Examining the relationship between active travel,weather, and the built environment: a multilevel approach using a GPS-enhanced dataset

This study examines how the built environment and weather conditions influence the use of walking as a mode of transport. The Halifax Regional Municipality in Nova Scotia, Canada is the study area for this work. Data are derived from three sources: a socio-demographic questionnaire and a GPS-enhanced prompted recall time-use diary collected between April 2007 and May 2008 as part of the Halifax Space-Time Activity Research project, a daily meteorological summary from Environment Canada, and a comprehensive GIS dataset from the regional municipality. Two binary logit multilevel models are estimated to examine how the propensity to use walking is influenced by the built environment and weather while controlling for socio-demographic characteristics. The built environment is measured via five attributes in one model and a walkability index (derived from the five attributes) in the other. Weather conditions are shown to affect walking use in both models. Although the walkability index is significant, the results demonstrate that this significance is driven by specific attributes of the built environment—in the case of this study, population density and to a lesser extent, pedestrian infrastructure.     

Socio-demographic and built environment influences on the odds of being overweight or obese: The Atlanta experience

This paper explores the association of socio-demographic and built environment characteristics on the odds of being overweight and obese using data from the Atlanta SMARTRAQ travel survey. A new methodological framework based on a multinomial logit (MNL) model and an enhanced odds ratio plot is presented. The use of an MNL model overcomes limitations of many prior studies that employ a sequence of binary logit models to examine multiple weight categories. The use of an enhanced odds ratio plot provides important information into the relative importance of socio-demographic and built environment characteristics. Several new findings for the Atlanta area result from this study. Socio-demographic variables, including age and educational attainment, exhibit a non-linear relationship with the odds of being overweight or obese. Gender, age, ethnicity, and educational attainment are strongly associated with the odds of being overweight or obese, while income and number of students between 5 and 16 years old in the household have smaller effects. Built environment characteristics such as increased net residential densities and enhanced street connectivity are associated with reductions in the odds of being overweight and/or obese. Relative to socio-demographic variables, however, such built environment characteristics have a much smaller impact on describing the odds of being overweight or obese.     

Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice

Concerns over transportation energy consumption and emissions have prompted more studies into the impacts of built environment on driving-related behavior, especially on car ownership and travel mode choice. This study contributes to examine the impacts of the built environment on commuter’s driving behavior at both spatial zone and individual levels. The aim of this study is threefold. First, a multilevel integrated multinomial logit (MNL) and structural equation model (SEM) approach was employed to jointly explore the impacts of the built environment on car ownership and travel mode choice. Second, the spatial context in which individuals make the travel decisions was accommodated, and spatial heterogeneities of car ownership and travel mode choice across traffic analysis zones (TAZs) were recognized. Third, the indirect effects of the built environment on travel mode choice through the mediating variable car ownership were calculated, in other words, the intermediary nature of car ownership was considered. Using the Washington metropolitan area as the study case, the built environment measures were calculated for each TAZ, and the commuting trips were drawn from the household travel survey in this area. To estimate the model parameters, the robust maximum likelihood (MLR) method was used. Meanwhile, a comparison among different model structures was conducted. The model results suggest that application of the multilevel integrated MNL and SEM approach obtains significant improvements over other models. This study give transportation planners a better understanding on how the built environment influences car ownership and commuting mode choice, and consequently develop effective and targeted countermeasures.     

Extent and correlates of walking in the USA

This paper examines data about walking trips in the US Department of Transportation’s 2001 National Household Travel Survey. The paper describes and critiques the methods used in the survey to collect data on walking. Using these data, we summarize the extent of walking, the duration and distance of walk trips, and variations in walking behavior according to geographic and socio-demographic factors. The results show that most Americans do not walk at all, but those who do average close to thirty minutes of walking a day. Walk trips averaged about a half-mile, but the median trip distance was a quarter of a mile. A significant percentage of the time Americans’ walk was spent traveling to and from transit trips. Binary logit models are used for examining utility and recreational walk trips and show a positive relationship between walking and population density for both. For recreational trips, this effect shows up at the extreme low and high ends of density. For utility trips, the odds of reporting a walk trip increase with each density category, but the effect is most pronounced at the highest density categories. At the highest densities, a large portion of the effect of density occurs via the intermediary of car ownership. Educational attainment has a strong effect on propensity to take walk trips, for both for utility and recreation. Higher income was associated with fewer utility walk trips but more recreational trips. Asians, Latinos, and blacks were less likely to take utility walk trips than whites, after controlling for income, education, density, and car ownership. The ethnic differences in walking are even larger for recreational trips.     

