Public Transit Modes Research Articles

Transfer learning-based nonstationary traffic flow prediction using AdaRNN and DCORAL

Traffic flow prediction is an integral part of an intelligent transportation system (ITS) for proactive transportation planning and management in public transit network systems. However, due to the influence of passengers’ travel modes and the difficulty of data collection, some traffic flow datasets are not only nonstationary in temporal distribution but also insufficient in data size, leading to inaccurate prediction results. Therefore, a transfer learning-based method is proposed to predict nonstationary traffic flow with inadequate data in the public transit system. In the proposed model, a novel approach named AdaRNN-DCORAL is presented to achieve accurate traffic flow prediction in the temporal dimension. Specifically, AdaRNN is an adaptive prediction network for nonstationary traffic flow data, while DCORAL performs domain adaptation between the source and target domain in the public transit system. First, two domains of traffic flow datasets in two public transit modes are established, which are the target domain with insufficient data and the source domain with sufficient data. Subsequently, the traffic flow datasets are divided into weekday and holiday time series based on their distribution characteristics. On this basis, AdaRNN-DCORAL is trained on the constructed datasets, thus achieving the precise nonstationary prediction of data scarcity in the target domain. Finally, the experiments demonstrate the improved performance of the proposed method over that of state-of-the-art models in terms of prediction accuracy and computation time.

Spatial accessibility and equity of community healthcare: unraveling the impact of varying time and transport mode.

Achieving a higher level of accessibility and equity to community healthcare services has become a major concern for health service delivery from the perspectives of health planners and policy makers in China. In this study, we introduced a comprehensive door-to-door (D2D) model, integrating it with the open OD API results for precise computation of accessibility to community hospitals over different transport modes. For the D2D public transit mode, we computed the temporal variation and standard deviation of accessibility at different times of the day. Additionally, accessibility values for D2D riding mode, D2D driving mode, and simple driving mode were also computed for comparison. Moreover, we introduced Lorenz curve and Gini index to assess the differences in equity of community healthcare across different times and transport modes. The D2D public transit mode exhibits noticeable fluctuations in accessibility and equity based on the time of day. Accessibility and equity were notably influenced by traffic flow between 8 AM and 11 AM, while during the period from 12 PM to 10 PM, the open hours of community hospitals became a more significant determinant in Nanjing. The moments with the most equitable and inequitable overall spatial layouts were 10 AM and 10 PM, respectively. Among the four transport modes, the traditional simple driving mode exhibited the smallest equity index, with a Gini value of only 0.243. In contrast, the D2D riding mode, while widely preferred for accessing community healthcare services, had the highest Gini value, reaching 0.472. The proposed method combined the D2D model with the open OD API results is effective for accessibility computation of real transport modes. Spatial accessibility and equity of community healthcare experience significant fluctuations influenced by time variations. The transportation mode is also a significant factor affecting accessibility and equity level. These results are helpful to both planners and scholars that aim to build comprehensive spatial accessibility and equity models and optimize the location of public service facilities from the perspective of different temporal scales and a multi-mode transport system.

How Does the Introduction of Shared Ride-Sourcing Services Affect Demand for Existing Modes for Non-Commuting Trips? Evidence from a Joint RP-SP Study in Metro Vancouver

The introduction and subsequent growth of ride-sourcing services have been found to affect the use of existing modes of travel. Although prior studies have explored the impacts of these services as a whole, relatively little work has been done to explore the relationship between shared ride-sourcing and existing modes of travel. Given the potential for shared ride-sourcing to help mitigate the negative externalities associated with ride-sourcing, understanding the factors influencing the use of these services and their relationship with existing modes can inform efforts to help ensure that this potential is realized. This study uses data from a web-based survey of Metro Vancouver residents to estimate a joint revealed preference–stated preference (RP–SP) model of mode choices for non-commuting trips. The model is then applied to explore the potential impacts of shared ride-sourcing on the demand for existing modes. To the authors’ knowledge, this is the first study to use a joint RP–SP model to explore the potential impacts of shared ride-sourcing on the demand for existing modes. The results suggest these services can affect the demand for exclusive ride-sourcing and attract demand from more sustainable modes such as public transit and active modes. This information can be used to help inform policies that help ensure that the benefits of shared ride-sourcing are realized. Shared ride-sourcing use can be encouraged by increasing the difference between the cost of exclusive and shared services; however, limiting the impacts of these services on the demand for more sustainable modes is also important.

