Notice2022-20188
Enhancing the Safety of Vulnerable Road Users at Intersections; Request for Information
Primary source
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Published
September 16, 2022
Issuing agencies
Transportation Department
Abstract
Improving the safety of pedestrians, bicyclists, and other vulnerable road users (VRUs) is of critical importance to achieving the objectives of DOT's National Roadway Safety Strategy (NRSS), and DOT's vision of zero fatalities and serious injuries across our transportation system. According to data from the National Highway Traffic Safety Administration (NHTSA), in 2020 there were 10,626 traffic fatalities in the United States at roadway intersections, including 1,674 pedestrian and 355 bicyclist fatalities. These fatalities at intersections represent 27% of the total of 38,824 road traffic deaths recorded in 2020. Separately, considerable development efforts have been made into automation technologies over the past two decades, including in the areas of vehicle automation, machine vision, perception and sensing, vehicle-to-everything (V2X) communications, sensor fusion, image and data analysis, artificial intelligence (AI), path planning, and real-time decision-making. DOT is interested in receiving comments on the possibility of adapting existing and emerging automation technologies to accelerate the development of real-time roadway intersection safety and warning systems for both drivers and VRUs in a cost-effective manner that will facilitate deployment at scale.
Full Text
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<title>Federal Register, Volume 87 Issue 179 (Friday, September 16, 2022)</title>
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[Federal Register Volume 87, Number 179 (Friday, September 16, 2022)]
[Notices]
[Pages 57019-57022]
From the Federal Register Online via the Government Publishing Office [<a href="http://www.gpo.gov">www.gpo.gov</a>]
[FR Doc No: 2022-20188]
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DEPARTMENT OF TRANSPORTATION
[Docket No. DOT-OST-2022-0096]
Enhancing the Safety of Vulnerable Road Users at Intersections;
Request for Information
AGENCY: Department of Transportation (DOT).
ACTION: Notice; request for information (RFI).
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SUMMARY: Improving the safety of pedestrians, bicyclists, and other
vulnerable road users (VRUs) is of critical importance to achieving the
objectives of DOT's National Roadway Safety Strategy (NRSS), and DOT's
vision of zero fatalities and serious injuries across our
transportation system. According to data from the National Highway
Traffic Safety Administration (NHTSA), in 2020 there were 10,626
traffic fatalities in the United States at roadway intersections,
including 1,674 pedestrian and 355 bicyclist fatalities. These
fatalities at intersections represent 27% of the total of 38,824 road
traffic deaths recorded in 2020. Separately, considerable development
efforts have been made into automation technologies over the past two
decades, including in the areas of vehicle automation, machine vision,
perception and sensing, vehicle-to-everything (V2X) communications,
sensor fusion, image and data analysis, artificial intelligence (AI),
path planning, and real-time decision-making. DOT is interested in
receiving comments on the possibility of adapting existing and emerging
automation technologies to accelerate the development of real-time
roadway intersection safety and warning systems for both drivers and
VRUs in a cost-effective manner that will facilitate deployment at
scale.
DATES: Written submissions must be received within 30 days of the
publication of this RFI. DOT will consider comments received after this
time period to the extent practicable.
ADDRESSES: Please submit any written comments to Docket Number DOT-OST-
2022-0096 electronically through the Federal eRulemaking Portal at
<a href="https://www.regulations.gov">https://www.regulations.gov</a>. Go to <a href="https://www.regulations.gov">https://www.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 further information contact
<a href="/cdn-cgi/l/email-protection#6e1d0f080b07001a0b1c1d0b0d1a0701001d2e0a011a40090118"><span class="__cf_email__" data-cfemail="a1d2c0c7c4c8cfd5c4d3d2c4c2d5c8cecfd2e1c5ced58fc6ced7">[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#5c283531332834257237303935321c383328723b332a"><span class="__cf_email__" data-cfemail="76021f1b19021e0f581d1a131f183612190258111900">[email protected]</span></a>.
SUPPLEMENTARY INFORMATION: DOT is committed to the vision of zero
fatalities and serious injuries on our Nation's roadways, and improving
the safety of vulnerable road users (VRUs) at intersections is an
important component of that vision. According to data from NHTSA, in
2020 there were 10,626 traffic fatalities in the United States at
intersections, including 1,674 pedestrians and 355 bicyclists. These
fatalities at intersections represent 27% of the total of 38,824 road
traffic deaths recorded in 2020. Ensuring VRU safety is an urgent issue
as it is essential to allowing pedestrians, bicyclists, wheelchair
users, and others the safe use of roadways in urban and rural
environments in the United States. Reducing crashes at roadway
intersections is an important component of making our streets safer for
all users.
