Lingxi Li

4.5k total citations · 4 hit papers
187 papers, 3.1k citations indexed

About

Lingxi Li is a scholar working on Automotive Engineering, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Lingxi Li has authored 187 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Automotive Engineering, 50 papers in Control and Systems Engineering and 28 papers in Computational Theory and Mathematics. Recurrent topics in Lingxi Li's work include Autonomous Vehicle Technology and Safety (48 papers), Traffic control and management (34 papers) and Traffic Prediction and Management Techniques (25 papers). Lingxi Li is often cited by papers focused on Autonomous Vehicle Technology and Safety (48 papers), Traffic control and management (34 papers) and Traffic Prediction and Management Techniques (25 papers). Lingxi Li collaborates with scholars based in United States, China and United Kingdom. Lingxi Li's co-authors include Fei‐Yue Wang, Xiao Wang, Long Chen, Christoforos N. Hadjicostis, Yaobin Chen, Dewang Chen, Li Li, Jiateng Yin, Yunfeng Ai and Siyu Teng and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Automatic Control.

In The Last Decade

Lingxi Li

165 papers receiving 3.0k citations

Hit Papers

Motion Planning for Autonomous Driving: The State of the ... 2022 2026 2023 2024 2023 2022 2023 2023 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
Lingxi Li United States 31 892 808 632 478 416 187 3.1k
Enrique Onieva Spain 26 827 0.9× 908 1.1× 323 0.5× 691 1.4× 593 1.4× 96 2.7k
Zhiguang Cao Singapore 29 471 0.5× 447 0.6× 616 1.0× 607 1.3× 488 1.2× 93 3.1k
Chao Huang China 35 1.7k 1.9× 1.3k 1.7× 1.1k 1.8× 446 0.9× 284 0.7× 194 4.0k
Fenghua Zhu China 26 620 0.7× 823 1.0× 573 0.9× 366 0.8× 876 2.1× 165 3.1k
Saiedeh Razavi Canada 20 477 0.5× 788 1.0× 311 0.5× 593 1.2× 552 1.3× 76 2.8k
Shuo Feng China 22 1.6k 1.8× 1.4k 1.7× 255 0.4× 543 1.1× 323 0.8× 50 2.9k
Yannis Marinakis Greece 34 473 0.5× 335 0.4× 399 0.6× 1.2k 2.6× 343 0.8× 81 3.0k
Kunfeng Wang China 27 805 0.9× 799 1.0× 1.6k 2.5× 710 1.5× 1.1k 2.6× 108 4.1k
Markus Maurer Germany 22 1.7k 1.9× 778 1.0× 608 1.0× 386 0.8× 164 0.4× 115 2.7k
Jianping Wu China 32 598 0.7× 780 1.0× 296 0.5× 361 0.8× 781 1.9× 222 3.2k

Countries citing papers authored by Lingxi Li

Since Specialization
Citations

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

Fields of papers citing papers by Lingxi Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingxi Li

