Sol Hee Yoon

890 total citations
28 papers, 578 citations indexed

About

Sol Hee Yoon is a scholar working on Social Psychology, Safety, Risk, Reliability and Quality and Automotive Engineering. According to data from OpenAlex, Sol Hee Yoon has authored 28 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Social Psychology, 9 papers in Safety, Risk, Reliability and Quality and 7 papers in Automotive Engineering. Recurrent topics in Sol Hee Yoon's work include Human-Automation Interaction and Safety (17 papers), Traffic and Road Safety (9 papers) and Autonomous Vehicle Technology and Safety (5 papers). Sol Hee Yoon is often cited by papers focused on Human-Automation Interaction and Safety (17 papers), Traffic and Road Safety (9 papers) and Autonomous Vehicle Technology and Safety (5 papers). Sol Hee Yoon collaborates with scholars based in South Korea, United States and Germany. Sol Hee Yoon's co-authors include Yong Gu Ji, Seul Chan Lee, Young‐Woo Kim, Hwan Hwangbo, Daeyoung Roh, Chan‐Hyung Kim, Hyang Sook Kim, Yiqi Zhang, Philipp Wintersberger and Jeh-Kwang Ryu and has published in prestigious journals such as Accident Analysis & Prevention, The Journal of Nervous and Mental Disease and Ergonomics.

In The Last Decade

Sol Hee Yoon

25 papers receiving 568 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sol Hee Yoon South Korea	13	387	204	136	89	59	28	578
Ioannis Politis United Kingdom	12	525 1.4×	270 1.3×	193 1.4×	85 1.0×	48 0.8×	25	655
Tuomo Kujala Finland	15	386 1.0×	163 0.8×	100 0.7×	132 1.5×	37 0.6×	58	548
Johannes Kraus Germany	20	800 2.1×	270 1.3×	199 1.5×	80 0.9×	27 0.5×	48	1.1k
Susanne Stadler Austria	8	393 1.0×	60 0.3×	125 0.9×	76 0.9×	27 0.5×	17	590
Jonathan Dobres United States	14	361 0.9×	156 0.8×	54 0.4×	106 1.2×	46 0.8×	45	615
David R. Large United Kingdom	19	628 1.6×	226 1.1×	196 1.4×	222 2.5×	74 1.3×	62	846
Lucinda A. Simmons United States	11	458 1.2×	317 1.6×	92 0.7×	40 0.4×	101 1.7×	18	714
David Miller United States	13	474 1.2×	235 1.2×	169 1.2×	73 0.8×	62 1.1×	32	620
Shannon C. Roberts United States	11	254 0.7×	180 0.9×	93 0.7×	28 0.3×	35 0.6×	51	411
Ericka Rovira United States	12	435 1.1×	50 0.2×	92 0.7×	22 0.2×	27 0.5×	38	631

Countries citing papers authored by Sol Hee Yoon

Since Specialization

Citations

This map shows the geographic impact of Sol Hee Yoon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sol Hee Yoon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sol Hee Yoon more than expected).

Fields of papers citing papers by Sol Hee Yoon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sol Hee Yoon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sol Hee Yoon. The network helps show where Sol Hee Yoon may publish in the future.

Co-authorship network of co-authors of Sol Hee Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Sol Hee Yoon. A scholar is included among the top collaborators of Sol Hee Yoon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sol Hee Yoon. Sol Hee Yoon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lee, Seul Chan, et al.. (2025). Development and validation of Generative AI Competence Scale (GenAIComp) among university students. Technology in Society. 84. 103059–103059.