Considerable development efforts have occurred in automation and
vehicle automation technologies over the past two decades, including in
the areas of machine vision, perception and sensing, vehicle-to-
everything (V2X) communications, sensor fusion, image and data
analysis, artificial intelligence (AI), path planning, and real-time
decision-making on board vehicles. For the purposes of this RFI, these
automation technologies are considered to include but are not limited
to advanced driver assistance systems (ADAS), automated driving systems
(ADS) and associated vehicle connectivity technologies, as well as
other automation technologies that can enhance the safety of VRUs at
roadway intersections. DOT is interested in receiving comments on the
feasibility of adapting these automation technologies to the
application of warning systems that provide real-time safety and
warning alerts for both VRUs and drivers at intersections in a cost-
effective manner that will facilitate the deployment of these systems
at scale. Such safety systems could warn of and mitigate the effects of
an impending crash at an intersection for VRUs and vehicles alike.
A Conceptual VRU and Vehicle Warning System
The on-vehicle automation technologies currently being developed
for fully automated vehicle operation--including machine vision,
perception, sensor fusion, real-time decision-
[[Page 57020]]
making, artificial intelligence and V2X--could be used today to enhance
safety for all road users. Consider the deployment of these
technologies as infrastructure assets at each roadway intersection,
pedestrian crossing, and railroad crossing, in order to alert
approaching vehicles of the approach or incursion of pedestrians,
bicyclists and other VRUs, and vice versa. A conceptual VRU and vehicle
warning system will likely be made up of fixed infrastructure assets
that use robust sensing and computational technologies to perform
optimally across a range of environmental and operational conditions,
including non-line-of-sight (NLOS) conditions. The conceptual
intersection safety system that is described in this RFI should not be
considered as prescriptive, but merely one potential configuration
amongst many possible designs.
At busy roadway intersections across any particular time period
there will be a large number of vehicle and VRU movements, including
vehicles turning, pedestrians crossing the roadway, bicyclists crossing
the roadway, etc. For the majority of these movements, including those
that involve close interaction between drivers and VRUs, the vehicle-
VRU interaction will proceed without incident. A small fraction of
those interactions might involve near-misses where a vehicle comes
close to colliding with another vehicle or a VRU at a roadway
intersection. A much smaller fraction of those interactions results in
a collision between vehicles and VRUs, resulting in injury or in a
smaller fraction yet, an entirely avoidable pedestrian or VRU fatality.
It is the intent of this RFI to investigate the possibility of
developing new technologies, or new technology and/or system
combinations, to prevent vehicle-VRU crashes while facilitating normal
traffic flows and VRU movements.
For the purposes of this RFI, VRUs are defined as pedestrians,
bicyclists, and micro-mobility device users, including users of
scooters, e-skateboards, wheelchairs, etc. Vehicles are defined as any
roadway vehicles including passenger cars, trucks, vans, public transit
buses, and commercial vehicles. Equipping each roadway intersection
location today with the requisite machine vision hardware,
computational capability, networking, communications, and safety
alerting and warning technology would likely cost hundreds of thousands
of dollars per roadway intersection. While this concept of repurposing
mobile (vehicle) automation technologies in the fixed domain is not
new, it has not been commercialized or implemented at scale due to the
high system costs involved and the complexities of developing a
standardized and proven safety solution. There is an imperative to
reduce the cost of providing advanced safety systems that can ensure
the safety of all road users at roadway intersections, pedestrian
crossings, trail-roadway crossings, and railroad crossings. A cost
reduction of 10-100x for such a system--down to under $10,000 for the
hardware and software ``stack'' per intersection--would significantly
accelerate the implementation and deployment of these potentially life-
saving road safety technologies. As an example of the potential of cost
reduction in an adjacent domain, LiDAR units for automated vehicles
(AVs) have seen a 100x reduction in cost while progressing from large
roof-mounted electro-mechanical systems to smaller solid-state devices.
