Transit Vehicles Research Articles

A latent class analysis to understand riders' adoption of on-demand mobility services as a complement to transit.

The online version contains supplementary material available at 10.1007/s11116-022-10351-3.

Optimal curbside pricing for managing ride-hailing pick-ups and drop-offs

Recent years have witnessed the rise of ride-hailing mobility services thanks to ubiquitous emerging technologies. Curbside spaces, as a category of public infrastructure, are being used by private ride-hailing services to pick up and drop off passengers, in addition to deliveries and parking access. This becomes quite common in urban areas and has led to additional congestion for ride-hailing, private and public transit vehicles on the driving lanes. Curb utilization by various traffic modes further alters travelers’ choices in modes/routes, clogging streets and polluting urban environment. However, there is a lack of theories and models to evaluate the effects of curbside ride-hailing stops in regional networks and to effectively manage ride-hailing pick-ups and drop-offs for system optimum. In view of this, this paper develops a bi-modal network traffic assignment model considering both private driving and ride-hailing modes who are competing for roads and curb spaces in general networks. To model the impact of limited curbside capacity to through traffic, a curbside queuing model is utilized to quantify the effect of congestion on both curbs and driving lanes induced by curbside stops in terms of waiting time and queue lengths. Travelers make joint choices of modes (driving or ride-hailing), curb stopping locations or parking locations. In addition, this study explores the option to regulate the amount of curbside stops to improve system performance, which is done by imposing a location-specific stopping fee on ride-hailing trips for using curbs to pick-up and drop-off. The curb pricing would influence travelers’ modal choices and parking location choices. To determine the optimal curbside pricing, a sensitivity analysis-based method is developed to minimize the total social cost of the network among all trips. The proposed methods are examined on three networks. We find that the optimal curbside pricing could effectively reduce curbside congestion and total social cost of the traffic system, benefiting all trips in the network.

Impact of Ride-Hailing Services on Transportation Mode Choices: Evidence from Traffic and Transit Ridership

The rise of technology-enabled ride-hailing services has affected individuals’ transportation-related decisions. The impact of these ride-hailing services likely varies across traveler segments that differ in their usage of various modes of transportation. In this paper, we develop and leverage a framework that allows us to examine the impact of ride-hailing services on the transportation mode choice for three traveler segments: drivers (who primarily use a personal automobile to travel), riders (who primarily use public transit to travel), and walkers (who primarily use non-motorized modes of transport). We first develop a framework outlining how the behavior of different traveler segments would be impacted by the introduction of ride-hailing services and show how this affects traffic congestion and public transportation ridership. To test the framework, we compiled a rich dataset, combining data on public transportation ridership, traffic congestion, and individual transportation mode choice. Employing a difference-in-differences methodology, we show that the Uber entry in a market enabled those who were walkers and riders prior to the entry of Uber to travel more conveniently, leading to an increase in traffic congestion, and induced those who were drivers to substitute their use of private automobiles with a combination of Uber and public transit. We introduced urban compactness to assess the heterogeneous impact of ride-hailing services for cities that differ in their distribution of traveler segments. We found that Uber entry increases traffic congestion and reduces public transit demand more in cities with higher levels of urban compactness, i.e., where the proportion of riders and walkers is higher than that of drivers. This work provides a holistic framework to understand the mechanism underlying the impact of ride-hailing services on public transit and traffic congestion. Urban planners and policy makers can leverage our framework, methodology, and empirical results to guide city planning decisions that have implications for sustainability.

