Public Transit Service Research Articles

What does it take for rural-urban commuters to switch from driving to carpooling?

This study aims at identifying the potential ways to increase the willingness to carpool, particularly in rural–urban travel settings, where there is no/minimal public transit service (due to low population density) and purchasing a personal vehicle poses a significant financial burden for many households. To do so, we used time flexibility, defined as the tolerance for increased commute time (which can happen because of re-routing and picking up others when carpooling), as a proxy to willingness to carpool. Using structural equation modeling and survey responses from about 1000 workers and college students living in a rural county in Central Pennsylvania, we analyzed the sociodemographic, attitudinal, and situational factors that can lead to higher time flexibility when carpooling. We also investigated whether people’s time flexibility changes when they are offered monetary incentives (in terms of travel costs reimbursement). The results indicated that being a driving fan and seeking privacy when traveling reduces time flexibility, while being conscientious about environment and health leads to higher time flexibility. Moreover, females, people who had inconvenient past carpool experiences, and those living closer (within 20 min of driving) to their workplace/college showed lower time flexibility. On the other hand, people with lower income and higher driving costs were willing to tolerate longer commute times if reimbursed for a portion of their travel costs. We also found that if there is no initial level of willingness to carpool, reimbursement offers cannot do much to sway people’s decisions.

When to Measure Accessibility? Temporal Segmentation and Aggregation in Location-Based Public Transit Accessibility

Accessibility analyses are important for public transit (PT) planning, as they reveal possible deficits in PT services. Since such accessibility analyses are highly time-dependent, the Modifiable Temporal Unit Problem (MTUP) should be considered. In this context, one approach is to calculate accessibility continuously for an entire day and aggregate it appropriately. However, this approach is complex and computationally intensive and is therefore rarely, if ever, applied. Instead, practitioners and researchers rely on simplified methods without considering temporal effects in detail. This paper bridges this gap by developing a simple yet representative method to account for the temporal variability of PT services. For this purpose, we calculate and compare PT accessibility for different time windows and through different aggregation methods for Germany. The results show that PT analyses between 9–11 a.m. were most representative. Alternatively, the time windows between 7–9 a.m. and between 1–3 p.m. adequately reflected accessibility. The median was suitable for aggregating individual time intervals into a representative value for the PT service throughout a day, while the maximum or mean value distorted the results. For practical planning purposes, we therefore recommend using the 9–11 a.m. time window.

Research On the Design of Public Transit Services for The Elderly in China

As China enters an aging society, the elderly in China are increasingly becoming an important user group of public transportation. This study uses service design thinking to optimize the inclusiveness of Chinese elderly people's travel by bus and subway, and explores the feasibility of applying service design thinking to the field of public transportation. This paper adopts the observation method, with Guangzhou and Beijing as the research areas. The researchers conduct service design research based on the entire process of elderly travel, summarize the travel needs and pain points of elderly passengers, optimize the station guidance system, intelligent interface and service platform, make the public transportation service environment more friendly, and thus make the public transportation service environment more inclusive. Analyze the passenger flow, contact points, and stakeholders of the station, draw character portraits and journey maps, and output service design strategies to improve the travel experience of Chinese elderly passengers. In summary, this study aims to improve the convenience of Chinese elderly passengers taking public transportation and provide theoretical support for the transformation and optimization of China's public transportation services.

Neoliberalism and the splintering of city-regionalism: the case of Denver’s regional transit agency in times of COVID-19 urban austerity

ABSTRACT Public transit service provision is fraught with contradictions and tensions, which today tend to converge around the city-regional scale of planning and governance. The promise of public transit is to promote economic development and improve regional accessibility, mobility, equity, and sustainability. However, these priorities can often conflict with each other, resulting in the splintering of the corresponding city-regional planning and governance structures set up to finance and deliver major transit infrastructure projects. Drawing upon a case study of transit-led city-regionalism in Denver, Colorado, USA, this article explores how the tensions and contradictions embedded within regional public transit service planning are exposed and exacerbated during times of financial austerity, such as during the COVID-19 pandemic. It examines how the neoliberal goals of promoting transit-oriented redevelopment in Denver alongside expanding service to Denver’s wealthier suburbs clash with the pandemic-induced expediency of targeting transit service for front-line workers and transit-dependent populations in core urban neighborhoods. The article demonstrates that in times of COVID-19-induced urban austerity the entrepreneurial city-regional approach to infrastructure provision originally developed for the FasTracks expansion program is increasingly at odds with regional objectives to use mass transit to foster equity and transport justice.

