[Federal Register Volume 89, Number 87 (Friday, May 3, 2024)]
[Notices]
[Pages 36848-36851]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2024-09645]


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DEPARTMENT OF TRANSPORTATION

[Docket No. DOT-OST-2024-0049]


Opportunities and Challenges of Artificial Intelligence (AI) in 
Transportation; Request for Information

AGENCY: Department of Transportation (DOT)

ACTION: Notice; Request for Information (RFI).

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SUMMARY: The U.S. Department of Transportation's Advanced Research 
Projects Agency--Infrastructure (ARPA-I) is seeking input from 
interested parties on the potential applications of artificial 
intelligence (AI) in transportation, as well as emerging challenges and 
opportunities in creating and deploying AI technologies in applications 
across all modes of transportation. The purpose of this Request for 
Information (RFI) is to obtain input from a broad array of stakeholders 
on AI opportunities, challenges and related issues in transportation 
pursuant to Executive Order (E.O.) 14110 of October 30, 2023 entitled 
``Safe, Secure, and Trustworthy Development and Use of Artificial 
Intelligence''.

DATES: Written submissions must be received within 60 days of the 
publication of this RFI.

ADDRESSES: Please submit any written comments to Docket Number DOT-OST-
2024-0049 electronically through the Federal eRulemaking Portal at 
https://regulations.gov. Go to https://regulations.gov and select 
``Department of Transportation (DOT)'' from the agency menu to submit 
or view public comments. Note that, except as provided below, all 
submissions received, including any personal information provided, will 
be posted without change and will be available to the public on https://www.regulations.gov. You may review DOT's complete Privacy Act 
Statement in the Federal Register published on April 11, 2000 (65 FR 
19477) or at https://www.transportation.gov/privacy.

FOR FURTHER INFORMATION CONTACT: For questions about this RFI, please 
email [email protected]. You may also contact Mr. Timothy A. Klein, 
Director, Technology Policy and Outreach, Office of the Assistant 
Secretary for Research and Technology (202-366-0075) or by email at 
[email protected].

SUPPLEMENTARY INFORMATION: Advances in artificial intelligence (AI) 
bring significant potential benefits and risks, and they have the 
potential to transform American society with deep implications for 
safety, access, equity and resilience in the transportation sector. 
Virtually all aspects of transportation and mobility--from the design, 
construction, operation, and maintenance of physical infrastructure 
systems to the operation of the digital infrastructure that underpins 
and enables the movement of people and goods--will likely be impacted 
by the deployment of AI tools and applications.Beyond the direct impact 
of the technology itself, AI has the potential to reshape how 
individuals, communities, corporations, governments, and other users 
interact with the transportation network in ways that are difficult to 
anticipate. In recognition of AI's rapidly evolving

[[Page 36849]]

capabilities and implications across all facets of government, society 
and our economy, the Biden Administration issued Executive Order (E.O.) 
14110 on Safe, Secure, and Trustworthy Development and Use of 
Artificial Intelligence on October 30, 2023. In section 8, ``Protecting 
Consumers, Patients, Passengers, and Students'', under Sub-section (c), 
the E.O. directs the U.S. Department of Transportation to ``promote the 
safe and responsible development and use of AI in the transportation 
sector, in consultation with relevant agencies''. Paragraph (iii) under 
sub-section (c) further requires that ARPA-I ``explore the 
transportation-related opportunities and challenges of AI--including 
regarding software-defined AI enhancements impacting autonomous 
mobility ecosystems''.
    This RFI seeks information that will assist ARPA-I and the U.S. 
Department of Transportation (DOT) in carrying out their 
responsibilities under section 8 (c)(iii) of E.O. 14110 noted above.

About ARPA-I

    The Advanced Research Projects Agency--Infrastructure (ARPA-I) is 
an agency within DOT (see https://www.transportation.gov/arpa-i) that 
Congress established ``to support the development of science and 
technology solutions that overcomes long-term challenges and advances 
the state of the art for United States transportation infrastructure.'' 
(Pub. L. 117-58, section 25012, November 15, 2021; 49 U.S.C. 119). 
ARPA-I is modeled after the Defense Advanced Research Projects Agency 
(DARPA) within the U.S. Department of Defense and the Advanced Research 
Projects Agency-Energy (ARPA-E) within the U.S. Department of Energy. 
ARPA-I offers a once-in-a-generation opportunity to improve our 
nation's transportation infrastructure, both physical and digital, and 
supports DOT's strategic goals of Safety, Economic Strength and Global 
Competitiveness, Equity, Climate and Sustainability, and 
Transformation. ARPA-I focuses on developing and implementing 
technologies, rather than developing policies and processes or 
providing regulatory support. ARPA-I has a single overarching goal and 
focus: to fund external innovative advanced research and development 
(R&D) programs that develop new technologies, systems, and capabilities 
to improve transportation infrastructure in the United States.
    The aims of ARPA-I include ``lowering the long-term costs of 
infrastructure development, including costs of planning, construction, 
and maintenance; reducing the lifecycle impacts of transportation 
infrastructure on the environment, including through the reduction of 
greenhouse gas emissions; contributing significantly to improving the 
safe, secure, and efficient movement of goods and people; promoting the 
resilience of infrastructure from physical and cyber threats; and 
ensuring that the United States is a global leader in developing and 
deploying advanced transportation infrastructure technologies and 
materials.'' (Pub. L. 117-58, section 25012, November 15, 2021; 49 
U.S.C. 119). Funding the development and use of AI technologies to 
address these challenges is expected to be a key future activity of 
ARPA-I.