An evaluation of the impact of COVID-19 safety measures in public transit spaces on riders' Worry of virus contraction

The coronavirus pandemic has brought about global change in travel behavior. Transit ridership volumes have dropped to record lows. Concerning environmental, health, and social consequences lie in store if transit networks are not able to regain a substantial portion of pre-pandemic users. Transit providers have implemented several interventions aimed at both slowing the spread of the virus and retaining riders as travel restrictions lift. While the effectiveness of these measures has been evaluated with respect to spread rate reduction, little consideration has been given to their impact on riders' feelings of worry regarding virus contraction. By deploying a photo-simulation approach in a randomized control trial, this study finds that level of compliance with safety measures and the conditions of transit spaces themselves significantly impact riders' levels of worry. Given these findings, a series of recommendations are made regarding compliance practices that are expected to lessen rider worry regarding the risks of COVID-19 infection.

Spatial Distribution Characteristics of Japan’s Forest Therapy Bases and Their Influencing Factors

Forest therapy bases are essential ecological recreational locations to promote mental and physical health while at the same time allowing people to enjoy and appreciate the forest. The article took Japan, where the development of forest therapy is in a mature stage, as the research object. Using multi-data and the methodologies of Kernel Density Analysis in ArcGIS and GeoDetector, the spatial distribution characteristics of Japan’s forest therapy bases were investigated, as well as the influencing factors. The results reveal that the spatial distribution of forest therapy bases in Japan is unbalanced, with an aggregated distribution in economically developed and densely populated areas. The spatial density of natural landscape resources, Gross Domestic Product (GDP), the spatial density of population, distance from three major metropolitan areas, rail transit ridership, and spatial density of tourism resources are factors influencing the distribution of forest therapy bases in Japan. The factors interact with each other, forming the spatial distribution pattern. Among these factors, GDP has the greatest explanatory power for the spatial distribution of forest therapy bases in Japan, followed by the distance from Japan’s three major metropolitan areas and spatial density of tourism resources, while the spatial density of population, spatial density of natural landscape resources, and rail transit ridership have a relatively weaker influence on forest therapy bases in Japan. The findings provide some insight into the macroscopic layout of forest therapy bases in various regions of different countries, demonstrating that excellent transportation facilities and good natural resources are the fundamental considerations for the location of forest therapy bases and that densely populated urban areas with a strong economic foundation are key areas for the development of forest therapy bases. Additionally, to take advantage of industrial agglomeration and synergize regional development, considerations for merging with existing resources, such as national parks, forest parks, and recreation forests, should be made.

Understanding transit ridership in an equity context through a comparison of statistical and machine learning algorithms

Building an accurate model of travel behaviour based on individuals’ characteristics and built environment attributes is of importance for policy-making and transportation planning. Recent experiments with big data and Machine Learning (ML) algorithms toward a better travel behaviour analysis have mainly overlooked socially disadvantaged groups. Accordingly, in this study, we explore the travel behaviour responses of low-income individuals to transit investments in Greater Toronto and Hamilton Area, Canada, using statistical and ML models. We first investigate how the model choice affects the prediction of transit use by the low-income group. This step includes comparing the predictive performance of traditional and ML algorithms and then evaluating a transit investment policy by contrasting the predicted activities and the spatial distribution of transit trips generated by vulnerable households after improving accessibility. We also empirically investigate the proposed transit investment by each algorithm and compare it with the city of Brampton’s future transportation plan. While, unsurprisingly, the ML algorithms outperform classical models, there are still doubts about using them due to interpretability concerns. Hence, we adopt recent local and global model-agnostic interpretation tools to interpret how the model arrives at its predictions. Our findings reveal the great potential of ML algorithms for enhanced travel behaviour predictions for low-income strata without considerably sacrificing interpretability.

