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At least 271 records · Page 15

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Robotic system for the servicing of the orbiter thermal protection system

This paper describes the design and development of a mobile robotic system to process orbiter thermal protection system (TPS) tiles. This work was justified by a TPS automation study which identified tile rewaterproofing and visual inspection as excellent applications for robotic automation.

Graham, Todd↗

Data-driven surface traversability analysis for Mars 2020 landing site selection

This paper is to describe the engineering challenges in the surface mobility of the Mars 2020 Rover mission that are considered in the landing site selection process, introduce new automated traversability analysis capabilities, and present the preliminary analysis results for top candidate landing sites.

Heverly, Matthew↗

Automation, robotics, and inflight training for manned Mars missions

The automation, robotics, and inflight training requirements of manned Mars missions will be supported by similar capabilities developed for the space station program. Evolutionary space station onboard training facilities will allow the crewmembers to minimize the amount of training received on the ground by providing extensive onboard access to system and experiment malfunction procedures, maintenance procedures, repair procedures, and associated video sequences. Considerable on-the-job training will also be conducted for space station management, mobile remote manipulator operations, proximity operations with the Orbital Maneuvering Vehicle (and later the Orbit Transfer Vehicle), and telerobotics and mobile robots. A similar approach could be used for manned Mars mission training with significant additions such as high fidelity image generation and simulation systems such as holographic projection systems for Mars landing, ascent, and rendezvous training. In addition, a substantial increase in the use of automation and robotics for hazardous and tedious tasks would be expected for Mars mission. Mobile robots may be used to assist in the assembly, test and checkout of the Mars spacecraft, in the handling of nuclear components and hazardous chemical propellent transfer operations, in major spacecraft repair tasks which might be needed (repair of a micrometeroid penetration, for example), in the construction of a Mars base, and for routine maintenance of the base when unmanned.

Holt, Alan C.↗

2021–2022 Can Do Colorado E-Bike Full-Scale Pilot Program Study

In 2021–2022, the Colorado Energy Office conducted a full-scale pilot program study on e-bike usage as part of the Can Do Colorado initiative, providing e-bikes to low-income participants across the state. A [2020 mini pilot program study](https://www.nlr.gov/transportation/secure-transportation-data/tsdc-2020-can-do-colorado-e-bike-pilot-program.html) informed the full-scale study. Both studies used pedal-assist e-bikes, which feature an electric motor and battery to help power the bike. The motor amplifies the power behind each pedal stroke, augmenting the energy you put into the bike. #### Data Collection Agency The Colorado Energy Office conducted the study in partnership with local organizations in Adams and Broomfield counties (Smart Commute Metro North), Boulder (Community Cycles), Durango (Four Corners Office for Resource Efficiency), Fort Collins (City of Fort Collins), Pueblo (Pueblo County), and Vail (Town of Vail). #### Survey Methodology Program participants received an e-bike and accessories at no cost and manually submitted travel data and feedback via the CanBikeCO smartphone app. Developed in partnership with NLR, the app used a customized version of the open-source [NLR OpenPATH platform](https://www.nlr.gov/transportation/openpath.html). #### Survey Records and Data Survey records include 170 participants. The six datasets contain up to 18 months of partially automated travel diaries, combining sensed and surveyed travel behavior data—patterns of multimodal, end-to-end, individual human mobility—as well as demographic information from participants. The number of e-bike trips and e-bike miles traveled per location are 1,560 and 4,179 for Adams and Broomfield counties; 8,481 and 27,000 for Boulder; 2,815 and 6,307 for Durango; 3,483 and 7,080 for Fort Collins; 4,022 and 14,887 for Pueblo, and 1,206 and 3,3361 for Vail.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2022 Bull E-Bike Pilot Program Study

