Exploring the connections among residential location,self-selection,and driving: Propensity score matching with multiple treatments

A large number of studies have investigated the association between the built environment and travel behavior. However, most studies did not explicitly quantify the contribution of residential self-selection to the connection. Using the 2006 data collected from a regional travel diary in Raleigh, NC, this study applies propensity score matching to explore the effects of the regional location of individuals’ residences on their vehicle miles driven. We found that residential location plays a more important role in affecting driving behavior than residential self-selection; and that the self-selection effect is non-trivial when we compare driving behavior between urban residents and people living in other areas. Therefore, for such comparisons, the observed influence of residential locations on driving should be appropriately discounted when we evaluate the causal impacts of the built environment on travel behavior.     

Exploring the influence of built environment on tour-based commuter mode choice: A cross-classified multilevel modeling approach

Understanding travel behavior and its relationship to urban form is vital for the sustainable planning strategies aimed at automobile dependency reduction. The objective of this study is twofold. First, this research provides additional insights to examine the effects of built environment factors measured at both home location and workplace on tour-based mode choice behavior. Second, a cross-classified multilevel probit model using Bayesian approach is employed to accommodate the spatial context in which individuals make travel decisions. Using Washington, D.C. as our study area, the home-based work (Home-work) tour in the AM peak hours is used as the analysis unit. The empirical data was gathered from the Washington-Baltimore Regional Household Travel Survey 2007–2008. For parameter estimation, Bayesian estimation method integrating Markov Chain Monte Carlo (MCMC) sampling is adopted. Our findings confirmed the important role that the built environment at both home location and work ends plays in affecting commuter mode choice behavior. Meanwhile, a comparison of different model results shows that the cross-classified multilevel probit model offers significant improvements over the traditional probit model. The results are expected to give a better understanding on the relationship between the built environment and commuter mode choice behavior.     

The influences of past and present residential locations on vehicle ownership decisions

This study explores the relationship between historical exposure to the built environment and current vehicle ownership patterns. The influence of past exposure to the built environment on current vehicle ownership decisions may be causal, but there are alternative explanations. Households may primarily select to live in neighborhoods that facilitate their vehicle ownership preferences, or they may retain preferences that they have developed in the past, irrespective of their current situations. This study seeks to control for these alternative explanations by including the built environment attributes of households’ past residences as an influence on vehicle ownership choices. We use a dataset from a credit reporting firm that contains up to nine previous residential ZIP codes for households currently living in the 13-county Atlanta, Georgia, metropolitan area. Results show that past location is significant, but of marginal influence relative to the attributes of the current location. From a practical perspective, our results suggest that models that include current but not past neighborhood attributes (also controlling for standard socioeconomic variables) can forecast vehicle ownership decisions reasonably well. However, models that include both current and past neighborhood attributes can provide a more nuanced understanding of the built environment’s potentially causal influences on vehicle ownership decisions. This better understanding may provide more realistic forecasts of responses to densification or other travel demand management strategies.     

Built environment,travel behavior,and residential self-selection: a study based on panel data from Beijing,China

The influence of the built environment on travel behavior has been the subject of considerable research attention in recent decades. Scholars have debated the role of residential self-selection in explaining the associations between the built environment and travel behavior. The purpose of this study is to make a contribution to the literature by adopting the cross-lagged panel modeling approach to analyze a panel data, which scholars have recommended as the ideal design for studying the influence of the built environment on travel behavior accounting for the residential self-selection. To that objective, we collected activity-travel diary data from a sample of 229 households in Beijing before and after they moved from one residential location to another. We developed a two-wave structural equation model linking the residential built environment to travel behavior and taking into consideration travel-related attitudes before and after residential change. The modeling results show that individuals’ travel attitudes may change after a home relocation. We found no evidence of residential self-selection, but significant influence of the built environment on travel preference. Nevertheless, the direct influence of travel preference on travel behavior seems to be stronger than that of the built environment. As one of the very few studies to use panel data, this research presents new insights into the relationship between the built environment and travel behavior and the role of residential self-selection.

