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REPORT
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Publication Number:  FHWA-HRT-16-057    Date:  December 2016
Publication Number: FHWA-HRT-16-057
Date: December 2016

 

Cooperative Adaptive Cruise Control Human Factors Study: Experiment 2—Merging Behavior

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FOREWORD

This report presents human factors experimental results from an examination of the effects of cooperative adaptive cruise control (CACC) on driver performance in a variety of situations. The experiment was conducted in a driving simulator using a scenario in which the driver was required to enter into a stream of vehicles. CACC is envisioned as an automated vehicle application that complements the capabilities of the vehicle operator without degrading the vehicle operator’s alertness and attention.

This task was completed with and without speed assistance during the merge. Merging maneuvers with the CACC system successfully reduced workload and eliminated collisions during merges. Drivers who were required to manually control speed and enter a continuous flow of traffic experienced a significant number of crashes, which indicated that drivers’ merging maneuvers are highly sensitive to the behavior of other drivers and to merging distances.

This report informs the discussion among transportation professionals about how automated vehicle applications will be embraced by everyday drivers. The experiment results should be useful to researchers and transportation professionals interested in the effects of automation on driver behavior.

Monique R. Evans, P.E.
Director, Office of Safety
Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers’ names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

 

Technical Report Documentation Page

1. Report No.
FHWA-HRT-16-057
2. Government Accession No. 3. Recipient’s Catalog No.
4. Title and Subtitle
Cooperative Adaptive Cruise Control Human Factors Study: Experiment 2—Merging Behavior
5. Report Date
December 2016
6. Performing Organization Code:
7. Author(s)
Stacy A. Balk, Steven Jackson, and Brian H. Philips
8. Performing Organization Report No.
9. Performing Organization Name and Address
Leidos, Inc.
6300 Georgetown Pike
McLean, VA 22101-2296
10. Work Unit No.
11. Contract or Grant No.
DTFH61-13-D-00024
12. Sponsoring Agency Name and Address
Office of Safety Research and Development
Federal Highway Administration
6300 Georgetown Pike
McLean, VA 22101-2296
13. Type of Report and Period Covered
Final Report: February 2014–June 2015
14. Sponsoring Agency Code
HRTM-30
15. Supplementary Notes
The Contraction Officer’s Representative was David Yang, and the Government’s Task Manager was Brian Philips.
16. Abstract

This study is the second in a series of four experiments exploring human factors issues associated with the introduction of cooperative adaptive cruise control (CACC). Specifically, this study explored drivers’ abilities to merge into a stream of continuously moving vehicles in a dedicated lane. Participants were asked to complete one of three different types of merges in the Federal Highway Administration Highway Driving Simulator:

  • Merge with non-CACC vehicle into a left dedicated lane without CACC platooning and varying vehicle gaps.
  • Merge with CACC vehicle into the middle of a CACC platoon or continuous stream of vehicles without speed assistance.
  • Merge with CACC vehicle into a CACC platoon with longitudinal speed assistance.

As measured by the National Aeronautics and Space Administration Task Load Index, drivers’ perceived workload was significantly less for both groups that drove with the CACC system engaged than for the group that was required to manually maintain speed the entire drive. Perhaps surprisingly, participant condition did not significantly affect physiological arousal as assessed by galvanic skin response (GSR). However, across all groups, GSR was significantly greater during the merges than during cruising/straight highway driving time periods.

The participants who drove with the CACC system during the merges (as defined by the operation of the system) did not experience any collisions. Both groups that were required to manually adjust speed to merge into the platoon of vehicles experienced collisions in 24 (18 percent) of the merges, suggesting that some gaps may be too small for drivers to merge into at high speeds. An alternative explanation, supported by participant feedback, is that drivers expect others to act in a courteous manner and to create larger gaps for entrance onto a freeway—something that may not be possible in real-world CACC deployment.

17. Key Words
Cooperative adaptive cruise control, CACC, human factors, driving simulation, attention, distraction
18. Distribution Statement
No restrictions. This document is available through the National Technical Information Service, Springfield, VA 22161.
http://www.ntis.gov
19. Security Classif. (of this report)
Unclassified
20. Security Classif. (of this page)
Unclassified
21. No. of Pages
36
22. Price
N/A
Form DOT F 1700.7 Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

TABLE OF CONTENTS

CHAPTER 1. INTRODUCTION

CHAPTER 2. METHOD

CHAPTER 3. RESULTS

CHAPTER 4. DISCUSSION

ACKNOWLEDGEMENTS

REFERENCES

 

LIST OF FIGURES

Figure 1. Graph. Estimated mean workload (NASA-TLX) by treatment group and location
Figure 2. Graph. Estimated mean GSR (z-score, conductance) by period
Figure 3. Graph. Estimated mean pupil diameter (z-score, conductance) by period
Figure 4. Graph. Estimated mean merge position by treatment group
Figure 5. Graph. Estimated mean distance used to merge by merge number and experimental condition
Figure 6. Screenshots. Illustrated dynamic merge area ROI

 

LIST OF TABLES

Table 1. Driving period descriptions
Table 2. Demographic breakdown of participants in experiment 2 by treatment group
Table 3. The number of participants engaging in observable non-driving related activities by experimental condition group, combined across both observation periods
Table 4. Frequency of collisions by treatment group and merge number
Table 5. Gaps presented to the control group and corresponding number of times selected

 

LIST OF ABBREVIATIONS

ACC adaptive cruise control  
CACC cooperative adaptive cruise control  
FHWA Federal Highway Administration  
GEE generalized estimating equation  
GSR galvanic skin response  
HOV high-occupancy vehicle  
NASA-TLX National Aeronautics and Space Administration Task Load Index  
ROI region of interest  
SSQ simulator sickness questionnaire  
V2I vehicle-to-infrastructure  
V2V vehicle-to-vehicle  

 

 

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