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At least 1,495 records · Page 83

Development of Super Ensemble-Based Aviation Turbulence Guidance (SEATG) for Air Traffic Management

A new method for forecasting turbulence is developed and evaluated using the high resolution weather model and in situ turbulence observations from commercial aircraft. The new method is an ensemble of various turbulence metrics from multiple time-lagged ensemble forecasts created using a sequence of four procedures. These include weather modeling, calculation of turbulence metrics, mapping the metrics into a common turbulence-scale, and production of final forecast. The new method uses similar methodology as current operational turbulence forecast with three improvements. First, it uses a higher resolution ((delta)x = 3 km) weather model to capture cloud resolving scale phenomena. Second, it computes the metrics for multiple forecasts that are combined at the same valid time resulting in a time-lagged ensemble of multiple turbulence metrics. Finally, it provides both deterministic and probabilistic turbulence forecasts. Results show the new forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on research period. Overall performance skill of the new turbulence forecast compared with the observed EDR data during the research period is superior to any single turbulence metric. The probabilistic turbulence forecast is used in an example air traffic management application for creating a wind-optimal route considering turbulence information. The wind-optimal route passing through areas of 50% potential for moderate-or-greater turbulence and the lateral turbulence avoidance routes starting from three different waypoints along the wind-optimal route from Los Angeles international airport to John F. Kennedy international airport are calculated using different turbulence forecasts. This example shows additional flight time is required to avoid potential turbulence encounters.

modeling↗

Three-Dimensional Trajectory Design for Reducing Climate Impact of Trans-Atlantic Flights

The impact of aircraft emissions and contrails on the environment adds an additional aspect to aircraft trajectory optimization. This study developed a three-dimensional trajectory optimization algorithm for trans-Atlantic flights in cruise to generate aircraft trajectories that minimize environmental impacts due to CO2 emissions and contrails in the presence of winds. The climate-optimal trajectory is developed using dynamic programming that adjusts a wind-optimal aircraft heading while determining the optimal locations, altitudes and times for en-route step climbs. Flying wind-optimal routes minimize aircraft travel time, fuel burn and associated emissions during cruise while adjusting aircraft heading and en-route step climbs at the optimal locations and times minimize climate impact of contrails. This capability integrates an air traffic management simulation with aircraft fuel burn and emissions models, contrail formation and dispersion models, simplified climate response models, and a common climate metric. A study was conducted to evaluate the potential cost and benefits of flying climate-optimal routes in North Atlantic Airspace and their impacts to the Organized Track System design based on the trans-Atlantic air traffic during a day, July 12, 2012. Results show eastbound flights achieved a larger environmental benefit with less additional fuel burn than westbound flights that operated in strong headwinds that caused more additional fuel burn and aircraft emissions to avoid traversing contrails favorable regions.

climate impact of aviation↗

Impact of Different Trajectory Option Set Participation Levels within an Air Traffic Management Collaborative Trajectory Option Program

