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REPORT
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Publication Number:  FHWA-HRT-16-058    Date:  December 2016
Publication Number: FHWA-HRT-16-058
Date: December 2016

 

Cooperative Adaptive Cruise Control Human Factors Study: Experiment 3—The Role of Automated Braking and Auditory Alert in Collision Avoidance Response

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FOREWORD

This final report presents human factors experimental results that examine the effects of cooperative adaptive cruise control (CACC) on driver performance in a variety of situations. The experiment was conducted in a driving simulator scenario in which the subject driver was embedded in a platoon of CACC-equipped vehicles. CACC is envisioned as an automated vehicle application that complements the capabilities of the vehicle operator without degrading his or her alertness and attention.

The experiment explored the interaction effect of the presence or absence of an auditory warning with the presence or absence of automated braking on drivers’ responses to a maximum deceleration crash avoidance event. The CACC system was effective in assisting drivers in avoiding collisions when both automated braking and an auditory warning were present. Braking or auditory warning alone were not effective in reducing the probability of a collision.

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-16-058
2. Government Accession No. 3. Recipient’s Catalog No.
4. Title and Subtitle
Cooperative Adaptive Cruise Control Human Factors Study: Experiment 3—The Role of Automated Braking and Auditory Alert in Collision Avoidance Response
5. Report Date
December 2016
6. Performing Organization Code:
7. Author(s)
Vaughan W. Inman, 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: 10/1/2013–12/1/2015
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 report is the third in a series of four human factors experiments to examine the effects of cooperative adaptive cruise control (CACC) on driver performance in a variety of situations. The experiment reported here was conducted in a driving simulator scenario in which the subject driver was embedded in a platoon of CACC-equipped vehicles. The experiment explored the interaction effect of the presence or absence of an auditory warning with the presence or absence of automated braking on drivers’ responses to a maximum deceleration crash avoidance event. The subject was in the fourth position in a five-car platoon. Dependent measures were crash avoidance (yes/no), manual brake reaction time (seconds), and adjusted time to collision (seconds). The results indicated that a crash avoidance safety benefit was achieved with full CACC (warning and automated braking) but not otherwise. Brake reaction times were longer when automated braking was present, but without the auditory alarm, about half the drivers took too long to react.

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
24
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. METHODS

CHAPTER 3. RESULTS

CHAPTER 4. DISCUSSION

ACKNOWLEDGEMENTS

REFERENCES

LIST OF FIGURES

Figure 1. Screenshot. A typical section of the simulated roadway
Figure 2. Graph. Reaction time from onset of braking by platoon-lead vehicle
Figure 3. Graph. TTC results

LIST OF TABLES

Table 1. Factorial design of experiment 3
Table 2. Age distribution within the experimental groups
Table 3. Crash results by experimental group
Table 4. Frequency of drivers for whom precise values of adjusted TTC could not be calculated

LIST OF ABBREVIATIONS

ACC adaptive cruise control  
CACC cooperative adaptive cruise control  
CACC-A cooperative adaptive cruise control with alarm when engine braking authority is exceeded  
CACC-AB cooperative adaptive cruise control with automated braking and alarm when automated braking authority is exceeded  
CACC-B cooperative adaptive cruise control with automated braking but no auditory alarm  
CL confidence limit  
FHWA Federal Highway Administration  
GLM generalized linear model  
TTC time to collision  

 

 

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