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    <title>Research in Progress (RIP)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Research in Progress (RIP)</title>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Communicable disease preparedness: Aircraft cabin disease dispersion study for model validation</title>
      <link>https://rip.trb.org/View/2675923</link>
      <description><![CDATA[This research supports the Federal Aviation Administration's (FAA’s) Aviation Safety Research Strategy Public Health Preparedness thrust and depends on access to National Research Council Canada’s Centre for Air Travel Research facility. To strengthen public health preparedness, the Office of Aerospace Medicine must quantitatively model disease transmission risk in commercial aviation and evaluate mitigation strategies. Building on preliminary work under prior work, risk analysis models have been developed for interagency Safety Risk Management (SRM) use, with broader dissemination planned to public health planners, industry, and academia.

This project directly responds to the final recommendation of GAO-22-104579, which highlighted critical gaps in prior models. The project will publish key human behavior and ventilation datasets, enabling peer review, independent replication, and expanded application.]]></description>
      <pubDate>Mon, 02 Mar 2026 10:19:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/2675923</guid>
    </item>
    <item>
      <title>Communicable Disease Preparedness: TRIP-X Improvements and Validation</title>
      <link>https://rip.trb.org/View/2518970</link>
      <description><![CDATA[The Office of Aerospace Medicine needs to quantitatively model disease transmission risk in commercial air travel and assess mitigations to inform public health preparedness. Preliminary work under a prior project developed two risk modeling approaches for an inter-agency Safety Risk Management (SRM) team. One approach, advanced through a FAA partnership with international, interagency, and industry partners, built on work by the Boeing Confident Traveler Initiative, to develop the Travel Risk In Pandemics (TRIP-X) tool. Further work is required to refine the model beyond SRM needs and prepare it for broader use. Tasks include finalizing parameters; integrating disease testing and quarantine risk controls; model validation; improving computational efficiency and user experience; and documenting the model. This research supports the FAA’s Aviation Safety Research Strategy Public Health thrust and depends on concurrent data from National Research Council Canada and NIOSH for validation.]]></description>
      <pubDate>Tue, 04 Mar 2025 14:38:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2518970</guid>
    </item>
    <item>
      <title>Layered Model for Disease Transmission Safety Risk Analysis</title>
      <link>https://rip.trb.org/View/2518969</link>
      <description><![CDATA[The Office of Aerospace Medicine needs to quantitatively model disease transmission risk in commercial air travel and assess mitigations to inform public health preparedness. Preliminary work under A11J.AM.19 developed two risk modeling approaches for an inter-agency Safety Risk Management (SRM) team convening in Q2FY26. One approach, advanced through FAA research, built on work by the Munich University of Applied Sciences combing microscopic crowd simulation with airborne pathogen transmission in the Vadere platform. Further work is required to refine the model beyond SRM needs and prepare it for broader use. Tasks include finalizing parameters, model validation, improving computational efficiency and user experience, and documenting the model. 
This research provides the FAA with a validated, user-ready model to quantify disease transmission risk in air travel and evaluate mitigations in support of safety risk management. The model will enable the division and operational stakeholders to assess public health hazards using a repeatable, data-driven approach aligned with SMS and SRM processes. The outcome will support national preparedness planning and provide transferable modeling capability to operators and interagency partners.
]]></description>
      <pubDate>Tue, 04 Mar 2025 14:31:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2518969</guid>
    </item>
    <item>
      <title>Communicable Disease Preparedness: Airline Cabin Inflight Ventilation Assessment</title>
      <link>https://rip.trb.org/View/2518968</link>
      <description><![CDATA[The Federal Aviation Administration's (FAA’s) Office of Aerospace Medicine needs to quantify disease transmission risks during the gate-to-gate travel segment, considering various risk factors and controls, to support safety risk assessment. This project builds on a prior project (Communicable Disease Preparedness: M&S Framework for Analyzing Cabin Health Hazards), where Boeing developed a risk assessment M&S tool using behavioral data and ventilation data from airports, jet bridges, and aircraft cabins collected by National Research Council Canada. However, prior data collection was limited to aircraft at the gate. To address a U.S. Government Accountability Office recommendation, this project will gather ventilation data for off-gate portions under operational conditions.]]></description>
      <pubDate>Tue, 04 Mar 2025 14:25:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2518968</guid>
    </item>
    <item>
      <title>A Bi-Objective Optimization Approach for Emergency Evacuation Planning under Pandemic Setting</title>
      <link>https://rip.trb.org/View/2509045</link>
      <description><![CDATA[Different types of hazards occur quite often in different parts of the globe. These hazards may cause significant property damages, monetary losses, and human fatalities. Emergency evacuation can be extremely challenging in rural areas that may not have emergency shelters with adequate capacity in their vicinity, and transportation infrastructure may not be able to handle a large number of evacuees. Furthermore, a frequent occurrence of pandemics makes emergency evacuation planning even more challenging. Rushing to the closest emergency shelter may not be the best choice, because the closest shelters may operate at the capacity level. Overcrowded emergency shelters are expected to have a high risk of virus transmission under pandemic settings. Therefore, this project proposes a new bi-objective optimization model for emergency evacuation planning, aiming not only to minimize the total travel time of evacuees to the assigned emergency shelters but also to minimize the risk of virus transmission in the assigned emergency shelters as well. A custom multi-objective optimization algorithm is developed to solve the proposed bi-objective optimization model. Various case studies are conducted to demonstrate applicability of the proposed methodology for real-life emergency evacuation scenarios. Evacuation of populations residing in rural counties is directly considered during the numerical experiments. The findings from this research can be used to better prepare rural populations for approaching natural hazards and ensure their safety throughout the evacuation process. ]]></description>
      <pubDate>Wed, 12 Feb 2025 17:29:10 GMT</pubDate>
      <guid>https://rip.trb.org/View/2509045</guid>
    </item>
    <item>
      <title>Air Quality Inside Buses</title>
      <link>https://rip.trb.org/View/2149961</link>
      <description><![CDATA[The COVID-19 pandemic brought air quality to the forefront of the transit industry. In the summer of 2022, due to the immediate need to understand the issue, the Transit Cooperative Research Program (TCRP) conducted its first Insight Event. TCRP Insight Event--Air Quality in Transit Buses explored how air quality inside transit vehicles, especially buses, may contribute to the spread of infections. During that event, presentations and conversations about dispersion, ventilation, circulation, and filtration issues were held. Presentations from the event and the literature search results are available on the TCRP Insight Event web page at https://www.nationalacademies.org/event/06-21-2022/trb-tcrp-insight-event-air-quality-in-transit-buses. 

