Soyoung Ahn

4.0k total citations
102 papers, 3.1k citations indexed

About

Soyoung Ahn is a scholar working on Control and Systems Engineering, Transportation and Building and Construction. According to data from OpenAlex, Soyoung Ahn has authored 102 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Control and Systems Engineering, 53 papers in Transportation and 39 papers in Building and Construction. Recurrent topics in Soyoung Ahn's work include Traffic control and management (69 papers), Transportation Planning and Optimization (51 papers) and Traffic Prediction and Management Techniques (35 papers). Soyoung Ahn is often cited by papers focused on Traffic control and management (69 papers), Transportation Planning and Optimization (51 papers) and Traffic Prediction and Management Techniques (35 papers). Soyoung Ahn collaborates with scholars based in United States, South Korea and China. Soyoung Ahn's co-authors include Danjue Chen, Yang Zhou, Zuduo Zheng, Jorge Laval, David A. Noyce, Madhav Chitturi, Christopher Monsere, Meng Wang, Michael J. Cassidy and Michael J. Cassidy and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and Molecules.

In The Last Decade

Soyoung Ahn

94 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Soyoung Ahn United States 29 2.6k 1.6k 1.4k 1.1k 784 102 3.1k
Vincenzo Punzo Italy 30 2.0k 0.8× 1.1k 0.7× 1.3k 0.9× 1.1k 1.0× 656 0.8× 59 2.6k
Larry Head United States 27 3.0k 1.2× 2.3k 1.4× 1.0k 0.7× 2.0k 1.8× 731 0.9× 92 3.7k
Rahim F. Benekohal United States 24 1.7k 0.6× 1.4k 0.9× 497 0.4× 1.2k 1.1× 772 1.0× 214 2.5k
Mark Brackstone United Kingdom 18 1.9k 0.7× 1.0k 0.7× 1.0k 0.7× 732 0.7× 833 1.1× 53 2.3k
Alireza Talebpour United States 19 1.8k 0.7× 1.2k 0.7× 1.4k 1.0× 662 0.6× 614 0.8× 61 2.4k
Dong Ngoduy Australia 34 2.9k 1.1× 2.1k 1.4× 1.3k 0.9× 1.5k 1.4× 439 0.6× 118 3.6k
Yang Zheng China 22 2.6k 1.0× 877 0.6× 1.5k 1.1× 684 0.6× 203 0.3× 50 3.3k
Nan Zheng China 25 1.4k 0.5× 1.4k 0.9× 649 0.5× 970 0.9× 153 0.2× 86 2.1k
Jorge Laval United States 30 3.2k 1.2× 2.5k 1.6× 1.1k 0.8× 1.6k 1.5× 821 1.0× 95 3.5k

Countries citing papers authored by Soyoung Ahn

Since Specialization
Citations

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

Fields of papers citing papers by Soyoung Ahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soyoung Ahn. 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 Soyoung Ahn. The network helps show where Soyoung Ahn may publish in the future.

Co-authorship network of co-authors of Soyoung Ahn

This figure shows the co-authorship network connecting the top 25 collaborators of Soyoung Ahn. A scholar is included among the top collaborators of Soyoung Ahn 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 Soyoung Ahn. Soyoung Ahn 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.
Huang, Heye, et al.. (2025). RiskNet: interaction-aware risk forecasting for autonomous driving in long-tail scenarios. Transportation Research Part E Logistics and Transportation Review. 205. 104478–104478.
3.
Wang, Xin, et al.. (2024). A generic stochastic hybrid car-following model based on approximate Bayesian computation. Transportation Research Part C Emerging Technologies. 167. 104799–104799. 9 indexed citations
4.
Zhou, Yang, et al.. (2024). Planning trajectories for connected and automated vehicle platoon on curved roads: A two-dimensional cooperative approach. Transportation Research Part C Emerging Technologies. 165. 104718–104718.
6.
Zhou, Yang, et al.. (2024). A Deep Long Short-Term Memory Network Embedded Model Predictive Control Strategies for Car-Following Control of Connected Automated Vehicles in Mixed Traffic. IEEE Transactions on Intelligent Transportation Systems. 25(7). 8209–8220. 5 indexed citations
7.
Ahn, Soyoung, et al.. (2024). Understanding heterogeneity of automated vehicles and its traffic-level impact: A stochastic behavioral perspective. Transportation Research Part C Emerging Technologies. 164. 104667–104667. 2 indexed citations
8.
Chen, Qián, et al.. (2023). Data-driven analysis for disturbance amplification in car-following behavior of automated vehicles. Transportation Research Part B Methodological. 174. 102768–102768. 15 indexed citations
9.
Ahn, Soyoung, et al.. (2019). Variable Speed Release (VSR): Speed Control to Increase Bottleneck Capacity. IEEE Transactions on Intelligent Transportation Systems. 21(1). 298–307. 21 indexed citations
10.
Ding, Fan, et al.. (2019). Deep Long Short-Term Memory Network based Long-Term Vehicle Trajectory Prediction. Transportation Research Board 98th Annual MeetingTransportation Research Board.
11.
Chen, Danjue & Soyoung Ahn. (2018). Harnessing Connected and Automated Vehicle Technologies to Control Lane Changes at Freeway Merge Bottlenecks. Transportation Research Board 97th Annual MeetingTransportation Research Board. 3 indexed citations
12.
Chen, Danjue, et al.. (2017). Variable speed limit control at fixed freeway bottlenecks using connected vehicles. Transportation Research Part B Methodological. 98. 113–134. 6 indexed citations
13.
Ahn, Soyoung, et al.. (2017). Stochastic Modeling of Breakdown at Freeway Merge Bottleneck. Transportation Research Board 96th Annual MeetingTransportation Research Board. 1 indexed citations
14.
Ahn, Soyoung, et al.. (2014). Prediction Of Merge Ratio Using Lane Flow Distribution. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 3 indexed citations
15.
Ahn, Soyoung, Michael J. Cassidy, & Jorge Laval. (2007). Effects of Merging and Diverging on Freeway Traffic Oscillations. Transportation Research Board 87th Annual MeetingTransportation Research Board. 2 indexed citations
16.
Kothuri, Sirisha, Kristin Tufte, Soyoung Ahn, & Robert L. Bertini. (2007). Using Archived ITS Data to Generate Improved Freeway Travel Time Estimates. Transportation Research Board 86th Annual MeetingTransportation Research Board. 3 indexed citations
17.
Ahn, Soyoung, et al.. (2007). A NEW FINITE DIFFERENCE FORMULA OF DIRICHLET PROBLEM ON TRIANGULAR GRIDS. 3(2). 89–91. 2 indexed citations
18.
Mauch, Michael, Koohong Chung, Soyoung Ahn, & Alexander Skabardonis. (2006). Evaluation of the Bay Area Incident Response System (BAIRS). RePEc: Research Papers in Economics. 2 indexed citations
19.
Bertini, Robert L., et al.. (2006). INFLUENCE OF VARIABLE SPEED LIMIT AND DRIVER INFORMATION SYSTEM ON KEY TRAFFIC FLOW PARAMETERS ON A GERMAN AUTOBAHN. 3 indexed citations
20.
Ahn, Soyoung, U Jin Choi, & А. Г. Рамм. (2005). A scheme for stable numerical differentiation. Journal of Computational and Applied Mathematics. 186(2). 325–334. 29 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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