In 2022, the City of Durham conducted an e-bike pilot program study to learn more about how electric bikes (e-bikes) could improve the transportation experience in the "Bull City" (a.k.a., Durham, North Carolina). The study used pedal-assist e-bikes, which feature an electric motor and battery to help power the bike. The motor amplifies the power behind each pedal stroke, augmenting the energy you put into the bike. #### Data Collection Agency The City of Durham's Transportation Department conducted the study. #### Survey Methodology Program participants used electric-assist e-bikes for at least 4 weeks between August and November 2022 in exchange for sharing information about their experiences, including tracking their travel via a smartphone app. In addition to the e-bike, participants received maintenance support along with a helmet, bike lock, and other accessories. Data collection was enabled by the [NLR OpenPATH platform](https://www.nlr.gov/transportation/openpath.html). #### Survey Records and Data Survey records include a total of 76 participants. The dataset contains 3 months of partially automated travel diaries, combining sensed and surveyed travel behavior data—patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from participants. The number of total trips was 6,488, the number of e-bike trips was 2,183, and the number of e-bike miles traveled was 5,450.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Airspace Technology Demonstration 2 (ATD-2) Phase 2 Technology Description Document (TDD)

This Technology Description Document (TDD) provides an overview of the technology for the Phase 1 Baseline and Phase 2 Fused demonstrations of the Integrated Arrival, Departure, and Surface (IADS) prototype system of the National Aeronautics and Space Administration’s (NASA) Airspace Technology Demonstration 2 (ATD-2) project, which has been demonstrated since October of 2017 at Charlotte Douglas International Airport (CLT). Development, integration, and field demonstration of relevant technologies of the IADS system directly address recommendations made by the Next Generation Air Transportation System (NextGen) Integration Working Group (NIWG) on Surface and Data Sharing and the Surface Collaborative Decision Making (Surface CDM) concept of operations developed jointly by the Federal Aviation Administration (FAA) and aviation industry partners. NASA has been developing the IADS traffic management system under the ATD-2 project in coordination with the FAA, flight operators, CLT airport operators, and the National Air Traffic Controllers Association (NATCA). The primary goal of ATD-2 is to improve the predictability and operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation’s most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 project is a 5-year research activity beginning in 2015 and extending through 2020. The Phase 1 Baseline IADS capability resulting from the ATD-2 research has been demonstrated at the CLT airport since the beginning of October 2017. Phase 1 provided data exchange and integration with the initial demonstration of the integrated system of strategic and tactical scheduling, collaborative tactical surface metering, tactical departure scheduling to an en route meter point and overhead stream insertion, initial integration of a TFDM SWIM prototype feed, and an early implementation prototype of a Terminal Flight Data Manager (TFDM) Electronic Flight Data (EFD) system. The strategic surface scheduling element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 The Phase 2 Fused IADS system provided substantial updates to baseline IADS Demonstration capability. Improvements were made to the IADS modeler; tactical surface scheduling, and metering; tactical departure scheduling for overhead stream insertion; Electronic Flight Data (EFD) and the integration with the FAA Advanced Electronic Flight Strip (AEFS); RTC/RMTC, and departure trajectories. New capabilities included a TFDM SWIM prototype feed and delivery of IADS data via the TFDM Terminal Publication (TTP) service of the FAA’s SWIM system; strategic surface scheduling and metering as well as fusion with tactical surface metering; integration and ingestion of data from TTP-connected Mobile App and texting industry for General Aviation (GA) flights; and expansion of airspace deployments to include adjacent Center automation, in particular interface with the Atlanta Center (ZTL) arrival metering TBFM system to evaluate pre-scheduling of flights. Improvements in Data Analysis and System Health (DASH) monitoring and updates were completed as well.