Federal Activities on AI Most Closely Related to DOT's Work

    E.O. 14110 directs agencies all across government, including the 
Department of Transportation, to take a wide range of actions that will 
help ensure the United States leads the way in seizing AI's promise and 
managing its risks. This work includes actions to manage AI's safety 
and security risks, promote innovation and competition, advance equity 
and civil rights, protect Americans' privacy, stand up for consumers 
and workers, and more. Beyond E.O. 14110, the Federal Government has 
also fostered and funded work to advance the responsible development of 
AI and machine learning (ML) for decades. Examples of such work range 
from early work conducted by the Department of Defense's Advanced 
Research Projects Agency (now DARPA) to ongoing efforts summarized in 
the 2023 Update to the National Artificial Intelligence Research and 
Development Strategic Plan, led by the White House Office of Science 
and Technology Policy (OSTP).
    In general, Federal investments in and other support for basic and 
applied research in AI in transportation are critical to achieving 
national priorities and build on applied AI research across the Federal 
government. Foundational research into and application of AI has been 
supported by the National Science Foundation (NSF), the Department of 
Defense (DOD), the Department of Energy (DOE), the Department of 
Homeland Security (DHS) Cybersecurity and Infrastructure Security 
Agency (CISA), the National Institute of Standards and Technology 
(NIST), and the National Aeronautics and Space Administration (NASA). 
Ongoing AI research at these agencies with high relevance to DOT 
priorities include developing effective methods for human-AI 
collaboration, ensuring the safety and security of AI-based systems, 
developing shared public datasets and environments for AI training and 
testing, measuring, and evaluating AI-based systems through standards 
and benchmarks.

DOT Activities on AI

    AI approaches are being applied to a range of activities and 
efforts across DOT; this section provides a brief, non-comprehensive 
overview.
    Operating administrations within DOT have developed and implemented 
many uses of AI. These range from use of AI and ML technologies to 
streamline transportation operations (e.g., weather prediction, routing 
and scheduling, transit automation), to research projects addressing 
safety (e.g., driver behavior classification, passenger safety, 
incident risk assessment, grade crossing safety video analytics), to 
tools for rapid analysis of text and component schematic data 
submissions, and to perform real-time asset management to maintain a 
state of good repair. AI and ML tools may have applications across all 
of DOT's operating administrations, with many actively exploring uses 
including the Federal Aviation Administration (FAA), Federal Highway 
Administration (FHWA), Federal Motor Carrier Safety Administration 
(FMCSA), Federal Railroad Administration (FRA), Federal Transit 
Administration (FTA), Great Lakes St. Lawrence Seaway Development 
Corporation (GLS), National Highway Traffic Safety Administration 
(NHTSA), Maritime Administration (MARAD), and Pipeline and Hazardous 
Materials Safety Administration (PHMSA).
    The Intelligent Transportation System Joint Program Office (ITS 
JPO) within DOT has established the AI for ITS Program, recognizing the 
promise that AI offers for achieving significant benefits in 
transportation safety, mobility, efficiency, equity, accessibility, 
productivity, and resilience, while achieving reductions to individual 
and societal costs, emissions, and other negative environmental 
impacts. Currently, ITS JPO is developing AI-enabled ITS Capability 
Maturity Model and Readiness Checklists, and the Application of the 
NIST AI Risk Management Framework for ITS. ITS JPO published a review 
of AI for ITS in October 2022.
    Two DOT initiatives that include the application of AI to serve the 
Department's policy priorities are being led by the Office of the 
Assistant Secretary for Research and Technology (OST-R). The U.S. DOT 
Intersection Safety Challenge (https://its.dot.gov/isc/ isc/) is a prize-
based competition that is