Offline planning and online operation of zonal-based flexible transit service under demand uncertainties and dynamic cancellations

This paper introduces a comprehensive framework for planning and operating a zonal-based flexible transit (FT) service, a public transit mode designed to accommodate uncertain demand patterns. The framework addresses both offline planning based on stochastic demand distributions and cancellations, as well as online routing considering real-time orders and cancellation behaviour. Offline interzonal route planning is formulated as a two-stage recourse problem, while the intrazonal routing problem is modelled using a Markov decision process (MDP) that incorporates online information. To solve the problem, a service reliability-based decomposition method is employed to divide the problem into three mixed-integer subproblems. The first subproblem focuses on designing interzonal routes up to a specific demand level, taking into account a designated cancellation probability as determined by reliability measures. An insertion heuristic is developed for this subproblem to improve the solution efficiency. The second subproblem allocates passengers from certain categories to vehicles based on the passenger volume designated by reliability measures. Lastly, the third subproblem refines the vehicle intrazonal route according to the passenger assignment from the previous subproblem. The reliability measures are optimised iteratively until no further improvements are observed in consecutive iterations. The proposed FT service’s performance is evaluated using numerical simulations based on real New York City (NYC) taxi demand data, illustrating the effectiveness of the integrated planning and operational approach in accommodating uncertainties in on-demand transit systems.

Unveiling the Influential Factors of Commuters for Public Transit Mode Selection

Unveiling the Influential Factors of Commuters for Public Transit Mode Selection

Exploring the changes in the interrelation between public transit mode share and accessibility across income groups in major Canadian cities in the post-pandemic era

The COVID-19 pandemic has impacted the travel behaviour of urban residents in an unprecedented manner, especially public transit (PT) users. PT has experienced a decline in ridership around the world early in the pandemic and has been struggling to rebound again to the pre-pandemic levels, whereas other modes have reached their pre-pandemic levels. PT agencies have been trying to attract users back through service improvements and other policies; nevertheless, the impacts of policies that were effective prior to the pandemic are not guaranteed in the post-pandemic world due to the lasting effects of the pandemic on travel behaviour. This study compares the changes in the impacts of accessibility, the ease of reaching destinations, to jobs by PT on commute mode share pre- and post-pandemic (2016 and 2021) with an equity lens in the three largest metropolitan regions in Canada: Toronto, Montreal, and Vancouver. Results show that planning for accessibility is still an impactful tool to increase PT mode share in the post-pandemic era, yet the magnitude of the impact has declined by almost 50% in Toronto and Montreal and 30% in Vancouver for low-income groups. In the post-pandemic era, the impact of accessibility on PT mode share remains higher for the low-income compared to other-income groups, which is similar to the pre-pandemic times. Understanding the changing effects of accessibility, a major land use and transport planning tool, on travel behaviour is important as PT agencies are developing strategies to restore pre-pandemic levels of ridership and increase it to reach their sustainability goals.

On Accessibility Fairness in Intermodal Autonomous Mobility-on-Demand Systems

Research on the operation of mobility systems so far has mostly focused on minimizing cost-centered metrics such as average travel time, distance driven, and operational costs. Whilst capturing economic indicators, such metrics do not account for transportation justice aspects. In this paper, we present an optimization model to plan the operation of Intermodal Autonomous Mobility-on-Demand (I-AMoD) systems, where self-driving vehicles provide on-demand mobility jointly with public transit and active modes, with the goal to minimize the accessibility unfairness experienced by the population. Specifically, we first leverage a previously developed network flow model to compute the I-AMoD system operation in a minimum-time manner. Second, we formally define accessibility unfairness, and use it to frame the minimum-accessibility-unfairness problem and cast it as a linear program. We showcase our framework for a real-world case-study in the city of Eindhoven, NL. Our results show that it is possible to reach an operation that is on average fully fair at the cost of a slight travel time increase compared to a minimum-travel-time solution. Thereby we observe that the accessibility fairness of individual paths is, on average, worse than the average values obtained from flows, setting the stage for a discussion on the definition of accessibility fairness itself.

