{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T15:28:58Z","timestamp":1790782138190,"version":"4.1.0"},"reference-count":22,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,2,20]],"date-time":"2020-02-20T00:00:00Z","timestamp":1582156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In the development of highly automated driving systems (L3 and 4), much research has been done on the subject of driver takeover. Strong focus has been placed on the takeover quality. Previous research has shown that one of the main influencing factors is the complexity of a traffic situation that has not been sufficiently addressed so far, as different approaches towards complexity exist. This paper differentiates between the objective complexity and the subjectively perceived complexity. In addition, the familiarity with a takeover situation is examined. Gold et al. show that repetition of takeover scenarios strongly influences the take-over performance. Yet, both complexity and familiarity have not been considered at the same time. Therefore, the aim of the present study is to examine the impact of objective complexity and familiarity on the subjectively perceived complexity and the resulting takeover quality. In a driving simulator study, participants are requested to take over vehicle control in an uncritical situation. Familiarity and objective complexity are varied by the number of surrounding vehicles and scenario repetitions. Subjective complexity is measured using the NASA-TLX; the takeover quality is gathered using the take-over controllability rating (TOC-Rating). The statistical evaluation results show that the parameters significantly influence the takeover quality. This is an important finding for the design of cognitive assistance systems for future highly automated and intelligent vehicles.<\/jats:p>","DOI":"10.3390\/info11020115","type":"journal-article","created":{"date-parts":[[2020,2,21]],"date-time":"2020-02-21T08:59:47Z","timestamp":1582275587000},"page":"115","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["The Impact of Situational Complexity and Familiarity on Takeover Quality in Uncritical Highly Automated Driving Scenarios"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0414-6974","authenticated-orcid":false,"given":"Marlene Susanne Lisa","family":"Scharfe","sequence":"first","affiliation":[{"name":"Robert Bosch GmbH, 74232 Abstatt, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathrin","family":"Zeeb","sequence":"additional","affiliation":[{"name":"Robert Bosch GmbH, 74232 Abstatt, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nele","family":"Russwinkel","sequence":"additional","affiliation":[{"name":"Department of Psychology and Ergonomics, Technical University Berlin, 10587 Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.aap.2017.11.009","article-title":"Modeling take-over performance in level 3 conditionally automated vehicles","volume":"116","author":"Gold","year":"2018","journal-title":"Accid. 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