Agency Information Collection Activities; Approval of a New Information Collection Request: Safety Impacts of Human-Automated Driving System (ADS) Team Driving Applications
| Published date | 08 March 2024 |
| Record Number | 2024-04923 |
| Citation | 89 FR 16814 |
| Court | Federal Motor Carrier Safety Administration |
| Section | Notices |
Federal Register, Volume 89 Issue 47 (Friday, March 8, 2024)
[Federal Register Volume 89, Number 47 (Friday, March 8, 2024)]
[Notices]
[Pages 16814-16815]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2024-04923]
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DEPARTMENT OF TRANSPORTATION
Federal Motor Carrier Safety Administration
[Docket No. FMCSA-2023-0098]
Agency Information Collection Activities; Approval of a New
Information Collection Request: Safety Impacts of Human-Automated
Driving System (ADS) Team Driving Applications
AGENCY: Federal Motor Carrier Safety Administration (FMCSA), Department
of Transportation (DOT).
ACTION: Notice and request for comments.
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SUMMARY: In accordance with the Paperwork Reduction Act of 1995, FMCSA
announces its plan to submit the Information Collection Request (ICR)
described below to the Office of Management and Budget (OMB) for review
and approval. This notice invites comments on a proposed information
collection titled Safety Impacts of Human-Automated Driving System
(ADS) Team Driving Applications. It is a driving simulator study with a
series of questionnaires that will quantify the safety implications of
team driving applications between humans and ADS-equipped commercial
motor vehicles (CMVs). The study will assess the safety benefits and
disbenefits of human-ADS team driving applications and support the
analysis of potential requests for relief from FMCSA's hours of service
(HOS) regulations.
DATES: Comments on this notice must be received on or before April 8,
2024.
ADDRESSES: Written comments and recommendations for the proposed
information collection should be sent within 30 days of publication of
this notice to www.reginfo.gov/public/do/PRAMain. Find this information
collection by selecting ``Currently under 30-day Review--Open for
Public Comments'' or by using the search function.
FOR FURTHER INFORMATION CONTACT: Brian Routhier, Office of Research and
Registration, DOT, FMCSA, West Building 6th Floor, 1200 New Jersey
Avenue SE, Washington, DC 20590-0001; 202-366-1225;
[email protected].
SUPPLEMENTARY INFORMATION:
Title: Safety Impacts of Human-Automated Driving System (ADS) Team
Driving Applications.
OMB Control Number: 2126-00XX.
Type of Request: New ICR.
Respondents: Commercial motor vehicle drivers.
Estimated Number of Respondents: 80.
Estimated Time per Response: 17 hours.
Expiration Date: This is a new ICR.
Frequency of Response: One response.
Estimated Total Annual Burden: 508.5 hours.
Background
Over the past 15 years, ADS technology has advanced rapidly through
innovation. As more manufacturers and technology companies move toward
higher levels of automation (i.e., SAE International Level 4 (L4)), it
is not fully clear how human drivers will team with ADS-equipped
trucks. L4 ADS-equipped CMVs are capable of all functions and controls
necessary for driving without human monitoring in limited conditions,
and the human driver will not be asked to take over control of the
vehicle. L4 ADS will not operate outside of the conditions for which it
was designed. Currently, there are at least four use cases where a
human may team with an ADS-equipped CMV:
1. In-vehicle driver teams with an ADS CMV;
2. In-vehicle driver teams with a following ADS-equipped CMV;
3. In-vehicle driver teams with a remote assistant to monitor and
control an ADS CMV; and
4. Remote driver teaming with ADS CMV.
Each of the teaming use cases above offers different potential
human factors benefits and challenges. However, it is unclear how each
human-ADS teaming use case will affect safety, productivity, and
efficiency. Each teaming combination may positively or negatively
affect a driver's cognitive workload, level of fatigue, alertness, or
distraction compared to the case of a traditional driver in a truck
without ADS. For example, the in-vehicle drivers and remote assistants/
drivers in the above teaming use cases may experience varying workloads
and differences in the development of fatigue.
Previous research conducted by FMCSA found a paucity of extant
research related to ADS-equipped CMVs. To date, most commercial ADS on
U.S. roadways are in passenger vehicles, and ADS-equipped CMVs are only
recently being implemented in real-world operations. Therefore, FMCSA
needs more data on ADS-equipped CMVs to understand the human factors
surrounding team driving applications between humans and ADS-equipped
CMVs.
[[Page 16815]]
The purpose for obtaining data in this study is to quantify safety
implications of the four human-ADS teaming use cases described above.
Specifically, this project will provide data to assess the safety
benefits and disbenefits associated with human-ADS teaming scenarios:
(i) driver use, workload, fatigue, alertness, and distraction when
teaming with an ADS; (ii) remote assistant/driver use, workload,
fatigue, alertness, and distraction while actively monitoring and/or
controlling an ADS-equipped truck; (iii) driver re-engagement to the
driving task after taking over from ADS or remote driver control; and
(iv) fleet acceptance and future integration possibilities.