Mode choice analysis of first-mile shared autonomous vehicles service in Bangkok, Thailand

Shared autonomous vehicles (SAVs) are a promising first-mile mode to access public transportation. This study focuses on the mode choice analysis assuming that SAVs are introduced in Bangkok, Thailand. Stated preference experiments based on efficient design were conducted. The rescaled logit model was obtained from the nested logit trick on the combined revealed-preference and stated-preference data. The results showed that with the introduction of SAVs, the shares of existing taxi, motorcycle taxi (MC), and light public transit (LPT) modes will decrease by approximately 28.24%, 27.50% and 21.93%, respectively. These indicate that people who are accustomed to using taxi and MC as their first-mile services are respectively most likely and second-most likely to change their choices to SAVs. The values of times for income groups were estimated. Service providers should consider reducing travel cost to attract more lower-income users, and reducing travel time to attract more higher-income users. The average elasticities and simulation results imply that the improvement of the travel cost of SAVs should be a priority over travel time in order to effectively attract more individuals to the SAVs mode, and the improvement of travel time of SAVs leads to the greatest shift from taxi and MC.

Promoting service quality with incentive contracts in rural bus integrated passenger-freight service

A rural bus integrating passenger and freight transport is a new effective public transit mode to realise village interconnection and solve the first–last mile rural logistics service. Mixed services reduce logistics costs and generate additional income for transit operators. However, the mutual interpenetration of logistics and passenger services in a single bus trip may lead to a decline in the service quality of both passengers and goods. With this in mind, we designed a government subsidy incentive contract and a logistics alliance payment incentive contract respectively from the perspective of participants based on the principal-agent theory. In addition, a bi-level programming model consisting of two principals (government and logistics alliance) and one agent (transit operator) was proposed to incentivise bus operators and improve passenger and freight service quality. It scientifically realises the coordination of interests between the principals and agents. A Chinese case study was conducted to examine the proposed models and methods, and a passenger-based incentive subsidy programme from the government was proposed to replace the mileage-based one. With both incentive policies (government and logistics alliance), passenger travel time can be reduced by 4.2 min, and logistics transportation time can be shortened by 30 min. In addition, the total annual government budget can be reduced by 17.2% (¥450,000, $64,000) and annual fleet mileage savings by approximately 9.4% (62,000 km) compared with the mileage-based incentive programme in the case study. A sensitivity analysis is conducted to explore the impact on the collaborative system. This innovative concept, combined with incentive schemes, is a good reference for public administration to avoid the dilemma of having passenger and freight transport in low-demand areas.

Interconnectedness enhances network resilience of multimodal public transportation systems for Safe-to-Fail urban mobility

The growing interconnectedness of urban infrastructure networks presents challenges to their ability to handle unforeseen disruptions, particularly in the context of extreme weather events resulting from climate change. Understanding the resilience of interconnected infrastructure systems is imperative to effectively manage such disruptions. This study investigates the role of interconnectedness in enhancing the resilience of public transportation systems in Hong Kong, a city heavily reliant on public transit. Our results demonstrate that interconnected transportation systems improve resilience by reducing topological vulnerabilities, increasing attack tolerance, and enhancing post-disruption interoperability. Findings also identify the potential to integrate vulnerable systems for greater robustness and highlight the marginal benefits of enhancing intermodal transfer. Strengthening interconnectedness among modes of urban public transit fosters a safe-to-fail system, presenting a distinct resilience-by-design approach. This complements conventional resilience-by-intervention approaches that focus on improving individual systems or introducing entirely new systems.

Assessment of Satisfaction Level for Existing Public Transport Systems using Machine Learning: A Case of Bhopal (India)

Most people are now highly dependent on private motorize travel because of the low Satisfaction level of public transit modes. This leads to poor public transit share in most of the cities in India. This study is intended to identifying the influencing parameters; those affect the satisfaction level of a PT mode, and also develop a model for assessing the Satisfaction Level of these public transport modes in Bhopal, India. A Machine Learning-based approach is used to analyze 1189 responses from the user. It classifies data in various dimensions that shape customers satisfaction among each mode of public transport (i.e. BRTS, Mini-Buses and Magic-Van service) and develops a model for evaluating the overall satisfaction of these PT modes in Bhopal. An On-board opinion surveys were done for identifying the parameters which influence the Satisfaction of these PT modes and also develop a model for evaluating the Satisfaction of these modes. Based on the literature, Delphi survey and opinion survey, eight parameters have been identified that influence the satisfaction level of these modes in Bhopal. Further by correlation matrix, most influencing parameters (key parameters) were considered amongst them for evaluating the satisfaction level for these modes. To determine the coefficient values acting from each of the respective elementary scores, we used a trained linear regression, multilinear regression, considering the classification of customers who assessed the performance of their satisfaction. This model will help to increase the Satisfaction of these PT Modes which result to increase the transit ridership in Bhopal. Adopted methodology in this study can help decision-makers to improve public transport services so that transit ridership can be improved.