This paper presents the methodology and results of a Human-In-The-Loop (HITL) simulation study conducted in the Airspace Operations Laboratory at NASA Ames Research Center. This study is a part of NASA's ongoing research into developing an Integrated Demand Management (IDM) concept, whose aim is to improve traffic flow management (TFM) by coordinating the FAA's strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The purpose of TFM is to regulate air traffic demand so that it is delivered efficiently through constrained airspace resources without exceeding their capacity limits. The IDM concept leverages a new TFMS capability called the Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for managing traffic tactically by generating precise arrival schedules. Unlike other TFM tools, CTOP gives flight operators the option of submitting a set of user-preferred alternative trajectories for each flight. CTOP can then use these trajectory option sets (or TOSs) to find user-preferred alternative routes to reduce demand on an overloaded resource. CTOP's effectiveness in redistributing demand is limited, however, by the availability of flights with alternative routes. The research presented in this paper focuses on evaluating the impact on TFM operations by varying the percentage of flights that submit a multiple-option TOS ('TOS participation levels'). Results show the impact on overall system performance and on the rerouted flights themselves. The simulation used a Newark (EWR) airport arrival scenario, with en route weather affecting traffic inbound from the west. Participants were asked to control each of the three arrival flows (north, west, and south) to meet their individual capacity constraints while simultaneously ensuring efficient utilization of the capacity at the destination airport. A large, permeable convective weather cell located southeast of Chicago severely reduced the capacity of the west flow. The study evaluated the impact of five different TOS participation levels on CTOP's ability to re-allocate traffic from the west and improve TFM performance in terms of delay assignment and traffic delivery rate to the airport. Overall, the results showed that increasing TOS submissions allowed the overall system delays to be reduced and fairly distributed among the three arrival flows, at the same time achieving the airport throughput rate. Moreover, it was found that aircraft who submitted a TOS saw a greater reduction in delay, even when they were assigned longer routes. This was particularly true when fewer aircraft submitted a TOS. The results confirm that the CTOP operations with higher TOS participation levels helped utilize the overall National Airspace System (NAS) resources as well as benefited the users who participated.

Yoo, Hyo-Sang↗

Performance Evaluation of Conflict-Free Trajectory Taxiing in Airport Ramp Area Using Fast-Time Simulations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been collaborating to conduct joint research addressing future surface traffic management challenges. The surface management tool from DLR, called Taxi Routing for Aircraft: Creation and Controlling (TRACC), was adapted to be integrated in NASA's fast-time simulation environment called Surface Operations Simulator and Scheduler (SOSS). The research described in this paper 1) applied TRACC to trajectory-based ramp traffic management, where TRACC generates conflict-free aircraft trajectories in a congested ramp area, 2) investigated the feasibility of the concept through the integrated TRACC-SOSS fast-time simulation, and 3) evaluated the performance of the integrated system. For this activity, TRACC was adapted for ramp operations at Charlotte Douglas International Airport, called TRACC_PB (TRACC for pushback optimization). TRACC_PB provides four-dimensional taxi trajectories with a command speed profile for each aircraft following standard taxi routes within the ramp area. In this study, departures are given the Target Movement Area entry Times (TMATs) provided by the baseline surface metering scheduler based on NASA's Spot and Runway Departure Advisor (SARDA). TRACC_PB also calculates optimal pushback times for departures, as well as the times when arrivals shall enter the ramp, the Target Movement area Exit Times (TMETs). The initial results showed that the TRACC_PB successfully generated conflict-free trajectories for the ramp area taxi operations and improved taxiing efficiency compared to the baseline results. TRACC_PB aimed to provide conflict-free taxi routes avoiding any stops while taxiing. This resulted in longer gate hold times for departures and postponed throughput values compared to the baseline simulation without trajectory optimization. Having conflict-free routes without stoppage also created shorter taxi times but required renegotiation of the given TMATs. TRACC_PB also achieved reductions in both fuel consumption and engine emissions (17% for departures and 10% for arrivals), which correlate with the ramp taxi time reduction.

trajectory-based taxi operations↗

Evaluation of a Dynamic Weather-Avoidance Rerouting Tool in Adjacent-Center Arrival Metering

Dynamic Reroutes for Arrivals in Weather (DRAW) is a NASA-developed decision-support tool for Traffic Management Coordinators (TMCs) at the Federal Aviation Administration's Air Route Traffic Control Centers ("Centers"). DRAW proposes weather-avoidance reroutes for en route arrival flights subject to metering restrictions when transitioning into a busy terminal airspace. The prior DRAW study demonstrated that TMCs' use of DRAW promotes earlier reroutes of arrivals, and reduces the number of routes conflicting with weather in the Center. The present paper focuses on how DRAW benefits metering delivery accuracy when schedule freeze horizon distance was altered. A human-in-the-loop simulation was conducted at NASA Ames Research Center in October-November 2018, where retired TMCs and controllers performed simulated metering operations for southeast arrivals through the Atlanta and Jacksonville Centers to the Hartsfield-Jackson Atlanta International Airport during convective weather periods. Results demonstrated that DRAW use reduced the frequency of manual adjustments of Scheduled Times of Arrival and lowered TMC workload. DRAW use also made the metering accuracy, the number of reroute amendments after the freeze horizon, and the en route sector controller workload more robust to the effect of different freeze horizon distance.