Stressors for bus commuters and ways of improving bus journeys

Based on the people-environment conceptual framework, this paper measures the level of transport stress experienced by bus commuters and examines its relationship with a wide range of environmental and personal stressors, as well as different stress responses. A total of 28 environmental stressors, 9 personal stressors, 4 time-related stressors and 6 stated stress responses are examined. The data were collected through a large-scale online questionnaire survey among bus commuters of a major franchised bus company in Hong Kong (n = 5,908). A factor analysis and a structural equation model (SEM) are conducted to unveil the interlinkages among bus-related environmental stressors, personal stressors, travel characteristics, perceived transport stress and stated stress responses. Results indicate that bus commuters reported an average stress level of 47.10 out of 100 (SD = 29.50). The average transport stress level is lower than money, work and family stress but higher than relationship stress. Spatially, there are great variations within the city, with notably higher stress levels for some new towns in Northwest New Territories and the central business district during evening commutes. Based on the SEM results, the number of bus transfers (β = 0.05) and travel time (β = 0.06) are strongly associated with transport stress. Poor bus stop environment (β = 0.14), crowding at bus stops and compartments (β = 0.13), hostile attitudes of passengers and drivers (β = 0.08), and unreliable waiting and travel time (β = 0.08) are important environmental stressors. Many of these factors have not been closely examined in previous studies. In relation to health, transport stress is positively associated with negative physical (β = 0.43) and emotional (β = 0.48) responses. Feeling exhausted, irritated and anxiety were the most commonly reported responses to transport stress. To enhance bus commutes, priorities should be given to improving the bus stop environment, reducing crowding throughout the bus journeys, and alleviating road congestion. Overall, the empirical findings from this large-scale study on transport stress can help governments to formulate targeted measures to enhance the quality of public transit services and to support sustainable urban transport.

Increasing the precision of public transit user activity location detection from smart card data analysis via spatial–temporal DBSCAN

Smart Card (SC) systems have been increasingly adopted by public transit (PT) agencies all over the world, which facilitates not only fare collection but also PT service analyses and evaluations. Spatial clustering is one of the most important methods to investigate this big data in terms of activity locations, travel patterns, user behaviours, etc. Besides spatio-temporal analysis of the clusters provide further precision for detection of PT traveller activity locations and durations. This study focuses on investigation and comparison of the effectiveness of two density-based clustering algorithms, DBSCAN, and ST-DBSCAN. The numeric results are obtained using SC data (public bus system) from the metropolitan city of Konya, Turkey, and clustering algorithms are applied to a sample of this smart card data, and activity clusters are detected for the users. The results of the study suggested that ST-DBSCAN constitutes more compact clusters in both time and space for transportation researchers who want to accurately detect passengers’ individual activity regions using SC data.

Study on Factors of Urban Transportation Service Quality Based on Analytic Hierarchy Process: A Case Study of Gangtok City