Patterns and predictors of public dental service utilisation among refugees in Victoria, Australia: a latent profile and multilevel analysis

BackgroundThe purpose of the study was to explore, analyse, and describe the patterns of public dental service utilisation among the refugee populations in Victoria, Australia, and determine their predictors at the individual and contextual levels.MethodsData on the refugees who attended Victorian public dental services between July 2016 to June 2020 was gathered from the Dental Health Program dataset. Latent profile analysis was used to identify discrete groups among the refugee clientele with similar mean utilisation patterns across six indicator variables describing the attributes of dental services received and the site of care provision, over the study period. Multilevel multinomial logistic regression analysis was performed to examine the individual and contextual level correlates of the identified utilisation patterns.ResultsSix distinct profiles of public dental service utilisation were identified among the study population (n = 25,542). The largest group comprised refugees predominantly using restorative services under general course of care (38.10%), followed by extraction services under emergency course of care (23.50%). Only a small proportion were estimated as having a higher mean utilisation of preventive services under general course of care (9.10%). Multilevel analysis revealed that the following variables had a significant association with refugee utilisation pattern: at the individual-level – demographic and ethnic attributes including age, gender, region of birth, preferred language for communication, use of language interpreter services, and type of eligibility card; at the contextual-level – characteristics of refugees’ neighbourhood of residence including urbanicity, socioeconomic disadvantage, delivery of Refugee Health Program at the community health centres, and spatial accessibility to public dental services via driving and public transit modes of travel.ConclusionsThe study represents a significant step towards the development of an evidence-based knowledge around public dental service utilisation among Victorian refugees. Overall, the study findings reiterate the critical need for targeted strategies to promote the importance of routine dental visits, oral disease prevention, and timely intervention among refugee groups.

Transportation Justice in Vermont Communities of High Environmental Risk

Transportation justice studies have largely focused on metropolitan areas, and the transportation disparities in rural areas and their most disadvantaged population are not well understood. Our study explored transportation injustices in high environmental risk communities in Vermont. We found that low-income communities and people of color disproportionately face inequitable access to transportation services: they are more likely to be concerned about lack of transportation, more likely to not own or lease a personal vehicle and rely more heavily on public transportation. Our study also found that those without a personal vehicle and those largely dependent on public transportation have less access to healthy food, are likely to go hungry, have greater reports of asthma, and have less access to primary care physicians and jobs. The transportation policies in the state are also procedurally unjust. These disadvantages, combined with higher exposures to environmental risks, also pose implications for public health and well-being. A combined transition toward sustainable mobility and transportation justice should prioritize greater equity in the distribution of transportation investment in infrastructure and services; recognition of historical patterns that inform current uneven and unequal mobilities; procedural and democratic engagement of the marginalized in transportation design, planning and policy-making; a capabilities approach to plan transportation systems that improve opportunities, wellness, and quality of life for the most disadvantaged population. Consideration should also be given to designing a sustainable transportation transition that prioritizes attention for all modes of transport accessibility and mobility, including non-motorized and public transit modes, in planning and policies so that streets are not dominated by a single mode of transportation, such as cars.

Identifying the Determinants of Anticipated Post-Pandemic Mode Choices in the Greater Toronto Area: A Stated Preference Study.

The COVID-19 pandemic had a significant impact on travel mode choices in cities across the world. Driven by perceptions of risk and the fear of infection, the pandemic resulted in an increased preference for private vehicles and active modes and a reduced preference for public transit and ride-sourcing. As travel behavior and modal preferences evolve, a key question is whether the pandemic will result in long-term changes to travel mode choices. This study uses data from a web-based survey to examine the factors influencing mode choices for non-commuting trips in the post-pandemic era. Specifically, it uses stated preference data to develop a random parameter mixed logit model, which is used to compare the elasticity of key variables across different income and age groups. The results of the study highlight the influence of sociodemographic attributes and pre-pandemic travel habits on anticipated post-pandemic mode choices. Additionally, the results suggest that frequent users of private vehicles, public transit, and active modes are likely to continue to use these modes post-pandemic. Furthermore, the results highlight the potential for the perception of shared modes to influence post-pandemic mode choice decisions. The results of the study offer insights into policy measures that could be applied to address the increased use of private vehicles and reduced use of transit during the pandemic, while also emphasizing the need to ensure that certain segments of the population can maintain a sufficient level of mobility and access to transport.

