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151.
Using the UK National Travel Survey from 2002 to 2006, this paper investigates the influence of households’ residential self-selectivity, parents’ perceptions on accessibilities and their travel patterns on their children daily travel mode share. In doing this, this study introduces a model structure that represents the complex interactions between the parents’ travel patterns, their perceptions on public transport services and their reported residential self-selectivity reasons and the children travel mode shares. This structure is analysed with structural equation modelling. The model estimation results show that parents’ residential self-selectivity, parents’ perceptions and satisfactions on accessibilities and their daily travel patterns significantly influence the children’s daily travel mode shares. However, the effects are not uniform across household members. This study has revealed that households’ residential self-selectivity behaviours have more correlations with the children’s non-motorised mode shares, whilst the parents’ perceptions and satisfactions on transport infrastructure and public transport service qualities have more correlations with parents’ mode shares. The results also confirm that parents’ non-motorised modes use in travelling is highly correlated with the children’s physically active travel mode shares. However, at the same time, the results also show that the effects of mothers’ car use to the children travel mode shares is more apparent than fathers’. 相似文献
152.
153.
Trip generation of vulnerable populations in three Canadian cities: a spatial ordered probit approach 总被引:1,自引:0,他引:1
Matthew J. Roorda Antonio Páez Catherine Morency Ruben Mercado Steven Farber 《Transportation》2010,37(3):525-548
This paper provides an analysis of trip generation of three vulnerable groups: single-parent families, low income households, and the elderly. It compares the mobility of these groups to that of the general population in three Canadian urban areas of Hamilton, Montreal and Toronto, based on data from large-sample metropolitan transport surveys. An ordered probit model with spatially expanded coefficients is used for the analysis. Spatial expansion shows that there are spatial mobility trends for elderly populations and low-income populations even after socio-economic attributes are accounted for. Such spatial differences are not generally found for single parent families. This novel spatial analysis provides clues as to where vulnerable populations may experience greater degrees of social exclusion. It provides information to help prioritize transportation infrastructure projects or other social programs to take into account the needs of vulnerable populations with the lowest levels of mobility. 相似文献
154.
We propose a semiparametric approach that can capture the nonlinearity of deterministic components of the utility functions in discrete choice models and demonstrate it by analyzing travel mode choice behaviour for an interregional trip. The proposed smoothing spline-based specification method can be used to make ex ante evaluations regarding the parametric specifications of the deterministic utility functions in discrete choice models. 相似文献
155.
Effective prediction of bus arrival times is important to advanced traveler information systems (ATIS). Here a hybrid model, based on support vector machine (SVM) and Kalman filtering technique, is presented to predict bus arrival times. In the model, the SVM model predicts the baseline travel times on the basic of historical trips occurring data at given time‐of‐day, weather conditions, route segment, the travel times on the current segment, and the latest travel times on the predicted segment; the Kalman filtering‐based dynamic algorithm uses the latest bus arrival information, together with estimated baseline travel times, to predict arrival times at the next point. The predicted bus arrival times are examined by data of bus no. 7 in a satellite town of Dalian in China. Results show that the hybrid model proposed in this paper is feasible and applicable in bus arrival time forecasting area, and generally provides better performance than artificial neural network (ANN)–based methods. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
156.
从穿越瑞士列奇堡隧道的挤压变形性极强的碳质页岩带的经验中,可以得出下述结论:圆形含承压单元的支护截面,其收敛变形性总趋势要比马蹄形不含承压单元的支护截面小;圆形支护截面与马蹄形支护截面的变形性没有本质的区别;由于山体构造的不均一性,导致开挖断面的不规则变形,这是使承压单元过早脱落的原因。 相似文献
157.
158.
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: |
159.
This study introduces the concept of loss aversion to consumer behavioral intention at the personal psychological level to
develop an integrative structural equation model for analyzing traveler psychological decision making. In this model, the
relationship between behavioral intention and service quality is a non-smooth function based on the theory of loss aversion.
The expectation service quality in the SERVQUAL model proposed by Parasuraman, Zeithaml, and Berry (PZB) serves as a reference
point. This model can be applied to analyze the effect of non-smooth response of behavioral intention to service quality in
a traveler psychological decision-making process model. Intercity travel among cities in Taiwan is used as an empirical example.
Data were gathered in cities in Taiwan via a questionnaire survey, and the model was tested using path analysis performed
by LISREL. The empirical result shows that all causal relationships are statistically significant. Service quality loss influences
repurchase intention more than does Service quality gain. Finally, this study concludes by discussing managerial implications
and suggesting directions for future research.
相似文献
Jiun-Hung LinEmail: |
160.
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