Determining factors affecting public bike ridership and its spatial change before and after COVID-19

COVID-19, which has spread since late 2019, has caused drastic changes in transportation use. A few studies have already addressed the relationships between COVID-19 and transportation mode choice. However, in most cases, the analysis has been based on transit ridership during the early phases of the COVID-19 pandemic. In addition, few studies have focused on public bike use before and after COVID-19. This study examines the effect of COVID-19 on the ridership of public bikes and various determining factors of public bike use. An origin–destination (OD) analysis and spatial regression models were used with public bike ridership data from Seoul, Korea. The findings of the analysis can be summarized as follows. First, this study confirms that public parks have significantly influenced the increase in public bike ridership since the COVID-19 outbreak. This finding indicates that outdoor spaces such as riverside parks have played important roles in public bike ridership during the pandemic period. Second, this study finds that accessibility to subway stations strongly impacts the increase in public bike ridership. This means that the demand for public bikes as a connected transportation mode has increased since COVID-19. Third, access to bike lanes has had a significant impact on the increase in public bike ridership. This finding indicates the importance of expanding the public bike infrastructure network. Finally, this study makes policy proposals to promote public bike ridership during the COVID-19 pandemic.

Transit communication via Twitter during the COVID-19 pandemic.

Transit providers have used social media (e.g., Twitter) as a powerful platform to shape public perception and provide essential information, especially during times of disruption and disaster. This work examines how transit agencies used Twitter during the COVID-19 pandemic to communicate with riders and how the content and general activity influence rider interaction and Twitter handle popularity. We analyzed 654,345 tweets generated by the top 40 transit agencies in the US, based on Vehicles Operated in Annual Maximum Service (VOM), from January 2020 to August 2021. We developed an analysis framework, using advanced machine learning and natural language processing models, to understand how agencies' tweeting patterns are associated with rider interaction outcomes during the pandemic. From the transit agency perspective, we find smaller agencies tend to generate a higher percentage of COVID-related tweets and some agencies are more repetitive than their peers. Six topics (i.e., face covering, essential service appreciation, free resources, social distancing, cleaning, and service updates) were identified in the COVID-related tweets. From the followers' interaction perspective, most agencies gained followers after the start of the pandemic (i.e., March 2020). The percentage of follower gains is positively correlated with the percentage of COVID-related tweets, tweets replying to followers, and tweets using outlinks. The average like counts per COVID-related tweet is positively correlated with the percentage of COVID-related tweets and negatively correlated with the percentage of tweets discussing social distancing and agency repetitiveness. This work can inform transportation planners and transit agencies on how to use Twitter to effectively communicate with riders to improve public perception of health and safety as it relates to transit ridership during delays and long-term disruptions such as those created by the COVID-19 public health crisis.

Research on the quality evaluation method of rail transit vehicles maintenance based on the life cycle

In order to adapt to the current life cycle management mode of rail transit, this paper proposes a quality evaluation model based on vehicle life cycle maintenance. This model has three parts, which are objective evaluation, subjective evaluation and operational impact. The statistical process control method (SPC) is used in the objective evaluation. The subjective evaluation uses fuzzy algorithms to calculate the factors and weights that affect the maintenance quality, and then weights the actual number of failures to obtain the line deductions. Operation impact evaluation takes the main line failure as the analysis object, and combines the time, location and impact of the failure to obtain the line’s operational quality score. Then calculate the score of these three parts, the final line maintenance quality score. This evaluation system can more truly reflect the maintenance quality, and it has been applied in some pilot lines.

Facing the future of transit ridership: shifting attitudes towards public transit and auto ownership among transit riders during COVID-19.

The online version contains supplementary material available at 10.1007/s11116-022-10344-2.

The Puzzle of Income, Race, and Density: Preliminary Evidence on Transit Use from the 1991 American Housing Survey

The article presents the results of a preliminary analysis of transit ridership data from the 1991 American Housing Survey. The findings suggest that transit operators may find new markets in places they had not thought to look: among high income travelers, including high income minority travelers.