     

The built environment and travel behavior in urban China: A literature review

Interests in studying of the built environment impacts on travel behavior have proliferated from North America to other parts of the world including China. Until very recently, there has been very little research into travel behavior in China. However, during the last decade, there has been a fast growing interest in studying the built environment and travel behavior in Chinese cities, perhaps motivated by China’s unprecedented urbanization and rapid urban transport development. Case studies from China provide new insights into the impacts of built environment on travel behavior that can help to enrich existing scholarship. However, currently there is a generally poor understanding of the role played by Chinese research and how it has enriched the international literature. This paper aims to fill this gap by reviewing studies in and outside China by both Chinese and non-Chinese scholars. The focus is on the contribution of these studies to the international literature. We identify four areas of contribution: how the built environment has been developed and its implications for travel behavior; the importance of housing sources in defining residential built environment and explaining travel behavior; the unique Danwei (or work unit) perspective on jobs-housing relationships and commuting behavior; and the importance of neighborhood types in explaining travel behavior in Chinese cities. The findings from this review should be relevant for researchers interested in developing future studies that will further advance geographic knowledge of the built environment and travel behavior, specifically in China and with broader global contexts.     

Interdependencies between turning points in life and long-term mobility decisions

Turning points in life include important personal and familial events as well as changes in the places of residence, education and employment. The latter usually involve alterations in the spatial distribution of activities and, hence, in the activity space, thereby also influencing the daily travel behavior. In this context, the ownership of mobility tools, such as cars and different public transport season tickets, also plays an important role, since people commit themselves to particular travel behaviors as they trade large one-time costs for a low marginal cost at the time of usage. At the same time, decisions concerning mobility tool ownership have lasting effects, as have the decisions concerning location choices. A longitudinal perspective on the dynamics of these long-term mobility decisions is available from people??s life courses, which link different dimensions of life together. In order to study these dynamics and the influence of turning points in life, a longitudinal survey covering the 20?year period from 1985 to 2004 was carried out at the beginning of 2005 in a stratified sample of municipalities in the Zurich region, Switzerland. The paper describes the data collection and then presents results which show that there exist strong interdependencies between the various turning points and long-term mobility decisions during the life course, as events occur to a great extent simultaneously. Persons tend to aim for compensation between the different dimensions of life.     

Should subsidies to urban passenger transport be increased? A spatial CGE analysis for a German metropolitan area

In many countries passenger transport is significantly subsidized in a variety of ways for various reasons. The objective of this paper is to examine efficiency, distributional, environmental (CO₂ emissions) and spatial effects of increasing different kinds of passenger transport subsidies discriminating between household types, travel purposes and travel modes. The effects are calculated by applying a numerical spatial general equilibrium approach calibrated to an average German metropolitan area. In extension to most studies focusing on only one kind of subsidy, we compare the effects of different transport subsidies within the same unified framework that allows to account for two features not yet considered simultaneously in studies on transport subsidies: endogenous labor supply and location decisions. Furthermore, congestion, travel mode choice, travel related CO₂ emissions and institutional details regarding the tax system in Germany are taken into account. The results suggest that optimal subsidy levels are either small or even zero. While subsidizing public transport is welfare enhancing, subsidies to urban road traffic reduce aggregate urban welfare. Concerning the latter it is shown that making investments in urban road infrastructure capacity or reducing gasoline taxes may even be harmful to residents using predominantly automobile. In contrast, pure commuting subsidies hardly affect aggregate urban welfare, but distributional effects are substantial. All policies cause suburbanization of city residents and (except for subsidizing public transport) contribute to urban sprawl by raising the spatial imbalance of residences and jobs but the effect is relatively small. In addition, the policies induce a very differentiated pattern regarding distributional effects, benefits of landowners and environmental effects.     