Non-Linear Associations Between the Urban Built Environment and Commuting Modal Split: A Random Forest Approach and SHAP Evaluation

The study of commuting mode choice is crucial since driving, with all its associated environmental and economic consequences, is the United States’ most popular mode of transportation due to urban sprawl, priority to road construction and America’s love affair with the automobile. More attention needs to be paid to sustainable modes such as public transit and walking. The built environment is expected to have an impact on commuting mode choice. Built environments with higher density, diversity, intentional design, destination accessibility, and shorter distance to transit (collectively known as the 5 Ds of the built environment) are hypothesized to lead to more sustainable mode choices, including public transit and walking. In this paper, we evaluate the impact of built environment variables on commuting modal split, including the four modes of public transit-bus, public transit-rail, walking, and driving. The study is conducted in Mecklenburg County, North Carolina, at the geographic level of census block groups in year 2015. Given the complexity of relationships in the built environment-travel behavior subject, the random forest method is used to predict aggregated commuting mode choice. Random forest is employed as it is capable of capturing nonlinear relationships and is not constrained by limitations in other widely used methods, such as multinomial logistic regression. After predicting the commuting mode shares, SHAP values (SHapley Additive exPlanations) are used to evaluate the impact of the built environment on commuting mode choices. As an advanced machine learning method, SHAP values adds explainability to the model. This method resolves the known limitation of machine learning methods as being “black boxes” and converts them to “white boxes” by providing interpretability. They provide insights into both the direction and magnitude of the relationships. Thanks to its rigorous ML-based design, our study helps to solidify the state of knowledge with strong evidence that block groups with higher degrees of the 5Ds lead to more choices of public transit and walking modes. We discuss urban policy implications of this study.

Design and Development of a User-Centered Mobile Application for Intermodal Public Transit in Bangkok: A Design Thinking Approach

With the constant increase in public transit coverage in Bangkok Metropolitan Area in Thailand, many people are still hesitant to switch from using private to public transit, with one potential cause being the unavailability and difficulty in accessing accurate and timely information about their itineraries, while they are commuting. To assess and tackle such issues, the researchers adopted the user-centric Design Thinking methodology to empathize with target users' pain points in this study. They proposed a solution in a user-centric manner by assessing the usability flaws of existing mobile navigation applications, such as Google Maps and ViaBus. By developing a holistic mobile application called 'Disgovery' that covers all modes of public transit in the Bangkok Metropolitan Area and provides relevant information about their trips, the researchers aim to help commuters in Bangkok easily access it in a timely fashion. Through the user-friendly interface, commuters can eliminate the difficulty of finding routes and prices suitable to their needs. By making public transit more accessible with the help of ubiquitous mobile computing, commuters are also encouraged to switch from using private vehicles to public transit, which also can reduce accidents and carbon emissions. The findings from the usability testing in this study suggest that 'Disgovery' is an effective and user-friendly application for daily commuters in Bangkok that can help them achieve their goals without difficulties. The findings also indicate the importance of user interface and user experience guidelines in designing such applications.

Investigation of modal integration of bike-sharing and public transit in Seoul for the holders of 365-day passes

Bike-sharing has a mixed relationship with public transit—characterized by modal integration and modal substitution—and affects the public transit ridership. In previous studies, to investigate the relationships between public transit and bike-sharing, analyses based on either surveys or analysis based on trip record data have been conducted; thus, there have been several limitations to obtaining accurate and large data to reveal the relationships between public transit and bike-sharing. Unlike previous studies, owing to the mileage program of Seoul Bike, this study investigates the modal integration of bike-sharing and public transit using only trip records of bike-sharing integrated with public transit for the holders of 365-day Seoul Bike passes in detail using explanatory data and regression analyses. Additionally, considering that the relationship between bike-sharing and public transit might vary according to the mode of public transportation, this study investigates the spatio-temporal patterns of modal integration between bike-sharing and public transit, and the factors that influence the modal integration at the station level using binomial regression. The results indicate that the effects of various factors on the modal integration depend on the distance to the nearest subway station and the time when the trip occurs (weekdays or weekends and certain periods during the day). This study also suggests that the relationship between bike-sharing and public transit may vary according to the public transit mode. Although shared bikes seemed to be used in conjunction with both the subway and bus, the proportion of modal integration between bike-sharing and public transit among all trips using 365-day passes is likely to be affected more by the subway system than the bus system, especially for regular commutes. Furthermore, it is observed that shared bikes can be used to avoid overcrowded buses in connection with subways.

