Equity of transit connectivity in Tennessee cities

Federal and state agencies focus on providing captive users in mobility-vulnerable population groups with access to public transit resources. One challenge to the provision of equitable access is quantifying equity-oriented metrics for public transit service. This paper utilizes an approach that utilizes the available spatial demographic data and transit network characteristics to compute multimodal transit connectivity and equity. This method is exemplified by analyzing transit connectivity for three metropolitan cities in the state of Tennessee in the United States and overlapping that connectivity on demographic data. Results indicate that the distribution of transit services among vulnerable populations varies within and between cities. The case studies illustrate how this methodology can be used by public agencies to assess the performance of transit systems and to identify the distribution of these systems among various groups to improve the equity of transit connectivity.     

Identifying public transport gaps using time-dependent accessibility levels

One of the concerns that has aroused much scholarly attention in transport geography lately is the extent to which public transport provision enables the less privileged population segments, especially those without privately owned motorized vehicles, to participate in activities that are deemed normal within the society they live in. This study contributes to this line of inquiry by proposing a methodology for identifying public transit gaps, a mismatch between the socially driven demand for transit and the supply provided by transit agencies. The methodology draws on the latest accomplishments in the field of modeling time-continuous, schedule-based public transport accessibility. Accessibility levels to key destinations are calculated at regular time intervals, and synoptic metrics of these levels over various peak and off-peak time windows are computed for weekdays and weekends. As a result, a temporally reliable picture of accessibility by public transport is constructed. The obtained index of public transport provision is compared to a public transport needs index based on the spatial distribution of various socio-demographics, in order to highlight spatial mismatches between these two indices. The study area consists of Flanders, which is the northern, Dutch-speaking region of Belgium. The results indicate that mainly suburban areas are characterized by high public transport gaps. Due to the time-variability of public transport frequencies, these gaps differ over time.     

Measuring and visualizing place-based space-time job accessibility

Place-based accessibility measures, such as the gravity-based model, are widely applied to study the spatial accessibility of workers to job opportunities in cities. However, gravity-based measures often suffer from three main limitations: (1) they are sensitive to the spatial configuration and scale of the units of analysis, which are not specifically designed for capturing job accessibility patterns and are often too coarse; (2) they omit the temporal dynamics of job opportunities and workers in the calculation, instead assuming that they remain stable over time; and (3) they do not lend themselves to dynamic geovisualization techniques. In this paper, a new methodological framework for measuring and visualizing place-based job accessibility in space and time is presented that overcomes these three limitations. First, discretization and dasymetric mapping approaches are used to disaggregate counts of jobs and workers over specific time intervals to a fine-scale grid. Second, Shen's (1998) gravity-based accessibility measure is modified to account for temporal fluctuations in the spatial distributions of the supply of jobs and the demand of workers and is used to estimate hourly job accessibility at each cell. Third, a four-dimensional volumetric rendering approach is employed to integrate the hourly job access estimates into a space-time cube environment, which enables the users to interactively visualize the space-time job accessibility patterns. The integrated framework is demonstrated in the context of a case study of the Tampa Bay region of Florida. The findings demonstrate the value of the proposed methodology in job accessibility analysis and the policy-making process.     

Examining the influence of stop level infrastructure and built environment on bus ridership in Montreal

We studied transit ridership from the perspective of the transit provider, with the objective of quantifying the influence of transit system operational attributes, transportation system infrastructure attributes and built environment attributes on the disaggregate stop level boardings and alightings by time of day for the bus transit system in the Montreal region. A Composite Marginal Likelihood (CML) based ordered response probit (ORP) model, that simultaneously allows us to incorporate the influence of exogenous variables and potential correlations between boardings and alightings across multiple time periods of the day is employed. Our results indicate that headway affects ridership negatively, while the presence of public transportation around the stop has a positive and significant effect. Moreover, parks, commercial enterprises, and residential area, amongst others, have various effects across the day on boardings and alightings at bus stops. An elasticity analysis provides useful insights. Specifically, we observe that the most effective way to increase ridership is to increase public transport service and accessibility, whereas enhancements to land use have a smaller effect on ridership. The framework from our analysis provides transit agencies a mechanism to study the influence of transit accessibility, transit connectivity, transit schedule alterations (to increase/reduce headway), and land-use pattern changes on ridership.     