Promoting the use of public transportation requires an in - depth knowledge of the variables that affect the choice of public transportation mode, including the process of implementing policy, as it has become a crucial component of government strategies to reduce carbon emissions from the transportation sector globally. A variety of factors impacting the usage of public transportation have been identified in previous studies, but few have been included in a single study. In order to boost the use of public transportation, it is essential to make it more attractive to travellers by conducting frequent Service Quality (SQ) assessments and adjustments. Understanding the passengers’ expectations towards public transportation are important, and assessing the SQ is an important tool for evaluating the total performance of the Gangtok’s public transportation system. The purpose of the existing study was to study the expectations and perceptions of city’s passengers regarding SQ in public transportation. In order to comprehend how the present commuters’ prefer a particular service quality attribute a series of interviews with passengers were undertaken. MCDM technique was adopted for this. The paper focuses on service quality factors for urban transportation system by adopting AHP technique. In this study perception of passengers using public transport in Gangtok is taken from the field. The case study is taken for Gangtok city in the state of Sikkim. The study involves study of passengers from various bus stop locations of the city. The results of the research showed substantial discrepancies among expectations and perceptions of city’s commuters, along with widespread dissatisfaction with the delivery of public transit services in hilly areas as a whole. The reliability and adaptiveness of these service have been critical in describing the overall quality of transportation services in hilly areas, and best practices were used to develop a set of recommendations for transportation operators and local officials.

Service area delineation to support on-demand mobility for the transport disadvantaged

Given the significance of technology to enhance public transit services and its potential for improving access to and the delivery of transportation services, this paper addresses strategic neighborhood mobility improvements to aid the transportation-disadvantaged. A spatial optimization model is presented to identify underserved areas for which transit can be better tailored to meet their mobility needs. The introduction of mobility-on-demand in the Cincinnati metropolitan area to augment and complement existing fixed-route transit is reported. The use of spatial analytics to support targeted neighborhood system design is detailed. The study illustrates how new mobility-on-demand services will substantially enhance travel options for the transport disadvantaged. Further, the use of spatial analytics offers insights for transit service plan development and implementation by more precisely targeting mobility needs in service area delineation and operationalization.

A general coupled morning–evening traffic equilibrium model with rideshare, ride-hailing, and public transit services

We develop a general equilibrium model to capture the complex interactions between different modes, such as solo driving, public transit, as well as rideshare and ride-hailing services such as Uber and Lyft, under a joint morning and evening commute framework. Formulated as a variational inequality (VI) and equivalently as a mixed complementarity problem (MiCP), the model allows (a) travelers to switch between different transportation modes and (b) passengers from different Origin-Destination (OD) pairs to share a ride together. The computational results on the Sioux-Falls network show that our model captures the possible mode switches and the coupling effects between morning and evening commutes. Furthermore, our numerical examples demonstrate that modelling morning and evening commutes separately tends to overestimate the travelers' disutility and the average Vehicle Miles Traveled (VMT) in the network.

Review of City-Wide 30 km/h Speed Limit Benefits in Europe

To date, more and more European cities are systematically working to expand the proportion of their street network with a speed limit of 30 km/h. This paper endeavored to assess the effectiveness of city-wide 30 km/h speed limits in Europe. In an effort to condense research outputs, a quantitative approach along with qualitative assessments were implemented. This study described the changes in safety, environment, energy, traffic, livability, and health before and after the phased implementation of city-wide 30 km/h speed limits. The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Results from 40 different cities across Europe, including Brussels, Paris, and Zurich, indicated that reductions in speed limits improved road safety by decreasing the likelihood of crash risk and the severity of crashes that do occur. On average, the implementation of 30 km/h speed limits in European cities demonstrated a 23%, 37%, and 38% reduction in road crashes, fatalities, and injuries, respectively. Lower speed limits also yielded environmental benefits, with emissions decreasing on average by 18%, noise pollution levels by 2.5 dB, and fuel consumption by 7%, indicating enhanced fuel efficiency and reduced environmental impact. Encouraging citizens to embrace walking, cycling and utilizing public transit services can further contribute to a safer and environmentally sustainable urban environment.