Talebi, Ehsan↗

The Integration of Wi-Fi Location-Based Services to Optimize Energy Efficient Commercial Building Operations

This project investigated and demonstrated the use of Wi-Fi Location-Based Services (LBS) to perform occupancy sensing in commercial buildings. Wi-Fi LBS can be used to detect the presence of Wi-Fi enabled mobile devices and laptops that accompany occupants as they move through the building. These signals can be used to determine occupant presence, head count, and location. When integrated with the building automation system, this emerging technology approach can be used to manage other connected systems such as lighting and HVAC to reduce energy usage in the building and improve occupant comfort. An open source location detection algorithm was developed, which uses data collected from three or more Wi-Fi access points to determine the presence and estimate the location of mobile devices and laptops. Access points can detect Wi-Fi enabled devices even if they are not connected to the existing Wi-Fi network. Building occupancy is determined based on the presence, location, and movement of these devices through the space. From lab and small-scale in-situ testing, the Location Detection Algorithm (LDA) was found to be accurate to within 10 feet and could be further refined by tuning the algorithm for the specific space characteristics such as layout and obstructions (walls, furniture, etc.). An open source method to integrate the occupancy data with existing building automations systems was investigated. The Wi-Fi occupancy sensing approach was then demonstrated and validated at commercial buildings located in Saint Paul, MN; Madison, WI; New York City; and Fort Worth, TX.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Using Wi-Fi Location-Based Services (LBS) for Commercial Building Occupancy Sensing

From May 2019 through October 2022, this DOE-funded project investigated and demonstrated the use of Wi-Fi Location-Based Services (LBS) to perform occupancy sensing in commercial buildings. Wi-Fi LBS can be used to detect the presence of Wi-Fi enabled mobile devices and laptops that accompany occupants as they move through the building. These signals can be used to determine occupant presence, head count, and location. When integrated with the building automation system, this emerging technology approach can be used to manage other connected systems such as lighting and HVAC to reduce energy usage in the building and improve occupant comfort. An open source location detection algorithm was developed, which uses data collected from three or more Wi-Fi access points to determine the presence and estimate the location of mobile devices and laptops. Access points can detect Wi-Fi enabled devices even if they are not connected to the existing Wi-Fi network. Building occupancy is determined based on the presence, location, and movement of these devices through the space. From lab and small-scale in-situ testing, the Location Detection Algorithm (LDA) was found to be accurate to within 10 feet and could be further refined by tuning the algorithm for the specific space characteristics such as layout and obstructions (walls, furniture, etc.). An open source method to integrate the occupancy data with existing building automations systems was investigated. The Wi-Fi occupancy sensing approach was then demonstrated and validated at two commercial buildings located in Minnesota and Wisconsin.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High Density Vertiplex: Scalable Autonomous Operations Prototype Assessment Simulation

Urban Air Mobility (UAM) is a rapidly growing topic within the field of aviation because of the impact a refined ecosystem and uncrewed aerial vehicles could have on modern society, such as urban air mobility, cargo, and emergency transport. Before the UAM concept can be actualized, research is needed to understand how to integrate these new classes of vehicles and operations into the National Airspace System. One under-researched but critical piece of infrastructure required for UAM operations is Vertiport operations. Vertiports are the envisioned takeoff and landing locations for these uncrewed aerial vehicles. To accommodate the high use of the vertiport, new technologies and roles will be required for optimal use. At NASA, the High Density Vertiplex sub-project targets research into vertiports. The High Density Vertiplex team created an Urban Air Mobility ecosystem to test and evaluate different concepts and tools used to support higher density operations at vertiports. Part of the test and evaluation included the Prototype Assessment Operations simulation of highdensity operations around a vertiport to study vertiport management and vertiport operations. The research team also evaluated how the prototype Urban Air Mobility ecosystem supported fleet managers, ground control station operators, and vertiport managers in execution of nominal and off-nominal high-density operations. Results from this simulation provided insight regarding UAM ecosystem research and development and vertiport automation systems.

