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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Economic Analysis of On-Route Fast Charging for Battery Electric Buses: Case Study in Utah

Battery electric buses (BEBs) are increasingly being embraced by transit agencies as an energy-efficient and emission-free alternative to bus fleets. However, because of the limitations of battery technology, BEBs suffer from limited driving range, great battery cost, and time-consuming charging processes. On-route fast charging technology is gaining popularity as a remedy, reducing battery cost, extending driving range, and reducing charging time. With on-route fast charging, BEBs are as capable as their diesel counterparts in relation to range and operating time. However, transit agencies may have the following concerns about on-route fast charging: 1) on-route fast charging stations require massive capital costs; 2) on-route fast charging may lead to high electricity power demand charges; and 3) charging during peak hours may increase electricity energy charges. This study conducts a quantitative economic analysis of on-route fast charging for BEBs, thereby providing some guidelines for transit agencies. An integrated optimization model is first proposed to determine battery size, charger type, and recharging schedule for a general BEB route. Based on the model, an economic analysis of on-route fast charging is then performed on 10 real-world bus routes and a simplified general bus route with different parameters. The results demonstrate that given the current prices of on-route fast charging stations and batteries, it is always beneficial to install on-route fast charging stations for BEBs. A sensitivity analysis is also conducted to show the impact of potential price reductions of batteries.

Engineering↗
NASA NTRS2012

An Evaluation of Controller and Pilot Performance, Workload and Acceptability under a NextGen Concept for Dynamic Weather Adapted Arrival Routing

In todays terminal operations, controller workload increases and throughput decreases when fixed standard terminal arrival routes (STARs) are impacted by storms. To circumvent this operational constraint, Prete, Krozel, Mitchell, Kim and Zou (2008) proposed to use automation to dynamically adapt arrival and departure routing based on weather predictions. The present study examined this proposal in the context of a NextGen trajectory-based operation concept, focusing on the acceptability and its effect on the controllers ability to manage traffic flows. Six controllers and twelve transport pilots participated in a human-in-the-loop simulation of arrival operations into Louisville International Airport with interval management requirements. Three types of routing structures were used: Static STARs (similar to current routing, which require the trajectories of individual aircraft to be modified to avoid the weather), Dynamic routing (automated adaptive routing around weather), and Dynamic Adjusted routing (automated adaptive routing around weather with aircraft entry time adjusted to account for differences in route length). Spacing Responsibility, whether responsibility for interval management resided with the controllers (as today), or resided with the pilot (who used a flight deck based automated spacing algorithm), was also manipulated. Dynamic routing as a whole was rated superior to static routing, especially by pilots, both in terms of workload reduction and flight path safety. A downside of using dynamic routing was that the paths flown in the dynamic conditions tended to be somewhat longer than the paths flown in the static condition.

Johnson, Walter W.↗
NASA NTRS2012

Identification of Robust Terminal-Area Routes in Convective Weather

Convective weather is responsible for large delays and widespread disruptions in the U.S. National Airspace System, especially during summer. Traffic flow management algorithms require reliable forecasts of route blockage to schedule and route traffic. This paper demonstrates how raw convective weather forecasts, which provide deterministic predictions of the vertically integrated liquid (the precipitation content in a column of airspace) can be translated into probabilistic forecasts of whether or not a terminal area route will be blocked. Given a flight route through the terminal area, we apply techniques from machine learning to determine the likelihood that the route will be open in actual weather. The likelihood is then used to optimize terminalarea operations by dynamically moving arrival and departure routes to maximize the expected capacity of the terminal area. Experiments using real weather scenarios on stormy days show that our algorithms recommend that a terminal-area route be modified 30% of the time, opening up 13% more available routes that were forecast to be blocked during these scenarios. The error rate is low, with only 5% of cases corresponding to a modified route being blocked in reality, whereas the original route is in fact open. In addition, for routes predicted to be open with probability 0.95 or greater by our method, 96% of these routes (on average over time horizon) are indeed open in the weather that materializes

Pfeil, Diana Michalek↗
DOE OSTI2021

Multi-objective Eco-Routing Model Development and Evaluation for Battery Electric Vehicles.

