No abstract

HERE ARE 19,678 AIRPORTS, heliports, seaplane bases, and other landing facilities in the United States and its territories. Among them, 3,332 are included in the U.S. Federal Aviation Administration's National Plan of Integrated Airport Systems; they are open to the public and eligible for federal funding via the agency's Airport Improvement Program. Out of the total number of airports, 14,583 are for public use, and 5,105 are private. Six are owned by the U.S. Coast Guard, 96 by the U.S. Air Force, and 69 by the U.S. Navy; 137 are military owned, 14,408 are privately held, and 4,901 are publicly maintained. There are types of airports based on two definitions: statuary and policy. Among statuary airports, there are 395 primary facilities, including large, medium, small, and nonhub commercial service airfields, and 2,937 nonprimary airports, including nonhub commercial service, reliever, and general aviation terminals. Considering policy airports, there are four classifications, including 89 national, 531 regional, 1,261 local, and 813 basic airfields, in addition to 256 unclassified facilities. Airport infrastructure supports different transportation modes, including ground (transit buses, railways, cargo vehicles, and so on) and aviation (commercial and cargo planes as well as helicopters). Opportunities and Challenges Aviation operation is evaluated based on the safety, economic, environmental,

Promoting battery electric buses (BEBs) can reduce fuel consumption and air pollution from the transit system. A complete transition from the current diesel fleet to BEBs is costly and time-consuming. Thus, the intermediate solution is a combination of diesel, hybrid, and BEBs. Therefore, a planning framework is required that simultaneously tackles three contiguous aspects of transit electrification and their interconnections, namely charging infrastructure, fleet configuration, and scheduling. Accordingly, this study considers a mixed fleet of diesel and BEBs. It aims to concurrently find (i) the optimal location and capacity of charging infrastructure, considering micro-grid specifications, the impact of distributed energy resources, and time-of-use electricity rates and (ii) optimum operation and refueling strategies. Another objective of this study is to capture the impacts of adverse weather conditions on transit electrification. A mixed-integer problem is proposed and solved using a metaheuristic algorithm based on simulated annealing to minimize system costs, including infrastructure, fleet, and operation costs. A subnetwork of transit in Worcester, Massachusetts, is selected as a case study, including three routes, five candidate charging locations, and three bus types. Findings suggest that BEBs can operate and serve the passenger demand with sufficient charging infrastructure. Sensitivity analyses show that even though high-power chargers are more expensive per piece, they reduce the overall cost as fewer chargers are required. The cost rises for chargers with power of 350 kW or more. It is worth noting that the benefits of BEBs are more significant in smaller buses and are heavily affected by adverse weather conditions.

No abstract

Rising urban population, aging infrastructure, and increasing capital maintenance costs call for more efficient use of limited available resources. To address these concerns, the use of technology for urban infrastructure management and operational efficiency comes naturally with emerging technological advancements. Although there have been analyses on how to conceptually design a smart city from the ground up, they are often less applicable in transforming existing cities into smart ones. Retrofitting existing infrastructures requires integration and synergies with existing systems. Given the broad scope of smart cities, this paper equips planners with surface-level considerations in adopting smart mobility solutions. This provides an avenue to assess project feasibility, risk management, and investment requirement. The process is presented via a replicable framework with a use case with simplistic approaches that do not require complex constraints or modeling. The framework streamlines how to deduce a feasible set of user-centric smart solutions, which are then ranked according to their impacts for implementation priority. Middle East Technical University campus located in Ankara (Turkey) is considered for the use case. The main outcomes for the use case are deducing high-impact smart solutions based on the proposed framework. Preliminary system design analyses are showcased for three high-ranked solutions: electric vehicle charging station installation and investment optimization, autonomous electric shuttle system design, and bus network electrification strategies.