Does Public Transport Serve Those Who Need It Most?
John P. Pritchard, Technion Israel Institute of TechnologyShow Abstract
Anna Zanchetta, Technion Israel Institute of Technology
Karel Martens, Technion - Israel Institute of Technology
In social science, evaluating the situation of disadvantaged groups is a common research theme. Here, the Target Group Performance Index (TPI) is introduced as a measure to assess the situation of a subgroup or 'target group'. It uses two distinct population-specific benchmarks to determine the relative position of a target group: a theoretical worst-case situation and a theoretical best-case situation. In contrast to other equity-related measures, it does not rely on abstract ideal outcomes or on (arbitrary) suffciency thresholds. The TPI is applied in 49 of the largest US metropolitan areas to assess the match between the residential location and the accessibility to jobs by public transport of two target groups in need of public transport: adults without a car and adults living in poverty. Results show a higher match for car-less populations than for people in poverty. Cities with a better match for the car-less also tend to perform better in regard to the poor. However, in these cities, the difference between the TPI scores for the two groups is also larger. Cities in Florida, Texas and the western USA perform poorly in contrast to Northeastern, Mid-Atlantic and Midwestern cities. Large differences in the scale of the variable of interest (accessibility by transit) and the size of the target group (car-less or poor) do not preclude the comparison of the results. Given these properties, the TPI is a suitable measure for researchers and policy-makers interested in the performance of particular target groups.
Measuring Access to Public Transit for People with Disabilities Using Detailed Sidewalk Data
Kaylyn Levine, University of Texas, AustinShow Abstract
Alex Karner, University of Texas, Austin
The pedestrian network links individuals to public transit service, but it provides varying levels of physical accessibility based on individual and environmental characteristics. The physical accessibility of a public transit stop or station—whether an individual can easily reach it—is especially relevant for people with disabilities. Understanding the mobility needs of this group and the barriers they face is essential to improving their quality of life. Yet despite the explosion of academic work on access to opportunities (also referred to as accessibility) the literature has scarcely engaged with issues related to physical accessibility, in part because of data constraints. This paper addresses this gap in the literature by performing a detailed station-level analysis of physical accessibility for people with disabilities. Multiple challenges arise and must be overcome when pedestrian networks and public transit systems are evaluated for people with disabilities. Here, we perform a network analysis in Seattle, Washington to understand public transit’s physical accessibility for people with disabilities. Sidewalk observations were included as restrictions in the network analysis to model the barriers present in the pedestrian network. The inclusion of sidewalk observation data changes physical accessibility from census block origins to public transit stop destinations and disproportionately limits the mobility of people with disabilities. The share of census blocks and people with disabilities able to reach a transit stop decrease substantially with the inclusion of sidewalk observations. These results can be used by policymakers and other decision makers to prioritize pedestrian network improvements for people with disabilities.
Assessing the Equity Implications of Localized Congestion and Emissions Impacts of Four Traffic Assignment Scenarios in the Los Angeles Basin
Jessica Lazarus, University of California, BerkeleyShow Abstract
Ahmad Bin Thaneya, University of California, Berkeley
Ioanna Kavvada, University of California, Berkeley
Jane Macfarlane, University of California, Berkeley
Bin Wang, Lawrence Berkeley National Laboratory
This study seeks to investigate the equity implications of localized impacts produced by vehicles under four simulated static traffic assignment (TA) scenarios in the Los Angeles (LA) Basin. The four different TA scenarios include a travel time-based TA and a fuel-based TA, both solved for the user equilibrium and system optimal. Negative externalities in the form of traffic congestion and population exposure to harmful air pollutants are estimated and analyzed through the lens of transportation equity and environmental justice. A detailed emission-dispersion-exposure model is developed and applied to the TA results to produce high-fidelity estimates of carbon monoxide (CO) and particulate matter (PM) intake by resident populations as a result of each TA scenario. Equity implications were explored through the relative distribution comparison method, using median census income tract to segment the population. Results show that the time-based TAs yield the lowest overall exposure impacts, and the system optimal for time generates the least amount of delay. Routing principles of the fuel-based TAs move flow away from motorways and onto local roadways usually located near more populous areas, increasing pollutant exposure. Low income groups are disadvantaged by the TA flow allocation to some degree in terms of trip delay, and to a higher degree relative to pollutant exposure for all TA scenarios.