Assessing Transit Station Area Redevelopment: A Case Study of the Lindbergh Station in Atlanta

This article assesses the land-use, demographic, circulation, and economic development attributes of transit station area development. Findings from this assessment are applied to the Lindbergh Metropolitan Atlanta Rapid Transit Authority (MARTA) Station area in Atlanta, Georgia, for which a private-public partnership is currently being negotiated. Recommendations for the redevelopment of the Lindbergh Station area are provided, including a schematic design that integrates those recommendations. The resulting recommendations are intended to maximize the likelihood for transit ridership and economic benefit while offsetting traffic congestion and vehicle emissions—in keeping with the objectives of the Federal Transit Administration’s Livable Communities Initiative. A safe and inviting walking environment throughout a station area—extending well beyond the area of physical redevelopment itself—is fundamental to achieving these objectives. Existing barrier effects and lack of pedestrian connectivity associated with major transportation corridors within the Lindbergh Station area will significantly offset transportation and environmental benefits on which public investment in the redevelopment is predicated. Solutions are required that provide not only safer street crossings, but a larger proportion of rights-of-way devoted to pedestrian movement and the development of a “street life. “ Priority should be given to pedestrian improvements that increase access to transit for traditionally underserved populations. Finally, open space is required to effectively compete with other more auto-dependent areas and to draw higher income populations to transit station areas.

Increasing Transit Ridership: A Survey of Successful Transit Systems in the 1990s

This study examines trends in public transit ridership in the United States during the 1990s. Specifically, it focuses on agencies that increased ridership during the latter half of the decade. While transit ridership increased steadily by 13 percent nationwide between 1995 and 1999, not all systems experienced ridership growth equally. Some agencies increased ridership dramatically, some did so only minimally, and still others lost riders. What sets these agencies apart from one another? What explains the uneven growth in ridership?To examine these questions, we conducted a nationwide survey of transit agencies that added riders during the late 1990s. Specifically, transit general managers or their designees were asked about the factors they deemed important for ridership growth in their systems. We gathered information about specific transit planning efforts and programs that are not available from aggregate data sources, like the National Transit Database (NTD). This article reports the results of this survey and documents recent planning efforts of successful transit systems. We found that:1Service improvements and advertising/information programs are perceived by transit managers to have increased patronage, though opinions varied widely on how significantly such changes affected ridership.2While the literature generally suggests that fare changes affect ridership less than service improvements, universal fare coverage programs are widely perceived to have positively influenced ridership by the systems that implemented such programs.3Three factors outside of the control of transit managers and planners (population growth, economic/employment growth, and worsening traffic congestion) are frequently cited as significantly causing patronage to climb.

Simulated Relationships between Highway Capacity, Transit Ridership, and Service Frequency

This article analyzes the relationships between highway capacity additions and transit patronage, both in the short and long run. A methodology using a model of schedule disutility is shown to provide a technique to account for transit service frequency. This technique, combined with a supply-side model of a highway corridor is used to evaluate the impact of transit headway changes and highway capacity, increases on total transit ridership, using a synthetic sample of commuters. Simulation results are used to evaluate the impact on travel times and utility of the two modes and the long-run degradation of transit service predicted by the Downs-Thomson paradox.While the results do not show congestion as necessarily being worse than before capacity expansion, they do show that transit service frequency could be reduced significantly over time.

A Rural Transit Vehicle Management System and Condition Predictor Model

In an ongoing effort to improve mobility and quality of life for Alabama ‘s citizens, a computer database system has been developed to improve the States ability to manage and assess the condition of its rural transit fleet. The development of this management program consisted of a physical inspection of all state-owned vehicles. Upon completion of the physical inventory, the research team developed a vehicle inventory database to track Alabama s public transit vehicles and a data model to predict the condition of individual vehicles. The prediction model is presented as a tool to allow the State Department of Transportation to assign an individual vehicle condition rating for each vehicle, without the cost of a physical inventory. This vehicle rating is intended to support the equitable acquisition and disposal of vehicles reflecting the varied roadway conditions and socioeconomic conditions found statewide.