Dynamic transit accessibility and transit gap causality analysis

Public Transit Accessibility (PTA) analysis helps transit agencies and planners identify areas in need of transit service improvements and prioritize transit investments. To evaluate the accessibility of existing transit services and identify access gaps, it is critical to accurately estimate travel times between transit stops, which change throughout the day due to transit schedule variations. Commonly used methods in PTA ignore such temporal fluctuation. Moreover, these methods are unable to elucidate the causes of poor PTA. To address these issues, we first implemented an algorithm to effectively compute travel times at multiple departure times throughout the day in order to enable spatiotemporal PTA analysis. A series of indicators that are intuitive to interpret were developed to determine the varying causes of poor PTA and identify areas with immediate needs for improvements. We showcase the analytical framework using a transit network in the State of Utah operated by the Utah Transit Authority. The analysis is based solely on publicly-available open datasets, which makes it generally adaptable to other transit networks. Results can assist transit agencies with identifying areas in need of service improvement and prioritizing future investments.     

Identifying spatiotemporal transit deserts in Seoul,South Korea

Transit deserts can result from the inequitable distribution of resources and services, and people living in transit deserts have limited access to transportation system. The aim of this study was to perform spatiotemporal data analysis to identify transit desert areas in Seoul in three steps. First, the transit gap between peak and off-peak hours is evaluated and various spatial changes in each temporal transit desert area are identified. Second, a spatial analysis is conducted to identify transit desert and transit oasis areas that emerge during peak hours. Lastly, an independent T-test is conducted to identify how the socio-economic characteristics of transit deserts and transit oases are statistically different. Our analysis show that, transit deserts changed across space and over the time in Seoul. Furthermore, transit deserts in general appear to be associated with socio-economically vulnerable residential areas.     

A GIS-based spatial statistical approach to modeling job accessibility by transportation mode: case study of Columbus,Ohio

Improving job accessibility based on transport connectivity helps to address equity issues. Spatial autocorrelation (SA) is also a focus of interest in transportation planning, but has been neglected in analyzing job accessibility in metropolitan areas. In this study, GIS-based job accessibilities by walking, transit, and car are computed for the metropolitan area of Columbus, Ohio, and three transport-based spatial autoregressive (SAR) models are estimated to account for the SA of job accessibility among neighboring block groups, while controlling for built-environment and socioeconomic factors. SA intensities and extents are compared in order to better understand local spatial clusters of job accessibility across the region. Direct and indirect spillover effects due to an investment change in transportation facilities are estimated and provide important transportation planning information. The results also show that walking-accessed jobs are primarily related to physical settings (e.g., land uses) at the local level. Locations with a higher share of zero-vehicle housing units have better job accessibility by transit. There is a spatial mismatch between Asian population clusters and transit-accessed jobs, possibly because of the car-oriented residential clusters around Honda of America Manufacturing in suburban areas. More importantly, locations with a higher share of single-parent households are at a disadvantage in overall job accessibility. Due to its complex transportation needs, a society friendly to single parents should spatially integrate accessible jobs with other needed activities via land-use and transportation planning. Alternatively, car-ownership programs and non-spatial social supports also might be effective to help secure job opportunities and perform daily life activities.     

A flexible framework for measuring accessibility with destination bundling

A transit system's usefulness is governed by the freedom it provides to those who use it. This freedom, typically quantified as accessibility, is proportional to the amount and variety of destinations available to a potential transit user. Often, transit systems are designed with the commuter in mind; employment is a typical stand-in measure for all destinations when measuring accessibility in a city. This paper proposes a framework to “bundle” destination types into a more comprehensive profile of accessibility. The framework is flexible enough to adapt to local conditions and data availability, and provides a potential planner with the ability to tell a more nuanced story of transit accessibility in a city. Using population, employment, and crowd-sourced destination data in Calgary, Canada, we perform a comparison of destination bundling approach to find that the relative level of access to destinations varies greatly with the bundle of destinations used. We also analyze correlations between quality of access to destinations, suggesting that certain destinations can act as substitutes for others, and that using destinations with low correlations in their quality of access increases the results' sensitivity to the transit network. As this approach uses open data sources available in most jurisdictions, it can be easily applied to different urban areas, destination sets, and accessibility measures to tell a more comprehensive story of transit accessibility in cities.     

