Agency Information Collection Activities; Approval of a New Information Collection Request: Safety Impacts of Human-Automated Driving System (ADS) Team Driving Applications Publication: Federal Register Agency: Federal Motor Carrier Safety Administration Byline: Thomas P. Keane Date: 8 March 2024 Subjects: American Government , Autonomous Vehicles, Safety

[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; 
brian.routhier@dot.gov.

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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