Changes in travel mode use after residential relocation: a contribution to mobility biographies

In recent years, a growing body of research has been emerging that focuses on changes in travel behaviour over an individual’s life course. It has been labelled the ‘mobility biographies approach’ and highlights changes in travelling induced by key events and experiences in an individual’s life course. In this context residential relocation plays an important role. This paper examines changes in travel mode use after residential relocations using structural equation modelling. It draws on retrospectively recorded empirical data collected in the region of Cologne. The findings show that relocations and associated changes in the built environment induce significant changes in car ownership and travel mode use and thus may be regarded as key events in an individual’s mobility biography. Changes in levels of satisfaction with attributes of the built environment have a significant impact in this context as well. The causal direction of the changes fulfils expectations: suburbanisation is followed by increases in car use and decreases in public transport use, bicycle use and walking. The opposite is true for relocations into the city. In addition, changes in household structure that tend to go along with relocation have significant effects. The findings provide further evidence for the built environment having a causal impact on mode use: modal changes temporally follow changes in the built environment and thus appear to be adjustments to the new spatial setting.     

Car use,commuting and urban form in a rapidly growing city: evidence from Beijing

The links between urban form and travel behaviour have been widely studied in the field of travel demand management. However, the existing literature is dominated by case studies from the developed countries. A study of a city in a developing and industrialising country can add some fresh evidence to the debate on the impacts of urban form on travel patterns. Using household survey data from Beijing, this paper finds that aspects of urban form have significant effects on workers' car use and the duration of travel by car in journeys to work, while controlling for socio-economic factors and households’ preferences related to residential location. The sprawling patterns of land development play a negative role in reducing motorised commuting trips and shortening vehicle hours travelled in the current processes of rapid urban expansion and motorisation. Since urban sprawl is greatly influenced by growing market forces, the findings in this paper reveal the negative effects of regulation–liberation of land development management on travel behaviour modification.     

A network equilibrium approach for modelling activity-travel pattern scheduling problems in multi-modal transit networks with uncertainty

An understanding of the interaction between individuals’ activities and travel choice behaviour plays an important role in long-term transit service planning. In this paper, an activity-based network equilibrium model for scheduling daily activity-travel patterns (DATPs) in multi-modal transit networks under uncertainty is presented. In the proposed model, the DATP choice problem is transformed into a static traffic assignment problem by constructing a new super-network platform. With the use of the new super-network platform, individuals’ activity and travel choices such as time and space coordination, activity location, activity sequence and duration, and route/mode choices, can be simultaneously considered. In order to capture the stochastic characteristics of different activities, activity utilities are assumed in this study to be time-dependent and stochastic in relation to the activity types. A concept of DATP budget utility is proposed for modelling the uncertainty of activity utility. An efficient solution algorithm without prior enumeration of DATPs is developed for solving the DATP scheduling problem in multi-modal transit networks. Numerical examples are used to illustrate the application of the proposed model and the solution algorithm.     

The role of urban form and transit in city car dependence: Analysis of 26 global cities from 1960 to 2000

Car dependence is in decline in most developed cities, but its cause is still unclear as cities struggle with priorities in urban form and transport infrastructure. This paper draws conclusions from analysis of data in 26 cities over the last 40 years of the 20th century. Statistical modelling techniques are applied to urban transport and urban form data, while examining the influence of region, city archetype and individual fixed effects. Structural equation modelling is employed to address causation and understand the direct and indirect effects of selected parameters on per capita vehicle kilometres travelled (VKT). Findings suggest that, while location effects are important, transit service levels and urban density play a significant part in determining urban car use per capita, and causality does flow from these factors towards a city’s levels of private vehicle travel as well as the level of the provision of road capacity.     

A heuristic model of bounded route choice in urban areas

There is substantial evidence to indicate that route choice in urban areas is complex cognitive process, conducted under uncertainty and formed on partial perspectives. Yet, conventional route choice models continue make simplistic assumptions around the nature of human cognitive ability, memory and preference. In this paper, a novel framework for route choice in urban areas is introduced, aiming to more accurately reflect the uncertain, bounded nature of route choice decision making. Two main advances are introduced. The first involves the definition of a hierarchical model of space representing the relationship between urban features and human cognition, combining findings from both the extensive previous literature on spatial cognition and a large route choice dataset. The second advance involves the development of heuristic rules for route choice decisions, building upon the hierarchical model of urban space. The heuristics describe the process by which quick, ‘good enough’ decisions are made when individuals are faced with uncertainty. This element of the model is once more constructed and parameterised according to findings from prior research and the trends identified within a large routing dataset. The paper outlines the implementation of the framework within a real-world context, validating the results against observed behaviours. Conclusions are offered as to the extension and improvement of this approach, outlining its potential as an alternative to other route choice modelling frameworks.     