Evaluating public transit services for operational efficiency and access equity

Assessing the performance of public transit services has long been an important yet challenging issue for transportation agencies and researchers. Transit service performance measurement reflects a very first step towards an efficient and proactive management, where public transit agencies are increasingly pressured to provide high-quality services in spite of constrained resources. However, the performance evaluation of transit services is complicated by an array of quantitative measures available to assess the goals and the diversity in the goals themselves, which usually include improving operational efficiency and providing equitable access. While much previous work has examined public transit services for achieving optimal operational efficiency and/or access equity separately, the interplay of the two has rarely been investigated to date. This article proposes a new method for evaluating the overall performance of public transit services via a combination of data envelopment analysis (DEA), Geographic Information System (GIS), and multi-objective spatial optimization techniques. The new method is applied to assessing the performance of fixed route bus services operated by the Utah Transit Authorities (UTA) in the Wasatch Front, Utah. Results demonstrate that the proposed method can effectively account for operational efficiency and access equity in an integrated framework, providing a more comprehensive assessment for transit service performance.     

Extending public transit accessibility models to recognise transfer location

A longstanding issue for public transit agencies has been how to assess the performance of transit service including spatial service coverage to meet the transport needs of the community. The conventional approach quantifies accessibility using door-to-door travel time in such a way that accessibility declines as the travel time to the opportunity increases. A new approach to modelling transit accessibility is proposed by incorporating the potential effect of transfer location. It builds on the premise that transit users may have a preference for a transfer location best located relative to the trip origin and destination points. The model is tested in Brisbane's bus network which has a radial form, where inner-city suburbs have relatively higher accessibility than outer-city suburbs, if only travel time is counted. Incorporating the transfer location refines the accessibility modelling so that some outer-city suburbs located along the major bus corridors have a relatively higher accessibility level. The new model also suggests that inner-city suburbs do not necessarily have better accessibility. Suburbs close to the city centre may have shorter transit travel time to reach other suburbs, but they do not have a well-connected transit network to other suburbs through service transfers.     

Measuring accessibility to grocery stores using radiation model and survival analysis

Measuring spatial accessibility to grocery stores and identifying food deserts have been of interest to planners and policy makers. However, measuring and quantifying accessibility in a way that relates to actual travel behaviors and preferences are challenging. This study aims to promote an existing radiation model by incorporating different transportation modes and time use diaries to provide a more realistic estimation of accessibility. We proposed a survival analysis method, such as the Cox proportional hazard model, as a novel approach to develop a cost decay function based on time use diaries. A multinomial logit model was applied to estimate the portion of people walking, traveling by car, and traveling by bus. A case study of grocery stores in Travis County, Texas, is used to illustrate the approach. The results indicate that for walking accessibility to grocery stores, the majority of zip codes fall into the very low, low, and moderate accessibility classes. Moreover, in most western zip codes transit accessibility to grocery stores is found to be very low. However, the spatial accessibility for some of such zip codes has been enhanced because of the presence of cars.     

Grocery store accessibility: Different metrics – Different modal disparity results and spatial patterns

Most accessibility studies focus on within transport mode travel performance variations. However, modal accessibility disparity analysis adds value to the single-mode analysis by assessing the interaction between different transport modes and land use. A review of modal disparity studies shows that different accessibility metrics lead to different results, and so it is unclear how this impacts modal accessibility disparity variation. Moreover, the correspondence of the disparity spatial pattern between the different metrics is unclear. This research examines how three typical accessibility metrics (closest facility, cumulative opportunity, space-time constrained) impact modal disparity of grocery store accessibility in Warsaw, Poland. Further, local indicators of spatial association are used to identify areas of similarity and difference between the metrics. This study finds that cumulative opportunities during non-rush hours indicate the best car advantage for all travel times but indicate the best transit advantage during rush hours for 15 min. Generally, the space-time metric indicates better transit accessibility than the closest facility metric which in turn shows better transit accessibility than cumulative opportunities. The city center has significant spatial similarity while peripheral, especially dense, areas have significant spatial difference. Similarity areas have higher transit stop and population densities, while difference areas have average-to-low stop, population, road and store densities.     

R-Tresis: developing a transport model system for regional New South Wales

This paper sets out a demand modelling framework for the development of a regional transport and land use model system (R-Tresis), to be implemented for New South Wales (Australia). Traditionally, the focus of such a model system has been major metropolitan areas such as Sydney, where we have developed Tresis (Hensher, 2002). Given the growing concern about regional accessibility to many service classes, there is a need for a modelling capability that can be used to prioritize and guide policy decisions in regions that are often described as remote, rural, low density and small town. In developing a framework that is capable of integrating both demand and supply elements of transportation and land use activity, we recognized the challenges in developing primary data sources, and the high likelihood of a reliance on secondary data sources. This suggested an alternative approach to demand modelling that was not dependent on choice models; namely a suite of continuous choice models in which we capture the actual activities undertaken by each mode on both the demand and supply side at high spatial resolution.     