The Modern Streetcar in the U.S.: An Examination of Its Ridership, Performance, and Function as a Public Transportation Mode

Seven U.S. cities reported operating streetcar service to the National Transit Database in 2012, and many other cities are building or planning streetcar investments. Yet despite the increased popularity of streetcar investments, there is a lack of information about how these investments function as transportation modes, as opposed to urban development tools. This paper examines the streetcar as a public transit mode by examining ridership, service, service productivity, cost effectiveness, and other indicators of the streetcar’s performance and function in the carriage of transit passengers. There is considerable variation in all of these measures, with the variability a function of the different environments in which streetcars operate, the different roles they play in the local transit system, and differences in the operating characteristics of the streetcars themselves. Among the cases, Portland’s streetcar emerges as a strong performer, Little Rock’s and Tampa’s streetcars as relatively poor performers, and the other streetcars have mixed performance results.

Bus Rapid Transit: A Viable Alternative?

Bus Rapid Transit (BRT) presents a significant opportunity for the public transit industry to enhance the set of transportation investment options that can be brought to bear on the mobility problems experienced by urban areas across the country. As new Census data are released, the picture of strong population growth in dispersed patterns, growing congestion levels, and stubbornly modest transit use levels emerges. This paints a compelling picture that merits serious consideration by transportation planners with regard to the full range of transportation investment options available for urban areas.This article addresses several specific characteristics of BRT that differentiate it from other public transit modes and supports the explicit consideration of BRT as an alternative in Major Investment Studies (MIS). Clearly, the high cost of rail transit limits the possible role it can play in urban mobility even under radical changes in modal spending priorities. The pursuit of more moderate costing infrastructure transit options increases the chances of public transit being able to make more meaningful contributions to urban mobility. A key characteristic of BRT is the prospect that it can offer a lower-cost method of providing better performing public transit service (not yet fully verified) that is able to both retain current and attract new customers as well as garner political and taxpayer support. Evidence provided by the Government Accounting Office (GAO) in its recent report on BRT indicated that the BRTprojects reviewed cost less to build than the light rail transit (LRT) projects reviewed, on a per-mile basis. In addition, the GAO also points out that ridership was comparable between the BRT and LRT systems reviewed and that five of the six BRT projects had higher overall system operating speeds than the LRT projects.This article also addresses the definition of BRT and the implications of the various definitions on branding of the mode. An interesting perspective on the BRT branding is offered by looking at it from the perspective of various user groups. In addition, the article explores the prospects of BRT becoming attractive to the public transit industry and with customers, decision-makers, and taxpayers. It continues by addressing certain aspects of BRT that differentiate it from LRT and the comparative impacts on land use by BRT and LRT. The article concludes by offering thoughts regarding the opportunities presented by BRT concept.

Disparities in spatial accessibility to public dental services relative to estimated need for oral health care among refugee populations in Victoria.

To examine the spatial accessibility to public dental services (PDS) relative to the estimated oral health needs of refugee populations within the state of Victoria, Australia. The study employed enhanced two-step floating catchment area method to measure spatial accessibility to PDS by driving and public transit modes at statistical area level 2 (SA2). Principal component analysis of select census-derived socioeconomic variables specific to the refugee population was conducted to derive an area-based indicator of refugee oral health needs, also at SA2 level. Individual indices were then developed for each of these components using standardized z-scores. Finally, an integrated need-accessibility index was developed to identify low-accessibility areas associated with high needs. The results show clear contrast in spatial accessibility to PDS for the refugee populations between metropolitan and rural areas as well as between driving and public transit modes. There are critical limitations in accessibility for refugees living in the rural areas and those dependent on public transit mode for travel. Also, there is evident disparity between the estimated oral health needs of refugees in metropolitan and rural areas. Overall, approximately 29% of all SA2s with refugee population are in the 'High' needs category, which comprise 19.8% of the total Victorian refugee population. Integrating accessibility and oral health needs measures revealed that about 30% and 18% of refugee population are identified as under-serviced, when considering driving and public transit modes respectively. The findings provide implications for researchers and policy makers to address the inequalities in access to PDS among the refugee population in Victoria. The methodology outlined in this study provides a complementary approach in planning oral health service provision in the absence of population level data at a small-area scale on access to dental services or need for oral health care.