Document ID: FMCSA-2023-0098-0001
Agency: fmcsa
Document Type: Notice
Title: Agency Information Collection Activities; Proposals, Submissions, and Approvals: Safety Impacts of Human-Automated Driving System Team Driving Applications
Posted Date: 2023-06-08T04:00Z

[Federal Register Volume 88, Number 110 (Thursday, June 8, 2023)]
[Notices]
[Pages 37597-37599]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-12254]

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DEPARTMENT OF TRANSPORTATION

Federal Motor Carrier Safety Administration

[Docket No. FMCSA-2023-0098]

Agency Information Collection Activities; New Information 
Collection: 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 its 
review and approval and invites public comment. 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). Specifically, 
this study will focus on team driving applications with an SAE Level 4 
(L4) CMV. In L4 automation, as specified by SAE (2021), 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. The L4 CMV will not 
operate outside of the conditions it was designed for without human 
control. Approximately 80 CMV drivers will participate in the study. 
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 August 7, 
2023.

ADDRESSES: You may submit comments identified by Federal Docket 
Management System (FDMS) Docket Number FMCSA-2023-0098 using any of the 
following methods:
     Federal eRulemaking Portal: https://www.regulations.gov. 
Follow the online instructions for submitting comments.
     Fax: 202-493-2251.
     Mail: Dockets Operations; U.S. Department of 
Transportation, 1200

[[Page 37598]]

New Jersey Avenue SE, West Building, Ground Floor, Room W12-140, 
Washington, DC 20590-0001.
     Hand Delivery or Courier: U.S. Department of 
Transportation, 1200 New Jersey Avenue SE, West Building, Ground Floor, 
Room W12-140, Washington, DC 20590-0001 between 9 a.m. and 5 p.m. ET, 
Monday through Friday, except Federal holidays.

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: 

Public Participation

    Instructions: All submissions must include the Agency name and 
docket number. For detailed instructions on submitting comments, see 
the Public Participation heading below. Note that all comments received 
will be posted without change to https://www.regulations.gov, including 
any personal information provided. Please see the Privacy Act heading 
below.
    Docket: For access to the docket to read background documents or 
comments received, go to https://www.regulations.gov, and follow the 
online instructions for accessing the docket, or go to the street 
address listed above.
    Privacy Act: In accordance with 5 U.S.C. 553(c), DOT solicits 
comments from the public to better inform its rulemaking process. DOT 
posts these comments, without edit, including any personal information 
the commenter provides, to www.regulations.gov, as described in the 
system of records notice (DOT/ALL-14 FDMS), which can be reviewed at 
www.dot.gov/privacy.
    Public Participation: The Federal eRulemaking Portal is available 
24 hours each day, 365 days each year. You can obtain electronic 
submission and retrieval help and guidelines under the ``FAQ'' section 
of the Federal eRulemaking Portal website. If you want us to notify you 
that we received your comments, please include a self-addressed, 
stamped envelope or postcard, or print the acknowledgement page that 
appears after submitting comments online. Comments received after the 
comment closing date will be included in the docket and will be 
considered to the extent practicable.

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 ``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 human to monitor and 
control an ADS CMV; and
    4. Remote monitor/operator 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 and 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 monitors/
operators 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 ADSs on 
U.S. roadways are in passenger vehicles, and CMV ADSs 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.
    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 on human-ADS teaming scenarios: (i) driver 
use, workload, fatigue, alertness, and distraction when teaming with an 
ADS; (ii) remote operator 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 
ADS or remote operator 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 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 for 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 operators during in-vehicle driving, in-
vehicle monitoring, and remote operation. 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 operator driving operation types. In the 
transportation safety field, GLMMs are

[[Page 37599]]

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.
    Title: Safety Impacts of Human-Automated Driving System (ADS) Team 
Driving Applications.
    OMB Control Number: 2126-00XX.
    Type of Request: New ICR.
    Respondents: CMV 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.
    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. The Agency will summarize or include your 
comments in the request for OMB's clearance of this ICR.

    Issued under the authority of 49 CFR 1.87.
Thomas P. Keane,
Associate Administrator, Office of Research and Registration.
[FR Doc. 2023-12254 Filed 6-7-23; 8:45 am]
BILLING CODE 4910-EX-P