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.     

Understanding accessibility through public transport users' experiences: A mixed methods approach

The quantitative measurement of accessibility through public transport has become more complex and accurate over time. However, it lacks many of the deeper nuances of how people actually experience their travel environments. Our previous works have highlighted the importance of incorporating the lived travel experiences of passengers within accessibility indicators, considering the quality of the walking environment and different attributes of the public transport services.Building on these works, this mixed-method research seeks to further improve the characterization of accessibility according to users' travel experiences, as described by those attributes that inhibit or enhance access to opportunities within the city. We use content analysis of focus groups, data gathered in a brief survey and sociodemographic and public transport data for our analyses. Our main contributions are (i) to develop a conceptual framework to analyze qualitative data on how people relate and discuss their public transport accessibility experiences and (ii) to develop accessibility indicators differentiating user perceptions. We apply this novel conceptual framework and methods to the unique urban morphology of two municipalities of Santiago de Chile.We identified different ‘socially constructed’ narratives for buses and metro. The participants focused on barriers to accessibility, showing an important relationship between them, as well as substantial differences in their overarching positive perception of metro and negative for buses. However, when disaggregating the analysis by primary transport mode and location, we found ‘hidden’ values for buses, recognizing its capillarity and underlying connectivity with the metro system. Furthermore, we found a dissimilar perception of transport environments when disaggregating the analysis by gender, age and location, which translated into different accessibility profiles for the various public transport users. From these experiential qualitative perspectives, it was thus possible to determine some attributes that had been previously overlooked in more quantitative studies but which are important when analyzing public transport accessibility for different population groups.     

Improving rural accessibility by locating multimodal mobility hubs

In rural regions, public transportation is often characterized by low accessibility as well as long waiting and travel times. In order to improve rural transportation systems, public decision-makers intend to implement alternative on-demand mobility modes. Herein, new intermodal travel itineraries with transfers at multimodal mobility hubs may enable faster public connections and thereby strengthen public transportation. Against this background, we present a decision support tool for locating multimodal mobility hubs to improve intermodal accessibility. As objectives, we aim at maximizing accessibility to workplaces and to places of private need. Our model decides on locations of multimodal mobility hubs and on the available on-demand mobility modes offered in addition to existing public transportation. We develop our model in an agile process together with rural decision-makers in the district of Heinsberg, Germany, and apply it in a real-world case study. As input for our model, we account for the existing public transportation system, identify points-of-interest, and estimate commuting volumes to workplaces based on official commuting data. Results promise a high potential to improve accessibility in rural areas. However, most of the improvement stems from unimodal car sharing trips.     

Estimating the influence of crowding and travel time variability on accessibility to jobs in a large public transport network using smart card big data

Accessibility metrics are gaining momentum in public transportation planning and policy-making. However, critical user experience issues such as crowding discomfort and travel time unreliability are still not considered in those accessibility indicators. This paper aims to apply a methodology to build spatiotemporal crowding data and estimate travel time variability in a congested public transport network to improve accessibility calculations. It relies on using multiple big data sources available in most transit systems such as smart card and automatic vehicle location (AVL) data. São Paulo, Brazil, is used as a case study to show the impact of crowding and travel time variability on accessibility to jobs. Our results evidence a population-weighted average reduction of 56.8% in accessibility to jobs in a regular workday morning peak due to crowding discomfort, as well as reductions of 6.2% due to travel time unreliability and 59.2% when both are combined. The findings of this study can be of invaluable help to public transport planners and policymakers, as they show the importance of including both aspects in accessibility indicators for better decision making. Despite some limitations due to data quality and consistency throughout the study period, the proposed approach offers a new way to leverage big data in public transport to enhance policy decisions.     

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.     

