before joining the infrastructure team at Standard & Poor’s in 2002. He is currently retained by the rating agency on a freelance basis and, separately, provides transport-related technical support services to infrastructure funds, insurance companies and institutional investors. Robert recently completed a PhD at the Institute for Transport Studies—hence his affiliation with the University of Leeds. 相似文献
Robert BainEmail: |
Robert Bain spent the first 15 years of his career as a traffic and transportation consultant before joining the infrastructure team at Standard & Poor’s in 2002. He is currently retained by the rating agency on a freelance basis and, separately, provides transport-related technical support services to infrastructure funds, insurance companies and institutional investors. Robert recently completed a PhD at the Institute for Transport Studies—hence his affiliation with the University of Leeds. 相似文献
11.
This paper investigates the impact of a variety of travel information types on the quality of travel choices. Choice quality
is measured by comparing observed choices made under conditions of incomplete knowledge with predicted choice probabilities
under complete knowledge. Furthermore, the potential impact of travel information is considered along multiple attribute-dimensions
of alternatives, rather than in terms of travel time reductions only. Data is obtained from a choice experiment in a multimodal
travel simulator in combination with a web-based mode-choice experiment. A Structural Equation Model is estimated to test
a series of hypothesized direct and indirect relations between a traveler’s knowledge levels, information acquisition behavior
and the resulting travel-choice quality. The estimation results support the hypothesized relations, which provides evidence
of validity and applicability of the developed measure of travel-choice quality. Furthermore, found relations in general provide
some careful support for the often expected impact of information on the quality of travel choices. The effects are largest
for information services that generate previously unknown alternatives, and lowest for services that provide warnings in case
of high travel times only.
Caspar Chorus holds a PhD in Technical Sciences (cum laude) from Delft University of Technology, and is currently an Assistant Professor at Eindhoven University of Technology’s Urban Planning Group. His general interests include traveler behavior research / decision making under knowledge limitations / discrete choice analysis. Theo Arentze received a Ph.D. in Decision Support Systems for urban planning from the Eindhoven University of Technology. He is now an Associate Professor at the Urban Planning Group at the same university. His main fields of expertise and current research interests are decision support systems, activity-based modeling, discrete choice modeling, knowledge discovery and learning-based systems with applications in urban and transport planning. Harry Timmermans received a Ph.D. in Spatial Sciences from the University of Nijmegen. He is Chair of the Urban Planning Group and Director of the European Institute of Retailing and Consumer Services. His main fields of expertise concern behavioral modeling, consumer studies and computer systems in a variety of application contexts including transportation. 相似文献
Caspar G. ChorusEmail: |
Caspar Chorus holds a PhD in Technical Sciences (cum laude) from Delft University of Technology, and is currently an Assistant Professor at Eindhoven University of Technology’s Urban Planning Group. His general interests include traveler behavior research / decision making under knowledge limitations / discrete choice analysis. Theo Arentze received a Ph.D. in Decision Support Systems for urban planning from the Eindhoven University of Technology. He is now an Associate Professor at the Urban Planning Group at the same university. His main fields of expertise and current research interests are decision support systems, activity-based modeling, discrete choice modeling, knowledge discovery and learning-based systems with applications in urban and transport planning. Harry Timmermans received a Ph.D. in Spatial Sciences from the University of Nijmegen. He is Chair of the Urban Planning Group and Director of the European Institute of Retailing and Consumer Services. His main fields of expertise concern behavioral modeling, consumer studies and computer systems in a variety of application contexts including transportation. 相似文献
12.
Clarke Wilson 《Transportation》2008,35(4):485-499
Daily activity diaries can be recorded as sequences of characters representing events and their contexts as they unfold during
the day. Dynamic programming algorithms as used in bioinformatics have been used by a number of researchers to measure the
similarities and differences between travel patterns on the basis of temporal sequencing of events, activity transition, and
total activity time. The resultant similarity matrices have been shown to be more effective in classifying sequential patterns
than classifications based on alternative similarity indices. The basic algorithms can be amended to include the geographic
coordinates of events by a suitable amendment to the definition of distance. This permits quantitative classification of Hagerstrand-type
activity trajectories on the basis of both activity and spatial similarity. Such a classification can be used to group similar
trajectories and to identify representative trajectories that are analogous to measures of central tendency in univariate
statistics, giving more concrete meaning to the concept of the activity pattern than any other method now available. The paper
illustrates the effect of considering both events and locations in the classification of daily activity patterns using activity
diary data gathered in the town of Reading. The algorithm has been implemented in the Clustal_TXY alignment software package.
