Transit Service Coverage Research Articles

Will gated community affect public transit service coverage?

The proliferation of gated communities (GC) has prompted researchers worldwide to investigate its causes and consequences. The phenomenon has been extensively discussed as a significant residential form in the world, but most of the studies are primarily concerned with non-technical issues such as inequality and segregation, while technical issues such as urban transit (PT) systems have not been fully discussed. The significance of accessibility-focused PT planning to establish a sustainable urban transportation system makes this issue a crucial topic to explore. PT is a public good expected to be accessible to everyone, and this means the distance between people and the system needs to be minimized to maximize the service coverage, but the GC design is observed to be increasing the distance of its residents willing to use this service. Therefore, this study analyzed the impact of GC on the PT system using Bogor Municipality as a case study through GIS (Geographical Information System) methodologies and spatial data. The quantitative evidence showed that GC has a relatively strong negative correlation with PT service coverage (r (66) = from -0.611 to -0.631, p <.001). This means PT service coverage tends to be low in areas with a high GC ratio and vice versa. It was also discovered that an increase in GC ratio is likely to cause a reduction in PT service coverage in the study area (Beta = -0.48, t(67) = -5.17, p =.000). This article concludes with a discussion of a few potential ideas based on the observations to alleviate the negative impact of GC.

Developing a Method for Assessing National Demand-Response Transit Level of Service

Demand-response transit service is a major source of mobility for older adults and people with disabilities in both urban and rural areas in United States. Federal Transit Administration (FTA) grant programs under sections 5307, 5310, and 5311 all have components designed to increase the availability of paratransit or demand-response transit service. However, there is little information in the National Transit Database (NTD) or elsewhere about the extent of demand-response transit service coverage across the country. The lack of data makes it a challenge to identify gaps in service and unmet needs. The primary objective of this study was to fill the data gaps to the available NTD database to effectively determine the demand-response transit level of service. This study also developed a priority ranking procedure to identify where the greatest needs for service improvements exist in a state.

TTSAT: A New Approach to Mapping Transit Accessibility

Transit agencies have never had an accurate indicator of the extent of their service area based on riders’ door-to-door travel time. This is an important gap in knowledge, because travel time is one of the most important factors determining whether or not people will use public transit. This paper presents a powerful new travel time-based method to visualize and analyze transit service coverage—a computer application called the Time-Based Transit Service Area Tool (TTSAT). Unlike other service area metrics, TTSAT incorporates total trip travel time into the transit service area maps it generates. To make these travel-time estimates realistic, TTSAT integrates all segments of a complete, door-to-door transit trip into the trip time calculations. TTSAT’s mapping and analysis capabilities offer numerous potential applications for planners, developers, and members of the public working to create transit-accessible communities.

Asymmetric Gasoline Price Effects on Public Transit Ridership: Evidence from U.S. Cities

Using a nonlinear autoregressive distributive lag framework, the paper examines the dynamic effects of gasoline price, gasoline price volatility, income, and transit service coverage and frequency on public transit ridership in six U.S. cities (New York City, Chicago, Los Angeles, Boston, San Francisco, and Cleveland). The results indicate that, in the long run, rising gasoline prices increase transit ridership in all cities. More importantly, transit riders react differently, depending on the direction of gasoline price movements. The variable corresponding to price increases is found to have a larger elasticity than that for price decreases in five out of six cases, supporting gasoline price asymmetry. In Chicago, Los Angeles, Boston, and Cleveland, a small but statistically significant long-run effect of gasoline price volatility on transit ridership was found, suggesting that gasoline price uncertainty is an important factor affecting transit ridership in these cities. In the short run, transit service coverage is found to be the key determinant of transit ridership, implying that expanding transit service coverage can boost public transit ridership in the short term.

