{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T19:04:54Z","timestamp":1772219094967,"version":"3.50.1"},"reference-count":47,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T00:00:00Z","timestamp":1704412800000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.sagepub.com\/licence-information-for-chorus"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1739869"],"award-info":[{"award-number":["1739869"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019690","name":"Toyota Collaborative Safety Research Center","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100019690","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Hum Factors"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p> This study explores subjective and objective driving style similarity to identify how similarity can be used to develop driver-compatible vehicle automation. <\/jats:p><\/jats:sec><jats:sec><jats:title>Background<\/jats:title><jats:p> Similarity in the ways that interaction partners perform tasks can be measured subjectively, through questionnaires, or objectively by characterizing each agent\u2019s actions. Although subjective measures have advantages in prediction, objective measures are more useful when operationalizing interventions based on these measures. Showing how objective and subjective similarity are related is therefore prudent for aligning future machine performance with human preferences. <\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p> A driving simulator study was conducted with stop-and-go scenarios. Participants experienced conservative, moderate, and aggressive automated driving styles and rated the similarity between their own driving style and that of the automation. Objective similarity between the manual and automated driving speed profiles was calculated using three distance measures: dynamic time warping, Euclidean distance, and time alignment measure. Linear mixed effects models were used to examine how different components of the stopping profile and the three objective similarity measures predicted subjective similarity. <\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p> Objective similarity using Euclidean distance best predicted subjective similarity. However, this was only observed for participants\u2019 approach to the intersection and not their departure. <\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p> Developing driving styles that drivers perceive to be similar to their own is an important step toward driver-compatible automation. In determining what constitutes similarity, it is important to (a) use measures that reflect the driver\u2019s perception of similarity, and (b) understand what elements of the driving style govern subjective similarity. <\/jats:p><\/jats:sec>","DOI":"10.1177\/00187208221142126","type":"journal-article","created":{"date-parts":[[2023,1,5]],"date-time":"2023-01-05T15:28:06Z","timestamp":1672932486000},"page":"1545-1563","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Comparing Subjective Similarity of Automated Driving Styles to Objective Distance-Based Similarity"],"prefix":"10.1177","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8602-1448","authenticated-orcid":false,"given":"Amudha V.","family":"Kamaraj","sequence":"first","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4790-0108","authenticated-orcid":false,"given":"Joonbum","family":"Lee","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0857-0767","authenticated-orcid":false,"given":"Joshua E.","family":"Domeyer","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA and Toyota Collaborative Safety Research Center, Ann Arbor, Michigan, USA"}]},{"given":"Shu-Yuan","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9808-2160","authenticated-orcid":false,"given":"John D.","family":"Lee","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]}],"member":"179","published-online":{"date-parts":[[2023,1,5]]},"reference":[{"key":"bibr1-00187208221142126","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9280.2005.01619.x"},{"key":"bibr2-00187208221142126","doi-asserted-by":"publisher","DOI":"10.1145\/2909824.3020250"},{"key":"bibr3-00187208221142126","doi-asserted-by":"crossref","unstructured":"Bates D., M\u00e4chler M., Bolker B., Walker S. 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