相似文献
Clarke WilsonEmail: |
13.
In the US, the rise in motorized vehicle travel has contributed to serious societal, environmental, economic, and public health
problems. These problems have increased the interest in encouraging non-motorized modes of travel (walking and bicycling).
The current study contributes toward this objective by identifying and evaluating the importance of attributes influencing
bicyclists’ route choice preferences. Specifically, the paper examines a comprehensive set of attributes that influence bicycle
route choice, including: (1) bicyclists’ characteristics, (2) on-street parking, (3) bicycle facility type and amenities,
(4) roadway physical characteristics, (5) roadway functional characteristics, and (6) roadway operational characteristics.
The data used in the analysis is drawn from a web-based stated preference survey of Texas bicyclists. The results of the study
emphasize the importance of a comprehensive evaluation of both route-related attributes and bicyclists’ demographics in bicycle
route choice decisions. The empirical results indicate that travel time (for commuters) and motorized traffic volume are the
most important attributes in bicycle route choice. Other route attributes with a high impact include number of stop signs,
red light, and cross-streets, speed limits, on-street parking characteristics, and whether there exists a continuous bicycle
facility on the route.
Ipek N. Sener is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. She received her M.S. degrees in Civil Engineering and in Architecture, and her B.S. degree in Civil Engineering from the Middle East Technical University in Ankara, Turkey. Naveen Eluru is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. He received his M.S. degree in Civil Engineering from The University of Texas at Austin, and his Bachelors in Technology Degree from Indian Institute of Technology in Madras, India. 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: |
Ipek N. Sener is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. She received her M.S. degrees in Civil Engineering and in Architecture, and her B.S. degree in Civil Engineering from the Middle East Technical University in Ankara, Turkey. Naveen Eluru is currently a Ph.D. candidate in transportation engineering at The University of Texas at Austin. He received his M.S. degree in Civil Engineering from The University of Texas at Austin, and his Bachelors in Technology Degree from Indian Institute of Technology in Madras, India. 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
14.
Stephen Godwin 《运输规划与技术》2013,36(1):25-36
This paper presents an artificial neural network (ANN) based method for estimating route travel times between individual locations in an urban traffic network. Fast and accurate estimation of route travel times is required by the vehicle routing and scheduling process involved in many fleet vehicle operation systems such as dial‐a‐ride paratransit, school bus, and private delivery services. The methodology developed in this paper assumes that route travel times are time‐dependent and stochastic and their means and standard deviations need to be estimated. Three feed‐forward neural networks are developed to model the travel time behaviour during different time periods of the day‐the AM peak, the PM peak, and the off‐peak. These models are subsequently trained and tested using data simulated on the road network for the City of Edmonton, Alberta. A comparison of the ANN model with a traditional distance‐based model and a shortest path algorithm is then presented. The practical implication of the ANN method is subsequently demonstrated within a dial‐a‐ride paratransit vehicle routing and scheduling problem. The computational results show that the ANN‐based route travel time estimation model is appropriate, with respect to accuracy and speed, for use in real applications. 相似文献
15.
This paper presents a detailed exploratory analysis of joint activity participation characteristics using the American Time
Use Survey (ATUS). As a very large nationwide survey that explicitly elicited information on both household and non-household
companions for each activity episode, the ATUS is ideally suited for this analysis. Several intuitive and interesting results
are obtained. Joint episodes are found to be of longer durations, significantly likely to take place at the residence of other
people, and often confined to certain time periods of the weekday. In addition, important differences in these characteristics
are also observed based on activity purpose, companion type, and the day of the week. These findings are intended to provide
the basis for the justification of detailed collection of joint activity–travel participation information in household activity–travel
surveys, and also as a stimulant for further empirical analysis and modeling of joint activity participation behavior.
相似文献
Chandra R. BhatEmail: |
16.
Singapore motorisation restraint and its implications on travel behaviour and urban sustainability 总被引:1,自引:0,他引:1
Piotr S. Olszewski 《Transportation》2007,34(3):319-335
The example of Singapore shows that rapid urban and economic growth does not have to bring traffic congestion and pollution.
