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1.
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: |
2.
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: |
3.
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: |
4.
Modeling residential sorting effects to understand the impact of the built environment on commute mode choice 总被引:5,自引:2,他引:3
Abdul Rawoof Pinjari Ram M. Pendyala Chandra R. Bhat Paul A. Waddell 《Transportation》2007,34(5):557-573
This paper presents an examination of the significance of residential sorting or self selection effects in understanding the
impacts of the built environment on travel choices. Land use and transportation system attributes are often treated as exogenous
variables in models of travel behavior. Such models ignore the potential self selection processes that may be at play wherein
households and individuals choose to locate in areas or built environments that are consistent with their lifestyle and transportation
preferences, attitudes, and values. In this paper, a simultaneous model of residential location choice and commute mode choice
that accounts for both observed and unobserved taste variations that may contribute to residential self selection is estimated
on a survey sample extracted from the 2000 San Francisco Bay Area household travel survey. Model results show that both observed
and unobserved residential self selection effects do exist; however, even after accounting for these effects, it is found
that built environment attributes can indeed significantly impact commute mode choice behavior. The paper concludes with a
discussion of the implications of the model findings for policy planning.
相似文献
Paul A. WaddellEmail: |
5.
Children’s mode choice for the school trip: the role of distance and school location in walking to school 总被引:2,自引:0,他引:2
Noreen C. McDonald 《Transportation》2008,35(1):23-35
Rising levels of childhood obesity in the United States and a 75% decline in the proportion of children walking to school
in the past 30 years have focused attention on school travel. This paper uses data from the US Department of Transportation’s
2001 National Household Travel Survey to analyze the factors affecting mode choice for elementary and middle school children.
The analysis shows that walk travel time is the most policy-relevant factor affecting the decision to walk to school with
an estimated direct elasticity of −0.75. If policymakers want to increase walking rates, these findings suggest that current
policies, such as Safe Routes to School, which do not affect the spatial distribution of schools and residences will not be
enough to change travel behavior. The final part of the paper uses the mode choice model to test how a land use strategy—community
schools—might affect walking to school. The results show that community schools have the potential to increase walking rates
but would require large changes from current land use, school, and transportation planning practices.
Noreen C. McDonald is an Assistant Professor at the University of North Carolina at Chapel Hill. Her research focuses on how the environment affects children’s travel behavior. 相似文献
Noreen C. McDonaldEmail: |
Noreen C. McDonald is an Assistant Professor at the University of North Carolina at Chapel Hill. Her research focuses on how the environment affects children’s travel behavior. 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.
Xinyu ?Cao 《Transportation》2009,36(2):207-222
The causality issue has become one of the key questions in the debate over the relationships between the built environment
and travel behavior. Although previous studies have tested statistical and/or practical significance of the built environment
on travel behavior, few have quantified the relative roles of the built environment and residential self-selection in influencing
travel behavior. Using 1,479 residents living in four traditional and four suburban neighborhoods in Northern California,
this study explores the causal effect of neighborhood type on driving behavior and its relative contribution to the total
influence of neighborhood type. Specifically, this study applied Heckman’s sample selection model to separate the effect of
the built environment itself and the effect of self-selection. The results showed that, on average, the effect of neighborhood
type itself on driving distance was 25.8 miles per week, which accounted for more than three quarters of the total influence
of neighborhood type and 16% of individuals’ overall vehicle miles driven. These results suggest that the effect of the built
environment on driving behavior outweighs that of self-selection. This paper also discussed the advantages and weaknesses
of applying the Heckman’s model to address the self-selection issue.
相似文献
Xinyu (Jason) CaoEmail: |
8.
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.
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Andreas JustenEmail: |
9.
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: |
10.
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: |
11.
12.
