National Academies Press: OpenBook

Evaluation of the Exploratory Advanced Research Program (2022)

Chapter: Section 3 - Evaluation of EAR Program Outcomes and Impact

« Previous: Section 2 - Evaluation of EAR Program Processes
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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SECTION 3

Evaluation of EAR Program Outcomes and Impact

The existence of the EAR Program stems from the perceived dearth of funding at FHWA for “breakthrough research,” which was later rephrased as “exploratory advanced research.” Continued investment in the EAR Program may be justified in part by showing that the Program has invested in projects that fit the profile of exploratory advanced research and in part by demonstrating that the Program has identified, supported, and helped mature research leading to potential breakthroughs in innovation for FHWA’s needs.

Section 4 discusses the issue of whether the EAR Program is effective in supporting exploratory advanced research. This section presents data on the more immediate outputs and near-term outcomes that can be traced to EAR-funded research projects, focusing on those in the three case study topic areas.

3.1 Overview: Outputs and Outcomes Attributable to EAR Program Research

Recall from the EAR program logic model in Section 2 that EAR-funded projects are intended to have three main sets of outputs:

  • New data, knowledge, and knowledge tools;
  • Solutions to certain technical problems; and
  • Proof that an application based on the research may be feasible and justifies further R&D.

The EAR Program excludes the possibility of funding research that leads to products and services ready for commercial introduction or immediate application. Therefore, the outputs are expected to provide knowledge that will inform later technology development efforts but not create technologies that are ready for use. The exception to this condition is projects that create new research tools—such as analytical methods, instrumentation, or data processing techniques—where the end user is another researcher.

To track immediate outputs, the evaluation team focused on the following instances of knowledge dissemination:

  • Scholarly journal articles, where results are validated and published for use by the research community;
  • Conference presentations communicating project activities and results to a specific audience;
  • Patents, where research results are encapsulated in an invention that can be protected as intellectual property;
  • Students who participate in EAR-funded projects and, therefore, receive training and expertise in both the research process and the projects’ topic areas;
  • Datasets generated by research teams and opened for research use; and
  • Software or algorithms for data analysis.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Section 3.2 provides counts of these various instances of knowledge dissemination from EAR-funded projects and discusses their implications for evaluation.

The short-term outcomes of EAR-funded research are demonstrated through changes in behavior and activities of members of the surface transportation community, primarily those who are stakeholders in the EAR Program. The types of evidence used to trace these outcomes include:

  • Engagement with external partners. Involvement of third parties in EAR-funded research projects; direct discussions with external organizations about the research results.
  • Picked up for further research and technology development. Examples of new research projects that build on the research results from EAR-funded projects.
  • Influence on the R&T agenda. Research efforts in areas aligned with prior EAR-funded projects or investigations into new fields and topics revealed through EAR-funded research.
  • Engendering researcher–user interactions. Efforts that either field demonstration systems or subject prototype technologies to user testing based on EAR-funded research.
  • Adoption within the transportation industry. Products, processes, and services marketed by firms in the transportation domain that encapsulate knowledge or innovations produced by EAR-funded projects.
  • Informing and enhancing government policy and operations. References to findings from EAR-funded research or discussion of technologies and topics generated from EAR-funded projects in policy documents or guidelines published by U.S. DOT or state and local transportation authorities.
  • Informing the public. Use of techniques or findings from EAR-funded research in communications to the general public, such as safety guidelines or recommended best practices.

Most evidence of these outcomes can be gathered only through qualitative data collection and analysis, such as interviews with informed experts, public documents, surveys, and articles in professional or general-interest periodicals. Section 3.3 summarizes findings that include such evidence.

3.2 Outputs from Case Studies and Cross-Case Analysis

3.2.1 Analysis of EAR-Related Research Publishing Activity

Dissemination of project results through the research literature appears to be the primary method of publicizing the findings from EAR-funded research. In the survey of PIs, 16 of the 25 respondents reported that peer-reviewed journal publications resulted from their projects. Eighteen of the 25 respondents reported that their research produced at least one conference paper or similar report.