Kim, Young‐Woo & Sol Hee Yoon. (2025). Understanding drivers’ situation awareness in highly automated driving using SAGAT, SART, and eye-tracking data. Transportation Research Part F Traffic Psychology and Behaviour. 109. 1437–1450. 3 indexed citations

Yoon, Sol Hee, et al.. (2024). Development and validation of automated driving behavior questionnaire (ADBQ). Transportation Research Part F Traffic Psychology and Behaviour. 103. 608–622. 2 indexed citations

Wintersberger, Philipp, et al.. (2024). Development and classification of autonomous vehicle’s ambiguous driving scenario. Accident Analysis & Prevention. 200. 107501–107501. 8 indexed citations

Kim, Young Woo, Seul Chan Lee, & Sol Hee Yoon. (2024). Exploring e-scooter riders’ risky behaviour: survey, observation, and interview study. Ergonomics. 68(9). 1371–1387.

Kim, Young‐Woo, et al.. (2024). Not Merely Useful but Also Amusing: Impact of Perceived Usefulness and Perceived Enjoyment on the Adoption of AI-Powered Coding Assistant. International Journal of Human-Computer Interaction. 41(10). 6210–6222. 10 indexed citations

Zhang, Yiqi, et al.. (2023). What Do You Expect for Your AV? The 2nd Workshop on Behaviors of Autonomous Vehicles in Ambiguous Driving Scenarios. 264–266. 1 indexed citations

Kim, Young Woo, et al.. (2022). The 2nd Workshop on User Experience in Urban Air Mobility: From Ground to Aerial Transportation. 168–171. 3 indexed citations

Lee, Seul Chan, Yiqi Zhang, Sol Hee Yoon, et al.. (2022). A Workshop on Driving Style of Automated Vehicles in Ambiguous Driving Scenarios. 182–185. 3 indexed citations

10.

Kim, Young‐Woo, et al.. (2022). Understanding Driver's Situation Awareness in Highly Automated Driving. 132–136. 5 indexed citations

11.

Yoon, Sol Hee, Seul Chan Lee, & Yong Gu Ji. (2020). Modeling takeover time based on non-driving-related task attributes in highly automated driving. Applied Ergonomics. 92. 103343–103343. 36 indexed citations

12.

Lee, Seul Chan, Sol Hee Yoon, & Yong Gu Ji. (2020). Effects of Non-Driving-Related Task Attributes on Takeover Quality in Automated Vehicles. International Journal of Human-Computer Interaction. 37(3). 211–219. 47 indexed citations

13.

Yoon, Sol Hee, Young‐Woo Kim, & Yong Gu Ji. (2018). The effects of takeover request modalities on highly automated car control transitions. Accident Analysis & Prevention. 123. 150–158. 100 indexed citations

14.

Yoon, Sol Hee & Yong Gu Ji. (2018). Non-driving-related tasks, workload, and takeover performance in highly automated driving contexts. Transportation Research Part F Traffic Psychology and Behaviour. 60. 620–631. 77 indexed citations

15.

Yoon, Sol Hee, et al.. (2016). Preliminary Effectiveness and Sustainability of Group Aerobic Exercise Program in Patients with Schizophrenia. The Journal of Nervous and Mental Disease. 204(9). 644–650. 13 indexed citations

16.

Yoon, Sol Hee, et al.. (2015). Perceived Visual Complexity and Visual Search Performance of Automotive Instrument Cluster: A Quantitative Measurement Study. International Journal of Human-Computer Interaction. 31(12). 890–900. 24 indexed citations

17.

Yoon, Sol Hee, et al.. (2015). Assessment model for driver perceived visual complexity.

18.

Yoon, Sol Hee, et al.. (2014). Assessment model for perceived visual complexity of automotive instrument cluster. Applied Ergonomics. 46. 76–83. 21 indexed citations

19.

Hwangbo, Hwan, et al.. (2012). A Study of Pointing Performance of Elderly Users on Smartphones. International Journal of Human-Computer Interaction. 29(9). 604–618. 94 indexed citations

20.

Yoon, Sol Hee, et al.. (2012). Development of a Continuous Usage Model for the Adoption and Continuous Usage of a Smartphone. International Journal of Human-Computer Interaction. 29(9). 563–581. 30 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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