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SUMMARY REPORT
This summary report is an archived publication and may contain dated technical, contact, and link information
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Publication Number:  FHWA-HRT-17-025    Date:  December 2017
Publication Number: FHWA-HRT-17-025
Date: December 2017

 

Cooperative Adaptive Cruise Control Human Factors Study

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FOREWORD

This report presents results of human factors research to examine the effects of cooperative adaptive cruise control (CACC) on driver performance in a variety of situations. CACC has been envisioned as an automated vehicle application that complements the capabilities of the vehicle operator without degrading the vehicle operator’s alertness and attention.

Four experiments are summarized that were conducted in a driving simulator. Three of these experiments focused on the effects of CACC when drivers in a string of CACC-equipped vehicles had to respond to other drivers merging into the string or to rapid deceleration of the lead vehicle in the string. The remaining experiment focused on the human factors issues that arose when a driver merged into an existing string of CACC vehicles.

This report informs the discussion of how automated vehicle applications will be embraced by everyday drivers and affect their behavior. It should be useful to engineers, researchers, and transportation professionals who are evaluating and implementing connected vehicle technologies that include longitudinal vehicle control.

Jonathan Porter, Ph.D.
Acting Director, Office of Safety
Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation (USDOT) 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-17-025

2. Government Accession No. 3 Recipient's Catalog No.
4. Title and Subtitle

Summary Report: Cooperative Adaptive Cruise Control Human Factors Study

5. Report Date

December 2017

6. Performing Organization Code
7. Author(s)

Vaughan W. Inman, 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. (TRAIS)

11. Contract or Grant No.

DTFH61-13-D-00024

12. Sponsoring Agency Name and Address

Office of Safety
Federal Highway Administration
6300 Georgetown Pike
McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report; 10/1/2013–06/30/2016

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 summary report provides a high-level overview of four experiments that investigated human factors issues surrounding cooperative adaptive cruise control (CACC). CACC combines three driver assist systems: (1) conventional cruise control, which automatically maintains the speed a driver has set, (2) adaptive cruise control, which uses radar or light detection and ranging sensors to automatically maintain a gap the driver has selected between the driver’s vehicle and a slower-moving vehicle ahead, and (3) dedicated short-range communications to transmit and receive data with surrounding vehicles so that the cruise control system can more quickly respond to changes in speed and location of other CACC vehicles, even vehicles that the driver cannot see.

 

This report describes a series of experiments that examined how use of a CACC affected drivers’ workload, propensity to distraction, level of physiological arousal, ability to avoid a crash, merging abilities, and trust in the system.

 

The first experiment compared driving with CACC in a string of four or five vehicles with manual control of the following distance in the same strings. The second experiment explored driver performance when merging into a string of CACC vehicles. The third experiment took a closer look at the source of a substantial crash reduction benefit obtained with CACC in the first experiment. The fourth experiment examined the effect of a driver’s preferred following distance on performance and workload when using short and long CACC gap settings.

17. Key Words

Cooperative adaptive cruise control, CACC, human factors, driving simulation, attention, distraction, merging, emergency response, alarms.

18. Distribution Statement

No restrictions. This document is available through the National Technical Information Service, Springfield, VA 22161.
http://www.ntis.gov

19. Security Classification
(of this report)

Unclassified

20. Security Classification
(of this page)

Unclassified

21. No. of Pages

61

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

SI* (Modern Metric) Conversion Factors

Table of Contents

Chapter 1. Introduction

Chapter 2. Workload, Distraction, Arousal, Trust, and Crash Avoidance

Chapter 3. Merging Behavior

Chapter 4. The Role of Automated Braking and Auditory Alert in Collision Avoidance Response

Chapter 5. Preferred Following Distance and Performance in an Emergency Event

Chapter 6. Conclusions

Acknowledgments

References

List of Figures

List of Tables

List of Acronyms and Abbreviations

ACC

adaptive cruise control

CACC

cooperative adaptive cruise control

DSRC

dedicated short-range communications

FHWA

Federal Highway Administration

GEE

generalized estimating equation

GSR

galvanic skin response

NASA-TLX

National Aeronautics and Space Administration Task Load Index

TTC

time to collision

 

 

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