An effective roadway intersection safety system (designated here as
a ``conceptual VRU and vehicle warning system'') will likely require
machine vision, perception or sensing (LiDAR, radar, cameras, acoustics
etc. mounted on stationary structures), sensor fusion, computation,
communications, and warning systems to be developed, tested and
validated, and integrated along with software for vision, sensing, and
decision-making (to include AI). The intention of this RFI is to
ascertain the state of the art of relevant automation technologies, and
the potential for re-purposing existing and emerging technologies for
this stationary intersection safety application. The reduction in the
cost of these life-saving systems by a factor of 10-100x through the
targeted application of automation technologies would allow for the
development of a new, standardized VRU warning system that could
significantly benefit system end-users, including State, local, Tribal
and territorial DOTs and jurisdictions.
Additional Considerations for a VRU and Vehicle Warning System
The development of an automated VRU and vehicle warning system
should incorporate the use of existing standards and protocols to the
greatest extent possible. System-to-vehicle and vehicle-to-system
communications and networking (V2X), using standard and emerging
protocols, will likely be required (note that ``system'' here can
include fixed infrastructure elements or communication with portable
devices). For instance, smart mobile phone notifications for either
VRUs or approaching vehicles using near-field communications (such as
Bluetooth) might be a useful additional warning technology, beyond
other alerting systems, but the use of smart electronic devices by VRUs
should not be a requirement for the efficacy of an intersection safety
system. Virtual machine vision systems incorporating ``crowd-sourced''
vehicle-based real-time imaging and information sharing (moving and
parked vehicles) could also be of use. Ensuring night-time, low light,
and reduced visibility (e.g., fog, rain, snow) operation will be
critical for such an intersection safety system. It is anticipated that
developers of VRU and vehicle warning systems will benefit from the
collection of large amounts of data and imagery from the operation of a
real-world roadway intersection to develop vision systems and train
machine learning (ML) algorithms. This data could be developed and
shared to accelerate the parallel development of effective solutions.
Important considerations for any intersection safety technology
include its efficacy of operation while not degrading existing levels
of safety or traffic operation; its ability to be implemented and
deployed at scale; the system cost; consistent and reliable system
operation and performance; operation under all weather, lighting and
environmental conditions; reliability and maintenance requirements;
personnel and training requirements; ease of deployment; ease of
calibration and customization at a specific intersection location; its
potential for rapid commercialization and deployment within 3-5 years;
upgradeability and modularity, and interoperability and data transfer
capability with existing signal operating systems and traffic
management systems, while avoiding technological lock-in.
It is not anticipated that a single technical solution or system
will be suitable for implementation at all roadway intersections, but
it is anticipated that a single solution can be developed that will
suit a large proportion of the most crash-prone intersections. These
technologies may also serve to enhance the use of Data-Driven Safety
Analysis (DDSA) techniques that can inform State, local, Tribal, and
territorial DOTs in their decision making, and allow them to target the
implementation of infrastructure investments that improve safety and
equity. Once deployed in multiple locations, real-time data sharing
between adjacent or neighboring intersection safety systems could
further improve the safety of local road networks.
[[Page 57021]]
General Considerations for the Development of a VRU and Vehicle Warning
System
First, the addition of a VRU and vehicle warning system should not
degrade the baseline performance of any existing intersection. It is
acknowledged that a hardware and software-based intersection safety
system may have significant additional `soft' costs beyond the cost of
construction (or bill of materials for its constituent components)--
permitting, installation, testing, calibration, operation (although
operation should be fully automated), training, maintenance,
integration with other existing systems, R&D costs, etc. A VRU and
vehicle warning system should ideally leverage existing components,
systems and technologies to the greatest extent possible (including
open, interoperable communications to maximize the accessibility and
safety benefits), should meet all applicable Federal and State
standards, should be suitable both for new installations and retrofits,
and its software should use transparent non-opaque algorithms. Any
system installation, use, operation, and maintenance should be
expeditious and minimally disruptive to the road users. It is
anticipated that determining the performance of any intersection safety
system will require extensive testing in both benign and extreme
environments, including for electromagnetic compatibility, and will
probably require extensive data collection for overall system
development, testing, validation and calibration.
System Components and Hardware and Software Technologies--A Conceptual
Design
A conceptual design for a VRU and vehicle intersection safety
system would likely require the following elements and would probably
need to account for the associated features or considerations (these
potential design elements should not be considered to be prescriptive,
but merely representative of the current state of the art):
<bullet> Sensing and perception. A perception system will likely
require machine vision that includes cameras, LiDAR and radar that
provide a full field of view under all lighting and weather conditions,
and to provide redundancy. The resolution, bandwidth, latency, power
consumption, and cost considerations of the vision and perception
system will be important.