This figure shows the co-authorship network connecting the top 25 collaborators of Lingxi Li. A scholar is included among the top collaborators of Lingxi Li 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 Lingxi Li. Lingxi Li 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.
Li, Lingxi, et al.. (2025). Review and Perspectives on Pedestrian Trajectory Prediction for Safe Transportation. IEEE Transactions on Intelligent Transportation Systems. 27(1). 26–52.
2.
Cui, Can, Yupeng Zhou, Sung‐Yeon Park, et al.. (2025). On-Board Vision-Language Models (VLMs) for Personalized Motion Control of Autonomous Vehicles. 20349–20356. 1 indexed citations
3.
Wang, Dan, Jianhua Wu, Peiyue Li, et al.. (2024). Seasonal nitrate variations, risks, and sources in groundwater under different land use types in a thousand-year-cultivated region, northwestern China. Environmental Research. 251(Pt 2). 118699–118699. 34 indexed citations
4.
Vlacic, Ljubo, Hailong Huang, Mariagrazia Dotoli, et al.. (2024). Automation 5.0: The Key to Systems Intelligence and Industry 5.0. IEEE/CAA Journal of Automatica Sinica. 11(8). 1723–1727. 9 indexed citations
5.
Wang, Mengxin, et al.. (2024). Game-Generative Adversarial Imitation Learning for Pedestrian Simulation During Pedestrian-Vehicle Interaction. IEEE Transactions on Intelligent Vehicles. 1–12. 3 indexed citations
6.
Teng, Siyu, Luxi Li, Yuchen Li, et al.. (2024). FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion. Mechanical Systems and Signal Processing. 208. 111051–111051. 38 indexed citations
7.
Chen, Yaobin, et al.. (2024). Risk Analysis in Vehicle and Electric Scooter Interaction. 1316–1322. 1 indexed citations
8.
Li, Lingxi, Sabyasachee Mishra, Renran Tian, et al.. (2024). E-scooter Crash Data Analysis towards E-scooter Automatic Emergency Braking System Design and Validation for Automated Vehicles*. 1323–1328. 1 indexed citations
9.
Ye, Bao‐Lin, Peng Wu, Lingxi Li, & Weimin Wu. (2024). Uniformity of markov elements in deep reinforcement learning for traffic signal control. Electronic Research Archive. 32(6). 3843–3866.
10.
Shen, Xiaohui, et al.. (2024). A Novel Hybrid Algorithm Based on Beluga Whale Optimization and Harris Hawks Optimization for Optimizing Multi-Reservoir Operation. Water Resources Management. 38(12). 4883–4909. 4 indexed citations
11.
Chen, Long, et al.. (2023). MetaMining: Mining in the Metaverse. IEEE Transactions on Systems Man and Cybernetics Systems. 53(6). 3858–3867. 30 indexed citations
12.
Shen, Dan, et al.. (2022). Distributed Stochastic Model Predictive Control With Taguchi’s Robustness for Vehicle Platooning. IEEE Transactions on Intelligent Transportation Systems. 23(9). 15967–15979. 33 indexed citations
13.
Shen, Dan, Zhengming Zhang, Renran Tian, et al.. (2021). Assessing the Effectiveness of In-Vehicle Highway Back-of-Queue Alerting System. IUScholarWorks (Indiana University). 2 indexed citations
14.
Chen, Long, et al.. (2020). DenseLightNet: A Light-Weight Vehicle Detection Network for Autonomous Driving. IEEE Transactions on Industrial Electronics. 67(12). 10600–10609. 61 indexed citations
15.
Wang, Xiao, Shuangshuang Han, Linyao Yang, Tingting Yao, & Lingxi Li. (2020). Parallel Internet of Vehicles: ACP-Based System Architecture and Behavioral Modeling. IEEE Internet of Things Journal. 7(5). 3735–3746. 38 indexed citations
16.
Yi, Qiang, Dan Shen, Stanley Chien, et al.. (2019). Color and Height Characteristics of Surrogate Grass for the Evaluation of Vehicle Road Departure Mitigation Systems. SAE International Journal of Advances and Current Practices in Mobility. 1(4). 1461–1469. 1 indexed citations
17.
Han, Shuangshuang, Dongpu Cao, Li Li, et al.. (2018). From Software-Defined Vehicles to Self-Driving Vehicles: A Report on CPSS-Based Parallel Driving. IEEE Intelligent Transportation Systems Magazine. 11(1). 6–14. 22 indexed citations
18.
Li, Lingxi, Donghe Zhang, Yongqiang Hao, & Zuo Xiao. (2015). Influence of ionospheric diurnal variation on the estimated GPS differential code bias. Chinese Journal of Space Science. 35(2). 143–143.
19.
Li, Lingxi, et al.. (2013). Modeling and Analysis of Connected Traffic Intersections Based on Modified Binary Petri Nets. SHILAP Revista de lepidopterología. 2013. 1–10. 6 indexed citations
20.
Xiong, Jing, et al.. (2012). Failure detection for over-discharged Li-ion batteries. 1–5. 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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