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11.
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.
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Paul A. WaddellEmail: |
12.
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
13.
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
14.
This study presents a unified framework to understand the weekday recreational activity participation time-use of adults,
with an emphasis on the time expended in physically active recreation pursuits by location and by time-of-day. Such an analysis
is important for a better understanding of how individuals incorporate physical activity into their daily activities on a
typical weekday, and can inform the development of effective policy interventions to facilitate physical activity. Furthermore,
such a study of participation and time use in recreational activity episodes contributes to activity-based travel demand modeling,
since recreational activity participation comprises a substantial share of individuals’ total non-work activity participation.
The methodology employed here is the multiple discrete continuous extreme value (MDCEV) model, which provides a unified framework
to explicitly and endogenously examine time use by type, location, and timing. The data for the empirical analysis is drawn
from the 2000 Bay Area Travel Survey (BATS), supplemented with other secondary sources that provide information on physical
environment variables. To our knowledge, this is the first study to jointly address the issues of ‘where’, ‘when’ and ‘how
much’ individuals choose to participate in ‘what type of (recreational) activity’. 相似文献
15.
Stacey G. Bricka Sudeshna Sen Rajesh Paleti Chandra R. Bhat 《Transportation Research Part C: Emerging Technologies》2012,21(1):67-88
Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional survey-reported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPS-recorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-h period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics. 相似文献
16.
A conceptual framework of individual activity program generation 总被引:1,自引:0,他引:1
The research in this paper attempts to better understand the process by which activities are generated at an individual level. Activity-based travel analyses have gained popularity in recent years because they recognize the complexity of activity behavior and view travel as a derivative of this behavior. Most activity-based studies have focused on the spatial and temporal linkage of trips; that is, the scheduling of activities. They consider the agenda of activities for participation, and associated attributes of the activity participation (such as mode to activity and location of activity performance), as predetermined. This paper develops a comprehensive conceptual framework of the relatively unexplored area of activity agenda generation. Such a framework will be valuable in empirical modeling of activity generation behavior. A subsequent paper focuses on translating a part of this conceptual framework into an empirical model. 相似文献
17.
A retrospective and prospective survey of time-use research 总被引:6,自引:3,他引:3
The central basis of the activity-based approach to travel demand modeling is that individuals' activity-travel patterns are a result of their time-use decisions within a continuous time domain. This paper reviews earlier theoretical and empirical research in the time-use area, emphasizing the need to examine activities in the context or setting in which they occur. The review indicates the substantial progress made in the past five years and identifies some possible reasons for this sudden spurt and rejuvenation in the field. The paper concludes that the field of time-use and its relevance to activity-travel modeling has gone substantially past the "tip of the iceberg", though it certainly still has a good part of the "iceberg" to uncover. Important future areas of research are identified and discussed. 相似文献
18.
As leisure travel continues to grow, it has become a critical subject for planners and decision-makers since it significantly
impacts regional economic and social development as well as contributes to emission levels and congestion. Despite being a
significant percentage of our travel, however, leisure travel behavior is still not very well understood. The goal of this
article is to contribute to our understanding of leisure activity participation by considering leisure activity loyalty within
the travel context. In particular, this study focuses on one specific dimension of travel context: travel extent (i.e., whether
an individual participates in a leisure activity on a daily versus a long-distance basis). As such, this article first introduces
a unified conceptual framework for measuring leisure activity loyalties within a travel context, based on two distinct dynamics
of leisure loyalty behavior—destination attachment and activity involvement. Additionally, this article uses a unique 2001
NHTS dataset comprised of households’ daily and long-distance leisure activities to undertake a unique empirical analysis
of five distinct leisure activities using the conceptual framework and a copula-based model methodology. The findings confirmed
that households demonstrate significant loyalties to travel contexts across all leisure activities, especially resting and
sightseeing. 相似文献
19.
Chandra R. Bhat Ipek N. Sener Naveen Eluru 《Transportation Research Part B: Methodological》2010,44(8-9):903-921
This study proposes a simple and practical Composite Marginal Likelihood (CML) inference approach to estimate ordered-response discrete choice models with flexible copula-based spatial dependence structures across observational units. The approach is applicable to data sets of any size, provides standard error estimates for all parameters, and does not require any simulation machinery. The combined copula–CML approach proposed here should be appealing for general multivariate modeling contexts because it is simple and flexible, and is easy to implementThe ability of the CML approach to recover the parameters of a spatially ordered process is evaluated using a simulation study, which clearly points to the effectiveness of the approach. In addition, the combined copula–CML approach is applied to study the daily episode frequency of teenagers’ physically active and physically inactive recreational activity participation, a subject of considerable interest in the transportation, sociology, and adolescence development fields. The data for the analysis are drawn from the 2000 San Francisco Bay Area Survey. The results highlight the value of the copula approach that separates the univariate marginal distribution form from the multivariate dependence structure, as well as underscore the need to consider spatial effects in recreational activity participation. The variable effects indicate that parents’ physical activity participation constitutes the most important factor influencing teenagers’ physical activity participation levels. Thus, an effective way to increase active recreation among teenagers may be to direct physical activity benefit-related information and education campaigns toward parents, perhaps at special physical education sessions at the schools of teenagers. 相似文献
20.
Chandra R. Bhat Joseph L. Schofer Frank S. Koppelman Russell C. Bautch 《Transportation Research Part C: Emerging Technologies》1993,1(4)
A number of Advanced Traveler Information System (ATIS) field experiments are being undertaken to study the effectiveness of the ATIS concept in ameliorating traffic congestion and reducing delays. Many of these experiments require the participation of private drivers willing to allow in-vehicle navigation units to be installed in their vehicles over an extended period of time. A critical part of any ATIS field experiment is the selection or recruitment of private drivers to fulfill the multi-purpose participation needs of the ATIS experiment. To provide an informed basis for designing such a driver recruitment effort, it is important to understand the factors affecting driver recruitability or “willingness to participate.” This research presents the results of a quantitative analysis of driver recruitability conducted to aid in the design of recruitment procedures for ADVANCE (Advanced Driver and Vehicle Advisory Navigation Concept), the largest ATIS field experiment of its kind. The approach used a telephone survey to assess driver willingness to participate in the ADVANCE field experiment and to explore variations in that willingness among different drivers and across characteristics of the ADVANCE system and experimental design. The results indicate that the willingness to participate in the ADVANCE field test is greater for men, persons who hold executive or managerial occupations, individuals who drive extensively, persons who use electronic devices such as personal computers and car phones regularly, and persons who have positive beliefs regarding the usefulness of the ADVANCE concept. The result also suggest that drivers' willingness to participate is not strongly affected by monitoring/reporting requirements such as responding to surveys, mailing electronically stored records of system operation, and periodic service requirements. However, the willingness decreases considerably if drivers have to bear the financial responsibility for damage of the navigation equipment and any equipment-caused electrical failures to the car. Finally, the incentive of a lottery prize raises the level of participation willingness. These results have important implications for the recruitment effort, both in terms of recruiting drivers for participation in the demonstration and specifying the operational details of the field test. 相似文献