Urban activity spaces: Illustrations and application of a conceptual model for integrating the time and space dimensions

This work extends the conceptual argument for the use of ellipses to portray activity spaces and offers one example of how the ellipse construct can be used to analyze urban travel characteristics, based on observed trip making behavior and socio-economic variables. A problem in characterizing activity spaces has been in integrating the time and space dimensions into the same analytical framework while maintaining an understandable graphical representation of the space-time geographies envisioned by Hagerstrand and others. The ellipse allows this, as well as providing several quantifiable measures to be used for analyzing and characterizing activity spaces and urban travel behavior. In the current application, analysis of variance is used to analyze the resulting elliptic variables of 653 travelers. The results indicate that home location and household size are important factors in determining activity space characteristics and that the ellipse variables provide a different and useful approach for understanding urban travel behavior.     

On appropriate microstate descriptions in entropy modelling

Using an information-theoretic approach to entropy modelling, expressions for the possible number of microstates are derived from the sets of choices available to households and firms in given location/transport planning situations. In planning applications, the urban space is usually subdivided into discrete zones, and various classes of householders and firms are grouped into separate activities. Nevertheless, the location sites within zones may vary considerably in accessibility, price and quality, and amenity v. cost trade-offs between location and travel many differ markedly between individuals within the same activity group. The inclusion of such variations within a random utility framework is demonstrated to be equivalent to maximizing entropy with the microstates disaggregated to the level where these variations occur. Using constraints based on spatial conditions, observed behaviour and planning policy, entropy maximization is used to determine the most probable macrostate according to each choice set specification. The resulting distributions are compared and their revelance discussed.     

Optimal starting location of an HOV lane for a linear monocentric urban area

This paper analyzes the optimal starting location of a high-occupancy-vehicle (HOV) lane for a linear monocentric urban area. Both travel time and carpooling costs are taken into account. The research proposes an analytical framework for the case with a continuum demand distribution along a highway corridor. The objective is assumed to maximize social welfare of the transportation system, which is the difference between the total user benefit and travel cost. Numerical analysis via simulation experiments was conducted to seek the existence of an optimal solution. Based on the results of a sensitivity analysis, we find a specific relationship between the carpooling cost and the optimal design of the starting point of an HOV lane.     

Modeling travel behavior by the structural relationships between lifestyle,built environment and non-working trips

In the context of sustainable urban transport in developing countries, individuals’ travel behavior faces multiple factors which influence their mobility patterns. Recognizing these factors could be a favorable method to organize more regular and sustainable trip patterns. This study aims to identify the less well-known lifestyle along with more popular built environment as the main factors which shape travel behaviors. Employing data from 900 respondents of 22 urban areas in city of Shiraz, Iran, this paper explores travel behaviors as non-working trip frequencies by different modes. Results of structural equation model indicate a strong significant effect of individual’s lifestyle patterns on their non-working trips. However, built environment impact on travel behavior is small compared to lifestyle. Besides, other variables such as travel attitudes and socio-economic factors stay crucial in the mode choice selection. These findings indicate the necessity of regarding lifestyle orientations in travel studies as well as objective factors such as land use attributes.     

How perceptions mediate the effects of the built environment on travel behavior?

This study provides a better understand the mechanism underlying the built environment-behavior connection by systematically exploring the relationships between the objective (actual) environment and people’s perceptions of the environment, and their relative effects on travel behavior using the Stimuli-Organism-Response framework. Based on data for the Twin Cities, this study explores (1) How do perceptions mediate the effects of the objective environment on travel behavior? (2) How do travel attitudes influence the effects of perceptions on travel behavior? Among the eight empirical models tested here, six are consistent with the framework: objective built environment affects travel behavior through its influence on perceptions. Moreover, the framework fits walking and bicycling behavior better than transit and driving behavior. Furthermore, travel attitudes greatly moderate the influences of perceptions on travel behavior.