Hayashi, Miwa↗

Evaluation of a Dynamic Weather-Avoidance Rerouting Tool in Adjacent-Center Arrival Metering

Dynamic Reroutes for Arrivals in Weather (DRAW) is a NASA-developed decision-support tool for Traffic Management Coordinators (TMCs) at the Federal Aviation Administration's Air Route Traffic Control Centers ("Centers"). DRAW proposes weather-avoidance reroutes for en route arrival flights subject to metering restrictions when transitioning into a busy terminal airspace. The prior DRAW study demonstrated that TMCs' use of DRAW promotes earlier reroutes of arrivals, and reduces the number of routes conflicting with weather in the Center. The present paper focuses on how DRAW benefits metering delivery accuracy when schedule freeze horizon distance was altered. A human-in-the-loop simulation was conducted at NASA Ames Research Center in October-November 2018, where retired TMCs and controllers performed simulated metering operations for southeast arrivals through the Atlanta and Jacksonville Centers to the Hartsfield-Jackson Atlanta International Airport during convective weather periods. Results demonstrated that DRAW use reduced the frequency of manual adjustments of Scheduled Times of Arrival and lowered TMC workload. DRAW use also made the metering accuracy, the number of reroute amendments after the freeze horizon, and the en route sector controller workload more robust to the effect of different freeze horizon distance.

Air Traffic Management (ATM)↗

The Value of Near Real-Time Earth Observations for Improved Flood Disaster Response

Information is a critical resource in disaster response scenarios. Data regarding the geographic extent, severity, and socioeconomic impacts of a disaster event can help guide emergency responders and relief operations, particularly when delivered within hours of data acquisition. Information from remote observations provides a valuable tool for assessing conditions "on the ground" more quickly and efficiently. Here, we evaluate the social value of a near real-time flood impact system using a disaster response case study, and quantify the Value of Information (VOI) of satellite-based observations for rapid response using a hypothetical flooding disaster in Bangkok, Thailand. MODIS imagery from NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) system is used to produce operational estimates of inundation depths and economic damages.These rapid Earth observations are coupled with a decision-analytical model to inform decisions on emergency vehicle routing. Emergency response times from vehicles routed using flood damage data are compared with baseline routes without the benefit of advance information on road conditions. Our results illustrate how the application of near real-time Earth observations can improve the response time and reduce potential encounters with flood hazards when compared with baseline routing strategies. Results indicate a potential significant economic benefit (i.e.,millions of dollars) from applying near real-time Earth observations for improved flood disaster response and management.

emergency response↗

Planning for Compilation of a Quantum Algorithm for Graph Coloring

Recently, the problem of compiling general quantum algorithms for implementation on near-term quantum processors has been introduced to the AI community. Previous work demonstrated that temporal planning is an attractive approach for part of this compilation task, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to theMaxCut problem on a quantum processor architecture. In this paper, we extend the earlier work to route circuits that implement QAOAfor Graph Coloring problems. QAOA for coloring requires execution of more, and more complex, operations on the chip, which makes routing a more challenging problem. We evaluate the approach on state-of-the-art hardware architectures from leading quantum computing companies. Additionally, we investigate applying the planning approach to qubit initialization as well as routing. Our empirical evaluation shows that temporal planning compares well to reasonable analytic upper bounds [20], and that solving qubit initialization with a classical planner generally helps temporal planners in finding shorter-makespan compilations for QAOA for Graph Coloring.These advances suggest that temporal planning can be an effective approach for more complex quantum computing algorithms and architectures.