[[Page 36850]]

exploring how a combination of advanced sensing, perception, path 
planning and prediction, and AI-based decision making can help to 
improve intersection safety for vulnerable road users. The Complete 
Streets Artificial Intelligence (CSAI) Small Business Innovative 
Research (SBIR) program (https://its.dot.gov/csai/) is a multi-phase 
effort to develop powerful new decision-support tools for public 
agencies to assist in the siting, design, and deployment of streets and 
road networks that prioritize safety, efficiency, and connectivity.
    Additional AI-related activities at OST-R include extramural 
research conducted at a number of University Transportation Centers, 
work at the Highly Automated Systems Safety Center of Excellence, 
technology demonstration projects through the SMART Grants Program, and 
research at the U.S. DOT Volpe Center.
    Similarly, consistent with E.O. 14110, the Department's internal 
Non-Traditional and Emerging Transportation Technology (NETT) Council 
has work underway to identify use cases across the various operating 
administrations and share observations and potential implications for 
the use of AI throughout the existing transportation system. Finally, 
the Transforming Transportation Advisory Committee (TTAC) and the 
Advanced Aviation Advisory Committee (AAAC) have been directed by 
Secretary Buttigieg to provide insights on the Department's approach to 
AI and make recommendations for this technology's integration into 
operational advancements, in a manner that anticipates AI's benefits, 
while safeguarding against its negative impacts.

Potential Development and Uses of AI in Transportation

    This section provides illustrative use cases to help respondents to 
this RFI consider the breadth of potential uses of AI in 
transportation, including physical infrastructure, digital 
infrastructure, operations, and many other aspects.
    Many of the fundamental components of AI technologies and AI tools 
developed in other domains will be directly applicable to AI in 
transportation, from algorithmic advances, foundational model 
development, machine learning, deep learning techniques, and AI 
assurance methods to methods for ensuring cybersecurity, model 
transparency and trustworthiness.
    As the Federal government has emphasized, there are substantial 
ethical, legal, and societal risks and potential adverse effects 
surrounding the application of AI across society. Minimizing risks and 
adverse effects through developing trustworthy AI and enhancing trust 
in human-AI interactions, reducing bias in data, protecting privacy, 
and developing robust AI systems, standards, and frameworks will be 
integral to ensuring the effective incorporation of these new 
technologies into transportation and mobility systems.
    This RFI employs the meaning of ``artificial intelligence'' or 
``AI'' as used in E.O. 14110 and set forth in 15 U.S.C. 9401(3): ``a 
machine-based system that can, for a given set of human-defined 
objectives, make predictions, recommendations, or decisions influencing 
real or virtual environments. Artificial intelligence systems use 
machine- and human-based inputs to perceive real and virtual 
environments; abstract such perceptions into models through analysis in 
an automated manner; and use model inference to formulate options for 
information or action.'' ARPA-I defines ``Digital Infrastructure'' as 
the sensing, computation, automation, networking, connectivity, data 
management, analysis, optimization, control and virtual elements that 
underpin our physical transportation infrastructure. Beyond 
transportation-specific use cases, AI also has the potential to 
increase operational efficiencies for DOT's own internal core business, 
regulatory, and permitting functions, including such applications as 
analyzing consumer complaints, compiling and summarizing public 
comments, streamlining permitting and application processes and more.
    Potential areas for funded AI research and development at DOT will 
span all modes of transportation and mobility and could include:
     Enhancing the safety of pedestrians and vulnerable road 
users at roadway intersections through technologies such as ML and deep 
learning for computer vision, perception, sensor fusion, real-time 
decision making and warning systems,
     Real-time AI-based decision support tools, optimization 
and control of wide area traffic systems and transit operations,
     Autonomous mobility systems and vehicles on roads and 
rails, in the air, and on water (AI-intensive computation hardware and 
its design are beyond the scope of this RFI),
     Optimization of road traffic management systems and 
signalized intersections in cities and towns across timescales from 
seconds or minutes to hours, including such elements as variable speed 
limit control, queue detection and prediction, and wrong-way driving 
detection,
     Optimization of equitable curb management in urban areas,
     Transportation systems management and operations (TSMO) 
optimization and control,
     Use of AI to assess traveler behavior and preferences 
across modes,
     Real-time monitoring of transit rail systems for 
maintenance assessment and state of good repair,
     Real-time monitoring of transit facilities for incident 
risk analysis,
     Air traffic control optimization for large-scale aviation 
operations facilitated by AI,
     Development and operation of secure complementary 
position, navigation, and timing (PNT) systems using AI-based 
recognition and utilization of signals of opportunity,
     AI assessment and assurance tools, methods and frameworks, 
benchmarks, testing environments, validation and verification, and the 
creation of datasets for AI and AI-enabled systems across all modes of 
transportation,
     Automating and digitizing physical infrastructure asset 
management through AI to optimize planning, design, operations, 
construction, and maintenance, and end of life,
     Optimizing planning, design, build and permitting for 
infrastructure construction and repair, and reducing construction costs 
by incorporating best practices developed through generative AI, 
including natural language processing (NLP) and large language model 
(LLM)-based processing of existing knowledge and databases,
     Sensor output processing, sensor fusion, data analysis, 
and ML for analysis and control of large-scale transportation networks 
and systems, including remote sensing,
     Real-time control and optimization of traffic networks and 
signalization from the local scale to a full city or region,
     Optimization of multimodal freight and logistics networks 
and supply chains nationally, including commercial vehicle, marine, 
rail and aviation freight and logistics systems,
     Safe operation of uncrewed air systems (UAS) in emerging 
aviation applications,
     Developing shared mobility-on-demand (MOD) services, from 
AI-based dynamic route scheduling and fleet optimization for city or 
region-wide passenger demand using traveler decision support tools,
     Offline analysis of traffic data, transportation safety 
data, and emissions inventories,

