John D. Lee

22.6k total citations · 5 hit papers
317 papers, 15.6k citations indexed

About

John D. Lee is a scholar working on Social Psychology, Safety, Risk, Reliability and Quality and Automotive Engineering. According to data from OpenAlex, John D. Lee has authored 317 papers receiving a total of 15.6k indexed citations (citations by other indexed papers that have themselves been cited), including 213 papers in Social Psychology, 128 papers in Safety, Risk, Reliability and Quality and 37 papers in Automotive Engineering. Recurrent topics in John D. Lee's work include Human-Automation Interaction and Safety (204 papers), Traffic and Road Safety (124 papers) and Safety Warnings and Signage (67 papers). John D. Lee is often cited by papers focused on Human-Automation Interaction and Safety (204 papers), Traffic and Road Safety (124 papers) and Safety Warnings and Signage (67 papers). John D. Lee collaborates with scholars based in United States, Canada and Norway. John D. Lee's co-authors include Neville Moray, Linda Ng Boyle, Yulan Liang, Michelle L. Reyes, Timothy L. Brown, Daniel V. McGehee, Mahtab Ghazizadeh, Birsen Donmez, Bobbie Seppelt and Michael Regan and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and Journal of Geophysical Research Atmospheres.

In The Last Decade

John D. Lee

301 papers receiving 14.6k citations

Hit Papers

Trust in Automation: Designing for Appropriate Reliance 1992 2026 2003 2014 2004 2004 1992 1994 2021 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John D. Lee United States 56 10.5k 4.8k 2.4k 1.5k 1.4k 317 15.6k
Peter A. Hancock United States 68 9.3k 0.9× 2.1k 0.4× 1.1k 0.4× 1.6k 1.0× 1.1k 0.8× 517 17.3k
Neville A. Stanton United Kingdom 71 12.4k 1.2× 5.3k 1.1× 2.5k 1.0× 860 0.6× 825 0.6× 606 19.8k
Mica R. Endsley United States 47 12.7k 1.2× 2.3k 0.5× 1.2k 0.5× 2.6k 1.7× 2.4k 1.7× 168 19.7k
Christopher D. Wickens United States 75 16.4k 1.6× 3.0k 0.6× 2.0k 0.8× 1.6k 1.1× 2.7k 1.9× 501 26.3k
Joost de Winter Netherlands 56 6.9k 0.7× 4.3k 0.9× 3.4k 1.4× 512 0.3× 524 0.4× 266 13.0k
Paul M. Salmon Australia 62 6.4k 0.6× 2.6k 0.5× 519 0.2× 465 0.3× 375 0.3× 466 13.5k
David Kaber United States 36 3.8k 0.4× 852 0.2× 386 0.2× 503 0.3× 861 0.6× 206 6.0k
James Reason United Kingdom 36 3.3k 0.3× 2.8k 0.6× 254 0.1× 317 0.2× 880 0.6× 84 16.0k
Neville Moray United Kingdom 33 3.8k 0.4× 634 0.1× 323 0.1× 641 0.4× 802 0.6× 110 6.6k
David D. Woods United States 55 5.3k 0.5× 723 0.1× 408 0.2× 1.4k 0.9× 1.2k 0.9× 244 11.0k

Countries citing papers authored by John D. Lee

Since Specialization
Citations

This map shows the geographic impact of John D. Lee'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 John D. Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Lee more than expected).

Fields of papers citing papers by John D. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John D. Lee. 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 John D. Lee. The network helps show where John D. Lee may publish in the future.

