Do high income households reduce driving more when living near rail transit?

Transportation planning today requires an understanding of how income and near-rail residence jointly influence household travel behavior. This article fills a gap in the literature by showing how vehicle miles traveled (VMT) and transit trips taken (TT) vary with income and rail transit access by neighborhood type. Results indicate that, when comparing households with similar incomes and examining how the “near-rail” versus “far from rail” VMT and TT gap varies by income, the cross-sectional reduction in nominal VMT and the increase in TT on a percentage basis is generally larger for higher-income households (>$50,000), and particularly so in neighborhoods dense with both jobs and population. These findings offer support for the notion that near-transit housing targeting higher-income households can have both sustainability and transit use benefits. We note, though, that equity considerations are a strong reason to include low-income housing near rail transit, and argue that policies focusing overly singly on either low-income or high-income housing near rail transit will not be as impactful as a robust focus on mixed-income housing developments in rail transit-oriented developments (TODs).     

Exploring the influence of built environment on Uber demand

Ride-sourcing services have made significant changes to the transportation system, essentially creating a new mode of transport, arguably with its own relative utility compared to the other standard modes. As ride-sourcing services have become more popular each year and their markets have grown, so have the publications related to the emergence of these services. One question that has not been addressed yet is how the built environment, the so-called D variables (i.e., density, diversity, design, distance to transit, and destination accessibility), affect demand for ride-sourcing services. By having unique access to Uber trip data in 24 diverse U.S. regions, we provide a robust data-driven understanding of how ride-sourcing demand is affected by the built environment, after controlling for socioeconomic factors. Our results show that Uber demand is positively correlated with total population and employment, activity density, land use mix or entropy, and transit stop density of a census block group. In contrast, Uber demand is negatively correlated with intersection density and destination accessibility (both by auto and transit) variables. This result might be attributed to the relative advantages of other modes – driving, taking transit, walking, or biking – in areas with denser street networks and better regional job access. The findings of this paper have important implications for policy, planning, and travel demand modeling, where decision-makers seek solutions to shape the built environment in order to reduce automobile dependence and promote walking, biking, and transit use.     

How much can trip chaining reduce VMT? A simplified method

Trip chaining represents a way to reduce vehicle miles traveled (VMT) that does not require people to shift away from driving private automobiles. While the existing literature on trip chaining acknowledges this potential, little has been done by way of quantifying this. This research seeks to fill this gap by using a large travel survey from the San Francisco Bay area to model the VMT generated by automobile tours as a function of tour composition (i.e., the number and type of destinations on that tour). The model results indicate that many tours involving trips chains (i.e., those tours with more than one destination) generate significantly less VMT than would occur if the destinations in these tours were split into multiple tours with single destinations. Tours that combine a work and non-work destination (which are the most common types of trip chains) particularly demonstrate potential for VMT reduction. Adding a non-work destination to a work tour is usually (depending on the specific type of destination) predicted to result in a reduction of 6–11 VMT, or about 20–30 %. Adding two non-work destinations to a work tour is usually predicted to result in a reduction of 10–22 VMT, or about 25–50 %.     

The net effects of the built environment on household vehicle emissions: A case study of Austin,TX

Growing concerns over climate change have led to an increasing interest in the role of the built environment to reduce transportation greenhouse gas (GHG) emissions. Many studies have reported that compact, mixed-use, and well-connected developments reduce vehicle miles traveled (VMT). Others, however, argue that densification and mixture of land uses can slow down vehicle movements, and consequently generate more driving emissions. Methodologically, VMT is only a proxy, not an exact measure of emissions. This study quantifies the net effects of the built environment on household vehicle emissions through a case study of Austin, TX. The study employed structural equation modeling (SEM) techniques and estimated path models to improve understanding of the relationship between the built environment and vehicle emissions. The results show a rather complex picture of the relationship. Densification can reduce regional vehicle emissions despite its secondary effect of reduced vehicle travel speed. A 1% increase in density was found to reduce household vehicle emissions by 0.1%. However, intensification of the design feature of the built environment in developed areas may work in the opposite direction; the modeling results showed a 1% increase in grid-like network being associated with 0.8% increase in household vehicle emissions. Based on the results, the study addressed the potential of and the challenges to reducing vehicle emissions through modifying the built environment in local areas.     