Small Uncrewed Aerial Vehicle (sUAS)↗

A Parameterization Study of Sew-EZ Materials: Types #6 and #8

Two material types identified by Sew-EZ were tested in various configurations, and under various conditions, by Sandia National Laboratories (SNL). The primary focus of this study was to assess the filtration performance of these two materials and identify if they perform similarly to certified N95 respirators. Testing was conducted on two systems which use distinctly different techniques to characterize the aerosol penetration characteristics of materials: a) R&D Filtration System: A large-scale R&D filtration system was used with testing parameters that mimicked NIOSH guidelines, where possible. Efficiency data as a function of particle size was attained using NaC1 as the test aerosol and a Scanning Mobility Particle Sizer (SMPS) for measurements. A more detailed system description can be found in Omana et al. 2020. b) Automated Tester: A commercial, automated filter tester (100Xs, Air Techniques International) was used to provide penetration/efficiency data for Sew EZ materials. The 100Xs aerosolizes a polydisperse NaC1 aerosol with a consistent concentration and size profile. The 100Xs manual (Air Techniques International 2018) states, "The aerosol particle size and distribution are designed to meet all requirements as defined in the relevant sections of NIOSH 42 CFR, Part 84 (pg. 32)."

36 MATERIALS SCIENCE↗

Past US studies and developments for planetary rovers

The history of planetary rovers in the U.S. space program is outlined in the context of the goals, mission and spacecraft designs, and operations designs. The American lunar rover work has had three main stages. In the early sixties, the capacity of Surveyor lunar landers to deliver rovers with a mass of about 50 kg to the Moon was exploited. Several such machines were built and tested beginning in 1964 but none went to the Moon. A manned 400 kg short range rover was then developed. Three of these operated on the Moon in 1971 and 1972 as part of the Apollo 15, 16 and 17 missions. Following these Apollo successes, attempts were made to provide two kinds of follow on models: automated or dual mode (human carrying or not) rovers in the few hundred kg size class, and multi-ton mobile habitats that could carry humans on extended traverses. With the closing of both Soviet and American lunar exploration in the seventies, neither of these proposals succeeded. In parallel with these lunar developments, a lengthy technology program on Martian roving has gone on in the U.S., sometimes coming close to preproject status and sometimes fading away, but never quite being abandoned. As a result it is possible today to contemplate a wide range of lunar and Martian roving missions that could be made practical within a few years. However, with today's funding constraints none of the well studied, larger mission concepts appear to fit. Therefore new efforts are being made toward developing much smaller rovers taking advantage of new miniature techniques, not only in mobility systems but also in the scientific instruments that a small rover can carry. Illustrations are included.

Burke, James D.↗

Creating Formal Characterizations of Routine Contingency Management in Commercial Aviation

The identification, modelling, and analysis of root causes of accidents and incidents dominate conventional safety management approaches. However, the effect of humans’ safety-producing behavior on the overall resilience of the system is often neglected. Additionally, emerging aviation markets are giving rise to concepts of operation, such as urban air mobility and optionally piloted air cargo operations, that are leading to a shift in locus of control between humans and automation. Without an understanding of the human contribution to safety, it is difficult to assess the effects of these novel role allocations on overall system safety. In this work, safety-producing behaviors are identified and abstracted into resilient performance strategies. Production rules that encapsulate these strategies are then generated and classified in the Soar cognitive architecture. The strategies are then applied to a remotely-operated air cargo example to demonstrate how safe learning is facilitated. The learned rules and strategies are then formally verified.

Safety Critical Systems↗

Operator Workload and Task Allocation in m:N Operational Architectures of Uncrewed Aerial Systems

Uncrewed aerial systems (UAS) show promise in urban air transport, package delivery, and emergency services. UAS efficiency can be significantly improved by having fewer operators (m) manage a greater number of vehicles (N), or the m:N architecture of operation. The current study investigates how workload affects operators’ task-allocation decision-making and potential effects of two crucial human factors: trust and self-confidence. In the context of a simulated UAS package-delivery task, 10 participants with expertise in UAS operation were recruited. Each participant reported their preferred task-allocation strategy for a set of five subtasks while watching two sets of videos with different workload levels. Perceived workload, trust, and self-confidence were also measured after each video session. Overall, participants indicated a preference for automation for most of the subtasks under the delivery mission. Trust, rather than workload and self-confidence, played a significant role in experts’ decisions of task-allocation and assignment methods. Higher trust led to higher preference for automation.

workload↗