Minh Do↗

Corridor Design and Analysis for UAM Operations

The Urban Air Mobility (UAM) concept is a part of Advanced Air Mobility (AAM), a joint initiative between the Federal Aviation Administration (FAA), NASA, and industry to develop an air transportation system that uses new electric (i.e., green) air vehicles in geographical areas previously underserved by traditional aviation. Market forecast studies predict that there will be demand for alternate modes of air transportation using electric Vertical Take-off and Landing aircraft. UAM expands transportation networks by introducing short flights to move people and goods around metropolitan areas​. UAM is expected to improve mobility for the public, decongest road traffic, reduce trip time, and decrease strain on existing public transportation networks. Various challenges exist to make the introduction of UAM operations successful in the U.S. National Airspace System (NAS). These include but are not limited to integration with existing airports and airspace, provision of air traffic services (e.g., separation), vehicle design and certification, and community acceptance. The focus of this paper is on integration of UAM operations into the NAS via introduction of new airspace structures. UAM will operate within a regulatory, operational, and technical environment that is incorporated into the NAS​. As per the UAM Concept of Operations (ConOps), the FAA retains regulatory authority and is responsible for establishing operational parameters and maintaining oversight. The FAA’s UAM ConOps describes flights at low altitudes (below 5,000 ft) with minimal disruption to established conventional aircraft traffic and limited voice interactions with the Air Traffic Control (ATC). Early stages of UAM may use existing procedures to safely integrate UAM with conventional flights. This would involve flying under Part 91 Visual Flight Rules (VFR) and using voice for communications. The initial UAM ecosystem will utilize the current infrastructure such as routes, helipads, and ATC services, where practicable. ​A NASA study explored the use of existing helicopter routes in Dallas Fort Worth (DFW) airspace for initial UAM operations with a Letter of Agreement (LOA) that included procedures to request a Class B (controlled airspace) clearance. The research showed that the chosen approach was feasible for near-term, low-demand UAM traffic, but was not scalable. The growth of operations in today’s aviation system has resulted in airspace reorganization and procedures to ensure safety and efficiency as traffic rates increase. One proposed operating innovation that can help with the scalability of UAM is establishing routes and corridors. This may look similar to the Area Navigation (RNAV) procedures used today to streamline operations into busy airports. However, instead of FAA automation systems and ATC managing the flow of traffic, some UAM concepts envision a third-party service provider performing this role as part of the Provider of Services for UAM (PSU) network. The FAA’s UAM ConOps posits that new airspace structures such as UAM corridors include the following design criteria: 1) Minimal impact on existing NAS operations, 2) no or minimal additional ATC services, 3) public interest considerations such as noise, safety, and security, and 4) customer needs. The airspace available in urban environments is limited by the height of buildings, the effect of weather including wind gusts, privacy needs, and a clearance envelope. The new airspace structure would need to be designed around large airports and urban areas where the initial market demand is likely to exist. NASA has started evaluating airspace in the Dallas Fort Worth area to design new airspace structures, keeping the first two design criteria in mind. It is assumed that there will be an on-board pilot-in-command, and the flights will operate under VFR in Visual Meteorological Conditions. Corridors will be required in controlled airspace, whereas UAM operations can fly in uncontrolled Class G and E airspace using current day rules. Keeler et. al identified factors and heuristics for development of routes for UAM operations for integration with airspace close to large airports such as Dallas Fort Worth and Dallas Love Field. This paper describes the heuristics applied to define the corridors, analyzes them with respect to legacy traffic and presents key results.