Since that event and the end of the pandemic’s restrictions, the public transit industry has learned that air quality inside transit buses matters to bus operators and passengers. There is an increased focus on reducing the concentration of pathogens containing respiratory aerosols and other harmful pollutants in the air inside a bus cabin. Transit agencies are working to increase operators and passenger confidence in air quality. With increased confidence, riders will return, and it will be easier to hire bus operators. 

Transit systems are analyzing the current air quality inside their buses to better understand current airflows and possible risks. Measuring and controlling air quality inside the bus cabin has proven difficult.  Buses idle, constantly open their doors to embark or disembark passengers, and are exposed to traffic-related air pollutants, such as  exhaust.  

This reality has not hampered the desire to improve air quality inside cabins. Transit agencies are employing the following solutions to mitigate poor air quality: dilution, which consists of bringing more fresh air inside the bus while sending indoor air out; filtration with the use of better-quality filters; and cleaning, including the use of ultraviolet light and photocatalytic oxidation.  

Research is needed to find clear solutions to improve air quality on buses for operators and passengers. Transit systems are doing the best that they can to protect their employees and passengers. However, research can provide information to improve air quality and standardization of practice. 

The objective of this research is to create a research document that helps transit agencies understand air circulation inside a typical 40-foot heavy-duty transit bus and finds solutions to protect employees and passengers without decreasing passenger comfort, safety, and reliability of the system. The research should help guide the development of future design and performance criteria to support better transit rolling stock procurement and heating, ventilation, and air conditioning (HVAC) operations in emergency conditions (e.g., airborne diseases and wildfires).]]></description>
      <pubDate>Mon, 10 Apr 2023 17:08:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/2149961</guid>
    </item>
    <item>
      <title>Developing an Airport Communicable Disease Response Plan Template</title>
      <link>https://rip.trb.org/View/2104373</link>
      <description><![CDATA[Airport communicable disease response plans (CDRPs) are multi-agency coordination plans maintained by airports that outline the main roles and responsibilities of key agencies during various illness responses.  CDRPs allow for several types of responses and contingencies ranging from response to a single individual illness or death to a mass illness response.  They include potential locations for entry and exit screening, as well as responsibilities of partners during a pandemic.  CDRPs are also used by airport partners, including the Centers for Disease Control and Prevention (CDC) and its quarantine stations, to coordinate activities during public health responses.  Although not required by federal aviation regulation, many airports have found CDRPs valuable and would benefit from a template and guide for their development.  
OBJECTIVE: The objective of this research is to develop templates and a guide to help airports prepare CDRPs that are practical, scalable, implementable, and easily updated. The templates should be designed to help airports create CDRPs for the following situations, at a minimum:

Within an airport response plan at a port with a co-located CDC quarantine station;

As a stand-alone document at a port with a co-located CDC quarantine station;

As a document at a sub-port of a CDC quarantine station; and

For other commercial service and general aviation airports.


The templates should allow airports to respond to a range of situations (e.g., an isolated incident, pandemics) and consider various populations within an airport (e.g., employees, tenants, passengers).
The guide should help airports:

Select and populate the appropriate template based on their unique situation, goals, and priorities;

Identify and coordinate with relevant stakeholders when developing the plan; and

Provide suggestions for testing, benchmarking, and updating the plan.
]]></description>
      <pubDate>Thu, 26 Jan 2023 16:43:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/2104373</guid>
    </item>
    <item>
      <title> 
 Communicable disease preparedness: M&amp;S framework for analyzing cabin health hazards </title>
      <link>https://rip.trb.org/View/2072042</link>
      <description><![CDATA[The Federal Aviation Administration (FAA) has assumed a leadership role in developing a preparedness plan for communicable disease in air travel and identifying associated research needs. The FAA’s approach to the planning effort is to use its existing Safety Risk Management (SRM) process, as documented in FAA Order 8040.4B, to determine the risk of transmission of a disease requiring flight-related contact tracing within a population of airline passengers and cabin crewmembers between the times of population formation and dispersion and the expected impacts of mitigation activities. This research project will answer the question, what is a generalizable risk analysis framework and associated set of accepted and validated modeling, simulation, and analysis (MS&A) tools for determining baseline risk and evaluating the impact of risk control measures. The project will define an analysis framework for cabin health safety hazards; conduct a survey of existing MS&A tools, data sources, and non-destructive testing methods suitable for studying pathogen movement in transport aircraft cabins; select the preferred MS&A tool set and testing methods; and plan and conduct MS&A validation and analysis studies. The resulting analysis framework and associated MS&A tools and data will be transitioned for use in communicable disease transmission preparedness planning.]]></description>
      <pubDate>Wed, 30 Nov 2022 15:31:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2072042</guid>
    </item>
    <item>
      <title>Slowing COVID-19 Spread – Simulating Bus Seating Strategies</title>
      <link>https://rip.trb.org/View/1904959</link>
      <description><![CDATA[Taking public transportation is a critical way of commuting for many individuals living in
cities across the United States. Public transit is also an important mode for older adults,
wheelchair users, and individuals to whom biking, walking, and driving may not be
feasible, for example, one who has arthritis or other chronic pain that limits his/her level
or type of activity. Because the World Health Organization (WHO) reports that
coronavirus can last on surfaces for a few hours up to several days, like the other
indoor spaces, a potential risk of exposing to COVID-19 exist when using public transit.
Motivated by this, the research proposes to develop a python-based agent modeling
tool that enables simulation of in-bus passenger seating behavior based on the “social
distancing” awareness and supported with in-vehicle sanitizing practices. With
application of the proposed simulation tool in the City of Albuquerque transit system,
the research aims at identifying optimal and practically feasible seating strategies under
multiple scenarios of transit capacities, seats configurations, passenger volume
(occupancy), and bus schedules. The research is expected to help slow the spread of
COVID-19 on public transit, gain travelers’ confidence on the safety of transit during the
pandemic situation, and improve public health conditions, especially for transit riders
with low-income, disability, and other potentially underserved communities that have
higher risk for severe illness from COVID-19.]]></description>
      <pubDate>Thu, 20 Jan 2022 14:44:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/1904959</guid>
    </item>
    <item>
      <title>Analyzing the Role of Air‐Transportation in COVID‐19 Pandemic Disaster</title>
      <link>https://rip.trb.org/View/1884826</link>
      <description><![CDATA[COVID-19 pandemic has caused a worldwide lockdown and a complete stoppage of all non-essential activities. In particular, it has affected air-travel, which is a significant driver of the global economy through the movement of people and goods. In this proposal, the research team will address the impact of air travel on the pandemic both at the scale of the entire country and at the level of airports. The ongoing COVID-19 pandemic data can be considered as spatiotemporal point data scattered all over the world. The team will utilize Hawkes point process model to decluster this point data in terms of air-travel related cases or background events and the local spread cases which are off-springs of these background cases. This understanding can play a crucial role in devising strategies to micro-target and mitigate emergency transportation disruptions. The team will also utilize their past work to develop agent based models for COVID-19 spread to devise transportation policies regarding crowd management that will mitigate the second wave of COVID -19 as travel returns to normal levels.