Singapore has chosen to restrain car traffic demand due to its limited land supply. Transport policy based on balanced development
of road and transit infrastructure and restraint of traffic has been consistently implemented for the past 30 years. Combined
with land use planning, it resulted in a modern transport system, which is free from major congestion and provides users with
different travel alternatives. As the economic growth caused a substantial increase in demand for cars, several pricing policies
were introduced with the aim of restraining car ownership and usage. Growth of the vehicle population is now controlled and
potentially congested roads are subject to road pricing. These measures help to keep the roads free from major congestion,
maintain car share of work trips below 25% and keep the transport energy usage low. Although Singapore conditions are in many
aspects unique, its travel demand experience can provide useful lessons for other rapidly growing cities in Asia.
相似文献
Piotr S. OlszewskiEmail: |
17.
Anthony Chen Zhong ZhouWilliam H.K. Lam 《Transportation Research Part B: Methodological》2011,45(10):1619-1640
In this paper, we extend the α-reliable mean-excess traffic equilibrium (METE) model of Chen and Zhou (Transportation Research Part B 44(4), 2010, 493-513) by explicitly modeling the stochastic perception errors within the travelers’ route choice decision processes. In the METE model, each traveler not only considers a travel time budget for ensuring on-time arrival at a confidence level α, but also accounts for the impact of encountering worse travel times in the (1 − α) quantile of the distribution tail. Furthermore, due to the imperfect knowledge of the travel time variability particularly in congested networks without advanced traveler information systems, the travelers’ route choice decisions are based on the perceived travel time distribution rather than the actual travel time distribution. In order to compute the perceived mean-excess travel time, an approximation method based on moment analysis is developed. It involves using the conditional moment generation function to derive the perceived link travel time, the Cornish-Fisher Asymptotic Expansion to estimate the perceived travel time budget, and the Acerbi and Tasche Approximation to estimate the perceived mean-excess travel time. The proposed stochastic mean-excess traffic equilibrium (SMETE) model is formulated as a variational inequality (VI) problem, and solved by a route-based solution algorithm with the use of the modified alternating direction method. Numerical examples are also provided to illustrate the application of the proposed SMETE model and solution method. 相似文献
18.
Toshiyuki Yamamoto 《Transportation》2009,36(3):351-366
The interactions among different types of vehicle ownership including car, motorcycle and bicycle are examined by developing
simultaneous vehicle ownership models in this study. Large scale person trip survey data for Osaka metropolitan area, Japan
and Kuala Lumpur, Malaysia are used for empirical analysis. The results suggest that population density at residential area
significantly and negatively affects car ownership for both areas, and that the effects are larger for Osaka metropolitan
area than for Kuala Lumpur. Also, bicycle ownership becomes higher at higher population density area for Osaka area, while
higher at lower population density area for Kuala Lumpur, which represents the different usage patterns of bicycle between
the two areas.
相似文献
Toshiyuki YamamotoEmail: |
19.
Gerard de Jong Andrew Daly Marits Pieters Stephen Miller Ronald Plasmeijer Frank Hofman 《Transportation》2007,34(4):375-395
This paper provides a review of transport model applications that not only provide a central traffic forecast (or forecasts
for a few scenarios), but also quantify the uncertainty in the traffic forecasts in the form of a confidence interval or related
measures. Both uncertainty that results from using uncertain inputs (e.g. on income) and uncertainty in the model itself are
treated. The paper goes on to describe the methods used and the results obtained for a case study in quantifying uncertainty
in traffic forecasts in The Netherlands.
相似文献
Gerard de JongEmail: |
20.
Travel time functions specify the relationship between the travel time on a road and the volume of traffic on the road. Until recently, the parameters of travel time functions were rarely estimated in practice; however, a compelling case can be made for the empirical examination of these functions. This paper reviews, and qualitatively evaluates, a range of options for developing a set of travel time functions. A hierarchy of travel time functions is defined based on four levels of network detail: area, corridor, route and link. This hierarchy is illustrated by considering the development of travel time functions for Adelaide. Alternative sources of data for estimating travel time functions are identified. In general, the costs and benefits increase as the travel time functions are estimated at finer levels of network detail. The costs of developing travel time functions include data acquisition costs and analysis costs. The benefits include the potential for reducing prediction errors, the degree of application flexibility and the policy sensitivity of the travel time functions. 相似文献