Modeling job accessibility using online map data: An extended two-step floating catchment area method with multiple travel modes

Current quantitative measures of job accessibility rarely consider the interaction between job opportunities and labor force, and the effects of dynamic travel mode choice. Drawing upon multiple open-source datasets, we develop a job accessibility index by extending the two-step floating catchment area method (2SFCA). The job accessibility indices are calculated for different commuting scenarios concerning distance, time, and travel modes. The results suggest that job accessibility is very sensitive to travel modes, and using a single travel mode would contribute to a biased job accessibility index. The job accessibility indices with combined travel modes are more geographically balanced than using a single travel mode. Furthermore, the new index is employed to examine the spatial pattern of job accessibility and explore the relationship between job accessibility, housing, and population in the Pudong district, Shanghai. The new job accessibility indices manifest the impacts of ring roads on the spatial distribution of job accessibility. A comparative analysis shows that the floating population has poor driving-based job accessibility but can access job opportunities using public transit. Also, poor job accessibility leads to low rent prices but has little impact on medium-high rent. Both transit-based and drive-based job accessibility indices are positively related to housing prices. Our study highlights the importance of considering dynamic travel mode choice in job accessibility research. The research outcomes also contribute to the literature on spatial mismatch by revealing the unique relationship between job accessibility, housing, and population in urban China.     

Dynamic accessibility: Incorporating day-to-day travel time reliability into accessibility measurement

Travel times and hence accessibility in urban areas are susceptible to traffic disruption caused by events such as congestion, roadworks and traffic accidents. Being highly valued by travellers, travel time reliability affects their participation in activities and thus, plays a decisive role in accessibility. The aim of the study was to develop an approach to integrate travel time reliability into the measurement of accessibility. To achieve this, we extended a commonly-used accessibility indicator to include day-to-day variability in travel times. In a case study of the accessibility to the newly-built Queen Elizabeth University Hospital (QEUH) in Glasgow, we used real-time travel times with high temporal resolution collected over a long period of time to demonstrate the applicability and the utility value of this approach compared to the standard accessibility measurement. Our results revealed that travel time reliability varied both temporally and spatially, and zones experienced relatively high levels of accessibility loss due to higher travel time variability. The proposed approach provides a more realistic representation of actual network performance, allows for assessing the effect of travel time reliability on accessibility throughout the day and will help transport planners to trace equity impacts on accessibility due to travel time unreliability.     

Assessment of the socio-spatial effects of urban transport investment using Google Maps API

We analyze the spatially distributed impacts of transport investment in urban highways and public transport with a novel methodology based on the capabilities of online technology to replicate the (unobserved) condition without highways. This is based upon the intensive use of Google Maps API (GMA) to obtain travel times between each origin-destination pair at a highly detailed level to reveal the effects of new infrastructure on different zones and groups within a city. Santiago is used as a case study, as the city introduced 150 km of urban highways, a reorganization of surface transit, and new subway lines in a relatively short period. We show that the high-income segment of the population has been the most favored, simultaneously increasing the difference between transit and car travel times in those areas where car ownership is low, stimulating the acquisition of a car.     

Job accessibility through public transport and unemployment in Latin America: The case of Montevideo (Uruguay)

Accessibility to job opportunities is one of the factors that explains labor outcomes. For developing countries, public transport plays a key role in providing the population with access to employment opportunities. This paper aims to quantify accessibility by public transport to employment in Montevideo, Uruguay and to explore how accessibility to job opportunities via public transport relates to unemployment. To do so, we calculate a cumulative measure of accessibility to job opportunities for 1063 small zones—approximately 4–6 blocks each—within Montevideo. This measure yields accurate data on accessibility and can be assigned to individual households. Accessibility in Montevideo is unevenly distributed among social strata and is concentrated within the central (and wealthier) areas of the city. In addition, a multilevel logistic regression analysis indicates that greater accessibility to jobs via public transport is associated with a lower probability of being unemployed. This finding suggests that improving accessibility to job opportunities via public transit may enhance individual labor outcomes.     

