Journal of Public Transportation最新文献

In the current study, a meta-analysis is performed to synthesize the results of 61 original articles from 2000 to 2022 to quantitatively evaluate the community’s benefits in terms of users and the public sector of a general Mobility as a Service (MaaS) deployment both in rural and urban areas. Results show that such a deployment would be effective in terms of improving accessibility, safety, energy efficiency, employment opportunities, and reducing traffic congestion, but that spatial and temporal contexts play an important role. Moreover, higher community benefits could be reached, and these are the key recommendations, if (i) there is a focus on developing MaaS applications, particularly catering to the booking and shared system needs of disabled individuals, (ii) an expansion of novel mobility services is advanced to areas currently underserved by MaaS, and (iii) MaaS approaches are implemented to further reduce energy consumption, boost employment, and alleviate traffic congestion. The findings have implications for transport users, calling for the introduction of subsidy policies, tax regulations, and redefining public transport to propel MaaS progress. Regional authorities are encouraged to create favorable conditions for MaaS deployment, including improving transport infrastructure to support the mobility system. As MaaS gains traction as a viable alternative to personal vehicles, involving all stakeholders becomes crucial for the success of the emerging MaaS ecosystem.

Specific design features and functions on the platform and inside of the train carriage can significantly affect how efficiently and smoothly passengers can move in and out of the train. Industry follows the design standard and guidelines to satisfy the minimum requirement. However, the views of rail users are often overlooked and not well understood. This study fills the knowledge gap by investigating different platform and train carriage design features and understanding train passengers' perceptions and preferences for the proposed design. An online passenger survey targeting Melbourne Metro train users was conducted. By analyzing 429 valid responses, we gained insights into passengers' perceptions and preferences regarding train and platform design. A novel finding is that a vertical pole is the most preferred handhold type, while a rigid handrail is the least preferred handhold type. The 2+2 seating is voted as the most preferred interior layout, which is consistent with previous studies. The ranking on 2+2 seating layout is moderately associated with travel time and travel frequency, while the ranking on 2+3 seating is strongly associated with travel time. It is also found that the preferences for boarding sign and occupancy sign design are significantly associated with gender, age group, and travel frequency. Surprisingly, no statistically significant associations were found between any of the personal or travel variables with queuing sign preference, side seating ranking, or hanging strips ranking. The findings drawn from the analysis and the recommendation of this paper can provide valuable guidance for rail manufacturers in implementing design changes, as well as for service operators in adopting new strategies and interventions to enhance service quality and customer satisfaction.

This paper presents a study regarding the factors affecting the maximum distance travelers are willing to walk to a bus stop. The study focuses on bus services provided at and walking routes towards bus stops. Travelers’ evaluations are collected using a stated preference experiment. Based on 7911 evaluations of 879 respondents, a latent class ordered logit model is estimated showing that both bus service and walking route related attributes significantly contribute to the maximum distance travelers are willing to walk from home to a bus stop. The parameter estimates show that the most influential attributes are the bus frequency at the bus stop and the presence of street lighting along the route between home and bus stop. The model also shows that based on the evaluations three different classes of respondents can be distinguished. Membership of a class depends on traveler related characteristics: gender, residential area, and bus use.

Discussions of bus stop consolidation sometimes refer to average stop spacings, but there are no reliable statistics about spacings, nor methodologies for calculating them. This paper aims to clarify discussions of bus stop spacings by introducing clear definitions, a methodology for creating statistics from General Transit Feed Specification (GTFS) files, and a python package, gtfs-segments, which splits bus networks into isolated ‘segments.’ With the package, we calculate national-level statistics from 539 US transit providers and 83 Canadian providers, as well as agency-level statistics for 30 providers in the US, 10 in Canada, and a sample of 38 providers from other countries. Our estimates of US and Canadian mean spacings are both around 350 m (slightly wider than five stops per mile). US spacings are wider than sometimes claimed but narrower than those in other countries. Finally, the paper gives examples of metrics created by combining GTFS with data from other sources and proposes research ideas and applications to transit planning involving fine-grained stop spacing data.

Fare-free transit policy is not new to several public transit systems and communities in the U.S., as some local transit agencies have begun implementing fare-free transit policies or variations of them since the 1960s. Over time, the discussion regarding fare-free transit has been reignited by decreasing ridership trends in recent years and other thematic inquiries surrounding access, mobility and equity, operational efficiency, agency financial health, and community impacts. This research empirically investigates the effects of fare-free policy on transit ridership, labor force participation and income inequality. Using panel data regression models, we draw several conclusions: 1) Fare-free transit significantly increases ridership. 2) Fare-free transit neither significantly increases labor force participation rate nor reduces income inequality in small and medium-sized urbans. 3) Fare policy aside, external factors such as increased household income and work-from-home significantly reduce the demand for transit in small-urbanized areas.