Urban Air Mobility↗

A Flight Replanning Tool for Terminal Area Urban Air Mobility Operations

In this presentation we describe and evaluate a flight replanning tool, called the trial planner, for terminal area air transport applications. The trial planner employs predefined airspace structures to generate rerouting options between vertiports. In a simplified definition, vertiports are facilities that provide services for managing the take-off and landing of autonomous or manned electric vertical take-off or landing (eVTOL) aircraft. The airspace structures involved in our test cases are arrival routes that consist of predefined entry points to which a transitional path is computed dynamically from the current position of the aircraft. Rerouting options include the transitional path and approach segment along the arrival route; these rerouting options are not vetted for potential conflicts with other operations until a human operator commits to a choice and forwards the flight plan modification for approval from an automated airspace management service. A selected rerouting option is executed by loading a flight plan file to the aircraft ground control station. We conducted a qualitative evaluation of the trial planner using ratings provided by flight crews and air transportation human factors experts with relevant experience from air traffic control. Evaluation criteria included trust in the route recommendations and adequate explanation for the route options. We detail the logic and implementation of the trial planner, as well as report the results of the evaluation of the implementation herein.

Trial planning↗

Advances in Modeling Solar System Internet Structures and their Data Flows

With an ever-increasing presence in space, there is also an increasing burden on existing communications infrastructure. We are heading towards an inflection point where the traditional approach of scheduled, single-path communications for space will no longer be viable. One answer is Delay Tolerant Networking (DTN), which takes the once disparate system of point-to-point links and unifies them in a networked architecture, thereby making communications more scalable. However, much work remains for discovering and harnessing the underlying theory of DTN. For example, in the terrestrial setting the interplay between routing domains is well-understood, however this is not the case in DTNs. In this paper, we build up the fundamental foundations of DTN, with an emphasis on modeling time varying networks and data flows across them, with examples of cross-domain routing in a DTN. A lofty goal of DTN is to enable the so-called Solar System Internet (SSI), which implies a standardized and robust suite of protocols. These protocols include routing across disconnected networks using store, carry, and forward mechanisms, which is necessary due to the disconnections, delays, and mobility intrinsic to space networks. Due to these factors, each of which generalize traditional networking, there is a deep and rich theory of DTNs. Here we build off of past successes to broaden this theory while striving to keep actionable results a goal for future implementations and operations. The approach includes modeling the unicast, broadcast, and multicast communications using the language of hypergraphs, which capture the geometric properties of such networked communications algebraically. Also inherent to these networks is their time-varying nature, particularly given mobility, and hence we also cultivate modeling techniques that respect this time dependence. This leads us to develop models using tools from category theory and algebraic geometry, which provide a language well-suited to describing synchronization and optimization over such networks. We also introduce and study a novel generalization of curvature applicable to time-evolving networks, which provides quantitative controls on diffusion processes on the network. Because an interplanetary network would feature links with propagation delays the preclude discovery (feedback) mechanisms, they will always feature a scheduled component. However, it is beneficial to support discovery where possible. While DTNs do not yet have strong definitions for their analogues of autonomous systems or network areas, we show how to join dynamic and schedule-based routing domains, using the language of sheaves, which marks progress towards such definitions. We conclude with a discussion of the progress made, as well as suggestions for future work.

Delay Tolerant Networking↗

Computing Proximity to Threat Along Uncertain Trajectory to Support Urban Air Mobility

Many airspace threats affect the selection of a flight route, such as terrain, physical obstacles, adverse weather, and special-use airspace, among others. Threat avoidance during Urban Air Mobility (UAM) and Low Altitude Mobility (LAM) flights is especially challenging due to their lower cruising altitudes. These operations may be exposed to buildings, towers, trees, terrain undulations, etc., along much of their flight route. Moreover, these low-altitude flights in urban environments are expected to encounter very busy airspace, increasing the workload associated with threat avoidance. The Proximity to Threat (PtT) function aims to support onboard or remote pilots by computing the risk from geospatial threats in the airspace along an aircraft’s flight path. The threats are both static entities and dynamic airspace restrictions that have been modeled and stored in geo-referenced mapping databases. The flight path may be specified by waypoints, airways, or similar discrete route elements or by a time series of closely spaced position and altitude points. Flight path uncertainty can also be taken into account by assuming both the position and altitude to be sampled from two normal distributions, each being specified by a mean and variance. PtT uses this additional information to verify that the flight path remains clear of threats along a wider path or if a position is reached earlier or later than anticipated, assuring the pilot or operator that there will be an available safety margin even if the aircraft deviates due to one or more occurrences of unexpected wind gusts, mechanical failures, airspeed changes, collision avoidance maneuvers, etc. The client can specify an uncertainty confidence level to bound the set of trajectories evaluated for threats so that the confidence level corresponds to the client’s risk tolerance under the expected conditions. PtT can be used as a pre-flight planning tool to determine a safe route through known threats and in-flight to avoid emerging or changing threats. In this report, we present the PtT function, discuss how the trajectory uncertainty is incorporated into the PtT function, and describe the use of this PtT function in a representative scenario.