Integrating shared mobility services with public transit in areas of low demand

The increasing demand for shared mobility services has led to multiple Public-Private Partnerships (PPP), where public transit agencies and mobility providers work together to increase transit service coverage. However, several partnerships have failed due to budget constraints and lack of ridership. Furthermore, the limited data-sharing agreements restrict the analysis and dissemination of outcomes. This paper analyzes the integration of shared-mobility services into the public transit system using data from pilot programs in Austin, Texas. The use of Transportation Network Companies (TNCs) and microtransit service is evaluated as first-mile-last-mile (FMLM) and door-to-door solutions. The associated TNC, microtransit, and bus transit demand are analyzed using ridership data, and the trip characteristics are discussed and compared. Then, after controlling for confounding variables through matching, a difference-in-differences (DID) model is used to infer the effect of microtransit on bus transit demand. Specifically, by evaluating bus ridership before and after implementing the microtransit program, the DID model estimates the change in bus demand attributed to microtransit. The results suggest that the TNC services, focusing only on FMLM, were not as popular as microtransit services offering FMLM and intrazonal trips. Even though the microtransit trips were longer and, in some cases, the driver response times were higher than for TNC trips. Also, the DID model demonstrates that the microtransit service did not substantially impact the bus transit ridership, suggesting that the trips were mainly used for intrazonal door-to-door trips and not for FMLM trips. A further discussion highlights the need for performance metrics beyond demand and costs to capture the benefits of these partnerships for improving mobility, safety, and customer experience.

Investigation of Performance Indicator for Public Transit Connectivity in Multi-Modal Transportation Network of NCT Delhi

Centrality plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of centrality is well documented in social network literature and to some extent, transportation engineering literature. However, centrality measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks. In my study area, we propose measures to determine Network centrality from a QGIS SOFTWARE which is based on graph theoretic approach for all levels of transit service coverage integrating routes, schedules, socioeconomic, demographic and spatial activity patterns. The objective of using Network centrality as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.

Incorporating Low-Stress Bicycling Connectivity into Expanded Transit Service Coverage

The speed advantage in bicycling over walking is believed to ease first-and-last mile (F&amp;LM) travel and expand transit service coverage. To quantitatively investigate the potential effect of using bicycle as a F&amp;LM connector, the paper measures and compares the impacts of walking and bicycling F&amp;LM access on transit service coverage. In the estimation of transit service coverage, F&amp;LM travel decay functions representing the attractiveness of public transit that declines with increasing walking/biking time to access transit facilities and the spatial boundaries of transit catchment areas are developed using GPS trajectory data collected from the latest Cincinnati Household Travel Survey in Hamilton County, Ohio. Level of traffic stress is used to evaluate the bicycle suitability of streets and bike network connectivity. Based on the F&amp;LM distance decay functions and low-stress bike network connectivity, the transit service coverage area as well as the transit-served population and employment in Hamilton County, Ohio, are estimated. Results show that more population can reach transit services and therefore employment by bicycling than walking. Meanwhile, disadvantaged groups, that is, low-income and zero-car population, can be better served by transit if using bicycle as the F&amp;LM connector. In addition, low-stress bicycling connectivity is a significant factor determining the bicycle-transit service coverage, and a well-connected low-stress bike network with quality bikeways is crucial to guaranteeing that. These findings can be used as references to assist planners in their decision-making process to achieve better mobility and accessibility.

Promote transit via hardening first-and-last-mile accessibility: Learned from modeling commuters’ transit use

To understand how transit ridership would be increased via hardening first-and-last mile (F&LM) connections, the paper explores a quantity-based method to measure the effect of F&LM access when estimating workers’ commuting transit use in Hamilton County, Ohio. Considering variations in the spatial distribution of socioeconomics, built environment, and transportation services, a geographically weighted lasso (GWL) based structure is applied in modeling transit use so as to capture spatial heterogeneous role of F&LM access and to deal with local variable multicollinearity. In the GWL model, transit use is formulated as a function of transit service coverage, job accessibility by transit, and other socioeconomic, built environment, and transportation variables. The transit service coverage is articulated with choices of different F&LM modes (i.e., walking and biking), F&LM network connectivity to transit, and land use density; and job accessibility by transit is measured using the number of destination jobs covered by transit and transit journey time to destinations. The GWL modeling results suggest that a 10% growth in population covered by transit and job accessibility by transit can increase transit usage by 5.9% and 6.6% respectively, especially attracting more riders in the urban fringe. Then, the effectiveness of policy interventions such as dense development, promotion of bike usage, and increased bike connectivity in increasing transit ridership are subsequently estimated. Additionally, results indicate that providing improved F&LM access to car-less population, minority, and low-income people who tend to rely more on transit than others is more effective in promoting transit use.