To provide a more comprehensive analysis of EAR-related publishing activity, the evaluation team searched for articles attributable to specific EAR Program research projects contained in the following data sources:

  1. Dimensions (a bibliographic database of journal articles and conference proceedings),
  2. Web of Science (a database similar to Dimensions but with differing coverage of journals and conferences),
  3. TRB Publications Index,
  4. Reference lists in the EAR Program Research Results reports published periodically by FHWA,
  5. Project final reports, and
  6. Publications reported in PI survey responses.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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For the Dimensions and Web of Science databases, publications were extracted if they acknowledged funding from the agreement numbers associated with EAR Program projects. For the other sources, publications were extracted based on author names. The publications identified were then de-duplicated across those sources so that any publication listed in multiple sources was retained as a single record. Using agreement numbers alone may result in an undercount of publications because many journal authors might acknowledge FHWA without the number or may fail to acknowledge EAR Program funding entirely.

A total of 428 unique publications from 2007 through 2021 were identified as associated with any of the 86 projects awarded from 2007 through 2018. Because of the lag effect of publishing and the effort required to ramp up the Program’s operations, the body of published literature was relatively small in the years following the creation of the EAR Program but grew steadily as researchers began publishing their findings. Figure 3-1 shows the cumulative count of EAR Program–related publications from 2007 to 2021. These publications were associated with 46 EAR-funded projects during this period. (It should be noted that some of the sources used may not yet include recently published literature, which could explain the decline in more recent years; relatively few publications relate to projects awarded after 2014.) These publications were distributed across 135 different journals and periodicals.

Among those articles, 41 of the 75 PIs on EAR-funded projects were identified as authors. In other words, about 55% of the PIs published at least one article identified through this search strategy. Those 41 PIs appeared on publications with a total of 374 unique coauthors. This cohort of coauthors illustrates how EAR-funded research topics tend to be connected to researchers in a much broader community.

To further illustrate these connections, the publication data was used to construct a network analysis of coauthors using the VOSviewer bibliometric software package, developed at Leiden University in the Netherlands. This software calculates the number of publications associated with each unique coauthor and also the number of times that any two coauthors appear on the same publication. The authors are then clustered on a visualization, where each author is represented by a circle and coauthorship relationships are represented as lines between coauthors.

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Figure 3-1. Cumulative count of EAR Program–related publications.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
×

The size of the circle representing an author is determined by the number of publications for which the author appears in the dataset. The authors are then clustered so that those who are frequent coauthors are colocated on the network.

Figure 3-2 presents the resulting network visualization. The PIs on EAR-funded projects who were also the most prolific authors in the publication dataset include Gaurav Sant from the University of California, Los Angeles; YingLi Tian of the City College of New York; Anuj Sharma of Iowa State University; Jeffrey Bullard of Texas A&M University (previously at NIST when he was funded by the EAR Program); George Scherer of Princeton University (who collaborated with Bullard on an EAR-funded project); and Necati Catbas of the University of Central Florida. Dan Frangopol of Lehigh University is also a prominent author; he collaborated with Catbas on a project related to managing infrastructure maintenance under uncertain conditions. The authors were assigned a color using a community detection algorithm, illustrating clusters of authors who work in related subcommunities.

The publication analysis reveals some interesting patterns in the dissemination of EAR-funded research results. While research publications are the dominant form of dissemination in the EAR Program, nearly half of the PIs on EAR-funded projects do not appear as authors on articles related to those projects, and about half of the EAR-funded projects produced no research publications. A contributing factor might be the preference in academic publishing for fundamental scientific research. The topics studied in exploratory advanced research might be somewhat too applied for mainline scientific journals. The predominant journals where EAR-related articles appeared are concentrated in structural engineering, materials engineering, electronics and computer science, and transportation. The applied focus of the EAR Program is also reflected in the specializations of the publication authors. Based on each author’s departmental affiliation, over half of the 416 unique coauthors hold positions in engineering departments, followed by other disciplines in applied sciences. This distribution is captured in Table 3-1.