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.     

Analyzing commuter train user behavior: a decision framework for access mode and station choice

The purpose of the current research effort is to develop a framework for a better understanding of commuter train users’ access mode and station choice behavior. Typically, access mode and station choice for commuter train users is modeled as a hierarchical choice with access mode being considered as the first choice in the sequence. The current study proposes a latent segmentation based approach to relax the hierarchy. In particular, this innovative approach simultaneously considers two segments of station and access mode choice behavior: Segment 1—station first and access mode second and Segment 2—access mode first and station second. The allocation to the two segments is achieved through a latent segmentation approach that determines the probability of assigning the individual to either of these segments as a function of socio-demographic variables, level of service (LOS) parameters, trip characteristics, land-use and built environment factors, and station characteristics. The proposed latent segment model is estimated using data from an on-board survey conducted by the Agence Métropolitaine de Transport for commuter train users in Montreal region. The model is employed to investigate the role of socio-demographic variables, LOS parameters, trip characteristics, land-use and built environment factors, and station characteristics on commuter train user behavior. The results indicate that as the distance from the station by active forms of transportation increases, individuals are more likely to select a station first. Young persons, females, car owners, and individuals leaving before 7:30 a.m. have an increased propensity to drive to the commuter train station. The station model indicates that travel time has a significant negative impact on station choice, whereas, presence of parking and increased train frequency encourages use of the stations.     

Residential relocations and changes in vehicle ownership

While the relationship between automobile ownership and the built environment is well established, less is known about how household relocations—specifically, moves between urban and suburban geographies—affect the likelihood of owning an automobile. Using the Panel Study of Income Dynamics and a refined neighborhood typology, I examine the relationship between inter-geography moves and transitions into and out of carlessness. Results suggest that among low-income households, urban-to-suburban movers have an increased likelihood of becoming car owners; those moving in the “opposite” direction—from suburban to urban neighborhoods—show a high propensity to transition into carlessness. Patterns among higher-income households, while similar, are more pronounced. In particular, higher-income carless households that make urban-to-suburban moves are far more likely to become car owners than their low-income counterparts. This highlights the ease with which higher-income households adjust their car ownership levels to suit their post-move neighborhoods. Higher-income suburban-to-urban movers are also more likely to transition into carlessness than low-income households. Importantly, however, only households at the bottom end of the “higher income” distribution have an increased propensity to become carless; suburban-to-urban movers with more financial resources maintain vehicle ownership rates similar to households that remain in the suburbs.

     

Examining the effects of the built environment and residential self-selection on commuting trips and the related CO2 emissions: An empirical study in Guangzhou,China

Numerous studies have established the link between the built environment and travel behavior. However, fewer studies have focused on environmental costs of travel (such as CO₂ emissions) with respect to residential self-selection. Combined with the application of TIQS (Travel Intelligent Query System), this study develops a structural equations model (SEM) to examine the effects of the built environment and residential self-selection on commuting trips and their related CO₂ emissions using data from 2015 in Guangzhou, China. The results demonstrate that the effect of residential self-selection also exists in Chinese cities, influencing residents’ choice of living environments and ultimately affecting their commute trip CO₂ emissions. After controlling for the effect of residential self-selection, built environment variables still have significant effects on CO₂ emissions from commuting although some are indirect effects that work through mediating variables (car ownership and commuting trip distance). Specifically, CO₂ emissions are negatively affected by land-use mix, residential density, metro station density and road network density. Conversely, bus stop density, distance to city centers and parking availability near the workplace have positive effects on CO₂ emissions. To promote low carbon travel, intervention on the built environment would be effective and necessary.     