This paper develops a multi-objective eco-routing algorithm (combined eco- and travel time-optimum routing) for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs) and investigates the network-wide impacts of the proposed multi-objective Nash optimum (user equilibrium) traffic assignment on a large-scale network. Eco-routing is a technique that finds the most energy efficient route. ICEV and BEV energy consumption patterns are significantly different with regard to their sensitivity to driving cycles. Unlike ICEVs, BEVs are more energy efficient on low-speed arterial trips compared to highway trips. Different energy consumption patterns require different eco-routing strategies for ICEVs and BEVs. This study found that single objective eco-routing could significantly reduce the energy consumption of BEVs but also significantly increase their average travel time. Consequently, the study developed a multi-objective routing model (eco- and travel time-routing) to improve both energy and travel time measures. The model introduced a link cost function that uses the specification of the value of time and the cost of fuel/energy. The simulation study found that multi-objective routing could reduce the BEV energy consumption by 13.5%, 14.2%, 12.9%, and 10.7%, as well as ICEV fuel consumption by 0.1%, 4.3%, 3.4%, and 10.6% for “not congested, “slightly congested,” “moderately congested,” and “highly congested” conditions, respectively. The study also found that multi-objective user equilibrium routing reduced the average vehicle travel time by up to 10.1% compared to the standard user equilibrium traffic assignment for highly congested conditions, producing a solution closer to the system optimum traffic assignment. The results indicate that the proposed multi-objective eco-routing strategy can reduce vehicle fuel/energy consumption effectively with minimum impacts on travel times for both BEVs and ICEVs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2013

Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model

Contact Graph Routing (CGR) for Delay/Disruption Tolerant Networking (DTN) space-based networks makes use of the predictable nature of node contacts to make real-time routing decisions given unpredictable traffic patterns. The contact graph will have been disseminated to all nodes before the start of route computation. CGR was designed for space-based networking environments where future contact plans are known or are independently computable (e.g., using known orbital dynamics). For each data item (known as a bundle in DTN), a node independently performs route selection by examining possible paths to the destination. Route computation could conceivably run thousands of times a second, so computational load is important. This work refers to the simulation software model of Enhanced Contact Graph Routing (ECGR) for DTN Bundle Protocol in JPL's MACHETE simulation tool. The simulation model was used for performance analysis of CGR and led to several performance enhancements. The simulation model was used to demonstrate the improvements of ECGR over CGR as well as other routing methods in space network scenarios. ECGR moved to using earliest arrival time because it is a global monotonically increasing metric that guarantees the safety properties needed for the solution's correctness since route re-computation occurs at each node to accommodate unpredicted changes (e.g., traffic pattern, link quality). Furthermore, using earliest arrival time enabled the use of the standard Dijkstra algorithm for path selection. The Dijkstra algorithm for path selection has a well-known inexpensive computational cost. These enhancements have been integrated into the open source CGR implementation. The ECGR model is also useful for route metric experimentation and comparisons with other DTN routing protocols particularly when combined with MACHETE's space networking models and Delay Tolerant Link State Routing (DTLSR) model.

Segui, John S.↗
NASA NTRS2016

Airspace Technology Demonstration 3 (ATD-3): Dynamic Weather Routes (DWR) Technology Transfer Document Summary Version 1.0

Airspace Technology Demonstration #3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multiyear research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the first of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. This transfer consists of NASA's legacy Dynamic Weather Routes (DWR) work for efficient routing for en-route weather avoidance. DWR is a ground-based trajectory automation system that continuously and automatically analyzes active airborne aircraft in en route airspace to identify opportunities for simple corrections to flight plan routes that can save significant flying time, at least five minutes wind-corrected, while avoiding weather and considering traffic conflicts, airspace sector congestion, special use airspace, and FAA routing restrictions. The key benefit of the DWR concept is to let automation continuously and automatically analyze active flights to find those where simple route corrections can save significant time and fuel. Operators are busy during weather events. It is more effective to let automation find the opportunities for high-value route corrections.

