World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
49
Citations
8187
World Ranking
4370
National Ranking
863

Pan Liu publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Pan Liu sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 203 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Pan Liu D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Pan Liu sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 49 D-Index — 57th percentile

57% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Pan Liu is affiliated with Southeast University in China and has an established record in engineering research, with a focus on transportation safety and control systems. Their body of work includes 149 publications primarily in the field of engineering.

Their research spans several subfields, including:

  • Safety, Risk, Reliability and Quality
  • Automotive Engineering
  • Transportation
  • Control and Systems Engineering
  • Building and Construction

Main topics covered in their research include:

  • Traffic and Road Safety
  • Traffic control and management
  • Autonomous Vehicle Technology and Safety
  • Transportation Planning and Optimization
  • Traffic Prediction and Management Techniques
  • Urban Transport and Accessibility
  • Transportation and Mobility Innovations

Frequent publication venues for Pan Liu's work are:

  • Accident Analysis & Prevention
  • Transportation Research Part C Emerging Technologies
  • IEEE Transactions on Intelligent Transportation Systems
  • SSRN Electronic Journal
  • Journal of Advanced Transportation

Pan Liu has contributed to a range of papers, some of the recent ones include:

  • A review of surrogate safety measures and their applications in connected and automated vehicles safety modeling, 2021, Accident Analysis & Prevention
  • Effect of environmental awareness on electric bicycle users' mode choices, 2020, Transportation Research Part D Transport and Environment
  • The cooperative sorting strategy for connected and automated vehicle platoons, 2021, Transportation Research Part C Emerging Technologies
  • A physics-informed reinforcement learning-based strategy for local and coordinated ramp metering, 2022, Transportation Research Part C Emerging Technologies
  • Enhancing Transferability of Deep Reinforcement Learning-Based Variable Speed Limit Control Using Transfer Learning, 2020, IEEE Transactions on Intelligent Transportation Systems

They have collaborated frequently with a set of coauthors, including:

  • Zhibin Li
  • Yanyong Guo
  • Yuxuan Wang
  • Chengcheng Xu
  • Kequan Chen

Best Publications

  • A review of surrogate safety measures and their applications in connected and automated vehicles safety modeling.

    Chen Wang;Yuanchang Xie;Helai Huang;Pan Liu

  • Using support vector machine models for crash injury severity analysis.

    Zhibin Li;Pan Liu;Weixu Wang;Chengcheng Xu

  • The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets

    Chengcheng Xu;Junyi Ji;Pan Liu

  • Identifying if VISSIM simulation model and SSAM provide reasonable estimates for field measured traffic conflicts at signalized intersections.

    Fei Huang;Pan Liu;Hao Yu;Weixu Wang

  • A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data.

    Jie Bao;Jie Bao;Pan Liu;Satish V. Ukkusuri

  • Evaluation of the impacts of traffic states on crash risks on freeways.

    Chengcheng Xu;Pan Liu;Weixu Wang;Zhibin Li

  • Predicting crash likelihood and severity on freeways with real-time loop detector data

    Chengcheng Xu;Andrew P. Tarko;Weixu Wang;Pan Liu

  • Using Geographically Weighted Poisson Regression for county-level crash modeling in California

    Zhibin Li;Zhibin Li;Weixu Wang;Pan Liu;John M. Bigham

  • Reinforcement Learning-Based Variable Speed Limit Control Strategy to Reduce Traffic Congestion at Freeway Recurrent Bottlenecks

    Zhibin Li;Pan Liu;Chengcheng Xu;Hui Duan

  • Physical environments influencing bicyclists’ perception of comfort on separated and on-street bicycle facilities

    Zhibin Li;Wei Wang;Pan Liu;David R. Ragland

  • Using VISSIM simulation model and Surrogate Safety Assessment Model for estimating field measured traffic conflicts at freeway merge areas

    Rong Fan;Hao Yu;Pan Liu;Wei Wang

  • Comparative analysis of the spatial analysis methods for hotspot identification

    Hao Yu;Pan Liu;Jun Chen;Hao Wang

  • Identifying crash-prone traffic conditions under different weather on freeways

    Chengcheng Xu;Weixu Wang;Pan Liu

  • Exploring Bikesharing Travel Patterns and Trip Purposes Using Smart Card Data and Online Point of Interests

    Jie Bao;Chengcheng Xu;Pan Liu;Wei Wang

  • Comparative analysis of the safety effects of electric bikes at signalized intersections

    Lu Bai;Pan Liu;Yuguang Chen;Xin Zhang

  • A Genetic Programming Model for Real-Time Crash Prediction on Freeways

    Chengcheng Xu;Wei Wang;Pan Liu

  • Association rule analysis of factors contributing to extraordinarily severe traffic crashes in China.

    Chengcheng Xu;Jie Bao;Chen Wang;Pan Liu

  • Development of a variable speed limit strategy to reduce secondary collision risks during inclement weathers.

    Zhibin Li;Ye Li;Pan Liu;Weixu Wang

  • Modeling correlation and heterogeneity in crash rates by collision types using full bayesian random parameters multivariate Tobit model.

    Yanyong Guo;Yanyong Guo;Zhibin Li;Pan Liu;Yao Wu

  • Real-time estimation of secondary crash likelihood on freeways using high-resolution loop detector data

    Chengcheng Xu;Pan Liu;Bo Yang;Wei Wang

  • Optimal transit fare and service frequency of a nonlinear origin-destination based fare structure

    Di Huang;Zhiyuan Liu;Pan Liu;Jun Chen

Frequent Co-Authors

Chengcheng Xu
Chengcheng Xu Southeast University
Zhibin Li
Zhibin Li Southeast University
Xiao-Yuan Jing
Xiao-Yuan Jing Wuhan University
Chen Wang
Chen Wang Swansea University
Fei Wu
Fei Wu Zhejiang University
Yong Wang
Yong Wang Nanjing University
Jun Chen
Jun Chen Nankai University
Xiaobo Qu
Xiaobo Qu Xiamen University
Helai Huang
Helai Huang Central South University
Robert J. Schneider
Robert J. Schneider New York University

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