The impacts of COVID-19 pandemic on bus transit demand: A 30-month Naturalistic Observation in Jiading, Shanghai, China

The COVID-19 pandemic and subsequent governmental responses have had unprecedented effects on public transit (PT) demand. This paper presents a naturalistic observation of the Jiading bus transit system in Shanghai, China, spanning from April 2021 to October 2023 and covering different stages under various extreme policy response combinations. We employ Prais-Winsten regression to quantitatively assess the pandemic’s impact on bus demand and explore demand recovery patterns at both aggregated and individual levels in the post-pandemic era. Our findings reveal a strong negative correlation between bus demand and the stringency of containment policies, consistent across both levels of analysis. In the post-pandemic period, ridership has only rebounded to 77% of the pre-Omicron near-normal level, with notable spatial and temporal disparities across different regions. While the temporal distribution of ridership has largely normalized, the recovery of travel demand between zones outpaces that of travel within zones. Moreover, a persistent decline in individual travel frequency has been observed, which has not reverted in the post-pandemic period. The insights from this study can help policymakers better respond to potential future crises and improve PT services in the post-pandemic era.

Post-pandemic transit commute: Lessons from focus group discussions on the experience of essential workers during COVID-19

Public transit services, which provide a critical lifeline for many essential workers, were severely interrupted during the COVID-19 pandemic. As institutions gradually return to normal in-person operations, it is critical to understand how the pandemic affected essential workers' commute and what it will take to ensure the effective recovery of transit ridership and enhance the long-term resiliency and equity of public transportation systems for those who need it the most. This study used focus group discussions with essential workers who were pre-pandemic transit riders to understand how the COVID-19 pandemic has impacted their commute perceptions, experiences, motives, and challenges and explore the potential changes in their travel behavior post-pandemic. We used NVivo 12 Pro to conduct a thematic analysis of the transcripted discussion data and examined patterns of commute mode change with respect to participants' attributes, including job type, home location, and gender. The results show that public transit had multiple reliability and frequency challenges during the pandemic, which resulted in most participants switching away from public transportation. With the increased availability of hybrid remote work and pandemic-related parking policies, driving emerged as a safer and more affordable commute mode for many pre-pandemic transit riders, rendering transit services less efficient for those who continued to rely on it. Planning for post-COVID resilient and reliable mobility requires a major rethinking of providing an efficient and effective transport system and a more fundamental approach to long-term public transport policy. To recover transit ridership, transit agencies need to ensure transit service availability and provide reliable transit information through smartphone apps. Similarly, transit agencies need to coordinate with other employers to provide free or heavily subsidized transit passes, to facilitate the recovery of transit demand effectively.

Design and analysis of ride-sourcing services with auxiliary autonomous vehicles for transportation hubs in multi-modal transportation systems

Autonomous vehicles (AVs), which can be fully controlled by remote/online operators, could be an extension of ride-sourcing services provided by transportation network companies (TNCs). Meanwhile, substitutive and complementary relationships between ride-sourcing and public transit could also help TNCs increase their profit under certain strategies. Unlike previous studies that generally ignored either AVs or interactions between public transit and ride-sourcing, we introduce AV-involved operational strategies into a multi-modal system. In this paper, we focus on transportation hubs in an urban area and let the TNC assign AVs to these hubs for serving only within that particular hub at a differentiated fare; meanwhile, passengers could choose among AVs, human-driven vehicles (HVs), combined modes with public transit and AVs or HVs, or other travel modes to fulfill their travel needs. We develop a mathematical model to investigate the impacts of such an operational strategy, and formulate an optimisation problem to maximise the TNC's profit and minimise total waiting time simultaneously by adjusting AV fare and fleet size. We further propose a comprehensive modeling framework with the analytical model, optimisation problem, calibration method, and heuristic algorithm, making it a general approach for different real-world scenarios. Following the framework, we conduct a case study based on real-world datasets of public transit and ride-sourcing services in Hangzhou, China. Different market schemes are analyzed and compared with the currently existing situation. The results demonstrate that by adopting this auxiliary-AV-oriented operational strategy, the TNC's profit and public transit ridership can both be increased, and passengers could enjoy a shorter waiting time for HV ride-sourcing trips. Moreover, the TNC is more inclined to allocate more AVs to hubs with large commute needs and uncongested traffic, leading to a high profit for the TNC and a short waiting time for passengers. Societal preferences towards AV trips are also analyzed. The results provide in-depth references for real-world AV-related ride-sourcing operational problems.