ATD-3↗
NASA NTRS2021

Development of Near-term Urban Air Mobility Routes and Airspace Integration

Growing interest in Urban Air Mobility (UAM) has been demonstrated by a great deal of investment in related research made by industry, government, and academia. Based on this research effort along with considerations of the maturing concept for UAM airspace integration, a cognitive walkthrough exercise and a human-in-the-loop simulation were conducted with controller subject matter experts (SMEs) to evaluate Dallas-Fort Worth (DFW) current day helicopter routes for near-term use as UAM routes. One of the outcomes of this work is a set of heuristics that should be applied when designing UAM routes in the future. The following heuristics were identified as critical to UAM route design: the proximity of routes to surrounding airports (including approach and departure paths of traditional commercial traffic), the configuration of surrounding airports, avoiding congested or heavily populated areas, avoiding route segments that would go through several sectors, avoiding route segments that would go in and out of Class B airspace, creating routes outside of Class B airspace when able, using routes with two-way, altitude-separated traffic when able, minimizing the length of the route, avoiding commonly placed Temporary Flight Restrictions, and creating Non-Movement Areas or UNICOM Areas. This paper describes each of these identified heuristics and relevant examples based on a human-in-the-loop study conducted using the DFW area airspace.

Urban Air Mobility↗
NASA NTRS2003

Evaluation of a Dispatcher's Route Optimization Decision Aid to Avoid Aviation Weather Hazards

This document describes the results and analysis of the formal evaluation plan for the Honeywell software tool developed under the NASA AWIN (Aviation Weather Information) 'Weather Avoidance using Route Optimization as a Decision Aid' project. The software tool aims to provide airline dispatchers with a decision aid for selecting optimal routes that avoid weather and other hazards. This evaluation compares and contrasts route selection performance with the AWIN tool to that of subjects using a more traditional dispatcher environment. The evaluation assesses gains in safety, in fuel efficiency of planned routes, and in time efficiency in the pre-flight dispatch process through the use of the AWIN decision aid. In addition, we are interested in how this AWIN tool affects constructs that can be related to performance. The construct of Situation Awareness (SA), workload, trust in an information system, and operator acceptance are assessed using established scales, where these exist, as well as through the evaluation of questionnaire responses and subject comments. The intention of the experiment is to set up a simulated operations area for the dispatchers to work in. They will be given scenarios in which they are presented with stored company routes for a particular city-pair and aircraft type. A diverse set of external weather information sources is represented by a stand-alone display (MOCK), containing the actual historical weather data typically used by dispatchers. There is also the possibility of presenting selected weather data on the route visualization tool. The company routes have not been modified to avoid the weather except in the case of one additional route generated by the Honeywell prototype flight planning system. The dispatcher will be required to choose the most appropriate and efficient flight plan route in the displayed weather conditions. The route may be modified manually or may be chosen from those automatically displayed.

Dorneich, Michael C.↗
NASA NTRS2010

Meeting Air Transportation Demand in 2025 by Using Larger Aircraft and Alternative Routing to Complement NextGen Operational Improvements

A study was performed that investigates the use of larger aircraft and alternative routing to complement the capacity benefits expected from the Next Generation Air Transportation System (NextGen) in 2025. National Airspace System (NAS) delays for the 2025 demand projected by the Transportation Systems Analysis Models (TSAM) were assessed using NASA s Airspace Concept Evaluation System (ACES). The shift in demand from commercial airline to automobile and from one airline route to another was investigated by adding the route delays determined from the ACES simulation to the travel times used in the TSAM and re-generating new flight scenarios. The ACES simulation results from this study determined that NextGen Operational Improvements alone do not provide sufficient airport capacity to meet the projected demand for passenger air travel in 2025 without significant system delays. Using larger aircraft with more seats on high-demand routes and introducing new direct routes, where demand warrants, significantly reduces delays, complementing NextGen improvements. Another significant finding of this study is that the adaptive behavior of passengers to avoid congested airline-routes is an important factor when projecting demand for transportation systems. Passengers will choose an alternative mode of transportation or alternative airline routes to avoid congested routes, thereby reducing delays to acceptable levels for the 2025 scenario; the penalty being that alternative routes and the option to drive increases overall trip time by 0.4% and may be less convenient than the first-choice route.