Using connectivity for measuring equity in transit provision

This study proposes the assessment of equity in transit provision by using transit connectivity as a comprehensive impedance measure. Transit connectivity considers in-vehicle time, access/egress times, waiting time, service reliability, frequency, and ‘seamless’ transfers along multi-modal paths. In addition, transit connectivity weighs the impedance components according to their relative importance to travelers. The assessment of equity was performed for the multi-modal transit system in the Greater Copenhagen Area, renowned for its transit-oriented finger-plan. The assessment method used a GIS representation of the network (i.e., service lines, timetables, metro stations, train stations, and bus stops), and transit assignment results (i.e., level-of-service times, passenger flows). The assessment method proved effective in calculating location-based and potential-accessibility measures and Gini coefficients of inequality in the Greater Copenhagen Area. Results show that the transit-oriented development contributes to spatial equity with high connectivity in densely populated zones, vertical equity with comparable connectivity in high income and low income zones, inter-generational equity with good connectivity provision for students to higher-education and job opportunities. Also, results show that the north-west ‘finger’ is less equitable with lower connectivity for low population density and lower connectivity to higher-education opportunities regardless of the high number of students.     

Land use effects on bicycle ridership: a framework for state planning agencies

State and local agencies increasingly recognize the importance of bicycling activity and as the number of riders has grown over the past several years, the agencies are becoming more aware of the need to provide better bicycle infrastructure. This paper proposes a series of empirical models and applies them to the State of Maryland in the United States, using a spatial lag approach to explore land use, built environment, demographic, socio-economic, and traffic condition connections to bicycle ridership, defined as the number of bicycle trips generated by a given analysis zone per day. A set of models is proposed for three land-use typologies: urban, sub-urban and rural. The data that drives this analysis was obtained from a recently conducted Household Travel Survey (HTS) in the Baltimore–Washington region in Maryland. Results show that some land uses, socio-economic and demographic characteristics, and transit accessibility are positively correlated with bicycle ridership. Other types of land use, transport system characteristics and income level have an inverse relationship with bicycle ridership. The contributing factors to bicycle ridership vary with land-use typology. This proposed approach could be used to evaluate factors relevant to bicycle demand. State and local agencies are advised to build designated bicycle paths according to traffic conditions and increase bicycle-parking capacity in specific establishments.     

Public transit accessibility approach to understand the equity for public healthcare services: A case study of Greater Mumbai

Urban public health is one of the most critical yet neglected aspects of urban planning in developing countries such as India. Inequity in access to government healthcare facilities affects the overall urban population and can substantially negatively impact the vulnerable population, who mostly rely on government healthcare services. In this paper, the accessibility measure for healthcare services by public transport is developed using travel time and the number of transit stops (accounting for transit connectivity) for Greater Mumbai. We also identified socially vulnerable wards (administrative units) using a Social Vulnerability Index (SVI), developed based on 16 indicators using Principal Component Analysis (PCA). Developed regression models showed that the proposed accessibility measure explains the coverage and usage of healthcare services better than the traditional accessibility measure, which is based on only aggregate level travel time impedances. South Mumbai has relatively better accessibility for public hospitals and dispensaries, whereas, lower level of accessibility is observed in the eastern part for public healthcare services. Assessment for the spatial inequity based on the Gini index, bivariate Moran's I, and mean access value reveals a higher degree of spatial inequity for accessing government hospitals for the slum population. The study developed a decision framework to suggest effective policy measures, which can be prioritised based on SVI to reduce the disparity in the spatial distribution of accessibility to government healthcare systems for vulnerable groups. Our findings can aid transportation and urban planners, health researchers, and policymakers to improve accessibility in under-served areas and give special attention to the needs of the vulnerable population.     