This study aims to assess the public acceptance of Autonomous Modular Transit (AMT) and identify key factors influencing people’s intentions regarding the future use of AMT. While the integration of autonomy and modularity in transport systems has gained attention in recent years among researchers, the study of AMT acceptance is non-existent in the literature. To address this research gap, the study proposes an extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model to explore public acceptance of AMT. It integrates the original model’s constructs with two additional factors: trust and perceived green usefulness, while also investigating the role of public transport usage behavior in intention. Data were collected through an online survey involving 1662 participants from different cities in Iran. Structural equation modelling was used to evaluate the conceptual model. Multiple t-tests and ANOVA tests were conducted to evaluate the effects of public transport usage behavior and demographics on the model’s constructs. The results showed that the majority of respondents showed their acceptance toward using AMT when available despite their limited prior knowledge about the system. Perceived usefulness was the strongest predictor of intention, followed by social influence and hedonic motivations. Although the COVID-19 pandemic significantly reduced the number of public transport (PT) regular users, this group showed a higher intention to use AMT compared to PT non-regular users. Furthermore, respondents aged over 60 years stated a lower intention to use AMT than their younger counterparts. Given that the mass adoption of AMT depends on public acceptance, this study is expected to serve as a benchmark for comparing countries with similar cultural contexts.

This study analyzes the use of ride-hailing and bus services from a multi-modal user perspective by jointly modeling individuals’ monthly frequency of use of both bus and ride-hailing services. A bivariate ordered probit model is estimated to capture the influence of socio-demographic and attitudinal characteristics as well as unobserved factors that may simultaneously influence the travel frequency by both modes. We use data collected in a survey of travelers from Porto Alegre, Brazil. The results characterize the profile of local frequent ride-hailing users as young, medium-income, self-employed individuals with a propensity toward the use of technology and a low inclination for car ownership. Most importantly, we observe that after controlling for unobserved factors that simultaneously contribute to higher trip frequencies by both modes, frequent bus users demonstrate a lower propensity toward ride-hailing use.

As the airspace is increasingly gaining importance as a new frontier to improve urban mobility, aerial cable cars are being discussed and already appropriately implemented worldwide to supplement conventional modes of transport in urban areas. Transit planners and designers should carefully consider the interoperability and integration of cable car services with conventional modes of transport. In particular, excessive delays and overcrowding conditions due to deficits in interoperability should be avoided. This challenge of interoperability arises as conventional modes of transport operate predominantly on a timetable, and most cable car technologies operate in such close headways that they can be considered as almost continuous conveyors. The advantage of having almost always a transport vessel of a cable car ready for boarding ceases when large volumes of passengers arrive in batches, for example from higher-capacity modes of transport or at large events, resulting in long queues. Traditional manuals do not yet reflect these aspects of interoperability adequately. Consequently, this work filled this research gap about the interoperability of cable cars related to handling high volumes of incoming passenger arrivals that transfer in larger batches from feeder modes and often result in queues at cable car stations. The following objectives were targeted: (1) determine passenger capacity limits of conventional modes of transport acting as feeders to cable cars and (2) specify space requirements to be provided due to the potential queues that arise. To answer these, methods of Queuing Theory were used and results were placed in Levels of Services of traditional manuals. Key performance indicators included queue length, waiting time, and corresponding queue space. The results revealed that cable cars can be a useful complement to public transit but are of limited feasibility due to cumulative queues at arrival rates with larger crowds. High-capacity feeder modes (e.g., commuter rails) are limited to 20-minute headways depending on cable car technologies. Further, queuing areas of up to 1000 square meters (around 10,800 ft²) should be considered. Several operational limitations are presented as guidance for practitioners and policymakers.

Existing research underscores substantial gender-based variations in travel behavior on public transit. Studies have concluded that these differences are largely attributable to household responsibilities typically falling disproportionately on women, leading to women being more likely to utilize transit for purposes referred to by the umbrella concept of “Mobility of Care”. In contrast to past studies that have quantified the impact of gender using survey and qualitative data, we examine a novel data-driven workflow utilizing a combination of previously developed origin, destination, and transfer inference (ODX) based on individual transit fare card transactions, name-based gender inference, and geospatial analysis as a framework to identify mobility of care trip making. We apply this framework to data from the Washington Metropolitan Area Transit Authority (WMATA). Analyzing data from millions of journeys conducted in the first quarter of 2019, the results of this study show that our proposed workflow can identify mobility of care travel behavior, both in terms of (1) detecting times and places of interest where the share of women travelers in an equally-sampled subset (on basis of inferred gender) of transit users is 10 %–15 % higher than that of men, and (2) finding women significantly more likely to exhibit a consistent accompaniment patterns with riders who are children, elderly, or people with disabilities. The workflow presented in this study provides a blueprint for combining transit origin-destination data, inferred customer demographics, and geospatial analyses enabling public transit agencies to assess, at the fare card level, the gendered impacts of different policy and operational decisions.