Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles
Increasingly vehicle automation may convey greater capability than it actually possesses. The emergence of highly capable vehicle automation (e.g., SAE Level 4) and the promise of driverless vehicles in the near future can lead drivers to inappropriately cede responsibility for driving to the vehicl...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Society of Automotive Engineers of Japan, Inc.
2019-01-01
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| Series: | International Journal of Automotive Engineering |
| Online Access: | https://www.jstage.jst.go.jp/article/jsaeijae/10/1/10_20194085/_article/-char/ja |
| _version_ | 1797356812656181248 |
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| author | Morgan Price John Lee Azadeh Dinparastdjadid Heishiro Toyoda Joshua Domeyer |
| author_facet | Morgan Price John Lee Azadeh Dinparastdjadid Heishiro Toyoda Joshua Domeyer |
| author_sort | Morgan Price |
| collection | DOAJ |
| description | Increasingly vehicle automation may convey greater capability than it actually possesses. The emergence of highly capable vehicle automation (e.g., SAE Level 4) and the promise of driverless vehicles in the near future can lead drivers to inappropriately cede responsibility for driving to the vehicle with less capable automation (e.g., SAE Level 2). This inappropriate reliance on automation can compromise safety, and so we investigated how algorithms and instructions might mitigate overreliance. Seventy-two drivers, balanced by gender, between the ages of 25 and 55, participated in this study using a fixed-base driving simulator. Drivers were exposed to one of three vehicle steering algorithms: lane centering, lane keeping, or an adaptive combination. A gaze tracker was used to track eye glance behavior. While automation was engaged, participants were told they could interact with an email sorting task on a tablet positioned near the center stack. Changes in roadway demand—traffic approaching in the adjacent lane—varied across the drive. Instructions indicating the driver was responsible, in combination with the adaptive algorithm, led drivers to be particularly attentive to the road as the traffic approached them. These results also have implications for evaluating more capable automation (SAE Levels 4 and 5), where drivers need not attend to the road: unnecessary attention to roadway demands might indicate lack of trust and acceptance of control algorithms that guide driverless vehicles. |
| first_indexed | 2024-03-08T14:33:02Z |
| format | Article |
| id | doaj.art-74e378aafc0d48288eb69899f9fda52b |
| institution | Directory Open Access Journal |
| issn | 2185-0992 |
| language | English |
| last_indexed | 2024-03-08T14:33:02Z |
| publishDate | 2019-01-01 |
| publisher | Society of Automotive Engineers of Japan, Inc. |
| record_format | Article |
| series | International Journal of Automotive Engineering |
| spelling | doaj.art-74e378aafc0d48288eb69899f9fda52b2024-01-12T06:38:12ZengSociety of Automotive Engineers of Japan, Inc.International Journal of Automotive Engineering2185-09922019-01-01101737910.20485/jsaeijae.10.1_73Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated VehiclesMorgan Price0John Lee1Azadeh Dinparastdjadid2Heishiro Toyoda3Joshua Domeyer4University of Wisconsin-MadisonUniversity of Wisconsin-MadisonUniversity of Wisconsin-MadisonToyota Collaborative Safety Research CenterToyota Collaborative Safety Research CenterIncreasingly vehicle automation may convey greater capability than it actually possesses. The emergence of highly capable vehicle automation (e.g., SAE Level 4) and the promise of driverless vehicles in the near future can lead drivers to inappropriately cede responsibility for driving to the vehicle with less capable automation (e.g., SAE Level 2). This inappropriate reliance on automation can compromise safety, and so we investigated how algorithms and instructions might mitigate overreliance. Seventy-two drivers, balanced by gender, between the ages of 25 and 55, participated in this study using a fixed-base driving simulator. Drivers were exposed to one of three vehicle steering algorithms: lane centering, lane keeping, or an adaptive combination. A gaze tracker was used to track eye glance behavior. While automation was engaged, participants were told they could interact with an email sorting task on a tablet positioned near the center stack. Changes in roadway demand—traffic approaching in the adjacent lane—varied across the drive. Instructions indicating the driver was responsible, in combination with the adaptive algorithm, led drivers to be particularly attentive to the road as the traffic approached them. These results also have implications for evaluating more capable automation (SAE Levels 4 and 5), where drivers need not attend to the road: unnecessary attention to roadway demands might indicate lack of trust and acceptance of control algorithms that guide driverless vehicles.https://www.jstage.jst.go.jp/article/jsaeijae/10/1/10_20194085/_article/-char/ja |
| spellingShingle | Morgan Price John Lee Azadeh Dinparastdjadid Heishiro Toyoda Joshua Domeyer Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles International Journal of Automotive Engineering |
| title | Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles |
| title_full | Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles |
| title_fullStr | Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles |
| title_full_unstemmed | Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles |
| title_short | Effect of Automation Instructions and Vehicle Control Algorithms on Eye Behavior in Highly Automated Vehicles |
| title_sort | effect of automation instructions and vehicle control algorithms on eye behavior in highly automated vehicles |
| url | https://www.jstage.jst.go.jp/article/jsaeijae/10/1/10_20194085/_article/-char/ja |
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