Determining transit service coverage by non-motorized accessibility to transit: Case study of applying GPS data in Cincinnati metropolitan area

To more effectively expand transit service coverage through promoting bicycling, a practical approach is presented in the paper for estimating the coverage of transit service accessible by non-motorized modes (i.e. walking and bicycling). The non-motorized accessibility to transit is determined by the connectivity and facilities of non-motorized network. Using the data from 2009 to 2010 GPS-based Household Travel Survey in the Cincinnati metropolitan area, the study examines distance thresholds of such non-motorized transit access trips and identifies the spatial boundary and geographic area of transit catchment areas in the Geographic Information System environment. Results suggest that bicycle enables people to access the transit service. The bicycle-transit catchment area is estimated as 1.7 and 2.3 times of the size of pedestrian-transit catchment area at home and activity ends respectively. As a result, more households and employment can reach the transit service via bicycling than walking (52.45% vs. 36.72% for households and 47.82%. vs. 33.07% for employment in the study area). Suburbs, where near half of population and employment situate, are comparatively underserved. Especially, only 27.14% % of the disadvantaged population in suburbs, can access transit by walking, but the percent is increased to 50.96% if using a bicycle. Besides the distance threshold, the non-motorized accessibility to transit is found to be a significant factor determining transit catchment areas. The transit service area can be expanded if a safer and more comfortable bicycling environment is available. Those findings can also be further used as references in the transit-oriented development planning.

An investigation of timed transfer coordination using event-based multi agent simulation

While transfers extend transit service coverage by omnidirectional connections, poorly coordinated transfers significantly increase passenger waiting time, especially in case of missed connections. This paper proposes a simulation approach to investigate the feasibilities of different timed transfer strategies in both schedule planning and operational control. In particular, an Event-Based Multi-Agent Simulation (EMAS) model is proposed, that captures the interactions between the transit vehicles, its passengers and the (urban) environment by considering the transit vehicles and passengers as separate classes of agents which interact in a dynamic system. The model is validated by using observed Automatic Vehicle Location (AVL) and Automatic Fare Collection (AFC) data from two routes with transfers in South East Queensland, Australia. EMAS is then used to evaluate different timed transfer strategies for both schedule planning and operational control. The analysis on timed transfers in schedule planning provides valuable insights on the probability of missing a transfer and extra waiting time for transfer. Six different strategies for timed transfers in operational control are thoroughly tested, including an elaborate sensitivity analysis of the effectiveness of the strategies for different levels of transferring demand and schedule headways. This paper assists transit operators to exploit observed AVL and AFC data to augment the transfer coordination quality.

Exploring the impacts of land use by service coverage and station-level accessibility on rail transit ridership

In this study, we employ spatial regression analysis to empirically investigate the impacts of land use, rail service coverage, and rail station accessibility on rail transit ridership in the city of Seoul and the surrounding metropolitan region. Our analyses suggest that a rail transit service coverage boundary of 500m provides the best fit for estimating rail transit ridership levels. With regard to land use, our results confirm that density is positively related to rail transit ridership within a 750m radius of each station. In contrast, land use diversity is not associated with rail transit ridership. We also found that station-level accessibility is as important as land use for explaining rail transit ridership levels. Finally, we conclude that development density and station-level accessibility measures such as the number of station entrances or exits and the number of bus routes at the station are the most important and consistent factors for promoting rail transit ridership.