The role of socio-economic,built environment and psychological factors in parental mode choice for their children in an Iranian setting

This research investigated the role of parental psychological and socio-economic factors as well as built environment for the choice of their children’s (primary school pupils, aged 7–9 years) travel mode to school in Rasht, Iran. A total of 1078 questionnaires were distributed (return rate of 80 percent) among pupils in nine primary schools in January 2014. A mixed logit (ML) model was employed due to its ability to test heterogeneity among parents and also to determine its possible sources. Results of random coefficient ML modelling showed that several psychological, socio-economic and built environment characteristics were significant factors in parental mode choice. Only walking time perception to school had a significant random normal distribution coefficient and no other psychological and socio-economic variable had a random effect. Further investigation by random coefficient analysis showed that the possible source of household preference heterogeneity could be to own two or more cars. Regarding psychological variables, strong parental worry about their children walking alone to school had a negative impact on allowing them to walk to school. Parents who evaluated poor contextual and design preconditions for walking tended to choose school service more than private car and walking. Parents with stronger environmental personal norms were more willing to allow their children to walk. The findings suggest that infrastructural measures, such as sidewalk facilities, neighborhood security and safety, encourage parents to allow children to walk to school. Information campaigns targeting environmental norms may increase walking among pupils in an Iranian setting.     

Reducing car dependence in the heart of Europe: lessons from Germany,Austria, and Switzerland

Munich, Berlin, Hamburg, Vienna, and Zurich – the largest cities in Germany, Austria, and Switzerland – have significantly reduced the car share of trips over the past 25 years in spite of high motorisation rates. The key to their success has been a coordinated package of mutually reinforcing transport and land-use policies that have made car use slower, less convenient, and more costly, while increasing the safety, convenience, and feasibility of walking, cycling, and public transport. The mix of policies implemented in each city has been somewhat different. The German cities have done far more to promote cycling, while Zurich and Vienna offer more public transport service per capita at lower fares. All five of the cities have implemented roughly the same policies to promote walking, foster compact mixed-use development, and discourage car use. Of the car-restrictive policies, parking management has been by far the most important. The five case study cities demonstrate that it is possible to reduce car dependence even in affluent societies with high levels of car ownership and high expectations for quality of travel.     

Effect of built environment measures on trip distance and mode choice decision of non-workers from a city of a developing country,India

This paper investigates the influence of built environment measures on trip distance and walking decision of non-workers by segmenting the populace based on trip purpose, vehicle ownership, and the presence of school-going children in households. The built environment measures of home zone of individuals considered for the present analysis include zonal population density, zonal school enrolment, land use mix diversity index, and an indicator variable that captures if neighbourhoods have footpaths of adequate width available. Statistical analyses conducted on home-based trips indicate that an increase in the land use diversity of a zone has its strongest negative effect on distance travelled for participating in personal/household business activities. The non-vehicle owning group exhibit a higher tendency to walk than the vehicle-owning group for an increase in the land use diversity of zones. Further, the study suggests that school-enrolment in a zone also influences the travel decisions of non-workers in families with school-going children.     

Residential built environment and walking activity: Empirical evidence of Jane Jacobs’ urban vitality

This study intends to empirically verify Jacobs’ urban vitality theory, which was based on the observations of her New York City neighborhood in the mid-20th century. To examine the relationship between the residential built environment and walking activity, we used telephone survey data consisting of 1823 valid samples from across Seoul, a city characterized by a high population density and a well-established public transportation system. Respondents were asked questions about their residential location, their demographic and socioeconomic characteristics, and their walking activities. This study then used geographic information systems to measure objective indicators of built environment variables within 500-meter buffer areas based on the home addresses of the respondents. Then, this study constructed multilevel regression models with walking activity as the dependent variable. Our results indicated that walking activity is associated with Jacobs’ six conditions for urban vitality, including land use mix, density, block size, building age, accessibility, and border vacuums.     

Built environment impacts on walking for transport in Brisbane,Australia

This study examines the association between urban form and walking for transport in Brisbane, Australia based on both panel and cross-sectional data. Cross-sectional data are used to determine whether urban form was associated with walking for transport in 2011. Panel data are used to evaluate whether changes in the built environment altered walking behaviour between 2009 and 2011. Results from the cross-sectional data suggest that individuals are significantly more likely to be walkers if they live in an area with a well-connected street network and an accessible train station. The longitudinal analysis confirms these relationships; there also was however, a significant impact of travel attitudes and perceptions on walking behaviour. The findings suggest that the built environment continues to be an important factor to encourage walking; however, interventions are also required to change social norms in order to increase the receptiveness for and participation in walking.     