Measuring transit oriented development: a spatial multi criteria assessment approach for the City Region Arnhem and Nijmegen

Transit Oriented Development (TOD) is a planning approach that can stimulate sustainable development by encouraging better land use and transport integration. Arnhem Nijmegen City Region, a regional planning body, in the Netherlands, aims to promote sustainable development in their region and control the current pattern of increased use of cars vis-à-vis transit for longer commutes. Planning for TOD can help achieve this aim. It is believed that measuring the existing levels of TOD is a prerequisite for TOD planning and that it can be done using a TOD Index proposed in this research. A TOD Index measures multiple spatial indicators and aggregates them under the SMCA framework to arrive at a comprehensive value depicting the existing levels of TOD at a location or an area. Using this TOD Index, TOD levels were measured over the entire City Region covering approx. 1000 km². High levels of TOD imply that the urban development’s characteristics, at that location, are ripe for use of transit and these high levels, as expected, were found in the urban areas of Arnhem and Nijmegen. From the results of TOD Index measurement, using hot-spot analysis, those locations were identified that have high TOD levels but poor transit connectivity. These locations are accordingly recommended for better transit connectivity. As a part of our future work, it is intended to use the TOD Index to elevate TOD levels around existing transit nodes.     

Circuity in urban transit networks

This paper investigates the circuity of transit networks and examines auto mode share as a function of circuity and accessibility to better understand the performance of urban transit systems. We first survey transit circuity in the Minneapolis–St. Paul, Minnesota, region in detail, comparing auto and transit trips. This paper finds that circuity can help to explain mode choices of commuters. We then investigate thirty-five additional metropolitan areas in the United States. The results from these areas show that transit circuity exponentially declines as travel time increases. Moreover, we find that the circuity of transit networks is higher than that of road networks, illustrating how transit systems choose to expand their spatial coverage at the expense of directness and efficiency in public transportation networks. This paper performs a regression analysis that suggests the circuity of transportation networks can estimate transit accessibility, which helps to explain mode share.     

Spatial variations in active mode trip volume at intersections: a local analysis utilizing geographically weighted regression

Geographically weighted regression (GWR) models have been employed in previous studies regarding vehicular travel demands, but few studies have locally modeled walking travel demands at intersections to address the issue of spatially varying relationships. Harnessing a comprehensive collection of walking and bicycling traffic counts over 10 years in Chittenden County, Vermont, US, along with socioeconomic characteristics, transit accessibility indices, land use attributes and characteristics of intersections and roadway networks, this study utilizes GWR models to identify whether there are spatially varying relationships between active mode travel demands and ambient built-environment attributes. One Ordinary Least Square (OLS) model and two GWR models were parametrically calibrated: a full GWR model of all local variables and a mixed GWR model of both global and local variables. K-fold cross-validation method is used to select variables that significantly influence the volume of active travel modes in the OLS model. The uniform set of variables is investigated in two GWR models. Only residuals of the mixed GWR model exhibit spatial independence. The prediction accuracy of the three models is respectively compared by means of the k-fold cross-validation method. Results show that the mixed GWR model has higher prediction accuracy, while the other two models have roughly the same level of performance. We find that not all independent variables possess a spatially varying relationship with active mode volumes. The flexibility of the mixed GWR model that allows some independent variables to be global strengthens its prediction power. With these findings, transportation planners can dynamically estimate bicycle and pedestrian volumes at widespread intersections, and this geographical realism would facilitate local transportation planning, facility design, safety enhancement and operation analysis, as well as instilling new insights into interdisciplinary spatial research domain.     

Spatial disparity of income-weighted accessibility in Brazilian Cities: Application of a Google Maps API

Equity in public transit ridership has attracted the attention of planning authorities as a mechanism to tackle social exclusion. The association of accessibility indexing with different income groups is fundamental to analyses of socio-spatial inequalities and identifying gaps in public transit services. However, few studies have addressed accessibility inequalities in medium-sized cities of the global South. This paper aims to identify spatial gaps in public transit service in seven medium-sized Brazilian cities by analyzing the relative accessibility of public transit and private automobiles for travel to central business districts (CBDs), which are primary employment and service centers. Demographic and socioeconomic data on the seven cities were extracted from the country's 2010 population census. To measure accessibility to CBDs, a Google Maps application programming interface was used to produce realistic estimates of travel times for public transit and private automobiles over different time periods. This method is more accurate than traditional accessibility calculation methods and provides real-time information on traffic conditions, such as speed limits, traffic jams, and waiting times. The study found significant intra-regional differences in accessibility to CBDs by public transit and private automobiles, providing a scientific basis to optimize the socio-spatial distribution of public transit services in seven cities in five different regions of Brazil.