{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T13:35:55Z","timestamp":1793453755729,"version":"4.5.0"},"reference-count":29,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2016,3,16]],"date-time":"2016-03-16T00:00:00Z","timestamp":1458086400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Hum Factors"],"published-print":{"date-parts":[[2016,6]]},"abstract":"<jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>The aim of this study was to quantify the impact of traffic density and verbal tasks on takeover performance in highly automated driving.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>In highly automated vehicles, the driver has to occasionally take over vehicle control when approaching system limits. To ensure safety, the ability of the driver to regain control of the driving task under various driving situations and different driver states needs to be quantified.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Seventy-two participants experienced takeover situations requiring an evasive maneuver on a three-lane highway with varying traffic density (zero, 10, and 20 vehicles per kilometer). In a between-subjects design, half of the participants were engaged in a verbal 20-Questions Task, representing speaking on the phone while driving in a highly automated vehicle.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>The presence of traffic in takeover situations led to longer takeover times and worse takeover quality in the form of shorter time to collision and more collisions. The 20-Questions Task did not influence takeover time but seemed to have minor effects on the takeover quality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>For the design and evaluation of human\u2013machine interaction in takeover situations of highly automated vehicles, the traffic state seems to play a major role, compared to the driver state, manipulated by the 20-Questions Task.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Application:<\/jats:title>\n                    <jats:p>The present results can be used by developers of highly automated systems to appropriately design human\u2013machine interfaces and to assess the driver\u2019s time budget for regaining control.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/0018720816634226","type":"journal-article","created":{"date-parts":[[2016,3,17]],"date-time":"2016-03-17T00:04:39Z","timestamp":1458173079000},"page":"642-652","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":424,"title":["Taking Over Control From Highly Automated Vehicles in Complex Traffic Situations"],"prefix":"10.1177","volume":"58","author":[{"given":"Christian","family":"Gold","sequence":"first","affiliation":[{"name":"Institute of Ergonomics, Technical University of Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moritz","family":"K\u00f6rber","sequence":"additional","affiliation":[{"name":"Institute of Ergonomics, Technical University of Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Lechner","sequence":"additional","affiliation":[{"name":"Institute of Ergonomics, Technical University of Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Klaus","family":"Bengler","sequence":"additional","affiliation":[{"name":"Institute of Ergonomics, Technical University of Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2016,3,16]]},"reference":[{"key":"bibr1-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1177\/0018720813482327"},{"key":"bibr2-0018720816634226","volume-title":"Crash warning system interfaces: Human factors insights and lessons learned","author":"Campbell J. 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Intelligent transport systems\u2014Forward vehicle collision warning systems\u2014Performance requirements and test procedures","author":"International Organization for Standardization","year":"2013"},{"key":"bibr11-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2013.02.008"},{"key":"bibr12-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1016\/S1364-6613(02)00011-6"},{"key":"bibr13-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1177\/1541931214581352"},{"key":"bibr14-0018720816634226","author":"K\u00f6rber M.","journal-title":"The influence of age on the re-gain of vehicle control in highly automated driving"},{"key":"bibr15-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1177\/1541931214581351"},{"key":"bibr16-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1177\/0018720812442087"},{"key":"bibr17-0018720816634226","unstructured":"National Highway Traffic Safety Administration. (2013). Preliminary statement of policy concerning automated vehicles. Retrieved from http:\/\/www.nhtsa.gov\/staticfiles\/rulemaking\/pdf\/Automated_Vehicles_Policy.pdf"},{"key":"bibr18-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1177\/1071181312561415"},{"key":"bibr19-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1177\/1541931214581434"},{"key":"bibr20-0018720816634226","volume-title":"Cognitive systems engineering","author":"Rasmussen J.","year":"1994"},{"key":"bibr21-0018720816634226","doi-asserted-by":"publisher","DOI":"10.1145\/1734454.1734549"},{"key":"bibr22-0018720816634226","volume-title":"SAE surface vehicle information report: Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems","author":"SAE International","year":"2014"},{"key":"bibr23-0018720816634226","volume-title":"Integration fahrstreifenbezogener Kenngr\u00f6\u00dfen und seitlicher Detektionsdaten in ein makroskopisches Verkehrsflussmodell f\u00fcr dreistreifige Richtungsfahrbahnen","author":"Sch\u00f6pplein S. 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