Smith, Jeremy C.↗
DOE OSTI2021

Routing packets based on congestion metric thresholds and weights

A technique includes receiving a packet at a network device, wherein the packet is to be routed in a network to a destination network device; determining a plurality of candidate routes for the packet to be routed to the destination network device; grouping the plurality of candidate routes into a first set of candidate routes and a second set of candidate routes based on hop counts associated with the plurality of candidate routes; selecting one of the first or second sets based on a congestion metric threshold; selecting a candidate route from the selected first or second set based on weight metric values associated with the candidate routes of the selected first or second set; and selecting an egress port associated with the selected candidate route.

McDonald, Nicholas George↗
DOE OSTI2026

Quantum Routing and Entanglement Dynamics Through Bottlenecks

To implement arbitrary quantum circuits in architectures with restricted interactions, one may effectively simulate all-to-all connectivity by routing quantum information. We consider the entanglement dynamics and routing between two regions only connected through an intermediate “bottleneck” region with few qubits. In such systems, where the entanglement rate is restricted by a vertex boundary rather than an edge boundary of the underlying interaction graph, existing results such as the small incremental entangling theorem give only a trivial constant lower bound on the routing time (the minimum time to perform an arbitrary permutation). We significantly improve the lower bound on the routing time in systems with a vertex bottleneck. Specifically, for any system with two regions 𝐿,𝑅 with 𝑁 𝐿 ,𝑁 𝑅 qubits, respectively, coupled only through an intermediate region 𝐶 with 𝑁 𝐶 qubits, for any 𝛿 > 0 we show a lower bound of Ω⁢(𝑁$^{1−𝛿}_{𝑅}$/√𝑁 𝐿⁢ 𝑁 𝐶 ) on the Hamiltonian quantum routing time when using piecewise time-independent Hamiltonians, or time-dependent Hamiltonians subject to a smoothness condition. We also prove an upper bound on the average amount of bipartite entanglement between 𝐿 and 𝐶,𝑅 that can be generated in time 𝑡 by such architecture-respecting Hamiltonians in systems constrained by vertex bottlenecks, improving the scaling in the system size from 𝑂⁡(𝑁 𝐿⁢ 𝑡) to 𝑂⁡(√𝑁 𝐿⁢ 𝑡). As a special case, when applied to the star graph (i.e., one vertex connected to 𝑁 leaves), we obtain an Ω⁡(√𝑁 1−𝛿 ) lower bound on the routing time and on the time to prepare 𝑁/2 Bell pairs between the vertices. We also show that, in systems of free particles, we can route optimally on the star graph in time Θ⁡(√𝑁) using Hamiltonian quantum routing, obtaining a speedup over gate-based routing, which takes time Θ⁡(𝑁).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Analysis of Multi-Flight Common Routes for Traffic Flow Management

This paper presents an approach for creating common weather avoidance reroutes for multiple flights and the associated benefits analysis, which is an extension of the single flight advisories generated using the Dynamic Weather Routes (DWR) concept. These multiple flight advisories are implemented in the National Airspace System (NAS) Constraint Evaluation and Notification Tool (NASCENT), a nation-wide simulation environment to generate time- and fuel-saving alternate routes for flights during severe weather events. These single flight advisories are clustered together in the same Center by considering parameters such as a common return capture fix. The clustering helps propose routes called, Multi-Flight Common Routes (MFCR), that avoid weather and other airspace constraints, and save time and fuel. It is expected that these routes would also provide lower workload for traffic managers and controllers since a common route is found for several flights, and presumably the route clearances would be easier and faster. This study was based on 30-days in 2014 and 2015 each, which had most delays attributed to convective weather. The results indicate that many opportunities exist where individual flight routes can be clustered to fly along a common route to save a significant amount of time and fuel, and potentially reducing the amount of coordination needed.