Transit Ridership Efficiency as a Function of Fares

The purpose of this study is to assist in the development of transit fare policies that exploit the benefits of public transit in the mix of transportation options for Washington State. The study relates fares to ridership performance, fare-box recovery, and system utilization.Ridership efficiency, a measure of transit performance, is estimated for 24 State transit systems. A mathematical model is developed that relates fares to ridership efficiency. The ridership efficiency function follows the complement of a cumulative normal probability distribution. The tail of the distribution is reached at $0.95. Higher fares have little impact on ridership efficiency. An operating cost model to estimate the fare-box recovery and operating cost subsidy is developed. Ridership, fare-box recovery, and system utilization estimates are made for selected transit systems.

Optimization of Travel in Bus Rapid Transit-Based Multimodal Corridors

Frequently, urban transportation infrastructure and services are operated in a suboptimal manner with respect to key policy objectives such as enhancing mobility, avoiding severe congestion, improving public transit ridership, reducing fuel consumption, and emissions. To overcome this problem, a hybrid simulation-optimization methodology was developed for identification of values of demand management variables that result in the most favorable travel condition in a multimodal corridor regarding a policy objective. This methodology was applied to a bus rapid transit-based major travel corridor in Ottawa (Canada). The travel simulation part of the model is implemented within the EMME/2 modeling framework, supported by a transitway simulation technique. The optimization part of the methodology is based on direct search method that identifies the optimal values of key demand management variables for policy responsiveness. Optimization results are presented for bus modal split, in-vehicle travel time, fuel consumption, and greenhouse gas emission.

Factor Analysis for the Study of Determinants of Public Transit Ridership

Behavioral studies based on attitude survey questionnaires with numerous variables may be tainted with repetitions and correlations. To overcome these deficiencies, a factor analysis approach is demonstrated that produces clusters of uncorrelated factors. From 47 observable variables contained in the Ottawa-Carleton Transportation Commission (OC Transpo) attitude survey, only 8 underlying factors have emerged. Bus information service is the most important factor. In addition to factor analysis, this article reports on a logistic regression model, based on key factors, for estimating the odds of ridership.

Door-to-Door Mobility: Evaluating a Bus Rapid Transit Community Transport Concept

Portland, Oregon’s regional government, Metro, has designated specific communities in outer Southeast Portland as areas that should be planned to accommodate future population growth. Both Metro and the Tri-County Metropolitan Transportation District of Oregon (Tri-Met) have expressed a desire for Bus Rapid Transit (BRT) service to this area from downtown Portland, within a corridor approximately following Southeast Powell Boulevard and Foster Road.A preliminary analysis of BRT alignment alternatives was completed for this study. After six possible alignment options linking downtown Portland with Pleasant Valley and Damascus Town Centers were identified, a multivariate corridor analysis was applied to each option. Criteria used to select the best alignment alternative included regional connectivity, local ridership, operational costs, trip duration, distance, right-of-way and political feasibility, environmental costs, and capital costs. In addition, recommendations have been made for possible station locations along the preferred alternative corridor.This analysis is intended to assist Tri-Met in its efforts to begin planning, designing, and implementing a BRT system in this area. The results of the analysis suggest that a BRT system is feasible for the Powell/Interstate 205/Foster alignment. The outcome also suggests that BRT has the capacity to influence land use and could generate high transit ridership. Overall, it is recommended that Tri-Met and Metro continue to evaluate opportunities for BRT in this alignment.

Niche Marketing Strategies: The Role of Special-Purpose Transportation Efforts in Attracting and Retaining Transit Users

This study evaluates the use of public transit niche strategies as an alternative marketing strategy designed to attract and retain new public transit riders. Four niche efforts, a university football shuttle, professional football shuttle, summer metropolitan park shuttle, and suburban subscription vanpool are the focus of the investigation. A total of 738 intercepts provide the data for the research. The researchers conclude that niche marketing efforts are an effective strategy, and therefore should be an important tool in the public transit industry’s efforts to attract and retain new riders in order to offset the prolonged decline in public transit market share.