Robust accessibility: Measuring accessibility based on travelers' heterogeneous strategies for managing travel time uncertainty

Uncertainties in travel times due to traffic congestion and delay are risks for drivers and public transit users. To avoid undesired consequences such as losing jobs or missing medical appointments, people can manage the risks of missing on-time arrivals to destinations using different strategies, including leaving earlier to create a safety margin and choosing routes that have more reliable rather than fastest travel times. This research develops a general analytical framework for measuring accessibility considering automobile or public transit travelers' heterogeneous strategies for dealing with travel time uncertainty. To represent different safety margin plans, we use effective travel time (expected time + safety margin), given specified on-time arrival probabilities. Heterogeneity in routing strategy is addressed using different Pareto-optimal routes with two main criteria: faster travel time vs. higher reliability. Based on various safety margin and routing strategy combinations, we examine how accessibility changes under varying safety margin plans and routing strategies. Also, we define and measure robust accessibility: geographic regions that are accessible regardless of the safety margin planning and routing strategy. Robust accessibility can provide a conservative and reasonable view of accessibility under travel time uncertainty. To demonstrate the applicability of the methods, we carry out an empirical study on measuring the impacts of new transit service on healthcare accessibility in a deprived neighborhood in Columbus, Ohio, USA.     

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.     

Location quotient-based travel costs for determining accessibility changes

Accessibility is not a static feature because it is affected by a large number of factors, such as changes in transport infrastructure, the spatial distribution of human activities, and their interdependence. In this study, we examine the role of location quotient-based travel costs as the travel impedance function in accessibility measurement to better capture accessibility changes over time. The travel impedance function is one of the most widely studied aspects of accessibility. In most studies, travel impedance is determined by a negative exponential function in the travel cost assessment of the accessibility measure as a means to incorporate the distance decay effect. Here, we apply an accessibility index that uses location quotient-based travel costs and an accessibility measure with simple travel costs in order to test the proposed theory. The results of the two methods vary considerably. The location quotient method is discussed in detail, including its potential advantages for measuring accessibility changes. We argue that the location quotient-based travel cost is an appropriate method for determining the travel impedance function in accessibility measurements, especially for analyzing accessibility changes.     

The spatial characteristics and influencing factors of modal accessibility gaps: A case study for Guangzhou,China

This paper presents an analysis of the spatial characteristic of the modal accessibility gap (MAG) in Guangzhou based on travel times for public transport and cars to public centers calculated by the Travel O-D point Intelligent Query System (TIQS). Four spatial regression models are used to investigate the effect on the MAG of six factors of the built environment (distance to city public centers, residential density, landuse mix, bus stop density, metro station density and road network density). The results show that travel time for a given origin to destination (OD) trip is likely to be larger by public transport than by car, especially for a trip of longer travel time. The MAG values of all the communities are larger than 0, indicating that when compared with public transport, travelling by car takes less travel time for individuals. Residential density, land-use mix, bus stop density and metro rail station density have significant negative direct impacts and indirect impacts (spatial spillover effects) on MAG, which indicates that appropriate increase in community residential density, providing diversified service facilities within a community, and improving public transport supply are beneficial to promote modal shift. Specifically, the role of metro rail is greater than that of buses. However, the road network density has significant direct positive impacts on MAG, and its spillover effect is also significantly positive, which indicates that building more roads is not an effective way to narrow the accessibility gap between public transport and cars but may facilitate more car travel instead.     

Evaluating spatial accessibility to healthcare services under travel time uncertainty: A reliability-based floating catchment area approach

Most existing healthcare accessibility studies ignore the travel time uncertainty that are commonly encountered in road networks. This study aims to examine the impacts of travel time uncertainty on healthcare accessibility. A reliability-based two-step floating catchment area (2SFCA) method is proposed to evaluate healthcare accessibility under travel time uncertainty. The proposed measure generalizes the conventional 2SFCA measure by explicitly considering individuals' reliability constraints when scheduling visits to healthcare facilities in the face of travel time uncertainty. The proposed measure is further used to investigate travel time uncertainty impacts in a comprehensive case study. A big dataset of taxi trajectories is collected in the case study to extract dynamic information on travel time distributions. The results of the case study highlight the significant but heterogeneous impacts of travel time uncertainty on healthcare accessibility for various parts of the city at different times of the day. They also have several methodological implications for the evaluation of healthcare accessibility under travel time uncertainty.     

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.     

