David A. Abbink

5.1k total citations · 1 hit paper
165 papers, 3.6k citations indexed

About

David A. Abbink is a scholar working on Social Psychology, Cognitive Neuroscience and Mechanical Engineering. According to data from OpenAlex, David A. Abbink has authored 165 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Social Psychology, 50 papers in Cognitive Neuroscience and 44 papers in Mechanical Engineering. Recurrent topics in David A. Abbink's work include Human-Automation Interaction and Safety (83 papers), Traffic and Road Safety (42 papers) and Teleoperation and Haptic Systems (40 papers). David A. Abbink is often cited by papers focused on Human-Automation Interaction and Safety (83 papers), Traffic and Road Safety (42 papers) and Teleoperation and Haptic Systems (40 papers). David A. Abbink collaborates with scholars based in Netherlands, Germany and France. David A. Abbink's co-authors include Mark Mulder, Erwin R. Boer, Max Mulder, M. M. van Paassen, Joost de Winter, F.C.T. van der Helm, Sebastiaan M. Petermeijer, H. Boessenkool, Cock Heemskerk and F.C.T. van der Helm and has published in prestigious journals such as Nature Communications, PLoS ONE and The Journal of Physiology.

In The Last Decade

David A. Abbink

158 papers receiving 3.5k citations

Hit Papers

Haptic shared control: smoothly shifting control authority? 2011 2026 2016 2021 2011 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David A. Abbink Netherlands 31 2.0k 1.1k 998 814 757 165 3.6k
Erwin R. Boer United States 32 1.7k 0.9× 1.1k 1.0× 827 0.8× 1.2k 1.4× 518 0.7× 111 3.7k
M. M. van Paassen Netherlands 34 2.9k 1.5× 636 0.6× 1.1k 1.1× 487 0.6× 601 0.8× 440 5.0k
Mark Mulder Netherlands 22 1.1k 0.5× 613 0.5× 484 0.5× 433 0.5× 319 0.4× 68 2.0k
Klaus Bengler Germany 39 5.5k 2.8× 2.7k 2.4× 831 0.8× 3.2k 3.9× 478 0.6× 358 7.5k
Walter W. Wierwille United States 31 2.2k 1.1× 582 0.5× 245 0.2× 1.1k 1.3× 443 0.6× 130 3.4k
R. Brent Gillespie United States 24 416 0.2× 367 0.3× 728 0.7× 111 0.1× 831 1.1× 132 2.6k
Jwu‐Sheng Hu Taiwan 28 596 0.3× 143 0.1× 572 0.6× 272 0.3× 356 0.5× 217 2.9k
Takahiro Wada Japan 25 504 0.3× 432 0.4× 436 0.4× 208 0.3× 166 0.2× 170 1.7k
Errol R. Hoffmann Australia 28 1.0k 0.5× 269 0.2× 181 0.2× 488 0.6× 949 1.3× 136 2.4k
Stewart Birrell United Kingdom 29 1.2k 0.6× 735 0.6× 183 0.2× 620 0.8× 116 0.2× 95 2.7k

Countries citing papers authored by David A. Abbink

Since Specialization
Citations

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

Fields of papers citing papers by David A. Abbink

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. Abbink. 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 David A. Abbink. The network helps show where David A. Abbink may publish in the future.

Co-authorship network of co-authors of David A. Abbink

This figure shows the co-authorship network connecting the top 25 collaborators of David A. Abbink. A scholar is included among the top collaborators of David A. Abbink 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 David A. Abbink. David A. Abbink 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.
Zaga, Cristina, et al.. (2024). First International Workshop on Worker-Robot Relationships: Exploring Transdisciplinarity for the Future of Work with Robots. University of Twente Research Information. 1367–1369. 1 indexed citations
2.
Bosch, Karel Van den, et al.. (2024). Enabling Embodied Human-Robot Co-Learning: Requirements, Method, and Test With Handover Task. IEEE Robotics and Automation Letters. 10(2). 1425–1432. 1 indexed citations
4.
Zgonnikov, Arkady, et al.. (2024). A model of dyadic merging interactions explains human drivers’ behavior from control inputs to decisions. PNAS Nexus. 3(10). pgae420–pgae420. 1 indexed citations
5.
Heemskerk, Cock, et al.. (2024). Augmenting visual feedback with visualized interaction forces in haptic-assisted virtual-reality teleoperation. Frontiers in Robotics and AI. 11. 1427095–1427095. 1 indexed citations
6.
Huang, Heye, et al.. (2023). General Optimal Trajectory Planning: Enabling Autonomous Vehicles with the Principle of Least Action. Engineering. 33. 63–76. 11 indexed citations
7.
Bruijnes, Merijn, et al.. (2022). Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid. Scientific Reports. 12(1). 16193–16193. 10 indexed citations
8.
Abbink, David A., et al.. (2019). Perception and control of low cable operation forces in voluntary closing body-powered upper-limb prostheses. PLoS ONE. 14(11). e0225263–e0225263.
9.
Heemskerk, Cock, et al.. (2018). Haptic Assistance Improves Tele-Manipulation With Two Asymmetric Slaves. IEEE Transactions on Haptics. 12(2). 141–153. 8 indexed citations
10.
Abbink, David A., Tom Carlson, Mark Mulder, et al.. (2018). A Topology of Shared Control Systems—Finding Common Ground in Diversity. IEEE Transactions on Human-Machine Systems. 48(5). 509–525. 143 indexed citations
11.
Pool, Daan M., et al.. (2018). A New Haptic Shared Controller Reducing Steering Conflicts. Research Repository (Delft University of Technology). 2705–2710. 10 indexed citations
12.
Abbink, David A., et al.. (2017). High Cable Forces Deteriorate Pinch Force Control in Voluntary-Closing Body-Powered Prostheses. PLoS ONE. 12(1). e0169996–e0169996. 9 indexed citations
13.
Winter, Joost de, et al.. (2016). Does haptic steering guidance instigate speeding? A driving simulator study into causes and remedies. Accident Analysis & Prevention. 98. 372–387. 21 indexed citations
14.
Paassen, M. M. van, et al.. (2015). Haptic Guidance, Interaction Between the Guidance Model and Tuning. 410. 1 indexed citations
15.
Mugge, Winfred, David A. Abbink, Alfred C. Schouten, et al.. (2012). Force control in the absence of visual and tactile feedback. Experimental Brain Research. 224(4). 635–645. 10 indexed citations
16.
Mulder, Mark, David A. Abbink, & Erwin R. Boer. (2012). Sharing Control With Haptics. Human Factors The Journal of the Human Factors and Ergonomics Society. 54(5). 786–798. 179 indexed citations
17.
Abbink, David A., Max Mulder, F.C.T. van der Helm, & Erwin R. Boer. (2011). Measuring Neuromuscular Control Dynamics During Car Following With Continuous Haptic Feedback. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 41(5). 1239–1249. 76 indexed citations
18.
Mulder, Mark, David A. Abbink, M. M. van Paassen, et al.. (2011). Identification of time variant neuromuscular admittance using wavelets. 1474–1480. 14 indexed citations
19.
Winter, Joost de, Max Mulder, M. M. van Paassen, David A. Abbink, & Peter A. Wieringa. (2008). A Two-Dimensional Weighting Function for a Driver Assistance System. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 38(1). 189–195. 20 indexed citations
20.
Abbink, David A.. (2006). Neuromuscular analysis of haptic gas pedal feedback during car following. Research Repository (Delft University of Technology). 69 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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