urban air mobility↗

Wireless Power Transfer

Wireless Power Transfer is an innovative approach using magnetic resonance coupling of air core transformers designed for today's growing plug-in electric vehicle market. This technology can provide a convenient, safe and flexible means to charge electric vehicles under stationary and dynamic conditions. Plug-in Electric Vehicles (PEV) are burdened by the need for cable and plug charger, galvanic isolation of the on-board electronics, bulk and cost of this charger and the large energy storage system (ESS) packs needed. With a system where you have to physically plug in there are a number of occasions where the owner could very well forget to charge the vehicle. For stationary applications (like charging of a PHEV at home), ORNL's innovative wireless power transfer technology adds a convenience factor compared to actually plugging in which will mean that the vehicle will have a full charge every morning. Electric vehicle charging must be safe, compact and efficient in order to be convenient for customers. By reconfiguring the transformer and altering the resonance frequency, energy is transferred to the battery with lower energy losses and with fewer demands on the primary circuit by the rest of the transformer system. The ORNL discovery shows that sufficient power for the battery can be transferred from the primary to secondary circuits without significant energy losses if the operating frequency is set at 50% to 95% of the resonance frequency of the circuit. The electrical power is then transmitted to the chargeable battery, which is electrically coupled to the secondary circuit through the air core transformer. Some advantages include: Reduced energy losses during transfer of energy to the battery; A charge potential that is relatively unaffected by up to 25% misalignment of vehicle; and Other receiving components draw less power from the primary circuit. These advantages allow wireless power technology applications to expand at the workplace and beyond as the demand for EV rises. For vehicles that operate over a fixed route such as busses and shuttle vehicles, Wireless Power Transfer (WPT) means that a smaller battery pack can be used. In the traditional system, the battery pack is designed to accommodate the needs of the entire route or shift. With WPT the battery can be downsized because it can be charged when the vehicle stops on its route (a rental car shuttle bus, for example, can charge when it waits in the terminal and again when it waits at the rental car place. Thus the battery only needs enough charge to get to the next stop. This decrease in battery size means significant cost savings to electrify the vehicle. This technology enables efficient "opportunity charging stations" for predefined routes and planned stops reducing down time. Charging can occur in minutes. This improvement also eliminates the harmful emissions that occur in garages while buses are at idle during charging. In larger cities, dynamic charging offers an even greater impact utilizing existing infrastructure. As vehicles travel along busy freeways and interstate systems, wireless charging can occur while the vehicle is in motion. With this technology a vehicle essentially has unlimited electric range while using a relatively small battery pack. In-motion charging stations use vehicle sensors to alert the driver. Traveling at normal speeds, sensors establish in-motion charging. WPT transmit pads sequentially energize to the negotiated power level based on vehicle speed and its requested charging energy. Lower power when vehicle speed is slow and much higher power for faster moving vehicles. Vehicle to Infrastructure communications (V2I) coordinates WPT charging level according to on-board battery pack state-of-charge. V2I activates the roadway transmit pads placing them in standby mode and negotiates charging fee based on prevailing grid rate and vehicle energy demand. Dynamic charging would allow electricity to supply a very large fraction of the energy for the transportation sector and reduce greatly petroleum consumption. Previously worrisome traffic delays now provide longer periods of charge while passing over in-motion chargers. Inclement weather such as rain and snow do not affect the charging capability. At ORNL, we are working to develop the robust nature of wireless power technology to provide a convenient, safe and flexible means to charge electric vehicles under stationary and dynamic conditions.