3.2.2 Analysis of EAR-Related Patenting

Given this applied focus, EAR-funded research appears likely to produce inventions protected by patents in addition to publications. Patents are precursors to technology development because they document and protect the basic mechanisms and methods devised during R&D, which can then become the basis of products or services.

However, relatively few EAR-funded projects have supported the development of patented inventions. By law, the patent for any invention developed at least in part with federal funding must include a “government interest statement” acknowledging the funding agency and the agreement number of the funded project. PatentsView (https://patentsview.org), an index of U.S. patents developed with funding from the U.S. Patents and Trademark Office, was used to search for any patents that credited EAR Program agreement numbers. This produced nine patents, listed in Table 3-2. These patents are attributed to eight projects awarded from 2007 through 2014. The patents cover a range of technical domains, including VA, nanomaterials, sensor technologies, and energy. Note that most federally funded research projects do not result in patents, so it is noteworthy that over 10% of projects awarded before 2015 led to at least one patent.

3.2.3 Analysis of EAR Program Role in Student Research and Training

The EAR Program’s research funding also supported training for undergraduate and graduate students and postdoctoral researchers at universities. The Program does not track data on the role of its funding in training. However, respondents to the PI survey provided limited data on

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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
×
Image
Figure 3-2. Bibliometric network of EAR Program–related authors and coauthors.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Table 3-1. Top disciplines of authors and coauthors on EAR-related publications.

Discipline Count Share
Engineering 226 54.3%
Computer science 40 9.6%
Transportation 21 5.0%
Materials science 14 3.4%
Artificial intelligence 10 2.4%
Unknown 51 12.3%
Other 54 13.0%

Table 3-2. Patents attributed to EAR Program funding.

Patent Number Patent Title Contract Number Project Title
US8861842B2 Method and Apparatus for Real-Time Pedestrian Detection for Urban Driving DTFH61-07-H-00039 Layered Object Recognition System for Pedestrian Collision Sensing
US9506848B2 Frequency Doubling Antenna Sensor for Wireless Strain and Crack Sensing DTFH61-10-H-00004 Carbon Nanotube Based Self-Sensing Concrete for Pavement Structural Health Monitoring
US9759811B2 Radar Vehicle Tracking DTFH61-14-C-00004 Innovative Applications for Emerging Real Time Data
US9776916B2 Processes for Depositing Nanoparticles upon Non-conductive Substrates DTFH61-13-H-00010 Development of Structural Carbon Nanotube-Based Sensing Composites for Rehabilitation of Deteriorating and Fatigue-Damaged Steel Bridges
US9799096B1 System and Method for Processing Video to Provide Facial De-identification DTFH61-14-C-00001 Automated Feature Extraction
US10121055B1 Method and System for Facial Landmark Localization DTFH61-14-C-00006 CMU Driver Behavioral Situational Awareness System
US10297855 Rechargeable Multi-cell Battery DTFH61-10-H-00003 Roadway Wind-Solar Hybrid Power Generation and Distribution System Towards Energy-Plus Roadways
US10745320B2 Compositions of Matter Comprising Nanoparticles and Non-conductive Substrates DTFH61-13-H-00010 Development of Structural Carbon Nanotube-Based Sensing Composites for Rehabilitation of Deteriorating and Fatigue-Damaged Steel Bridges
US10769459B2 Method and System for Monitoring Driver Behavior DTFH61-14-C-00007 DMask: A Reliable Identity Masking System for Driver Safety Video Data
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
×

students and independent researchers who worked on their projects. Across the 25 responses, PIs reported that their projects involved a total of 25 postdocs, 63 graduate students, and over 42 undergraduate students. Undergraduates were used primarily in two types of projects: CM and VA. Graduate students were used more consistently across projects, but with higher concentrations in projects related to CM, nanoscale science, data analysis, and VA. Postdocs were also evenly spread across numerous projects, with slightly greater involvement in materials and data analysis projects.