Evaluating the impacts of supply-demand dynamics and distance decay effects on public transit project assessment: A study of healthcare accessibility and inequalities

Previous studies evaluating the impacts of transport interventions on accessibility to healthcare have largely overlooked competition among patients for limited resources and the tendency to use healthcare located closer to them (i.e., distance decay effects). This study aims to demonstrate how overlooking supply-demand dynamics and distance decay effects can distort the evaluation of a new public transit service's impacts on healthcare accessibility and inequalities. Specifically, using a new bus rapid transit (BRT) service in Columbus, Ohio, USA, as an example, we compare three types of measures: 1) cumulative-opportunity, 2) multimodal two-step floating catchment area (2SFCA), and 3) multimodal generalized 2SFCA (G2SFCA) accessibility metrics. To understand the similarities in results obtained from different accessibility measures, we use the Pearson correlation coefficients of standardized accessibility change scores. Further, we leverage an inequality index, the Palma ratios, to examine how inequality assessments can be sensitive to the choice of accessibility measure. The correlation analysis reveals notable differences among the three measures. This indicates that neglecting supply-demand dynamics and distance decay effects can lead to differences in results, potentially distorting transit project evaluations and misleading stakeholders. Moreover, although overall conclusions about inequalities are largely consistent, we observed nuanced and statistically significant differences in Palma ratios when derived from cumulative-opportunity metrics compared to the multimodal 2SFCA and multimodal generalized 2SFCA measures. Our findings underscore the importance of considering supply-demand dynamics and distance decay effects for a more realistic and accurate assessment of new transit service's impacts on healthcare accessibility and inequalities.

Travel Satisfaction of Bus Rapid Transit Users in A Developing Country: The Case of Bhopal City, India

India's burgeoning population has led to an increased demand for transportation services, particularly in urban areas. To address the growing mobility needs and mitigate the adverse effects of personal vehicle usage, efficient public transit services are imperative. Several Indian cities have implemented bus rapid transit (BRT) systems to address this problem, but ridership for the majority of the BRT systems remains below breakeven (this refers to the point at which the revenue generated from ridership equals or surpasses the costs associated with operating and maintaining the transportation system). Thus, it is necessary to assess the determinants of commuter satisfaction with BRT. The present study aims to examine factors affecting travel satisfaction among BRT commuters. By using structural equation modeling (SEM), the effect of demographic (age and gender) and travel-related variables (fare price, travel time, trip frequency, reliability, ease of using bus service, and comfort level) on BRT commuters' satisfaction and usage of BRT services were analyzed. It was found that while ease of using the service, comfort level, and reliability positively affect BRT travel satisfaction, trip frequency is significantly affected by the ease of using the service only. Furthermore, demographic variables (age, and gender of respondents) were not found to have significant effect of travel satisfaction and trip frequency. The findings from this can study serve as a base for policymakers, city officials, and urban planners to identify commuters' priorities for a well-functioning BRT in India and formulate policies to attract riders by enhancing their preferences.

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.