33 ADVANCED PROPULSION SYSTEMS↗

Systems and methods for vehicle speed management

Controlling a speed of a vehicle based on at least a portion of a route grade and a route distance divided into a plurality of route sections, each including at least one of a section grade and section length. Controlling the speed of the vehicle is further based on determining a cruise control speed mode for the vehicle for each of the plurality of route sections and determining a speed reference command of the vehicle based on at least one of the cruise control speed mode, the section length, the section grade, and a current speed.

42 ENGINEERING↗

Using Map Service API for Driving Cycle Detection for Wearable GPS Data: Preprint

Following advancements in smartphone and portable global positioning system (GPS) data collection, wearable GPS data have realized extensive use in transportation surveys and studies. The task of detecting driving cycles (driving or car-mode trajectory segments) from wearable GPS data has been the subject of much research. Specifically, distinguishing driving cycles from other motorized trips (such as taking a bus) is the main research problem in this paper. Many mode detection methods only focus on raw GPS speed data while some studies apply additional information, such as geographic information system (GIS) data, to obtain better detection performance. Procuring and maintaining dedicated road GIS data are costly and not trivial, whereas the technical maturity and broad use of map service application program interface (API) queries offers opportunities for mode detection tasks. The proposed driving cycle detection method takes advantage of map service APIs to obtain high-quality car-mode API route information and uses a trajectory segmentation algorithm to find the best-matched API route. The car-mode API route data combined with the actual route information, including the actual mode information, are used to train a logistic regression machine learning model, which estimates car modes and non-car modes with probability rates. The experimental results show promise for the proposed method's ability to detect vehicle mode accurately.

33 ADVANCED PROPULSION SYSTEMS↗

Network reliability assessment

The present disclosure pertains to systems and methods for assessing reliability of communication links in a software defined network (SDN). In one embodiment, a system may include an SDN architecture subsystem configured to generate SDN architecture information and a bandwidth subsystem configured to generate bandwidth information. A latency subsystem may receive the bandwidth information from the bandwidth subsystem and may be configured to generate latency information using the bandwidth information. A failover subsystem may receive the SDN architecture information, the bandwidth information, and the latency information and generate a failover assessment and a failover route for the communication link. A reliability assessment subsystem may receive the SDN architecture information, the bandwidth information, and the latency information, and the failover assessment and generate a reliability assessment. A traffic routing subsystem may receive the reliability assessment and route data traffic to the failover route based on the reliability assessment.

Smith, Rhett↗

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗

NREL On-Demand Transit Research and Fort Erie Case Study

On-demand systems have increased in popularity in recent years, especially in rural and smaller-sized communities. This presentation provides a brief introduction to NREL's on-demand mobility research and an in-depth case study of the town of Fort Erie, Ontario. Fort Erie is a relatively sparsely populated region of 32,901 residents, spread across a land area of 166 square kilometers (64 square miles), for an average population density of 193 residents per square kilometer (500 per square mile). In October 2021, the town implemented a mobility-on-demand system integrated with smartphone software to replace its fixed-route community bus system, which consisted of four buses with three routes, each with a roughly 1-hour, one-way loop. The new service utilizes a fleet of six minivans, two of which are retrofitted with wheelchair-accessible ramps. The system may require that a passenger requesting a standard van walk up to 400 meters (a quarter mile) to their pickup location to optimize vehicle routing while providing origin-to-destination service. The on-demand system proved effective in providing service, eclipsing pre-pandemic ridership by 40%, decreasing greenhouse gas emissions per ride by 63%, and decreasing the cost to the town per ride by 29%. This presentation documents both the previous system and the new system in terms of routes, ridership, costs, fuel, and other notable system parameters. This work is part of an ongoing series of case studies on providing small communities with on-demand, right-sized vehicle service coupled with a smartphone application.

emerging technology↗