<bullet> Sensor fusion, image and data analysis. This will likely
require high computational throughput (of the order of gigapixels per
second), and should utilize industry-standard computational and
networking bus architectures. The real-time image and data analysis
should sense the movement of individual VRUs and vehicles, and be
capable of inferring intent. Privacy protections should be maintained,
and precise timing (derived from global navigation satellite systems
[GNSS] or secondary or back-up sources that can be space- or land-
based) should be used. It is likely that the sensor fusion, image, and
data analysis will require significant levels of AI (and ML) capability
and be capable of high gigabit per second data throughputs.
<bullet> Path planning and prediction. The discrete paths of motion
of all vehicles and VRUs in or near the intersection (perhaps as many
as twenty or more items of interest) will likely need to be tracked and
predicted simultaneously in order to determine potential or impending
vehicle-VRU conflicts. This computation, logic and decision-making will
likely need to be performed by a high bandwidth, low latency, high
speed microprocessor-based system located at the intersection (perhaps
in a roadside unit, or RSU). The real-time decision-making process will
need to result in an ``alert or no alert/warning or no warning'' output
that minimizes false positives and false negatives while ultimately
providing safe and actionable warnings to the VRUs and/or approaching
vehicles.
<bullet> Data handling and storage. Large quantities of data
(potentially terabytes of data per day per intersection) may be
required to be stored and archived, with attention paid to
anonymization, privacy, and cybersecurity threats. This will likely
include local storage as well as cloud- or edge-based archiving.
<bullet> Communications and networking. A roadside unit or other
form of infrastructure (i.e., Access Point, small-cell set-up, or edge-
computer) will likely be required to house the computational hardware
as well as providing full connectivity--perhaps to include 5G
connectivity, V2X, Wi-Fi or other near-field communications, and GPS or
its equivalent (for precision timing). The roadside infrastructure will
likely provide secure interconnection to the intersection traffic
signals (via a signal cabinet) and to a central traffic management
system for that jurisdiction (potentially through a wireless or fiber
optic link).
<bullet> Warning system. A VRU and vehicle warning system will
likely require audible alarms, visual alerts, and other more advanced
real-time alerts, such as haptic or projected images, for example. It
will require real-time interconnection with the intersection's traffic
signals, perhaps to adjust signal timing in real-time. The alerting
system will need to be capable of alerting VRUs who are visually or
hearing impaired, and offer ADA-compliant operation.
<bullet> Other intersection safety system considerations. A fully
automated system is desired that does not degrade the underlying
existing safety of an intersection, is upgradeable by virtue of a
modular hardware and software design, uses open architectures to the
fullest extent possible, including potentially open-source software,
utilizes industry-accepted software development practices and is
intrinsically cybersecure and maintains data privacy protections.
This RFI is intended to inform DOT on the status of automation
technologies and other complementary technologies that can be used to
improve or enhance the safety of pedestrians, bicyclists, and other
VRUs at or near roadway intersections. DOT seeks information on the
state of the art, and emerging trends in, perception, machine vision,
sensor fusion, real-time image and data analysis, path planning,
decision-making, connectivity, and warning systems that could be
implemented in real-time at intersections to improve pedestrian and
other VRU safety.
Specific Questions
Responses to this RFI are intended to inform DOT on the status of
technologies that can be used to improve or enhance the safety of
pedestrians, bicyclists, and other VRUs at or near roadway
intersections, including the status of the current technical
development or deployment of those technologies.
DOT is providing the following questions to prompt feedback and
comments. DOT encourages public comment on any or all of these
questions, and also 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 operators,
transportation-focused groups, organizations and associations, and the
public.
The questions to which DOT is interested in receiving responses
are:
(A) General Technical Considerations
1. What is the overall feasibility of developing an effective
intersection safety system for vulnerable road users (VRUs) based on
existing and emerging mobile (vehicle) automation technologies
(including other
[[Page 57022]]
complementary technologies) as described in this RFI?
2. What perception, machine vision, and sensor fusion technologies
(and other sensing modalities or combinations) are best suited to an
effective intersection safety and VRU and vehicle warning system?
3. What real-time image and data analysis techniques are best
suited to provide the required machine vision and perception for an
effective intersection safety system?