Connecting People with Jobs: Light Rail’s Impact on Commuting Patterns
Maryam Khabazi, University of North Carolina, Chapel HillShow Abstract
Isabelle Nilsson, University of North Carolina, Chapel Hill
This paper examines the impact of light rail on commuting patterns in adjacent neighborhoods in a case study on Charlotte, North Carolina. The results show a reduction in the commuting distance experienced by higher-wage workers, while it is increased for lower-wage workers post opening of the city’s first light rail line. These results are expected as the light rail connects higher-wage neighborhoods to areas with significant shares of higher-wage jobs. Hence low- and medium-wage workers in light rail accessible neighborhoods have not seen a significant change in the spatial separation between their work place and place of residence after the opening of the light rail, which may conflict with goals of increasing accessibility for the most transit dependent population.
Innovation on Job Accessibility and Transit Scenario Planning with General Transit Feed Specification Data
Madison Swayne, University of Southern CaliforniaShow Abstract View Presentation
Marlon Boarnet, University of Southern California
Gary Painter, University of Southern California
This paper investigates job access in Los Angeles County, California via public transportation. We rely on the automated Remix access tool (aRat) developed by Swayne and Kundaliya (2019) to measure accessibility based on travel time, via transit, to jobs, across different transit network scenarios. Relying on open-source General Transit Feed Specification (GTFS) data we model the transit network in Remix, an online transit planning program. After modeling the network, we augment the existing transit system with planned improvements to the network and rely on aRat to measure the number of jobs accessible from the centroid of each of the county’s 2,345 census tracts within a 30- and 60-minute commute time in each of the transit network scenarios. The result is a method that leverages GTFS data and aRat to allow us to estimate how tract-level job access might change with improvements to transit infrastructure. We measure transit job access change across three different transit improvements: Expo Phase II, LAX/Green Line Extension, and the Vermont Bus Rapid Transit (BRT) Corridor. We illustrate that job access measures can go beyond the common “static” measures of access over existing networks and be used to evaluate different transit investment scenarios.
Whose Buses Run on Time?: The Social Equity of Bus On-Time Performance in Canada’s Largest City
Matthew Palm, University of TorontoShow Abstract
Amer Shalaby, University of Toronto
Steven Farber, University of Toronto
Bus routes provide critical lifelines to disadvantaged travelers in major cities. Bus route service performance is also more variable than the performance of other, grade-separated transit modes. Yet the social equity of bus operational performance is largely unexamined outside of limited statutory applications. Equity assessment methods for transit operations are similarly underdeveloped relative to equity analysis methods deployed in transit planning. This study examines the equity of bus on-time performance in Toronto, Ontario, the largest city in Canada. We deploy both census proximity and ridership profile approaches to defining minority serving routes, modifying USDOT Title VI methods to fit a Canadian context. We find bus on-time performance in Toronto is horizontally equitable. We also find that the USDOT approach of averaging performance between minority and non-minority routes masks the existence of under-performing routes with high minority ridership. These routes are overwhelmingly night routes, most of which are only classified as minority serving using a ridership definition. These results suggest that the under-performance of Toronto’s “Blue Night” network of overnight buses is a social equity issue. We also apply our on-time performance data to a household travel survey to identify disparities in the on-time performance of bus transit as experienced by different demographic groups throughout the city. We find that recent immigrants and carless households, both heavily transit dependent populations in the Canadian context, experience lower on-time bus performance than other groups.