Co-authorship network of co-authors of John D. Lee

This figure shows the co-authorship network connecting the top 25 collaborators of John D. Lee. A scholar is included among the top collaborators of John D. Lee 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 John D. Lee. John D. Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhou, Yang, et al.. (2025). Human-automated vehicle interactions: Voluntary driver intervention in car-following. Transportation Research Part C Emerging Technologies. 171. 104969–104969. 2 indexed citations
2.
See, J, et al.. (2025). Are humans still necessary? Expanding the discussion. Ergonomics. 1–16.
3.
Boyle, Linda Ng, et al.. (2023). Perceptions related to engaging in non-driving activities in an automated vehicle while commuting: A text mining approach. Transportation Research Part F Traffic Psychology and Behaviour. 94. 305–320. 3 indexed citations
4.
Kujala, Tuomo, et al.. (2023). On the relationship between occlusion times and in-car glance durations in simulated driving. Accident Analysis & Prevention. 182. 106955–106955. 5 indexed citations
5.
Krupp, Anna, Linsey M. Steege, John D. Lee, Karen Dunn Lopez, & Barbara King. (2022). Supporting Decision-Making About Patient Mobility in the Intensive Care Unit Nurse Work Environment: Work Domain Analysis. SHILAP Revista de lepidopterología. 5(1). e41051–e41051. 5 indexed citations
6.
Lee, Joonbum, et al.. (2022). Teaming with Your Car: Redefining the Driver–Automation Relationship in Highly Automated Vehicles. Journal of Cognitive Engineering and Decision Making. 17(1). 49–74. 18 indexed citations
7.
Hancock, Peter A., John D. Lee, & John W. Senders. (2021). Attribution Errors by People and Intelligent Machines. Human Factors The Journal of the Human Factors and Ergonomics Society. 65(7). 1293–1305. 10 indexed citations
8.
Lee, John D., et al.. (2016). Situation Awareness, Scenarios, and Secondary Tasks: Measuring Driver Performance and Safety Margins in Highly Automated Vehicles. SAE International journal of passenger cars. Electronic and electrical systems. 9(1). 237–242. 13 indexed citations
9.
Schall, Mark C., et al.. (2016). Time-to-contact estimation errors among older drivers with useful field of view impairments. Accident Analysis & Prevention. 95(Pt A). 284–291. 11 indexed citations
10.
Lee, John D., Jane Moeckli, Timothy A. Brown, et al.. (2013). Detection of Driver Distraction Using Vision-Based Algorithms. 11 indexed citations
11.
Schall, Mark C., et al.. (2011). Effects of Augmented Reality Cues on Driver Hazard Perception. Transportation Research Board 90th Annual MeetingTransportation Research Board. 1 indexed citations
12.
Lee, John D., Daniel V. McGehee, James L. Brown, et al.. (2011). Matching Simulator Characteristics to Highway Design Problems. Transportation Research Record Journal of the Transportation Research Board. 2248(1). 53–60. 9 indexed citations
14.
Donmez, Birsen, Linda Ng Boyle, & John D. Lee. (2008). Accounting for time-dependent covariates in driving simulator studies. Theoretical Issues in Ergonomics Science. 9(3). 189–199. 4 indexed citations
15.
Lees, Monica N., JonDavid Sparks, John D. Lee, & Matthew Rizzo. (2007). Change Blindness, Attention, and Driving Performance. 4 indexed citations
16.
Lees, Monica N. & John D. Lee. (2007). The influence of distraction and driving context on driver response to imperfect collision warning systems. Ergonomics. 50(8). 1264–1286. 129 indexed citations
17.
Hoffman, Joshua, John D. Lee, Timothy L. Brown, & Daniel V. McGehee. (2006). Comparison of Driver Braking Responses in a High Fidelity Driving Simulator and on a Test Track. 16(4). 56–61. 3 indexed citations
18.
Robertson, Margaret, et al.. (2002). Leisure Geographies of Young People: Cross-cultural Perspectives. eCite Digital Repository (University of Tasmania). 1 indexed citations
19.
Lee, John D.. (1986). Education of Native Adolescents in Inner-City Schools.. Canadian journal of native education. 13(2). 22–26. 2 indexed citations
20.
Lee, John D., et al.. (1967). Diary of the Mormon Battalion Mission. New Mexico historical review. 42(3).

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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