]]></description>
      <pubDate>Mon, 11 Oct 2021 23:27:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/1884826</guid>
    </item>
    <item>
      <title>Modeling Future Outbreaks of COVID-19 Using Traffic as Leading Indicator</title>
      <link>https://rip.trb.org/View/1884829</link>
      <description><![CDATA[The movement of people is inherently connected to the spread of viral diseases. Infected individuals expose others as they travel between home, work, school, shopping, and recreation destinations. Understanding the relationship between social/economic activity and the spread of COVID-19 could prove invaluable, as the nation looks to reopen. Unfortunately, some states that reopened first are experiencing spikes in COVID-19 cases. For example, Florida, which entered Phase 1 of the reopening process on May 18, 2020, recorded significant increases in the daily number of COVID-19 cases approximately two weeks later and by June 9th saw the highest single day increases in positive cases. Prior research has demonstrated how drastic changes in human behavior can be measured using highway volume data as a representation of personal activity. As states begin to reopen, it would appear that increases in highway traffic might be a leading indicator of where and when outbreaks of COVID-19 are likely to occur. This research will investigate and model the relationship between roadway traffic and viral outbreaks. The traffic informed SIR model developed by this research will help identify where and when second wave outbreaks are likely to occur and assist in the planning of recovery effort.]]></description>
      <pubDate>Mon, 11 Oct 2021 23:22:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1884829</guid>
    </item>
    <item>
      <title>Countermeasures for Maintaining Safe and Effective Public Transit Service in the Post-COVID-19 Era</title>
      <link>https://rip.trb.org/View/1881803</link>
      <description><![CDATA[COVID-19 pandemic has changed all the aspects of our daily life dramatically, including the transportation area. Because of the high density of passengers, which could facilitate the virus spread, public transit service has been hit even harder than any other transit mode. At the beginning of the pandemic, to prevent the spread of the coronavirus, countries all adopted several safety measures, including masking, social distancing, as well as stay-at-home orders. All these measures affected public transit and resulted in sharp declines in ridership and revenue. However, with the increase of the vaccination rate, more and more countries started to gradually reopen, and the demand for public transit services also started to bounce back. Therefore, there is a need to investigate how to restore public transit services while minimizing the risk of infection for passengers at the same time. Although many countermeasures and strategies have been applied by different public transit agencies in different countries, and some of which have been approved to be effective, there is a lack of a method for quantitatively evaluating the effectiveness of these countermeasures and assessing their feasibilities.
This project is to recommend cost-effective countermeasures for maintaining safe and effective public transit services in Post-COVID-19 era and to develop a method for quantitatively evaluating the effectiveness of these countermeasures. The results of this project can help the public transit agencies to choose the most cost-effective countermeasures and strategies that can prevent the spread of the coronavirus and maintain high-quality public transit service.
The research is developed based on the CAMMSE theme of addressing the FAST Act research priority area of “Improving Mobility of People and Goods.” The research is relevant to the CAMMSE research thrust “Develop data modeling and analytical tools to optimize passenger and freight movements.” Specific project objectives include:
(a)	Review the existing countermeasures on restoring public transit service while keeping passengers safe,
(b)	Recommend feasible countermeasures,
(c)	Develop a new method for quantitatively evaluating the effectiveness of the recommended countermeasures, and
(d)	Conduct a case study to demonstrate the implementation of the developed method.
]]></description>
      <pubDate>Mon, 04 Oct 2021 12:17:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/1881803</guid>
    </item>
    <item>
      <title>URBANO.IO V2 
The only tool that connects urban design, mobility, and public health</title>
      <link>https://rip.trb.org/View/1878047</link>