4. What techniques are most effective in providing real-time
vehicle and VRU path planning and prediction capabilities at fixed
roadway intersections?
5. What new and emerging technologies can enhance machine-based
decision making at intersections--including determining potential
vehicle-VRU conflicts, incidents, dilemma zones, and encroachment in
real-time?
6. What is the potential role of AI and/or ML in perception, image
analysis, data analysis and decision-making at intersections, both in
real-time and asynchronously? What is the potential for real-time
learning and group learning across a number of similarly-equipped
intersections?
7. How could such a system work effectively with all types of VRUs
(pedestrians, bicyclists, wheel-chair users, users of electric
scooters, etc.) and all types of vehicles (cars, trucks, vans, transit
buses, commercial vehicles, etc.)?
(B) System Installation and Deployment
1. How can the required installation, setup and calibration
requirements for a perception and decision-making based intersection
safety system be minimized?
2. What pedestrian and VRU alerting and warning methodologies and
systems would be most useful, including for example, visual (or
projected), audible, haptic, connected, other?
3. What vehicle driver alerting and warning systems would be most
useful, to alert drivers in real-time of impending conflicts at
intersections?
4. What potential modes of connectivity, such as V2X (V2N, V2P,
V2V, V2I . . . ), cellular or Wi-Fi, for connecting vehicles,
infrastructure, signals, and VRUs, would be most useful and effective
to assure the greatest degree of accessibility for all intersection
users?
5. What industry standards, best practices, processes, protocols,
and interoperability requirements and capabilities are needed or best
suited for the development of an effective intersection safety system?
6. How can interfaces with traffic signal controllers and traffic
management systems be best implemented? What data storage and curation
of the system performance history (on-board, at the edge or in the
cloud) are required?
7. How can issues related to reduced visibility (e.g., night-time,
low light, bad weather) be addressed and mitigated during both the
development and deployment of an effective intersection safety system?
8. Are there any existing research and development efforts,
deployments, or pilot demonstrations underway that aim to provide some
or all of the capabilities described in this RFI?
(C) Human Factors and Performance Measurement
1. What human behavioral considerations are most important in the
implementation of an intersection safety system to ensure maximum VRU
and driver compliance with the warnings and alerts provided?
2. What are the most relevant human factors, cognition and human-
machine interface (HMI) considerations for both VRUs and drivers to
ensure the maximum efficacy of an intersection safety system?
3. What metrics, key performance indicators, and measures of
success are important for determining the performance and efficacy of
an intersection safety system?
4. How would testing and validation of an intersection safety
system best be accomplished before full system deployment at active
intersections?
5. How can a testing and validation plan be devised that would
balance testing and development safety with the ultimate real-world
performance of an intersection safety system?
6. What performance data would be required to validate the testing
and efficacy of an intersection safety system, and how could that
performance data be generated?
7. What measurement and statistical approaches are applicable to
real-time decision-making at intersections? How can decision or warning
errors be minimized (e.g., through reducing false positives and/or
false negatives)?
(D) Development Costs and Time to Deployment
1. What is the potential schedule and cost to develop an effective
intersection safety system? What are the potential future hardware and
software ``stack'' costs for a system that can be deployed at the scale
of (for example) 100,000 commercial installations after 3-5 years of
development?
2. What equity considerations factor into the potential testing,
implementation, and deployment of an effective intersection safety
system?
3. What team composition of development, commercialization and
deployment partners would be required to achieve the successful
commercialization and deployment of such a system?
4. For what proportion of intersections (signalized and/or
unsignalized) would such a system be well-suited? What characteristics
or measures are important in determining whether a specific
intersection is well-suited for the implementation of an effective
intersection safety system? How could such a system be further
developed or adapted for use in rural areas?
5. What are the installation, calibration, training, maintenance,
and operating considerations for deployment of such a system across its
full life-cycle by a range of potential end-users, including State,
local, Tribal and territorial DOTs, cities and towns?
(E) Please Comment on Any Other Issues Relevant to the Development,
Commercialization, and Deployment of an Effective Intersection Safety
System
Confidential Business Information
Do not submit information whose disclosure 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 September 13, 2022.
Robert C. Hampshire,
Deputy Assistant Secretary for Research and Technology.
[FR Doc. 2022-20188 Filed 9-15-22; 8:45 am]
BILLING CODE 4910-9X-P
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