A new generalized travel cost based connectivity metric applied to Scandinavian airports

This article proposes a new, generalized travel cost based method to operationalize network accessibility provided by airports. The approach is novel as it integrates features of network topology with multiple quality aspects of scheduled air transport services into one metric. The method estimates generalized travel costs for the full set of feasible travel paths between an airport and all network destinations. Rooftop modeling accounts for schedule delay and isolates the most cost-efficient travel paths per O-D relation. Respecting the assumed arrival time preference of passengers and adjusting for destination importance, connectivity scores are derived. The method is then applied to explore changes in the global connectivity pattern of Scandinavian airports from 2004 to 2018. The results suggest distinct spatial differences throughout the network, but less pronounced in size than suggested by popularly applied connectivity measures. Findings also highlight the importance of the geographical location as a determinate of an airport’s connectivity.     

Flow-based accessibility measurement: The Place Rank approach

In this paper, we empirically test the viability of a flow-based approach as an alternative to transport accessibility measurement. To track where commuters travel from and to (but not commute times), we use transactional smartcard data from residents in Singapore to construct the (daily) spatial network of trips generated. We use the Place Rank method to demonstrate the viability of the flow-based approach to study accessibility. We compute the Place Rank of each of 44 planning areas in Singapore. Interestingly, even though the spatial network is constructed using only origin–destination information, we find that the travel time of the trips out of each planning area generally decreases as the area’s Place Rank increases. The same is also the case for in-vehicle time, number of transfers in the network and transfer time. This shows that a flow-based approach can be used to measure the notion of accessibility, which is traditionally assessed using travel time information in the system. We also compare Place Rank with other indicators, namely, bus stop density, eigenvector centrality, clustering coefficient and typographical coefficient to evaluate an area’s accessibility. The results show that these indicators are not as effective as the Place Rank method.     

Travel demand in the US urban areas: A system dynamic panel data approach

Using panel data from 85 urban areas over a 20-year period and applying a system panel data approach, this paper examines the relationship between travel demand in terms of per-capita VMT and urban spatial characteristics. Regression results show that road density and urban spatial size have positive and statistically significant effects on travel demand in the US urban areas. Urban population density and urban congestion have negative and statistically significant effects on travel demand.     

The capitalization of subway access in home value: A repeat-rentals model with supply constraints in Beijing

Urban rail transit enhances accessibility of the communities it serves and often contributes to the value of local real properties. A small number of studies have gone beyond the traditional cross-sectional hedonic analysis to use repeat-sales data in the US for more robust estimation of rail transit’s impact on property value. While the empirical literature generally supports the positive capitalization of rail transit in home value, it has produced widely varied estimates and failed to incorporate the theoretical insight that more elastic housing supply would reduce the extent of local amenities’ capitalization in home value. Observing Beijing’s rapid expansion of subway lines during the late 2000s, this study uses repeat rental transactions from 2005 to 2011 to investigate how home value reacts to the change in the home’s distance to nearest subway station. Repeat-rentals estimates suggest a rent-distance elasticity of −0.02, 70% below the cross-sectional hedonic estimate. Moreover, using the unique history of state-owned enterprise relocations as instrument for intra-city variation in land supply, we find that the capitalization of subway proximity in home value is weaker where land supply is more elastic. Our findings support the significant bias caused by omitted variables in the hedonic estimates and confirm housing supply’s role in explaining the intra-city spatial variation in estimates.     

Are we successful in reducing vehicle miles traveled in air quality nonattainment areas?

An important planning and policy question in the transportation, energy, and environment areas is whether or not air quality control and the associated funding preference and mitigation efforts to attain air quality conformity have indeed led to traveler behavior changes such as reduction in vehicle miles traveled (VMT) or VMT growth rates. In this research, we develop statistical models to analyze the relationship between air quality nonattainment designation and VMT between 1966 and 2004 based on observed data. These models employ different statistical methods, including hypothesis testing and simultaneous equations. Findings from these statistical models and datasets are consistent, and suggest there is a statistically significant negative correlation between nonattainment designation and VMT/VMT growth. For instance, the simultaneous equation model in this research, suggests that if a nonattainment area and an attainment area that are similar in all other aspects (population composition, socio-economics, urbanization, fuel price, vehicle stock, etc.) are compared, the VMT in the nonattainment area will be 1.80% less than that in the attainment area in the short run, and 7.61% less in the long run. While these results show strong statistical evidence that efforts in reducing VMT in nonattainment areas have been successful, future research should be conducted to attribute the VMT reduction effects to specific policy instruments for decision-making (e.g. the Congestion Management and Air Quality Improvement program, the conformity regulation in the transportation planning process, etc.).     