3.2.4 Analysis of EAR-Funded Development of Software and Datasets

Certain EAR-funded projects produced very valuable datasets and useful algorithms that were later used by academic and industrial researchers. Five of the respondents to the PI survey reported that their projects resulted in open-source software code distributed to the public. Software and datasets were a key by-product of EAR-funded work in VA. These projects had two major focus areas: extracting useful information from a naturalistic driving set, which included hundreds of hours of in-cabin and vehicular camera footage, and creating automated methods to obscure the faces of individuals captured on video to protect those subjects’ privacy and confidentiality.

The VA case illustrates how the EAR Program helped create new resources to expand research on emerging topics in transportation. The second Strategic Highway Research Program (SHRP 2) funded the development of a dataset of driving behaviors and incidents for use in safety research by recording and monitoring drivers in real time as they traveled in traffic. Thousands of hours of digital video footage are stored at the Virginia Tech Transportation Institute, requiring terabytes of data storage. Exploiting this massive dataset for applications like safety research is computationally intensive and difficult to manage. Also, because the video footage captures people conducting daily driving activities, the footage contains extensive personally identifiable information (PII). This means that before accessing the data, researchers must undergo extensive training and vetting, further reducing access to this resource.

The EAR Program helped fund the development of software for automated video feature extraction, removing extraneous data so that researchers could reduce the dataset to contain phenomena of direct research interest. Other projects developed facial masking technologies so that the video data could be anonymized to remove PII. In both cases, the technologies were designed to make the dataset accessible to a broader set of researchers. The facial masking software gained early adoption as a standard for anonymizing video data, although the PI reports that the technique has been superseded by new methods based on deep learning. The feature extraction effort was only partially successful, reducing the dimensionality of the dataset to be more manageable, but the repository still contains a prohibitively large volume of data. However, this work paved the way for other researchers to collect their own video footage and build smaller naturalistic datasets for specific experiments, adding a new capability in safety research.

Other EAR-funded projects had similar outputs. In several projects related to CM, research teams worked not only on developing new materials but also on methods for modeling and simulating the chemical and physical reactions that create cement and concrete. These techniques allow researchers to conduct initial tests of new materials in computer simulations and then advance more promising materials to the laboratory for real-world development and testing. Although still in its early stages, these methods could accelerate the development of new variations on cement and concrete. Similarly, EAR-funded projects on TP not only helped validate the feasibility of the technology but also collected open datasets of observational and performance data from real-world platooning experiments. Under normal conditions, such data would only be collected by firms developing platooning technology and would not be open to

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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
×

the broader research community. By making these datasets available to the community, the EAR Program helped build confidence in platooning systems. This helped justify the funding of much larger TP demonstrations on actual public roads. Those demonstration projects are also compiling more real-world data for analysis by researchers.

3.3 Outcomes from Case Studies and Cross-Case Analysis

Evidence of short-term outcomes of EAR-funded projects is difficult to gather systematically because it relies largely on self-reporting of activities and events by stakeholders. Some indicators of short-term outcomes were gathered through interviews with key participants in EAR-funded research. To make data collection more manageable, this outcome analysis focused on a few case studies where such outcomes were more likely to be evident.

3.3.1 Impact of EAR Program on FHWA R&T Capacity

FHWA staff who oversee EAR-funded projects (AOTRs) are drawn primarily from FHWA R&T Offices. These research staff members are empowered to observe the findings of EAR research relevant to their permanent positions and learn key findings of use to FHWA R&T priorities. Some AOTRs also leverage the EAR Program by suggesting topics that are of direct interest to them but are too early stage or high risk to justify direct funding by their offices. For example, in the CM domain, these project officers were involved in EAR projects on biologically based materials and other alternatives to traditional cement compounds, in part to assess the feasibility of pursuing this topic in future R&T research efforts. The EAR Program also puts FHWA R&T staff directly in contact with members of the transportation research community, exposing them to state-of-the-art research efforts and helping them stay current on recent developments.

