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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations
| REPORT |
| This report is an archived publication and may contain dated technical, contact, and link information |
 |
| Publication Number: FHWA-HRT-16-056 Date: December 2016 |
Publication Number: FHWA-HRT-16-056 Date: December 2016 |
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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 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 the vehicle operator’s alertness and attention.
The CACC system was effective in helping drivers avoid collisions when the vehicle at the head of the platoon decelerated with maximum force. No differences in driver alertness or arousal levels were found when comparing CACC with manual gap control. Drivers reported significantly less workload with CACC.
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.
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Technical Report Documentation Page
| 1. Report No. FHWA-HRT-16-056 |
2. Government Accession No. | 3. Recipient’s Catalog No. | ||||
| 4. Title and Subtitle Cooperative Adaptive Cruise Control Human Factors Study: Experiment 1—Workload, Distraction, Arousal, and Trust |
5. Report Date December 2016 |
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| 6. Performing Organization Code: | ||||||
| 7. Author(s) Vaughan W. Inman, Steven Jackson, and Brian H. Philips |
8. Performing Organization Report No. |
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| 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 |
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| 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 |
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| 14. Sponsoring Agency Code HRTM-30 |
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| 15. Supplementary Notes The Contraction Officer’s Representative was David Yang, and the Government’s Task Manager was Brian Philips. |
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16. Abstract
These questions were addressed in an experiment conducted in the Federal Highway Administration Highway Driving Simulator. A total of 49 licensed drivers were tested, with 12 or 13 participants in each of 4 groups. All of the groups drove in the third position in a five-vehicle platoon in which all of the other vehicles were equipped with simulated CACC. The groups differed as to whether the participant vehicle was equipped with CACC and the type of event at the end of the drive that disturbed the longitudinal spacing of the platoon. As assessed by the National Aeronautics and Space Administration Task Load Index, the CACC system did reduce perceived driver workload relative to driving without cruise control. CACC users appeared slightly more likely to engage in diversionary activities (e.g., listening to the car radio) than control group drivers. CACC yielded a substantial and statistically reliable reduction in the probability of a crash. No evidence was obtained to suggest that use of CACC leads to lower levels of driver arousal than manual gap control. Participants showed a great deal of trust in the CACC system. In a situation where all of the control participants used the brake to maintain a comfortable gap, only 2 of 36 CACC users overrode the system with the brake or accelerator. |
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| 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 |
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| 19. Security Classif. (of this report) Unclassified |
20. Security Classif. (of this page) Unclassified |
21. No. of Pages 42 |
22. Price N/A |
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| Form DOT F 1700.7 (8-72) | Reproduction of completed page authorized |
SI* (Modern Metric) Conversion Factors
Figure 1. Screen capture. Appearance of control group multifunction display
Figure 2. Screen capture. Typical section of the simulated roadway
Figure 3. Screen capture. Entrance ramp meter
Figure 4. Graph. Results of field and simulator gap maintenance testing
Figure 5. Screen capture. Reduced-size (75 percent) lead vehicle depicted with 1.1-s gap
Figure 6. Screen capture. The Ponzo illusion. (The vehicles in the picture are all the same size.)
Figure 7. Graph. NASA-TLX scores as a function of treatment group and location in the scenario
Figure 8. Graph. Standardized pupil diameter as a function of condition and period
Figure 9. Graph. Estimated mean proportion of drivers engaged in non-driving-related diversions increased with time into drive
Figure 10. Graph. GEE estimated mean percent of time gazing at the multifunction display as a function of condition and period
Figure 11. Equation. Adjusted minimum TTC
Figure 12. Graph. Estimated adjusted mean TTC
Figure 13. Graph. Estimated mean brake onset reaction times for the two groups that had the crash avoidance final event
Figure 14. Graph. Estimated mean time to from beginning of brake pedal depression to full braking
Table 1. Demographic breakdown of participants by treatment group
Table 2. Number of participants engaging in observable non-driving-related activities as the experiment progressed
Table 3. Percent of gaze time to defined objects as a function of condition and period
Table 4. Crash counts for the two groups that were exposed to the crash avoidance event
| ACC | adaptive cruise control | |
| CACC | cooperative adaptive cruise control | |
| DSRC | dedicated short-range communications | |
| FHWA | Federal Highway Administration | |
| GEE | generalized estimating equation | |
| GLM | generalized linear model | |
| GSR | galvanic skin response | |
| NASA-TLX | National Aeronautics and Space Administration Task Load Index | |
| SSQ | simulator sickness questionnaire | |
| TTC | time-to-collision |