New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas

The percentage of the population being served by a transit system in a metropolitan region is a key system performance measure but depends heavily on the definition of service area. Observing existing service areas can help identify transit system gaps and redundancies. In the public transit industry, buffers at 400 m (0.25 miles) around bus stops and 800 m (0.5 miles) around rail stations are commonly used to identify the area from which most transit users will access the system by foot. This study uses detailed OD survey information to generate service areas that define walking catchment areas around transit services in Montreal, Canada. The 85th percentile walking distance to bus transit service is found to be around 524 m for home-based trip origins, 1,259 m for home-based commuter rail trip origins. Yet these values are found to vary based on our analysis using two statistical models. Walking distances vary based on route and trip qualities (such as type of transit service, transfers and wait time), as well as personal, household, and neighbourhood characteristics. Accordingly, service areas around transit stations should vary based on the service offered and attributes of the people and places served. The generated service areas derived from the generalized statistical model are then used to identify gaps and redundancies at the system and route level using Montreal region as an example. This study can be of benefit to transport engineers and planners trying to maximize transit service coverage in a region while avoiding oversupply of service.

A measure of equity for public transit connectivity

An equitable transit system can cater to the needs of captive riders and maximize transit service coverage. Historically transit equity has not considered in planning or has been an afterthought in the process; leading to the underutilization of transit and encouraging travelers to be auto dependent. In this paper, the authors propose a methodology to estimate transit equity using a number of attributes such as frequency, speed, capacity, and built environment in a multi-modal transit network. We propose a methodology to measure transit equity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns.The objective of using equity is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; conforming with federal regulations; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes and assessing the effectiveness and efficiency for node/stop prioritization while choosing transit as a mode of travel. The methodology uses a stylized connectivity measure with a Gini index for equity estimation at different levels such as stop, line, zone and area. An example problem is presented to demonstrate the proposed methodology. The approach is then applied to the Washington–Baltimore region in the United States. The results show the existing transit service coverage at different locations. The proposed approach can be utilized as a tool for transit service planning.

OPTIMAL CIRCULAR BUS ROUTES PLANNING FOR TRANSIT NETWORK DESIGN PROBLEM IN URBAN AREAS

This paper presents a deterministic solution methodology for Transit route Network Design Problem (TrNDP). The main objective is to design a set of bus routes minimizing both users and operator costs while satisfying some constraints; such as minimum demand trips coverage, maximum bus route length and route directness. The proposed methodology provides an efficient set of circular closed bus routes. The formulation of the methodology consists of three parts; 1- representation of transit route network and input data, 2- representation of transit route network objectives and constraints as mathematical programming, 3- the structure of the solution methodology for bus route design. The methodology structure has been tested through Mandl’s benchmark network problem. The test results showed that the methodology developed in this study is able to improve a given network solution in terms of number of constructed routes, transit service coverage, transfer directness, and solution reliability. Based on the presented methodology, a more robust network optimization tool would be produced for public transportation planning purposes.

Combined Effects of Compact Development, Transportation Investments, and Road User Pricing on Vehicle Miles Traveled in Urbanized Areas

Vehicle miles traveled (VMT) is the primary determinant of traffic congestion, vehicle crashes, greenhouse gas emissions, and other effects of transportation. Two previous studies have sought to explain VMT levels in urbanized areas. This study updates and expands on previous work with more recent data, additional metrics, and structural equation modeling (SEM) to explain VMT levels in 315 urbanized areas. According to SEM, population, income, and gasoline prices are primary exogenous drivers of VMT. Development density is a primary endogenous driver. Urbanized areas with more freeway capacity are significantly less dense and have significantly higher VMT per capita. Areas with more transit service coverage and service frequency have higher development densities and per capita transit use, which leads to lower VMT per capita. The indirect effect of transit on VMT through land use, the so-called land use multiplier, is more than three times greater than the direct effect through transit ridership.