Quantifying the relative contribution of factors to household vehicle miles of travel

Household vehicle miles of travel (VMT) has been exhibiting a steady growth in post-recession years in the United States and has reached record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are increasingly seeking ways to curb vehicular travel to advance sustainable, vibrant, and healthy communities. Although there is considerable understanding of the various factors that influence household vehicular travel, there is little knowledge of their relative contribution to explaining variance in household VMT. This paper presents a holistic analysis to identify the relative contribution of socio-economic and demographic characteristics, built environment attributes, residential self-selection effects, and social and spatial dependency effects in explaining household VMT production. The modeling framework employs a simultaneous equations model of residential location (density) choice and household VMT generation. The analysis is performed using household travel survey data from the New York metropolitan region. Model results showed insignificant spatial dependency effects, with socio-demographic variables explaining 33 percent, density (as a key measure of built environment attributes) explaining 12 percent, and self-selection effects explaining 11 percent of the total variance in the logarithm of household VMT. The remaining 44 percent remains unexplained and attributable to omitted variables and unobserved idiosyncratic factors, calling for further research in this domain to better understand the relative contribution of various drivers of household VMT.     

Planning for pedestrian networks in North American downtowns

While North American urban regions are served by mechanical modes of transportation, downtowns are largely pedestrian environments. The growth and consolidation of office districts over the last twenty years have revived interest in developing coherent and efficient pedestrian networks, which can be coordinated with other transportation needs within the downtown. Ambitious plans for expansion of the downtown for offices, the retail and service industries as well as for housing and entertainment have been adopted in many North American cities during the 1980s. The successful integration of these large central areas depends to a considerable extent on the implementation of expanded pedestrian networks. This paper discusses certain spatial characteristics of North American cities which call for specific network designs and research into the walking environments of central areas. More knowledge is needed of the relative contributions to pedestrian regeneration of land use combinations, the design of networks and of walking paths.     

The role of VMT reduction in meeting climate change policy goals

This article evaluates the case for vehicle miles traveled (VMT) reduction as a core policy goal for reducing greenhouse gases (GHGs), concluding the economic impacts and social consequences would be too severe given the modest potential environmental benefits. Attempts to reduce VMT typically rely on very blunt policy instruments, such as increasing urban densities, and run the risk of reducing mobility, reducing access to jobs, and narrowing the range of housing choice. VMT reduction, in fact, is an inherently blunt policy instrument because it relies almost exclusively on changing human behavior and settlement patterns to increase transit use and reduce automobile travel rather than directly target GHGs. It also uses long-term strategies with highly uncertain effects on GHGs based on current research. Not surprisingly, VMT reduction strategies often rank among the most costly and least efficient options. In contrast, less intrusive policy approaches such as improved fuel efficiency and traffic signal optimization are more likely to directly reduce GHGs than behavioral approaches such as increasing urban densities to promote higher public transit usage. As a general principle, policymakers should begin addressing policy concerns using the least intrusive and costly approaches first. Climate change policy should focus on directly targeting greenhouse gas emissions (e.g., through a carbon tax) rather than using the blunt instrument of VMT reduction to preserve the economic and social benefits of mobility in modern, service-based economies. Targeted responses are also more cost effective, implying that the social welfare costs of climate change policy will be smaller than using broad-brushed approaches that directly attempt to influence living patterns and travel behavior.     

Workers wanted: Changing employee accessibility with industrial development ─ Evidence from Foxconn

In response to the trends of manufacturing revitalization and workforce shortage in the U.S., this study investigates how Foxconn changes accessibility to industrial employees by automobile and by transit in Southeast Wisconsin. Results suggest that there is a mismatch between the Foxconn site and the areas with high accessibility to industrial employees. With a great demand for labor, Foxconn reduces employee accessibility by automobile throughout the region, while its impact on employee accessibility by transit is more localized. The results inform industrial firm locations, workforce housing development, and transportation service provisions. The analysis framework shifts the angle of accessibility research to focusing on the perspective of employers, and it can be applied to investigate future large-scale economic development projects.     

A century of evolution of the accessibility concept

The concept of accessibility has acquired numerous meanings along multiple dimensions during the century of its evolution. This essay argues for the salience of two dimensions: application-based and definition-based. In its application, accessibility has incorporated positive and normative dimensions which have varied in prominence over time. In its definition, accessibility has varied between a mode of evaluation incorporating measured mobility and proximity, on the one hand, and a predefined market basket of urbanist improvements to transportation and land use systems, on the other. Advocates of the accessibility shift should emphasize both the measured approach to accessibility and accessibility’s normative side.     

