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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: |
3.
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
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.
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: |
6.
Despite widespread growth in on-road public transport priority schemes, road management authorities have few tools to evaluate
the impacts of these schemes on all road users. This paper describes a methodology developed in Melbourne, Australia to assist
the road management authority, VicRoads, evaluate trade-offs in the use of its limited road-space for new bus and tram priority
projects. The approach employs traffic micro-simulation modelling to assess road-space re-allocation impacts, travel behaviour
modelling to assess changes in travel patterns and a social cost benefit framework to evaluate impacts. The evaluation considers
a comprehensive range of impacts including the environmental benefits of improved public transport services. Impacts on public
transport reliability improvements are also considered. Although improved bus and tram reliability is a major rationale for
traffic priority its use in previous evaluations is rare. The paper critiques previous approaches, describes the proposed
method and explores some of the results found in its application. A major finding is that despite a more comprehensive approach
to measuring the benefits of bus and tram priority, road-space reallocation is difficult to economically justify in road networks
where public transport usage is low and car usage high. Strategies involving the balanced deployment of bus and tram priority
measures where the allocation of time and space to PT minimises negative traffic impacts is shown to improve the overall management
of road-space. A discussion of the approach is also provided including suggestions for further methodology development.
相似文献
Bill YoungEmail: |
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.
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: |
9.
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: |
10.
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
11.
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: |
12.
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
13.
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
14.
The ever-increasing use of cars is a big problem in metropolitan areas. To manage the traffic stream and alleviate air pollution,
most metropolitan governments are attempting to discourage the use of cars. Nevertheless, the results have not been satisfactory.
It is well known that normal-choice riders choose their travel mode based on utility, which is determined by mode-specific
impedances and individual characteristics. On the other hand, this study focuses on identifying car-dependent commuters who
tend to keep driving cars regardless of the circumstances they are confronted with. For this study, psychometric factors characterizing
car-dependent commuters were investigated. However, the performance of the mode-choice model was not sufficiently enhanced
despite incorporation of the psychometric factors. The performance improved considerably when the car-dependent commuters
were excluded. Based on psychometric factors, the support vector machine successfully separated the car-dependent commuters
from normal-choice riders.
相似文献
Keemin SohnEmail: |
15.
Understanding of the activity-travel patterns of children is becoming increasingly important to various policy makers. Further,
there is also a growing recognition that intra-household interactions need to be explicitly accommodated in travel models
for realistic forecasts and policy evaluation. In the light of these issues, this paper contributes towards an overall understanding
of the school-travel behavior of children and the related interdependencies among the travel patterns of parents and children.
An econometric model is formulated to simultaneously determine the choice of mode and the escorting person for children’s
travel to and from school. The 2000 San Francisco Bay Area Travel Survey (BATS) data are used in the model estimation process.
Empirical results indicate that the characteristics of child like age, gender, and ethnicity, and employment and work flexibility
characteristics of the parents have strong impacts on the mode choice decisions. In addition, the impacts of some of these
attributes on the choice of mode to school are different from the corresponding impacts on the choice of mode from school. The distance between home and school is found to strongly and negatively impact the choice of walking to and from
school, with the impact being stronger for walking to school. Several land-use and built-environment variables were explored,
but were found not to be statistically significant predictors.
相似文献
Sivaramakrishnan Srinivasan (Corresponding author)Email: |
16.
The influence of built environment to the trends in commuting journeys in the Netherlands 总被引:1,自引:0,他引:1
In this paper we describe commuting trends in the Netherlands in the past decade and examine the influence of urban form and
travel accessibility on commuting journeys over time on the basis of data from the Dutch National Travel Survey. Exploratory
analysis is performed to identify changes in commuting participation, departure time, commuting time, commuting distance and
the modal split. Regression analysis and choice models are used to examine the influence of the built environment on commuting
parameters over time. The results indicate that urban form has consistently influenced the parameters of commuting journey
in the Netherlands in the last 10 years. However, the trend of the influence is unique for each commuting model. Some influences
have become less significant in the last decade and some have become stronger.
相似文献
Kees MaatEmail: |
17.
This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific
activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal
and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict
optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The
daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of
composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether
the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal
activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate
the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed
activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero
frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating
the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations
of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.
相似文献
Eric J. MillerEmail: |
18.