weather uncertainty↗
NASA NTRSDate not supplied

Contact Multigraph Routing: Overview and Implementation

In Delay Tolerant Networking (DTN), the standard routing algorithm used to navigate time-varying networks has been Contact Graph Routing (CGR). In CGR, a globally distributed list of contacts, periods during which two DTN nodes may communicate, is used to construct a contact graph, in which contacts are vertices. A version of Dijkstra’s algorithm can then be used to find paths through this model of the timevarying network. However, since contact graphs may be large compared to the network, potentially growing with the square of the number of network nodes and linearly with the time interval represented, the resulting algorithm does not scale well with the size of the network or time. Any improvement to the routing algorithm will bring significant returns to scale. In a previous paper, we briefly introduced an alternative to the contact graph model for routing. This alternative model is based on a multigraph (a graph in which there may be multiple edges between a pair of vertices) where vertices represent network nodes instead of contacts. A version of Dijkstra’s algorithm in these multigraph models reduces the time needed to perform the same routing computations done in the existing CGR algorithm. Moreover, a modified version of Yen’s algorithm for multigraphs is included. Our variation of CGR, which we call Contact Multigraph Routing (CMR), provides an in-line replacement for the previously used pathfinding algorithms. This paper describes an implementation created based on the CMR approach, and experimental comparisons to traditional CGR are given. In addition, we explore some additional modifications to the routing pipeline traditionally assumed in CGR. These modifications range from the theoretical to the practical in terms of size and scope. We step forward our understanding of sheaftheoretic networking and describe how to model the routing pipeline using sheaves. We detail some enhanced route selection criteria that addresses some of the added complexity of DTNbased systems. We also include a future works section on future improvements and implementations that would be of service to the broader DTN community.

contact graph routing↗
DOE OSTI2021

Multi-objective Eco-Routing Model Development and Evaluation for Battery Electric Vehicles

This paper develops a multi-objective eco-routing algorithm (eco- and travel time-optimum routing) for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs) and investigates the network-wide impacts of the proposed multi-objective Nash optimum (user equilibrium) traffic assignment on a large-scale network. Unlike ICEVs, BEVs are more energy efficient on low-speed arterial trips compared with highway trips. Different energy consumption patterns require different eco-routing strategies for ICEVs and BEVs. This study found that single-objective eco-routing could significantly reduce the energy consumption of BEVs but also significantly increase their average travel time. Consequently, the study developed a multi-objective routing model (eco- and travel time-routing) to improve both energy and travel time measures. The model introduced a link cost function that uses the specification of the value of time and the cost of fuel/energy. The simulation study found that multi-objective routing could reduce BEV energy consumption by 13.5%, 14.2%, 12.9%, and 10.7%, as well as ICEV fuel consumption by 0.1%, 4.3%, 3.4%, and 10.6% for “not congested, “slightly congested,”“moderately congested,” and “highly congested” conditions, respectively. The study also found that multi-objective user equilibrium routing reduced the average vehicle travel time by up to 10.1% compared with the standard user equilibrium traffic assignment for highly congested conditions, producing a solution closer to the system optimum traffic assignment. The results indicate that the proposed multi-objective eco-routing strategy can reduce vehicle fuel/energy consumption effectively with minimum impacts on travel times for both BEVs and ICEVs.

Engineering↗
NASA NTRS1979

A graph-theoretic method to quantify the airline route authority

The paper introduces a graph-theoretic method to quantify the legal statements in route certificate which specifies the airline routing restrictions. All the authorized nonstop and multistop routes, including the shortest time routes, can be obtained, and the method suggests profitable route structure alternatives to airline analysts. This method to quantify the C.A.B. route authority was programmed in a software package, Route Improvement Synthesis and Evaluation, and demonstrated in a case study with a commercial airline. The study showed the utility of this technique in suggesting route alternatives and the possibility of improvements in the U.S. route system.

Chan, Y.↗
NASA NTRS2016

Routing Based on Length of Time of Available Connection

In an embodiment, a method of routing packets at a first node in an ad-hoc network is provided. The method includes receiving, at the first node, a plurality of route-alive messages corresponding to a destination, each of the plurality of route-alive messages including a route time indicating a length of time in which a communicative connection is available between the second node that sent the respective route-alive message and the destination. The method also includes determining an updated route time for each second node. The updated route time corresponds to a length of time in which a communication connection is available between the first node and the destination through the respective second node. A second node is selected for sending a packet to based on the updated route time for each of the second nodes, wherein a node having a longer updated route time is given higher priority for selection.