     

Gender,Residential Location,and Household Travel: Empirical Findings from Low‐income Urban Settlements in Durban,South Africa

Abstract

Urban development and transport policies designed to improve the livelihoods of poor communities need to consider the particular needs of women to be effective. Gender roles are played out in a spatial world, and can thus be expected to vary across the urban landscape. The paper examines empirical relationships between spatial factors—in particular residential location within the city—and travel behaviour for men and women in a cross‐section of low‐income communities in a large metropolitan area in South Africa. Data from a comprehensive household survey show that locality has a significant influence on gender experiences of mobility. Gender differences are greatest in more distant, rural localities, although site‐specific characteristics such as walking access to social services, informal work, and small‐scale agriculture help alleviate women’s inequitable travel burdens. Central localities display the smallest differences between men and women’s travel habits, supporting the notion that the high access afforded by centrally located housing helps to promote the satisfaction of women’s daily needs as well as their strategic empowerment. Households in peri‐urban and peripheral localities suffer the highest travel burdens, having neither the high access of a central location nor the livelihoods‐enhancing amenities of a rural environment. Women bear a large part of this burden. Urban development strategies to benefit the urban poor while promoting gender equity are highlighted, including an added emphasis on the provision of social and educational infrastructure within closer proximity to peripheral residential areas, coupled with better pedestrian access.     

Machine learning applications in activity-travel behaviour research: a review

ABSTRACT

This paper reviews the activity-travel behaviour literature that employs Machine Learning (ML) techniques for empirical analysis and modelling. Machine Learning algorithms, which attempt to build intelligence utilizing the availability of large amounts of data, have emerged as powerful tools in the fields of pattern recognition and big data analysis. These techniques have been applied in activity-travel behaviour studies since the early ’90s when Artificial Neural Networks (ANN) were employed to model mode choice decisions. AMOS, an activity-based modelling system developed in the mid-’90s, has ANN at its core to model and predict individual responses to travel demand management measures. In the dawn of 2000, ALBATROSS, a comprehensive activity-based travel demand modelling system, was proposed by Arentze and Timmermans using Decision Trees. Since then researchers have been exploring ML techniques like Support Vector Machines (SVM), Decision Trees (DT), Neural Networks (NN), Bayes Classifiers, and more recently, Ensemble Learners to model and predict activity-travel behaviour. A large number of publications over the years and an upward trend in the number of published articles over time indicate that Machine Learning is a promising tool for activity-travel behaviour analysis and prediction. This article, first of its kind in the literature, reviews these studies and explores the trends in activity-travel behaviour research that apply ML techniques. The review finds that mode choice decisions have received wide attention in the literature on ML applications. It was observed that most of the studies identify the lack of interpretability as a serious shortcoming in ML techniques. However, very few studies have attempted to improve the interpretability of the models. Further, some studies report the importance of feature engineering in ML-based studies, but very few studies adopt feature engineering before model development. Spatiotemporal transferability of models is another issue that has received minimal attention in the literature. In the end, the paper discusses possible directions for future research in the area of activity-travel behaviour modelling using ML techniques.     

Residential location and transit-oriented development in a new rail corridor

The relationship of form, use, and density in urban development and their influence on human behavior and travel is a key element of many land use and transport policies. Prior research indicates high-density urban development leads to decreased travel and thus sustainable mobility; however, personal attitudes seem to have greater effect on mobility than does the urban form. This research evaluates how households consider transit-oriented development (TOD) characteristics in their location decisions with regard to new Mandurah railway line stations opened in December 2007 in Perth, Western Australia. The results indicate that the choice of residence reflects neighborhood and housing attributes, with significant heterogeneity in the populations of the three precincts in terms of their valuation of various housing characteristics, proximity to urban facilities, and transport. There is also significant variation in households’ attitudes to natural and artificial environments. A better understanding of the complex relationships among environment, travel, socio-demographic characteristics, and household attitudes can help transport planners leverage the benefits of TOD and improve the quality of urban design and community life.