The impact of urban form on automobile travel: disentangling causation from correlation 总被引:5,自引:3,他引:2
A longstanding question within the field of transportation demand management is the strength of the relationship between urban
form and mobility behavior. Although several studies have identified a strong correlation between these variables, there is
as yet scant evidence to support policy interventions that target land use as a means of influencing travel. To the contrary,
some of the more recent research has cast skepticism on the proposition that the relationship is causative, recognizing the
possibility that households endogenously self-select themselves into communities that support their preferences for particular
transportation modes. Focusing on individual automobile travel, the present study seeks to contribute to this line of inquiry
by estimating econometric models on a panel of travel-diary data collected in Germany between 1996 and 2003. Specifically,
we employ the two-part model (2PM)—a procedure involving probit and OLS estimators—to assess the determinants of the discrete
decision to use the car and the continuous decision of distance traveled. Beyond modeling variables that capture the urban
form features that are commonly suggested to influence mobility behavior, including mixed use and public transit, this study
employs instrumental variables to control for potential endogeneity emerging from the simultaneity of residential and mode
choices. Unlike much of the work to date, our results suggest that urban form has a causative impact on car use, a finding
that is robust to alternative econometric specifications.
相似文献
Ralf HedelEmail: |
13.
This paper analyzes transportation mode choice for short home-based trips using a 1999 activity survey from the Puget Sound
region of Washington State, U.S.A. Short trips are defined as those within the 95th percentile walking distance in the data,
here 1.40 miles (2.25 km). The mean walking distance was 0.4 miles (0.6 km). The mode distribution was automobile (75%), walk
(23%), bicycle (1%), and bus (1%). Walk and bicycle are found less likely as the individual’s age increases. People are more
likely to drive if they can or are accustomed to. People in multi-person families are less likely to walk or use bus, especially
families with children. An environment that attracts people’s interest and provides activity opportunities encourages people
to walk on short trips. Influencing people’s choice of transport mode on short trips should be an important part of efforts
encouraging the use of non-automobile alternatives.
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Gudmundur F. UlfarssonEmail: |
14.
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
15.
Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto Travel-Activity Panel Survey (TTAPS) 总被引:1,自引:0,他引:1
Studies of urban travel behaviour typically focus on weekday activities and commuting. This is surprising given the rising
contribution of discretionary activities to daily travel that has occurred during the last few decades. Moreover, current
understanding of the relationship between travel behaviour and land use remains incomplete, with little research carried out
to explore spatial properties of activity-travel behaviour during the off-peak and weekend time periods. Weekend behaviours,
for example, influenced by the availability of time and the spatiotemporal distribution of “weekend” destinations, likely
produce spatially and temporally distinct activity-travel patterns. Using data from the first wave of the Toronto Travel-Activity
Panel Survey (TTAPS), this paper examines an area of research that has received little attention; namely, the presence of
spatial variety in activity-travel behaviour. The paper begins by looking at the extent to which individuals engage in spatially
repetitive location choices during the course of a single week. Area-based measures of geographical extent and activity dispersion
are then used to expose differences in weekday-to-weekend and day-to-day activity-travel patterns. Examination of unclassified
activities carried out over a 1 week period reveals a level of spatial repetition that does not materialise across activities
classified by type, travel mode, and planning strategy. Despite the inherent spatial flexibility offered by the personal automobile,
spatial repetition is also found to be surprisingly similar across travel modes. The results also indicate weekday-to-weekend,
and day-to-day fluctuations in spatial properties of individual activity-travel behaviour. These findings challenge the utility
of the short-run survey as an instrument for capturing archetypal patterns of spatial behaviour. In addition, the presence
of a weekday-to-weekend differential in spatial behaviour suggests that policies targeting weekday travel reduction could
have little impact on travel associated with weekend activities.
相似文献
Tarmo K. RemmelEmail: |
16.
This paper is a think piece on variations in the structure of stated preference studies when modelling the joint preferences
of interacting agents who have the power to influence the attribute levels on offer. The approach proposed is an extension
of standard stated choice methods, known as ‘stated endogenous attribute level’ (SEAL) analysis. It allows for interactive
agents to adjust attribute levels off a base stated choice specification that are within their control, in an effort to reach
agreement in an experimental setting. This accomplishes three goals: (1) the ability to place respondents in an environment
that more closely matches interactive settings in which some attribute levels are endogenous to a specific agent, should the
modeller wish to capture such behaviour; (2) the improved ability of the modeller to capture the behaviour in such settings,
including a greater wealth of information on the related interaction processes, rather than simply outcomes; and (3) the expansion of the set of situations that the modeller can investigate using experimental
data.
相似文献
John M. RoseEmail: |
17.