An integrated spatio-temporal GIS toolkit for exploring intra-household interactions 总被引:1,自引:0,他引:1
This paper reports on the development of an integrated spatio-temporal GIS toolkit that facilitates the exploration of intra-household
interactions. Two tools comprise the toolkit. The first tool, Space-Time Coincidence Analyst, identifies joint activity/travel episodes undertaken by household members. The core of this tool is a set of flexible criteria
for classifying episodes as either joint or independent. The second tool, Space-Time Path Visualizer, not only displays space-time paths for household members, but also shows joint episodes undertaken by any two household
members together. The toolkit can be applied to any household-based, activity/travel data set so long as required information
is specified by the user. To demonstrate its usefulness for research, the toolkit is applied to the TAPS (Toronto Activity
Panel Survey) 2002–03 data set. The results suggest that considerable variation exists in the number of joint activity/travel
episodes identified using different classification criteria. Specifically, when using restrictive criteria (i.e., same timing,
specific activity type/travel mode), only 2,265 joint activity/travel episodes are identified compared to 8,791 when using
more flexible criteria. In turn, our results show that certain key attributes for independent and joint activity/travel episodes
(i.e., frequency per household, starting time, ending time and duration) also vary under the different classification criteria.
Hejun Kang is a PhD candidate in the School of Geography and Earth Sciences at McMaster University. She holds a MSc degree in Geographic Information Science from the University of Calgary. Her doctoral research concerns intra-household interactions in the context of activity/travel behavior. Darren M. Scott is an Associate Professor of Geography at McMaster University. His current research centers on inter-agent decision making with regards to activity/travel behavior, and on issues concerning aggregation in activity-based travel demand models, most notably the treatment of space and the classification of activities. 相似文献
Darren M. ScottEmail: |
Hejun Kang is a PhD candidate in the School of Geography and Earth Sciences at McMaster University. She holds a MSc degree in Geographic Information Science from the University of Calgary. Her doctoral research concerns intra-household interactions in the context of activity/travel behavior. Darren M. Scott is an Associate Professor of Geography at McMaster University. His current research centers on inter-agent decision making with regards to activity/travel behavior, and on issues concerning aggregation in activity-based travel demand models, most notably the treatment of space and the classification of activities. 相似文献
19.
This contribution presents theoretical considerations concerning the connections between life situation, lifestyle, choice
of residential location and travel behaviour, as well as empirical results of structural equation models. The analyses are
based on data resulting from a survey in seven study areas in the region of Cologne. The results indicate that lifestyles
influence mode choice, although slightly, even when life situation is controlled for. The influence of life situation on mode
choice exceeds the influence of lifestyle. The influence that lifestyle, and in part also life situation, has on mode choice
is primarily mediated by specific location attitudes and location decisions that influence mode choice, respectively. Here
objective spatial conditions as well as subjective location attitudes are important.
相似文献
Joachim ScheinerEmail: |
20.
The impact of high-speed technology on railway demand 总被引:1,自引:0,他引:1
This paper estimates a passenger railway demand function to analyse effects arising from the introduction and use of high-speed
technologies. The paper reports estimates of demand elasticities with respect to price, income, quality of service and a range
of exogenous characteristics. The results show that travel time savings from conventional high-speed technology have a larger
impact on passenger demand than tilting train technology. The introduction of conventional high-speed technology is associated
with an 8% increase in passenger railway demand. Increasing the use of either type of high-speed technology appears to induce
small positive effects on demand beyond those obtained from usual traffic density increases on non-high-speed existing technology.
Antonio Couto is an assistant professor in the Faculty of Engineering (FEUP) at the University of Porto. He received his PhD from FEUP in 2005 having completed a thesis in railway transport economics. His research focuses on issues related to transport economics and infrastructures. Daniel J. Graham is a Reader in the Centre for Transport Studies at Imperial College London. He specialises in the economics of transport, focusing in particular on modelling the implications of transport provision and accessibility for productivity and economic growth. 相似文献
Daniel J. Graham (Corresponding author)Email: |
Antonio Couto is an assistant professor in the Faculty of Engineering (FEUP) at the University of Porto. He received his PhD from FEUP in 2005 having completed a thesis in railway transport economics. His research focuses on issues related to transport economics and infrastructures. Daniel J. Graham is a Reader in the Centre for Transport Studies at Imperial College London. He specialises in the economics of transport, focusing in particular on modelling the implications of transport provision and accessibility for productivity and economic growth. 相似文献