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.