Social inequalities of park accessibility in Shenzhen,China: The role of park quality,transport modes,and hierarchical socioeconomic characteristics

Identifying the geographic units with restricted access to intra-urban parks has become a hot issue in transport studies. Previous literature has examined the social inequalities of park accessibility under the Western context; however, the issue has seldomly investigated against the non-Western background, especially in China. Using a case of Shenzhen (China), this paper examines the accessibility to parks of three quality levels (official standard) under four transport modes (public transit, walking, bicycle, and private car). In particular, the daily travel time from each community (8117) to each park (625) was harvested from the Baidu Map during 18:30–20:30 in July 2016. We further, based on the travel time calculations, develop four baseline indicators (the weighted average, the minimum, the maximum, and the standard deviation travel time) and three tolerance indicators of park accessibility (weighted average travel time within visit tolerance thresholds, standard deviation travel time within visit tolerance thresholds, and number of parks within visit tolerance thresholds) to measure park accessibility for each community. Results show that the seven accessibility indicators generate different estimations and the quantified accessibility varies greatly with park quality levels and transport modes. Communities present greater variations in accessibility to the first quality level and second quality level parks via walking and public transit. In addition, hierarchical regression is utilized to quantify the relationships between park accessibility and sociodemographic characteristics at two geographic levels (community and district). It is found that the associations are subjected to park quality, transport modes, and geographic levels. In particular, we discover significant social inequalities in park accessibility under the mode of public transit, walking, and bicycle. Our study should provide some new insights into accessibility research and advance the understanding of unequal park provision in developing countries.     

Modelling new pricing strategies for the Santiago Metro

After twenty years of operation the Santiago Metro decided to start a new strategy of price differences by period in order to decrease congestion in the morning peak and to postpone the acquisition of new equipment. In this paper we report the results of a model specifically designed to test the impact of different price levels on patronage by period. Stated preference (SP) data was collected, focusing on three aspects: change in time of travel, price differences and comfort improvements. A goods-leisure microeconomics framework was adopted to decide on users segmentation and model specification. Two methodological aspects were explored, the non-linear marginal valuation of time displacements and the different known ways to analyse SP rating experiments. In this quest, models were calibrated both with a standard and an optimal probabilistic interpretation of the semantic scale and with the ordinal probit and binary logit models. Comparisons were made and conclusions reached about the more appropriate approach.Finally, the current time-of-day pricing strategy of the Santiago Metro, which commenced operation in February 1994, was simulated using the best models reported in the paper. This was done in order to test their validity against an observed reality.     

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.     

Give public transit a chance: A comparative analysis of competitive travel time in public transit modal share

Extensive research has found that people are more likely to choose the transport alternative which offers shorter travel time. But few studies approached the role of travel time across different transport alternatives and cities. This research assesses the influence of competitive travel time between car and public transit in public transit modal share for commute trips. São Paulo, New York, and Tokyo were selected to perform the analysis. A Fractional Logistic Regression in the binary form was drawn, and a competitive travel time index was calculated based on the Car/Public transit travel time ratio weighted by the number of the employed population at the origin and jobs at destinations in the absence of an Origin-Destination matrix. Findings suggest that, though car ownership was identified as the major factor, Car/Public transit travel time ratio is positively associated with the increase of public transit modal share. Furthermore, the Car/Public transit travel time ratio effect in public transit modal share consistently increases as people get increased access to cars.     

Measuring the long-distance accessibility of Italian cities

Long-distance accessibility is a crucial element for economic development and for territorial cohesion. To be revealing, however, a measure of accessibility must not only consider the distance or travel time of a single mode, but should include the fares, the frequency and the interchanges of all available modes.The paper aims to address whether and where there is an accessibility problem between Italian regions, through a comprehensive measure of accessibility covering the entire Italian territory. The measure used in the paper is potential accessibility, with an exponential decay impedance function. Different from similar studies, this one gives a more in-depth definition of impedance parameters due to the availability of a transport model that includes the entire Italian long-distance supply (roads, coaches, long-distance rail services, air services, and ferries). The opportunities at destination are proxied by population, and private and public sector employees.The main outputs are detailed maps of accessibility that are significantly more realistic than using simple infrastructure indicators or single-mode measures. In addition, some policy conclusions are drawn in terms of past and future investment policies.