How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities

Mixed findings have been reported in previous research regarding the impact of built environment on travel behavior, i.e. statistically and practically significant effects found in a number of empirical studies and insignificant correlations shown in many other studies. It is not clear why the estimated impact is stronger or weaker in certain urban areas, and how effective a proposed land use change/policy will be in changing certain travel behavior. This knowledge gap has made it difficult for decision makers to evaluate land use plans and policies according to their impact on vehicle miles traveled (VMT), and consequently their impact on congestion mitigation, energy conservation, and pollution and green house gas emission reduction. This research has several objectives: (1) Re-examine the effects of built-environment factors on travel behavior, in particular VMT in five U.S. metropolitan areas grouped into four case study areas; (2) Develop consistent models in all case study areas with the same model specification and datasets to enable direct comparisons; (3) Identify factors such as existing land use characteristics and land use policy decision-making processes that may explain the different impacts of built environment on VMT in different urban areas; and (4) Provide a prototype tool for government agencies and decision-makers to estimate the impact of proposed land use changes on VMT. The four case study areas include Seattle, WA; Richmond-Petersburg and Norfolk-Virginia Beach, VA; Baltimore, MD; and Washington DC. Our empirical analysis employs Bayesian multilevel models with various person-level socio-economic and demographic variables and five built-environment factors including residential density, employment density, entropy (measuring level of mixed-use development), average block size (measuring transit/walking friendliness), and distance to city center (measuring decentralization and level of infill development). Our findings show that promoting compact, mixed-use, small-block and infill developments can be effective in reducing VMT per person in all four case study areas. However, the effectiveness of land use plans and policies encouraging these types of land developments is different both across case study areas and within the same case study area. We have identified several factors that potentially influence the connection between built environment shifts and VMT changes including urban area size, existing built environment characteristics, transit service coverage and quality, and land use decision-making processes.

Performance indicators for public transit connectivity in multi-modal transportation networks

Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.

Analysis of Transit Service Coverage Level-of-Service Measures at Border Regions and Suggested Alternative Procedure

Transit service spatial availability is a key parameter in attracting ridership. The TCRP Transit Capacity and Quality of Service Manual (TCQSM) provides a simple methodology to analyze service coverage level of service (SC-LOS) for fixed-route transit service. SC-LOS is determined from the percentage of transit-supportive area (TSA) that has transit service coverage, that is, that lies within a certain walking distance from a bus stop. The TCQSM method of determining TSA is based on zonal demographic and economic data and may not lead to the most accurate estimation of SC-LOS for an area with a significant influx of transit passengers from external sources, such as from across an international border. When such a ridership pattern exists or is suspected, the onboard passenger origin-destination (O-D) survey method proposed in this research can be used to gather trip data to supplement the TCQSM's TSA estimates. Analysis showed that neglecting the data obtained from a recent onboard O-D survey conducted in the west side of the U.S. border city of El Paso, Texas, would result in an underestimation of the percentage of service area covered by transit and the SC-LOS.

Developing an Index of Transit Service Availability

The procedures and results associated with the development of an index of transit service availability are summarized. This index uses the factors that most effectively quantify the availability of public transit service (both bus and rail) in an urban area at a macroscopic planning level. The factors that are included in the index are based on FTA Section 15 data and information from the 1990 census. The development of the index involved the application of more than 30 prospective measures of transit service availability to 228 urban area transit systems throughout the United States. The index uses three measures that quantify transit service coverage, frequency of transit service, and transit system capacity. The index is designed to serve as a planning tool and was specifically developed to facilitate the comparison of transit service availability between urban areas with similar demographics and allow transit systems to examine service availability over time. The index is not intended for use in assessing transit system efficiency or performance.

Developing an Index of Transit Service Availability

The procedures and results associated with the development of an index of transit service availability are summarized. This index uses the factors that most effectively quantify the availability of public transit service (both bus and rail) in an urban area at a macroscopic planning level. The factors that are included in the index are based on FTA Section 15 data and information from the 1990 census. The development of the index involved the application of more than 30 prospective measures of transit service availability to 228 urban area transit systems throughout the United States. The index uses three measures that quantify transit service coverage, frequency of transit service, and transit system capacity. The index is designed to serve as a planning tool and was specifically developed to facilitate the comparison of transit service availability between urban areas with similar demographics and allow transit systems to examine service availability over time. The index is not intended for use in assessing transit system efficiency or performance.