Additionally, data from this study will support the analysis of
potential requests for relief from FMCSA's HOS regulations under 49
U.S.C. 31315 and 49 CFR part 381. Answers to these research questions
will provide insight into the potential safety implications and human
factors associated with human-ADS team driving applications.
The study includes data collection from a series of questionnaires
and a driving-simulator focused experiment. The collected survey data
will support the simulator experiment data. The survey data will be
used in two ways: in the assessment of driving performance data as
covariates in the model (to control for certain demographic variables,
such as age, gender, and experience, and to control for previous
perceptions of safety technologies) and to answer research questions on
the human factors and the relationship the safety benefits of each of
the four human-ADS team driving applications. Data on workload,
fatigue, alertness, inattention, and performance will be collected from
the simulator experiment. Eligible drivers will hold a valid commercial
driver's license, currently drive a CMV, be 21 years of age or older,
and pass the motion sickness history screening questionnaire.
We anticipate 80 participants in total will complete the driving
simulator study. Data will be collected over one study session lasting
up to 17 hours. Questionnaire data will be collected prior to the
simulator study, during the simulator study, and after the simulator
study. All questionnaires will be preloaded in an app format for
drivers to complete on a tablet.
The analysis methodology uses a multifaceted approach to address
research questions on driver workload, fatigue, alertness, distraction,
and rate of safety-critical events. The principal statistical method
for analyzing the data will include mixed models to account for
multiple, correlated data points from a single participant. Eye-
tracking data will be used to assess driver workload, fatigue,
alertness, distraction, and reaction time. These data will be described
using summary statistics and advanced plotting techniques to visually
compare drivers and remote drivers during in-vehicle driving, vehicle
monitoring, and remote assistance/driving. A generalized linear mixed
model (GLMM) will be used to assess differences in average fatigue,
workload, alertness, distraction, and reaction times between in-vehicle
driving and remote driving operation types. In the transportation
safety field, GLMMs are often used to analyze driver behavior and
assess relationships between driving scenarios and behaviors. Finally,
rates of safety-critical events, including unintentional lane
deviations (which are surrogates for fatigue and alertness), will be
analyzed using a Poisson or negative binomial mixed-effect regression
model. Poisson or negative binomial regression models are standard
practice for the assessment of events over a unit of exposure in the
field of transportation safety.
FMCSA published the 60-day Federal Register notice on June 8, 2023,
and the comment period closed on August 7, 2023 (88 FR 37597). A total
of three comments were received from the public. The first comment was
submitted by the American Property Casualty Insurance Association
(APCIA). APCIA supported the study, indicating that the study will
provide important data on how human-ADS teaming may affect driver
workload, fatigue, and alertness. Additionally, APCIA's comment
discussed the challenges associated with developing insurance policies
for ADS-equipped CMVs, which will be dependent on access to information
to identify vehicles with ADS and their functions. FMCSA agrees that
results from this study will provide important data on how human-ADS
teaming applications affect drivers' workload and attention; however,
it is not within the scope of this study to examine how the public and
insurers can access information on a CMV's ADS and its functions.
The second comment was submitted by an individual. This comment
expressed concerns for the safety of ADS-equipped CMVs and how ADS-
equipped trucks will be compliant during a roadside inspection. FMCSA
is actively engaged in many research and administrative activities to
help improve the safety of CMV drivers and the general public,
including research on ADS-equipped CMVs. There are many research
questions that need to be answered before ADS-equipped CMVs are
deployed at scale. Some of these research questions are focused on the
ADS technology itself to ensure that the ADS technology functions as
intended and incorporates the appropriate redundant failsafe systems.
Other research questions focus on the human factors associated with how
drivers will interact and team with ADS and how law enforcement will
ensure the safe operation of ADS-equipped CMVs. Results from this
study, and other studies focused on ADS-equipped CMVs, will help to
ensure the safety of ADS and drivers on the road.
The final comment was submitted by the Autonomous Vehicle Industry
Association (AVIA). AVIA supported the study as a means to gather
additional information that could be used, in part, to inform decisions
in response to potential requests for relief from FMCSA's HOS under 49
U.S.C. 31315 and 49 CFR part 381. Additionally, AVIA requested that
FMCSA amend the language in the study to align with terminology used in
SAE J3016. Specifically, AVIA recommended replacing the term ``remote
monitor'' with ``remote assistant'' and ``remote operator'' with
``remote driver.'' FMCSA agrees that the use of consistent terminology
is important when describing ADSs. FMCSA has revised those phrases to
align with SAE J3016.
Public Comments Invited: You are asked to comment on any aspect of
this information collection, including: (1) whether the proposed
collection is necessary for the performance of FMCSA's functions; (2)
the accuracy of the estimated burden; (3) ways for FMCSA to enhance the
quality, usefulness, and clarity of the collected information; and (4)
ways that the burden could be minimized without reducing the quality of
the collected information.
Issued under the authority of 49 CFR 1.87.
Thomas P. Keane,
Associate Administrator, Office of Research and Registration.
[FR Doc. 2024-04923 Filed 3-7-24; 8:45 am]
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