Measuring Accessibility and the Sustainable Development Goal Transport Target: A Case Study of Nairobi’s Matatus
Travis Fried, Word Resources InstituteShow Abstract View Presentation
Thet Hein Tun, World Resources Insitute
Jacqueline Klopp, Columbia University
Benjamin Welle, World Resources Institute
The urban Sustainable Development Goal (SDG) includes the target to provide “access to safe, affordable, accessible and sustainable transport systems for all” by 2030. However, debate exists around the best indicator to measure this target, and few actual measurements exist. This is in part because basic transit data is missing from many of the world’s cities including in Africa where popular or “informal” systems dominate. This paper explores how to make progress in measuring indicators for the SDG transport target using Nairobi’s minibus system, or matatus, as a case study. We apply the city’s SDG indicator as currently defined by the UN and show that although the analysis suggests generally favorable transit coverage, it also points to underlying transport inequalities for low-income residents. We then conduct a location-based accessibility analysis, incorporating income data as well as Nairobi’s highly monocentric spatial urban form, which reveals rapidly decreasing accessibility to opportunities as distance from city’s CBD increases. Accessibility-based analysis further highlights income-based transport inequalities, identifying opportunities for improving integrated transport for residents living on the city’s near- and far peripheries. Improving non-motorized transport (NMT) access for those living in low-income areas with high access potential would also be important to improve access. We recommend that cities start using open-sourced software and open data to measure a variety of indicators needed for data-driven policy, both to meet SDG 11.2 and go further to improve access to opportunities for all residents.
Transit Deserts: A Spatial-Temporal Analysis of Equity and Accessibility
Javad Jomehpour Chahar Aman, Southern Methodist UniversityShow Abstract
Janille Smith-Colin, Southern Methodist University
Areas where the disadvantaged and transit-dependent are provided with inadequate amounts of transit supply can be labeled transit deserts. Exploring transit deserts may help transit agencies improve accessibility to service while improving distribution and equity. This study utilizes the concepts of transit demand and transit supply to identify transit deserts in the City of Dallas. The comprehensive public transit accessibility (CPTA) index is introduced to evaluate accessibility to transit and to provide a holistic view of transit supply. While previous studies have only used proximity or spatial indicators to describe accessibility, this study utilizes a comprehensive set of spatial and temporal measures (connectivity to the network, connectivity to destinations, reliability, flexibility and time efficiency) to estimate accessibility to transit. Overlapping areas of high demand (transit dependency) and low supply (as measured using the CPTA) are then characterized as transit deserts. An equity analysis, using the Lorenz curve and Gini index, is then used to further capture inequities that exist within the transit desert areas. The CPTA Index and its application to the analysis of transit deserts provides a universal framework which can be broadly applied by transit agencies, city officials, and transit stakeholders. The contributions of this study are as follows: first, developing a comprehensive spatio-temporal framework to estimate transit supply or accessibility; second, developing a comprehensive methodology for identifying transit deserts; and third demonstrating how equity analysis can further reveal services that are insufficiently distributed to meet the needs of users.
Public Policy Enabled by Mobility-as-a-Service
Christina Ditmore, University of Alaska, AnchorageShow Abstract
Mobility as a Service (MaaS) is the concept through which travel whether by public or private transport is planned, booked, and paid for on a single platform through either a service or subscription-based model. MaaS provides a unique opportunity to the public sector to achieve public policy goals by leveraging emerging technologies in favor of the public good. Common policy goals that relate to transportation include equity considerations, environmental impact, congestion mitigation, etc. Strategies to address these policy goals include behavioral incentivization and infrastructure reallocation to name a few. An additional goal that could be included within a MaaS strategic plan is enhancing health related outcomes. This study begins with a review of the current state of MaaS considering potential policy drivers and provides examples of policy objectives that could guide a MaaS solution. It moves on to demonstrate several methods for measuring a specific type of policy objective to better inform the reader on how to measure an identified policy goal. The Methods section reviews a single study in greater detail to demonstrate how to develop a measurement approach to a data point, in this case, stress, within the definition phase of developing a policy goal for MaaS. The Discussion section reviews implications of this practice within the industry and concludes with suggestions for future studies to improve upon the existing body of work. This study focuses on MaaS as a policy enabler to improve health outcomes as related to the link between stress and commuting.