The effects of highway development on housing prices

The purpose of this research is to estimate the effects of highway development projects on the price of housing. Transportation development projects, highways in particular, improve a certain area’s accessibility but also increase its levels of exposure to traffic intensity and noise pollution. These externalities are evaluated by homeowners and residents and are reflected in the price of housing. In this paper, we use several repeat sales model specifications, including difference-in-differences estimators, and control for neighborhood effects to examine housing price trends in the municipalities around two newly developed highways in the Netherlands. The results of the research demonstrate that changes in accessibility result in a significant positive effect on the price of housing in nearby municipalities, but that increased noise pollution and traffic intensity levels result in a decrease in prices. The findings also confirm that combining the total effects of all externalities, the effect of highway development on the price of housing is generally positive, and this effect is salient even before the project is completed due to public anticipation effects.     

Factors influencing destination choice for the urban grocery shopping trip

Destination choice for the urban grocery shopping trip is hypothesized to be determined by three factors: the individual's perception of the destination, the individual's accessibility to the destination and the relative number of opportunities to exercise any particular choice. Results of a multinomial logit model estimation support this hypothesis and provide useful information concerning the role of urban form in this destination choice situation. It is determined that accessibility is the primary aspect influencing destination choice and that its effect is nonlinear.On leave 1977-78 from State University of New York at Buffalo, Buffalo, New York 14214.     

Comparative assessment of accessibility metrics across the U.S.

Accessibility-related research has advanced considerably since its foundational conception six decades ago. Yet, despite widespread acceptance of the concept, these methods are still rarely used in practical applications among transportation agencies and policymakers. Until recently, the challenges were mainly technical but now they are more practical. Practitioners are often faced with decisions about appropriate methods and metrics, which are difficult to answer from the current literature. This study attempts to produce a clearer understanding of the effects that those decisions have on practical outcomes, based on data spanning many geographies across the U.S. We test a variety of metrics—including different modes, destination types, analytical geographies, and metric definitions—in regions spanning seven states. This study points to several potential best practices, including the use of non-work walking accessibility metrics in multimodal analysis and the use of decay functions in accessibility metrics, and provides a strong foundation for future research.     

Analysis of Metropolitan Highway Capacity and the growth in vehicle miles of travel

A number of recent studies have examined the hypothesis of induced travel in an attempt to quantify the phenomenon (Hansen & Huang 1997; Noland, forthcoming). No study has yet attempted to adjust for potential simultaneity bias in the results. This study addresses this issue by the use of an instrumental variable (two stage least squares) approach. Metropolitan level data compiled by the Texas Transportation Institute for their annual congestion report is used in the analysis and urbanized land area is used as an instrument for lane miles of capacity. While this is not an ideal instrument, results still suggest a strong causal relationship but probably that most previous work has had an upward bias in the coefficient estimates. The effect of lane mile additions on VMT growth is forecast and found to account for about 15% of annual VMT growth with substantial variation between metropolitan areas. This effect appears to be closely correlated with percent growth in lane miles, suggesting that rapidly growing areas can attribute a greater share of their VMT growth to growth in lane miles.     

An innovative model to estimate the accessibility of a destination by public transport

Accessibility is a valuable indicator for assessing the effectiveness of a transport network. Nevertheless, its analysis can lead to very heterogeneous results depending on the method adopted, thus still struggling to be considered by policy makers and in planning processes. This article contributes to the development of an accessibility analysis as a planning tool, by proposing an alternative model to estimate the relative accessibility of a destination by public transport (PT). Indeed, PT is a mobility paradigm that has been supported to reduce the negative externalities produced by private transport, especially in environmentally fragile contexts. The model includes a set of eleven factors affecting public transport operation which refer to four macro topics: connectivity, multimodality, tariff/ticketing, and info-mobility. They are integrated into a Public Transport Accessibility index which analyses a series of nodes along a route and detects the progressive variation of accessibility. Eventual shifts are highlighted, including information about the factors feeding them. The model is tested for the Lana-Zurich (IT-CH) connection, showing how the most relevant issues are caused by difficulties in the transnational and transregional integration of the services. Through this process, the model aims at backing policy makers in the detection and understanding of public transport barriers and related causes.     

VMT, energy consumption, and GHG emissions forecasting for passenger transportation

Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998-2008, the authors develop simultaneous equation models for predicting VMT on different road functional classes and examine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.