Journal of Public Transportation最新文献

The world’s transportation system is overburdened by ever-growing travel demand, which brings mobility, safety, and pollution problems. To combat these issues and make better use of existing road capacity on urban arterials, public transit buses are designed to carry more people in fewer vehicles. However, transit buses travel slowly and make frequent intermittent stops, resulting in unreliable travel times and inconvenient riding experiences; this hinders people from choosing to travel on public transit buses. However, a research gap exists in using connected and automated vehicle (CAV) technologies specifically for transit bus operation optimization. To bridge this gap, the present study extended CAV applications to transit bus operation and developed a transit bus control method based on cooperative adaptive cruise control (CACC). The proposed model first optimized bus segment speeds to minimize schedule deviations and fuel consumption. Then, a CACC algorithm was integrated with optimal segment speed. The proposed control method was implemented through micro-simulations of an actual corridor in Jinan, Shandong, China. The evaluation results indicate that the proposed control method reduced the total arrival deviation up to 65.1% and total fuel consumption up to 6.8%. The study adapts CAV technologies to transit bus operation. The findings in this study validate CAV applications in transit bus operation.

We evaluate three strategies that transit operators might consider to increase ridership: a) increasing service on bus routes serving the highest share of low-income riders, b) increasing service on those bus routes with the highest ridership, and c) further providing the high-ridership routes identified in strategy (b) with exclusive bus lanes. In each scenario, we double the service frequency of buses on the focus routes and reduce the frequency on all other routes to maintain the total vehicle revenue miles, making the changes roughly cost-neutral. We tested these scenarios for Oshkosh, Wisconsin, and Atlanta, Georgia, using a modeling framework that combines CityCast, a commercially available data-driven planning tool to replicate observed travel patterns, and MATSim to simulate how travelers would change the route, mode, and time-of-day of the trips they make in response to the service changes. The results show substantial ridership gains for all but one scenario, suggesting that these strategies may provide a promising, low-cost means of increasing transit ridership in some contexts. However, impacts varied across the two case studies, indicating that local conditions play a role.

Utilizing passenger rail, including subways, to transport goods can have advantages over trucking in terms of efficiency and emissions. While some experimentation is ongoing in this area, combined passenger and rail opportunities in specific cities merit further attention. To more concretely examine how to leverage passenger rail for freight, this paper explores the potential of utilizing unused capacity in New York City (NYC) subway trains for transporting goods. Using General Transit Feed Specification (GTFS), rail and passenger data for the NYC subway, we found ways to use excess capacity and existing rail lines for freight transportation. We visualized a freight train timetable and graph, analyzed meet-errors between freight and passenger trains, and formulated prevention policies. Using U.S. Environmental Protection Agency data, we estimated emission reductions from replacing trucks with unused subway capacity. Our findings suggest that with adequate policies, investments and redesign, combining passenger rai and freight in the subways could significantly reduce truck trips, traffic congestion, and greenhouse gas emissions compared to trucking alone. However, implementing this approach requires careful collaborative planning, investment, enhanced security screening, and streamlined operations to minimize impacts on passenger transport. Further efforts should explore in more depth the costs and benefits and practical design and policy issues around using excess passenger rail capacity for freight transport in NYC and other cities.

In Indonesia, issues in the metropolitan transportation sector are considered severe. For instance, peripheral districts in the Jakarta metropolitan area (JMA), such as Bogor, Depok, Tangerang and Bekasi, contribute to the high mobility rate within the metropolitan area. This article examines the extent of motorcycle-based ride-hailing for commuting in the JMA and Bandung metropolitan areas (BMA). In particular, this study explores ride-hailing users’ characteristics—social, economic and spatial—and their proportion to the total commuter mobility in a metropolitan area. The study employed descriptive statistical models using commuter data in the JMA and BMA, respectively. Our results indicate that young and lower-income commuters are the dominant users of ride-hailing services. As motorcycle taxi services are relatively cheaper and accessible, young and lower-income commuters, including informal workers, prefer ride-hailing services. The study also suggests the impact of the intensification of inter-peri-urban mobilities of post-suburbanisation on the increasing demand for ride-hailing. In this sense, the study proposes that the long-overdue strengthening of metropolitan-scale governance is urgently required. It is also crucial for metropolitan governments to issue appropriate inter-district public transportation policies and engage in development.

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.

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.

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.

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.