Enhancing Public Transit System Through AI and IoT

The paper investigates the synergy between AI and IoT in revolutionizing public transit systems, emphasizing their role in addressing existing challenges and improving overall efficiency. It explores the application of IoT devices in creating a smart infrastructure that enables real-time data collection, monitoring, and management of transit operations. The research delves into the realm of predictive maintenance, showcasing how AI algorithms, powered by IoT data, can anticipate potential issues in transit vehicles. By analyzing sensor data, transit authorities can proactively address maintenance needs, minimizing downtime, reducing repair costs, and ensuring a more reliable and sustainable public transit service. Route optimization emerges as another crucial aspect of the study, highlighting how AI algorithms leverage historical and real-time data to recommend the most efficient transit routes. Factors such as traffic patterns, weather conditions, and passenger demand are considered to enhance overall system efficiency and reduce travel time for passengers. The paper introduces the concept of dynamic scheduling, illustrating how AI-driven algorithms adapt transit schedules in real-time based on changing passenger needs and external factors. This dynamic approach aims to provide more responsive services, ultimately reducing wait times and improving overall user satisfaction. Passenger information systems are explored as a pivotal component, illustrating how AI and IoT technologies enhance the passenger experience. Real-time communication through mobile apps, digital displays, and other channels ensures that passengers have accurate and timely information about arrival times, delays, and alternative routes, empowering them to make informed decisions. The researchers also delve into fare optimization, examining how AI algorithms analyze data on passenger demographics, travel patterns, and economic factors to create fair and affordable fare structures. This approach aims to encourage ridership, increase revenue, and improve the financial sustainability of public transit systems. The abstract presents a comprehensive overview of how the integration of AI and IoT technologies in public transit systems transforms urban mobility. The findings suggest that leveraging real-time data, predictive analytics, and dynamic solutions can significantly enhance the reliability, accessibility, and sustainability of public transit. As cities continue to explore innovative solutions, the abstract serves as a roadmap for developing smarter, user-friendly, and efficient urban transportation networks, ultimately contributing to improved quality of life for residents.

Passengers Flow Analysis of Public Transit Service in Pokhara

The motive of the study is to evaluate the existing public transportation system and propose recommendations for Pokhara public transportation to enhance its efficiency and effectiveness. In urban locations, a well-managed public transportation system is unquestionably required. According to the previous study, passengers faced various issues on their journey, such as delays in reaching their destination, bus congestion, an inappropriate time of departure, lane stoppage, and more. (Duwadi, et al., 2019) The primary and secondary data collected from fieldwork and the Yatayat Bibhag, respectively, were used in the research for the analysis. The volumes of passenger flows on ten different routes were analyzed. Mapping and modeling were done using GIS and CAD. Results show that the service frequency did not match the actual swings in consumer demand, resulting in increased time delays. It is recommended that well-managed loading areas be needed in areas with the highest person capacity of more than 3000 per stop per hour, such as Chipledhunga, Mahendrapool, Srijanachowk, and more. A practical operation schedule and service frequency, including 10% for backup and maintenance, were recommended. Demand for passengers on various routes and the number of years the capacity can fulfill the demand is calculated.

Differences in commuting between employee and self-employed workers: The case of Latin America

Commuting time represents a shock to worker time allocations that ultimately affects wellbeing. This paper analyzes the commuting behavior of employee and self-employed workers in urban areas of eleven Latin American countries. Using data from the ECAF data, results show that employees spend about 8.2 more minutes commuting to work than their self-employed counterparts, net of observable characteristics, a difference of around 18.5% of the employees' commuting time. This difference is qualitatively robust across the eleven countries and is concentrated in commutes by public transit, but is not explained by differences in access to public transit services. This analysis is a first cross-country exploration of self-employed and employee workers' commuting time in Latin America. By analyzing differences in commuting time between these two groups of workers, our analysis may serve to guide future planning programs.

Routing and charging optimization for electric bus operations

The transition to alternative energy sources and the adoption of on-demand operating modes in urban bus systems are crucial steps towards reducing carbon footprints and improving public transit services. This paper presents a two-phase approach for the collaborative optimization of charging schedules and passenger services, aimed at enhancing the operation of on-demand electric bus systems. First, we propose a label-setting dynamic programming algorithm that enables the efficient generation of bus-trips for each bus line in response to passenger requests. Second, we introduce a time–space network optimization model that facilitates integrated multiple bus-trip planning for the transit network, involving multiple bus lines and charging spots. The model selects bus-trips from various time–space arcs, which represent passenger carrying, bus deployment, and bus charging activities. To validate the effectiveness of our approach, we conduct a case study using real-world data from bus lines in Beijing, China. Computational results demonstrate that our approach can handle on-demand electric bus operations within minutes of solution time, efficiently serving over 2,000 passengers. Practically, our approach achieves a notable reduction in average transit time and effectively reduces the waste of public transit resources. The proposed approach can serve as a beneficial tool for decision-makers and operators seeking to enhance the performance and environmental impact of their electric bus systems.