Notice2024-09645
Opportunities and Challenges of Artificial Intelligence (AI) in Transportation; Request for Information
Primary source
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Published
May 3, 2024
Issuing agencies
Transportation Department
Abstract
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".
Full Text
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<title>Federal Register, Volume 89 Issue 87 (Friday, May 3, 2024)</title>
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[Federal Register Volume 89, Number 87 (Friday, May 3, 2024)]
[Notices]
[Pages 36848-36851]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[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
<a href="https://regulations.gov">https://regulations.gov</a>. Go to <a href="https://regulations.gov">https://regulations.gov</a> 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 <a href="https://www.regulations.gov">https://www.regulations.gov</a>. You may review DOT's complete Privacy Act
Statement in the Federal Register published on April 11, 2000 (65 FR
19477) or at <a href="https://www.transportation.gov/privacy">https://www.transportation.gov/privacy</a>.
FOR FURTHER INFORMATION CONTACT: For questions about this RFI, please
email <a href="/cdn-cgi/l/email-protection#f0b1a2a0b1ddb9b0949f84de979f86"><span class="__cf_email__" data-cfemail="37766567761a7e7753584319505841">[email protected]</span></a>. 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
<a href="/cdn-cgi/l/email-protection#1a6e7377756e72633471767f73745a7e756e347d756c"><span class="__cf_email__" data-cfemail="92e6fbfffde6faebbcf9fef7fbfcd2f6fde6bcf5fde4">[email protected]</span></a>.
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 <a href="https://www.transportation.gov/arpa-i">https://www.transportation.gov/arpa-i</a>) 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 (<a href="https://its.dot.gov/isc/">https://its.dot.gov/isc/</a> isc/) is a prize-
based competition that is
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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 (<a href="https://its.dot.gov/csai/">https://its.dot.gov/csai/</a>) 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:
<bullet> 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,
<bullet> Real-time AI-based decision support tools, optimization
and control of wide area traffic systems and transit operations,
<bullet> 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),
<bullet> 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,
<bullet> Optimization of equitable curb management in urban areas,
<bullet> Transportation systems management and operations (TSMO)
optimization and control,
<bullet> Use of AI to assess traveler behavior and preferences
across modes,
<bullet> Real-time monitoring of transit rail systems for
maintenance assessment and state of good repair,
<bullet> Real-time monitoring of transit facilities for incident
risk analysis,
<bullet> Air traffic control optimization for large-scale aviation
operations facilitated by AI,
<bullet> Development and operation of secure complementary
position, navigation, and timing (PNT) systems using AI-based
recognition and utilization of signals of opportunity,
<bullet> 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,
<bullet> Automating and digitizing physical infrastructure asset
management through AI to optimize planning, design, operations,
construction, and maintenance, and end of life,
<bullet> 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,
<bullet> Sensor output processing, sensor fusion, data analysis,
and ML for analysis and control of large-scale transportation networks
and systems, including remote sensing,
<bullet> Real-time control and optimization of traffic networks and
signalization from the local scale to a full city or region,
<bullet> Optimization of multimodal freight and logistics networks
and supply chains nationally, including commercial vehicle, marine,
rail and aviation freight and logistics systems,
<bullet> Safe operation of uncrewed air systems (UAS) in emerging
aviation applications,
<bullet> 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,
<bullet> Offline analysis of traffic data, transportation safety
data, and emissions inventories,
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<bullet> Enhancing mapping and spatial AI for real-time automation
and navigation across all modes, as well as for infrastructure design,
maintenance, and repair,
<bullet> AI-based robotic repair and repurposing of pipeline
infrastructure, and
<bullet> 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 <a href="http://Regulations.gov">Regulations.gov</a>. Comments submitted through <a href="http://Regulations.gov">Regulations.gov</a> 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
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