3.3.2 Application of EAR Research to Technical and Market Problems

Exploratory advanced research is intended to identify potential breakthrough innovations, where new technologies and knowledge provide novel and radical means to overcome long-standing challenges in areas such as highway safety and road system efficiency. As noted earlier, most EAR-funded projects do not result in immediate solutions to technical and market problems; instead they provide new options for addressing and specifying those problems. The development of new datasets through investments in VA and TP projects, for example, helped the broader research community pursue new means of conducting safety research through simulation and revealed key human factors concerns that might impede deployment of TP. Researchers in industry also noted that they have repurposed some of the work on VA to use those techniques in their own research on autonomous vehicle technology. The consensus expressed in interviews reflected the sentiment that the EAR Program directs its efforts at addressing key technical and market problems, although it may be able to make only partial progress toward creating solutions. In limited cases, external partners initiated development of market-focused solutions from EAR-funded research. In one instance, an insurance company adapted findings from investigations using behavioral economics to influence driver behavior and then developed interventions that promote driver safety and reduce accidents.

3.3.3 Connection of EAR Research to External Partners

The EAR Program facilitates connections between (primarily academic) transportation research on exploratory topics and external stakeholders. A large portion of EAR-funded projects involve partnerships between universities, firms, and state transportation authorities. PIs reported

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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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that industry partners were involved directly in their projects, most frequently by contributing in-kind support (such as datasets, equipment, and research tools) but also by facilitating access to other resources, such as research test beds or potential end users of solutions under development.

Another form of short-term outcome is the role of the EAR Program in building up the transportation research workforce. Results from the PI survey indicate that as many as half of the undergraduates involved in EAR-funded projects took jobs in the transportation industry, while more than two-thirds of graduate students continued their work in transportation after graduation. Virtually all postdoctoral scholars went on to conduct further transportation research. Several experts in transportation research noted during interviews that this domain has faced difficulties in recruiting new research talent because work in technical areas like IT is often seen by students as more interesting and remunerative. By introducing students to cutting-edge research topics and techniques, the EAR Program could play a significant role in recruiting and retaining early-career researchers who focus on problems in the transportation sector.

3.3.4 Influence of EAR Program Research on Follow-On R&D Efforts

Interviews with transportation-sector experts and PIs suggest that the role of the EAR Program, as an exploratory program, is to fund research for a defined time frame and then rely on other organizations to support ongoing R&D on these topics. A valuable purpose of the Program is to fund investigations into topics that seem to offer potential breakthroughs and then generate evidence indicating whether those topics can produce the benefits first estimated. If so, the EAR projects can then provide indication of the further research needed to bring the breakthrough innovations to fruition. Numerous examples from EAR-funded projects show that research results did contribute to later investments in continued research within areas identified by those results.

In TP, the work conducted by California Partners for Advanced Transportation Technology (PATH) and Auburn University contributed directly to building renewed interest in this technology at a time when it had been waning. The findings from those groups prompted FHWA to fund three follow-on Phase 1 demonstration projects of TP in 2019 and, more recently, to award a Phase 2 demonstration contract to California PATH to work with freight shipping firms on field-testing truck platoons on public roads. These projects also contributed to other work on TP systems funded by DOE and the U.S. Army.

In CM, early projects to develop new computation modeling techniques produced only mixed results. The computational models built on first principles and underlying knowledge of chemistry tended to underperform incumbent modeling techniques that were based on purely empirical observation. However, computational approaches and understanding of cement continued to evolve after EAR funding ended. These modeling approaches are now being used in situations where end users need to be able to mix cement and deploy concrete in more exotic conditions. The Army Corps of Engineers has explored the use of these techniques to develop alternatives to concrete that can be used to build structures in environments such as deserts because delivering concrete to those locales can be difficult. One researcher on an EAR-funded project is now consulting for a NASA effort to determine whether the agency can create a cement compound from lunar dust, anticipating that it could help in plans to establish a permanent human base on the Moon.

Researchers in VA projects reported that work on their techniques continued in projects funded by DARPA and the Intelligence Advanced Research Projects Activity, two agencies that fund exploratory research in national security.