A behavioural comparison of route choice on metro networks: Time,transfers, crowding,topology and socio-demographics

Understanding travellers’ behaviour is key element in transportation planning. This article presents a route choice model for metro networks that considers different time components as well as variables related to the transferring experience, train crowding, network topology and socio-demographic characteristics. The route choice model is applied to the London Underground and Santiago Metro networks, to make a comparison of the decision making process of the users on both cities. As all the variables are statistically significant, it is possible to affirm that public transport users take into account a wide variety of elements when choosing routes. While in London the travellers prefer to spend time walking, in Santiago is preferable to spend time waiting. Santiago Metro users are more willing to travel in crowded trains than London Underground users. Both user groups have a similar dispreference to transfers after controlling for the time spent on transfer, but different attitudes to ascending and descending transfers. Topological factors presented on a distorted Metro map are more important than actual topology to passengers’ route choice decisions.     

Variation of households<Emphasis Type="Bold">’</Emphasis> car ownership across time: application of a panel data model

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.

The association between transit access and auto ownership: evidence from Guangzhou,China

In many developing countries, massive investment in transit infrastructure is concurrent with the proliferation of automobiles. Planners expect that investment can slow the growth of auto ownership. However, few studies have examined the relationships between transit access and auto ownership in developing countries, whereas research in developed countries offers mixed findings and the outcomes may not be applicable to developing countries. This study employs a random effect ordered probit model on data collected from Guangzhou residents in 2011–2012. We find that transit access is negatively associated with auto ownership, after controlling for demographics and other built environment variables. This result suggests that, although income is the dominant driver for auto ownership in growing developing countries, transit investment is a promising strategy to slow the growth of auto ownership. This study also highlights the importance of addressing spatial dependency in clustered data.     

Examining the relationship between built environment and metro ridership at station-to-station level

Very few studies have examined the impact of built environment on urban rail transit ridership at the station-to-station (origin-destination) level. Moreover, most direct ridership models (DRMs) tend to involve simple a prior assumed linear or log-linear relationship in which the estimated parameters are assumed to hold across the entire data space of the explanatory variables. These models cannot detect any changes in the linear (or non-linear) effects across different values of the features of built environment on urban rail transit ridership, which possibly induces biased results and hides some non-negligible and detailed information. Based on these research gaps, this study develops a time-of-day origin-destination DRM that uses smart card data pertaining to the Nanjing metro system, China. It applies a gradient boosting regression trees model to provide a more refined data mining approach to investigate the non-linear associations between features of the built environment and station-to-station ridership. Data related to the built environment, station type, demographics, and travel impedance including a less used variable – detour, were collected and used in the analysis. The empirical results show that most independent variables are associated with station-to-station ridership in a discontinuous non-linear way, regardless of the time period. The built environment on the origin side has a larger effect on station-to-station ridership than the built environment on the destination side for the morning peak hours, while the opposite holds for the afternoon peak hours and night. The results also indicate that transfer times is more important variables than detour and route distance.     

Changes in level of household car ownership: the role of life events and spatial context

Recent longitudinal studies of household car ownership have examined factors associated with increases and decreases in car ownership level. The contribution of this panel data analysis is to identify the predictors of different types of car ownership level change (zero to one car, one to two cars and vice versa) and demonstrate that these are quite different in nature. The study develops a large scale data set (n = 19,334), drawing on the first two waves (2009–2011) of the UK Household Longitudinal Study (UKHLS). This has enabled the generation of a comprehensive set of life event and spatial context variables. Changes to composition of households (people arriving and leaving) and to driving licence availability are the strongest predictors of car ownership level changes, followed by employment status and income changes. Households were found to be more likely to relinquish cars in association with an income reduction than they were to acquire cars in association with an income gain. This may be attributed to the economic recession of the time. The effect of having children differs according to car ownership state with it increasing the probability of acquiring a car for non-car owners and increasing the probability of relinquishing a car for two car owners. Sensitivity to spatial context is demonstrated by poorer access to public transport predicting higher probability of a non-car owning household acquiring a car and lower probability of a one-car owning household relinquishing a car. While previous panel studies have had to rely on comparatively small samples, the large scale nature of the UKHLS has provided robust and comprehensive evidence of the factors that determine different car ownership level changes.