Anandappan, Thanga↗
NASA NTRS2018

Airspace Technology Demonstration 3 (ATD-3) Multi-Flight Common Route (MFCR) Technology Transfer Document Summary Version 2.0

Airspace Technology Demonstration - 3 (ATD-3) is part of NASA's Airspace Operations and Safety Program (AOSP) - specifically, its Airspace Technology Demonstrations (ATD) Project. ATD-3 is a multi-year research and development effort which proposes to develop and demonstrate automation technologies and operating concepts that enable air navigation service providers and airspace users to continuously assess weather, winds, traffic, and other information to identify, evaluate, and implement workable opportunities for flight plan route corrections that can result in significant flight time and fuel savings in en-route airspace. In order to ensure that the products of this tech-transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying technology artifacts satisfy the second of three Research Transition Products (RTPs) defined in the Applied Traffic Flow Management (ATFM) Research Transition Team (RTT) Plan. The original transfer, completed in December 2017, consisted of NASA's Multi-Flight Common Route (MFCR) research for efficient route corrections for en-route weather avoidance. This transfer updates the Concept of Operations document to a publicly-available NASA Technical Memorandum. The MFCR concept builds on the experience of the legacy Dynamic Weather Routes (DWR) and focuses on a better balance of potential savings with ATC acceptability, common route corrections options for multiple flights on similar routings, and better use of existing and/or modern automation for communication and coordination of route change options. All of these capabilities are expected to improve system performance significantly in terms of actual delay-reducing clearances issued to flights compared to that of the DWR tool and operating concept.

Tech transfer↗
NASA NTRS2019

Exploration of Near-Term Potential Routes and Procedures for Urban Air Mobility

Urban air mobility is gaining interest as the need for On Demand Mobility in today's congested traffic is becoming high in metropolitan areas. Urban Air Mobility (UAM) is envisioned as a concept to transport passengers and cargo safely and efficiently using innovative aircraft in the urban areas. It is expected to improve mobility for the general public, decongest road traffic, reduce transport time and reduce the strain on existing public transport networks. There exist several challenges to Urban Air Mobility (UAM) such as integration of procedures with airspace and the airport, noise levels that are acceptable to the general public, public safety, public acceptance, vehicle certification, and more. Most of the research in the United States and European skies (DLR - German Aerospace Center) related to urban areas has focused on small UAS (Unmanned Aircraft Systems) flights (NASA's UTM (UAS Traffic Management) research) and their integration with the airspace and building safe operations in densely populated areas. Previous studies on UAM have focused on fast time simulations of the routes that are separated via a separation service and network of routes. Similarly, research in Europe has focused on the approach profile for these innovative aircraft, vertiports and battery life among others. UAM as a part of the On-Demand Mobility effort has provided some guidelines for operations as shown below: Does not require additional ATC (Air Traffic Control) infrastructure; Does not impose additional workload on ATC; Does not restrict operations of traditional airspace users; Will meet appropriate safety thresholds and requirements; Will prioritize operational scalability; Will allow flexibility where possible and structure where necessary. This paper explores potential routes and procedures in a Human-In-The-Loop (HITL) experiment that could be applied in the near-term to allow integration of UAM flights into the airspace as well as a large airport. The airspace that was explored was Dallas Fort Worth (DFW) airspace managed by the DFW East Tower in South Flow only. In addition, Dallas Love Field (DAL) and Addison (ADS) airspace were also part of the testbed. The initial set of routes investigated in this study were published helicopter routes in the DFW area. Figure 1 shows class B airspace in DFW area and the origin/destination city pairs where UAM flights flew along with helicopter routes shown in blue. The research focused on exploring procedures for integrating UAM flights into Class Bravo and Class Delta airspace. Three different communication procedures, evaluated with three different levels of UAM traffic, are shown in Table 1. The current day routes were evaluated with current day communication procedures were explored as the first condition. The current day routes were also evaluated in the second condition with reduced communications, which was assumed due to the presence of a Letter Of Agreement (LOA). The purpose of the LOA was to reduce the verbiage associated with pilots getting clearance to Class B airspace from the controllers, pre-assigning beacons codes to the UAM flights, separate routes by assigning altitudes and speeds to flights going in any one direction. Flights were expected to automatically change frequency when exiting Class B airspace, thus transition points for entry and exit points were also specified in the LOA.

Urban Air Mobility↗