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     Enhancing mapping and spatial AI for real-time automation 
and navigation across all modes, as well as for infrastructure design, 
maintenance, and repair,
     AI-based robotic repair and repurposing of pipeline 
infrastructure, and
     AI-enhanced robotic mapping of sub-surface infrastructure 
and utilities for safe, efficient, and cost-effective ``dig once'' 
construction.

Specific Questions

    This RFI seeks information that will assist ARPA-I and the U.S. 
Department of Transportation in carrying out responsibilities under 
section 8 (c)(iii) of E.O. 14110, as noted above.
    DOT is providing the following specific questions to prompt 
feedback and comments. DOT encourages public comment on any of these 
questions and seeks any other information commenters believe is 
relevant.
    DOT is requesting information from all interested entities and 
stakeholders, including innovators and technology developers, 
researchers and universities, transportation system and infrastructure 
owners and operators, transportation-focused groups, organizations and 
associations, and the public. Where appropriate, responses should 
include discussion of real-world applications and actual examples of AI 
technologies, tools, and methods currently being used or contemplated 
for future use in the transportation and mobility domain.
    DOT is interested in receiving succinct and relevant responses to 
some or all of the following questions, keeping in mind the current 
efforts and potential use cases as described above:

Question 1: Current AI Applications in Transportation

    What are the relevant current or near-term applications of AI in 
transportation? If applicable, describe the mode(s) of transportation 
that these applications cover, referencing DOT's stated priorities 
(including safety, climate and sustainability, equity, economic 
strength and global competitiveness, and transformation) that these 
applications support.

Question 2: Opportunities of AI in Transportation

    What are the future potential opportunities in transportation that 
AI can facilitate? Describe the mode(s) of transportation that these 
opportunities cover, referencing DOT's stated priorities (including 
safety, climate and sustainability, equity, economic strength and 
global competitiveness, and transformation) as appropriate.

Question 3: Challenges of AI in Transportation

    What are the current or future challenges of AI in transportation, 
including risks presented by the use of AI in transportation and 
potential barriers to its responsible adoption? Describe the mode(s) of 
transportation that these challenges cover, referencing DOT's stated 
priorities (including safety, climate and sustainability, equity, 
economic strength and global competitiveness, and transformation) as 
appropriate.

Question 4: Autonomous Mobility Ecosystems

    What are the opportunities, challenges, and risks of AI related to 
autonomous mobility ecosystems, including software-defined AI 
enhancements? Describe how AI can responsibly facilitate autonomous 
mobility, including specifically safety considerations.

Question 5: Other Considerations in the Development of AI for 
Transportation

    Comment on any other considerations relevant to the development, 
challenges, and opportunities of AI in transportation that have not 
been included in the questions above. These considerations may include 
ones such as potential priorities in transportation-specific future AI 
R&D funding, access to transportation datasets, the development of AI 
testbeds, physical and digital infrastructure needs and requirements, 
and workforce training and education.

Confidential Business Information

    Do not submit information disclosure of which is restricted by 
statute, such as trade secrets and commercial or financial information 
(hereinafter referred to as Confidential Business Information ``CBI'') 
to Regulations.gov. Comments submitted through Regulations.gov cannot 
be claimed as CBI. Comments received through the website will waive any 
CBI claims for the information submitted.

    Issued in Washington, DC, on April 26, 2024.
Robert C. Hampshire,
Principal Deputy Assistant Secretary for Research and Technology and 
Chief Science Officer.
[FR Doc. 2024-09645 Filed 5-2-24; 8:45 am]
BILLING CODE 4910-9X-P