In both TP and VA, early work funded by the EAR Program has been eclipsed by the tremendous private investment in more advanced technologies, such as fully autonomous driving and

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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
×

artificial intelligence for video data analysis. Those developments are examples of a potential risk in pursuing exploratory research—research topics that appear promising can rarely forecast when newly emerging technologies will advance more rapidly and create competing technologies. This dynamic is seen most frequently in IT, where cheap and plentiful computing power and data storage has reduced the barriers to entry in technology development and expanded research capabilities worldwide. However, experts point out that even in these areas, the EAR Program is likely to focus research on domains that are often ignored by private research organizations, such as public safety. In light of this, investment by the EAR Program may be justified as a counterbalance to purely commercial research on similar technologies.

3.4 Potential and Realized Socioeconomic Outcomes of EAR Program Research

Ultimately, the EAR Program is expected to contribute toward the attainment of longer-term strategic goals for FHWA, including improvements in the safety, efficiency, reliability, and resilience of the national surface transportation system. Given the relatively small amount of funding allocated to the EAR Program and its focus on early-stage R&D that is far short of actual application, it is very difficult to specify the exact extent to which changes in those socioeconomic priority areas are directly attributable to EAR investments. The EAR Program funded a retrospective study on prior “breakthrough technologies” in surface transportation that revealed that many breakthroughs were based on research efforts that began decades before the appearance of actual applications and systems (Machek et al., 2018).

The EAR Program has been operating for less than 20 years, so it may still be premature to expect the appearance of significant breakthrough technologies that stem directly from EAR-funded research. In the selection of research topics, the EAR Program and its stakeholders focus explicitly on socioeconomic concerns that suffer from chronic underinvestment, such as safety technologies for disabled pedestrians or improved methods for detecting and predicting structural failures in roads and bridges. While this study was not able to establish a clear counterfactual (i.e., how socioeconomic conditions would be different if the EAR Program did not exist), available evidence indicates that investments in these underfunded domains would be even lower without a funding source like the EAR Program.

3.5 Findings from Outcomes Evaluation

The outcomes evaluation of the EAR Program highlighted a few broad findings about the nature of the shorter-term impacts and longer-term implications of exploratory research in surface transportation:

  • The EAR Program could be better equipped to trace its outputs and outcomes if it maintained a more systematic process for capturing data on outputs. Other federal research agencies have developed public access repositories for research literature published from funded projects. Notable examples include the PubMed database at the National Institutes of Health and the Public Access Repository at the NSF. While this function could be provided through the National Transportation Library, the collection of information from PIs and research partners on articles published, patent applications filed, students trained, and other outputs would require additional resources and staff effort within the EAR Program itself.
  • The EAR Program produces specific intangible benefits and impacts that are not communicated on a regular basis to stakeholders. The complementary relationship between EAR-funded projects and other research activities at FHWA R&T is highlighted occasionally in
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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  • FHWA publications but could be more clearly presented. These intangible benefits include the development of new research tools, software, and datasets that benefit the transportation research community. Tracking and publicizing these types of research outputs would highlight an aspect of the EAR Program that extends beyond its original mission to support potential breakthrough technology development.
  • Since even the short-term outcomes of EAR-funded research may take years to emerge, periodic retrospective analyses would help FHWA capture those impacts and understand their significance. This information could be collected through periodic interviews or surveys of PIs on completed EAR-funded projects and through conversations with external partners involved in previous EAR research efforts. That information could also be used to enhance current approaches to transition planning and communication strategies for active EAR projects because it would help PIs and FHWA staff appreciate the diverse benefits generated from EAR-funded research.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
×
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
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Suggested Citation:"Section 3 - Evaluation of EAR Program Outcomes and Impact." National Academies of Sciences, Engineering, and Medicine. 2022. Evaluation of the Exploratory Advanced Research Program. Washington, DC: The National Academies Press. doi: 10.17226/26616.
×
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Beginning in 2019, the U.S. Federal Highway Administration (FHWA) requested that TRB be directly involved in managing evaluations of selected projects undertaken by the agency.

The TRB Cooperative Research Program's CRP Special Release 2: Evaluation of the Exploratory Advanced Research Program presents an evaluation of the program, which works on a range of topics, including human-automation interaction, safety improvements through advanced data analysis, innovative materials for highway pavements and structures, methods to improve transportation system resilience, and technologies for alternative fuels development.

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