      <description><![CDATA[The current COVID-19 crisis reveals the vulnerability of urbanizing societies where cities are the current pandemic's focal points. Therefore, long-standing planning paradigms that promote urban density to enhance social life, increase efficiency, and sustainability must be re-evaluated using a data-driven approach. While U.S. transportation emissions dropped ~10% in 2020 as millions of workers stopped driving to work, the use of mass transportation may have accelerated the outbreak in specific locales like New York City. This suggests that the built environment, urban sustainability, and pandemic resilience are closely linked. To better understand how urban design choices relate to the spreading and containment of pathogens, practitioners and researchers need new tools at the nexus of urban design, mobility simulation, and public health modeling. This proposal seeks to elevate Urbano.io to version 2 by finalizing a new NHTS data-driven multimodal mobility model and by interfacing with existing public health models. The research team further develops a real-world, case study that enhances NYC OpenStreets and informs a large rezoning project to test and showcase new features in close collaboration with the executive user group.]]></description>
      <pubDate>Tue, 14 Sep 2021 16:54:29 GMT</pubDate>
      <guid>https://rip.trb.org/View/1878047</guid>
    </item>
    <item>
      <title>Future of Work: Scenario Planning for COVID-19 Recovery</title>
      <link>https://rip.trb.org/View/1845543</link>
      <description><![CDATA[The Future of Work Scenario Planning Workshop will engage experts in transportation, major employers, and real estate and development companies in June 2021. The experts (n=30 to 40) will define a key focal issue around the future of work in response to COVID-19 recovery and the corresponding timeline for the scenarios (e.g., 1 to 3 years, 4 to 6 years). The workshop will identify key driving forces including critical uncertainties, develop plausible scenario worlds, and identify key policy strategies and research recommendations to maximize social and environmental outcomes. University Transportation Center (UTC) researchers will integrate key findings from the Telemobility UTC longitudinal panel survey, which documents work-from-home/telework activities of respondents and their preferences for the future of work in COVID-19 recovery. The workshop will also inform future UTC respondent surveys on work-from-home/telework. The workshop will focus on employers and real estate/development company responses to COVID-19 recovery based on key driving forces, such as state of the virus/vaccine (public health and safety), employee preferences, and economic factors (productivity and revenue). Experts will examine potential impacts on transportation modes such as public transit, shared mobility, and auto ownership/use. The scenarios will also inform regional modeling efforts and policy strategies to maximize the public good.]]></description>
      <pubDate>Thu, 08 Apr 2021 11:44:00 GMT</pubDate>
      <guid>https://rip.trb.org/View/1845543</guid>
    </item>
    <item>
      <title>Regional Impacts of Telemobility Options:  Capitalizing on the Two-Way Relationship Between Infrastructure Investments and Travel Demand  </title>
      <link>https://rip.trb.org/View/1845536</link>
      <description><![CDATA[Communications technologies and e-commerce have a profound effects on travel, on the delivery of goods and services, and consequently, on the use of transportation infrastructure.  Experiences acquired as a result of travel restrictions or health concerns, e.g., working remotely, are likely to accelerate some of these trends.  Furthermore, widespread deployment of (innovative) services as a result of Covid-19, e.g., telehealth, may, fundamentally, alter travel patterns of many population segments.  Changing travel behaviors may have significant long-term implications on the tens of billions of dollars that are invested each year to keep highways, rail lines, ports, airports, public transit systems, and other infrastructure in a state of good repair.  For example, as e-commerce accelerates, streets in residential neighborhoods support increasing loads associated with delivery vehicles, and, in turn, deteriorate more quickly and require additional investments to provide the same level of service.  Perhaps more importantly, as we are redesigning physical and virtual supply chains for delivery of goods and services, there are tremendous opportunities to guide investments in transportation infrastructure that are going to have effects on travel behavior with both immediate and lasting positive economic, social, and environmental consequences.  Examples of significant short-term effects of infrastructure investments include increasing employment.  Long-term effects include opportunities to improve the efficiency, level-of-service, reliability, resilience of these supply chains.  The project objectives are, therefore, to develop a framework to evaluate the regional life-cycle and supply-chain consequences of investments in design, construction, and management of transportation infrastructure, and to validate it by considering a variety of scenarios.]]></description>
      <pubDate>Wed, 07 Apr 2021 19:16:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/1845536</guid>
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