Market segmentation studies in travel behavior research are ordinarily based on socioeconomic characteristics and personality
traits. This study explores the usefulness of a different approach, where the actual overall mobility levels across different
ground transportation modes, along with desired changes in the use of cars and transit, are used as clustering variables.
Using a given mode can in fact influence the personal representation of that mode, which in turn has been proven to be a key
element in transport behaviours. We form such multimodality-based clusters from two field studies, one involving employees
of the French transportation research institute INRETS and the other a representative sample of residents of the US San Francisco
Bay Area. We find that strong users of a given mode would like to bring more balance to their “modal consumptions” by decreasing
the use of this mode more than the average, and increasing the use of the alternative mode. However, concerning ground transport
travel budgets, the desire to travel more (or less) overall seems less strongly related to the composition of the modal balance. The US dataset shows also a greater latent demand for
travel than the French one. Socioeconomic characteristics of the clusters could not explain the patterns that were found,
confirming the importance of taking into account multimodality issues in travel behavior research. Some policy implications
from these findings are finally reported.
相似文献
Patricia L. MokhtarianEmail: |
18.
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
19.
Over the past few years, GPS has been used in a number of surveys in the US to assess the accuracy of household travel surveys.
The results have been somewhat alarming in that most of these exercises have shown that the standard trip-based CATI survey
conducted in the US under-reports travel by about 20–25%. It was decided to use GPS to assess the accuracy of the Sydney Household
Travel Survey, a continuous survey conducted by face-to-face interviewing. The procedure used was for the interviewers to
recruit households for the household travel survey in the normal manner, and then, if the household met certain criteria,
to endeavour to recruit the household to also undertake a GPS survey. A small sample of about 50 households was obtained,
and GPS devices successfully retrieved that measured data on the same day as the travel diary was completed. In addition,
participants in the GPS survey completed a prompted recall survey a week or two later, using maps and tabulations of travel
obtained from the GPS devices, to identify mode, purpose and occupancy for trips measured by the GPS, and also to check for
accuracy in defining trip ends and total number of trips. Based on the analysis of the GPS compared to the diary results,
it was found that respondents under-reported their travel by about 7%, which is much less than in the US CATI results. Respondents
were also found to under-report travel distances and over-report travel times. There was also a high incidence of non-reporting
for VKT.
相似文献
Peter StopherEmail: |
20.
In this paper, we take an initial look at the spatial and temporal flexibility in the activity patterns of the so-called “baby-boomer”
cohort (born 1947–1966) in comparison with younger and older adults. Using a unique longitudinal survey carried in Quebec
City from 2002 to 2005, we explore activity patterns and trip rates over a seven-day observation period during the first wave,
and take a first look at some aspects of their evolution over two subsequent waves at about one-year intervals. We model the
propensity to undertake activities within selected conventional non-work classifications such as “shopping” and “leisure”,
and also according to respondents’ own perceptions of the spatial and temporal flexibility of each out-of-home activity that
they had executed. While we cannot strictly separate cohort effects from age-related effects, after controlling for gender
and household structure, we infer that age and related lifestyle effects dominate in explaining these propensities. However,
the boomers were the only age stratum to increase their total out-of-home activity participation over the course of the panel,
an intriguing starting point for the future study of this cohort.
Luis F. Miranda-Moreno has been recently appointed as Assistant Professor in the Department of Civil Engineering and Applied Mechanics at McGill University. His research focuses on travel behaviour, transportation safety and evaluation of sustainable transport strategies. Martin Lee-Gosselin recently retired as Full Professor at the Graduate School of Planning and CRAD, Université Laval, Québec, and is Visiting Professor at Imperial College London. His research interests are transport and telecommunications behaviour, survey methods, energy efficiency and the impacts of transport on the environment and public health. 相似文献
Martin Lee-GosselinEmail: |
Luis F. Miranda-Moreno has been recently appointed as Assistant Professor in the Department of Civil Engineering and Applied Mechanics at McGill University. His research focuses on travel behaviour, transportation safety and evaluation of sustainable transport strategies. Martin Lee-Gosselin recently retired as Full Professor at the Graduate School of Planning and CRAD, Université Laval, Québec, and is Visiting Professor at Imperial College London. His research interests are transport and telecommunications behaviour, survey methods, energy efficiency and the impacts of transport on the environment and public health. 相似文献