World's Best Scientists 2026 revealed!
Tie-Qiao Tang

Tie-Qiao Tang

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
51
Citations
7074
World Ranking
1139
National Ranking
140

Tie-Qiao Tang publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Tie-Qiao Tang sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 133 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Tie-Qiao Tang D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Tie-Qiao Tang sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 51 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Overview

Tie-Qiao Tang is a researcher affiliated with Beihang University in China, specializing in engineering with a focus on automotive and transportation engineering. Their body of work spans various aspects of transportation systems, vehicle control, and safety.

The researcher has contributed to fields including:

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

Tang's research encompasses several main topics, such as:

  • Evacuation and Crowd Dynamics
  • Traffic Control and Management
  • Traffic and Road Safety
  • Transportation Planning and Optimization
  • Autonomous Vehicle Technology and Safety
  • Air Traffic Management and Optimization
  • Aviation Industry Analysis and Trends

Recent papers authored or co-authored by Tang illustrate an emphasis on vehicle control models and traffic systems. Selected publications include:

  • "ATAC-Based Car-Following Model for Level 3 Autonomous Driving Considering Driver's Acceptance," 2021, IEEE Transactions on Intelligent Transportation Systems
  • "Car-Following Model Based on Deep Learning and Markov Theory," 2020, Journal of Transportation Engineering Part A Systems

Other notable works from close collaborators or within the same research field encompass topics related to eco-driving and electric vehicle control:

  • "Eco-driving control for connected and automated electric vehicles at signalized intersections with wireless charging," 2020, Applied Energy
  • "An eco-driving strategy for electric vehicle based on the powertrain," 2021, Applied Energy
  • "Battery electricity bus charging schedule considering bus journey's energy consumption estimation," 2022, Transportation Research Part D Transport and Environment

Tang frequently collaborates with several researchers, including:

  • Jian Zhang
  • Tao Wang
  • Chuan-Zhi Xie
  • Liang Chen
  • Botao Zhang

The majority of Tang's publications have appeared in venues such as:

  • SSRN Electronic Journal
  • Journal of Advanced Transportation
  • Journal of Transportation Engineering Part A Systems
  • Simulation Modelling Practice and Theory
  • Journal of Transportation Safety & Security

The research output primarily consists of engineering-focused studies that aim to address issues related to vehicle automation, traffic safety, and energy-efficient transportation technologies.

Best Publications

  • An Optimal Charging Station Location Model With the Consideration of Electric Vehicle's Driving Range

    Jia He;Hai Yang;Tie-Qiao Tang;Hai-Jun Huang

  • A new car-following model with consideration of inter-vehicle communication

    Tieqiao Tang;Weifang Shi;Huayan Shang;Yunpeng Wang

  • Influences of the driver’s bounded rationality on micro driving behavior, fuel consumption and emissions

    Tie-Qiao Tang;Hai-Jun Huang;Hua-Yan Shang

  • A new car-following model accounting for varying road condition

    Tieqiao Tang;Yunpeng Wang;Xiaobao Yang;Yonghong Wu

  • A new car-following model with the consideration of the driver's forecast effect

    T.Q. Tang;C.Y. Li;H.J. Huang

  • Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice

    Chuan Ding;Yunpeng Wang;Tieqiao Tang;Sabyasachee Mishra

  • An extended macro traffic flow model accounting for the driver’s bounded rationality and numerical tests

    Tie-Qiao Tang;Hai-Jun Huang;Hua-Yan Shang

  • An extended two-lane car-following model accounting for inter-vehicle communication

    Hui Ou;Tie-Qiao Tang

  • A speed guidance model accounting for the driver's bounded rationality at a signalized intersection

    Tie-Qiao Tang;Jian Zhang;Kai Liu

  • A car-following model accounting for the driver’s attribution

    Tie-Qiao Tang;Jia He;Shi-Chun Yang;Hua-Yan Shang

  • An extended car-following model with consideration of the reliability of inter-vehicle communication

    Tie-Qiao Tang;Wei-Fang Shi;Hua-Yan Shang;Yun-Peng Wang

  • A new dynamic model for heterogeneous traffic flow

    T.Q. Tang;H.J. Huang;S.G. Zhao;H.Y. Shang

  • Stability of the car-following model on two lanes.

    Tie-Qiao Tang;Hai-Jun Huang;Zi-You Gao

  • A car-following model with real-time road conditions and numerical tests

    T.Q. Tang;J.G. Li;H.J. Huang;X.B. Yang

  • A new macro model with consideration of the traffic interruption probability

    T.Q. Tang;H.J. Huang;G. Xu

  • A new car-following model with consideration of roadside memorial

    T. Tang;T. Tang;Yong Hong Wu;Louis Caccetta;H. Huang

  • An aircraft boarding model accounting for passengers' individual properties

    Tie-Qiao Tang;Tie-Qiao Tang;Yong-Hong Wu;Hai-Jun Huang;Lou Caccetta

  • A new fundamental diagram theory with the individual difference of the driver's perception ability

    Tieqiao Tang;Chuanyao Li;Haijun Huang;Huayan Shang

  • A speed guidance strategy for multiple signalized intersections based on car-following model

    Tie-Qiao Tang;Zhi-Yan Yi;Jian Zhang;Tao Wang

  • A new macro model for traffic flow with the consideration of the driver's forecast effect

    T.Q. Tang;H.J. Huang;H.Y. Shang

  • An evacuation model accounting for elementary students’ individual properties

    Tie-Qiao Tang;Liang Chen;Ren-Yong Guo;Hua-Yan Shang

  • Impact of the honk effect on the stability of traffic flow

    T.Q. Tang;T.Q. Tang;C.Y. Li;Y.H. Wu;H.J. Huang

  • Modeling electric bicycle’s lane-changing and retrograde behaviors

    Tie-Qiao Tang;Xiao-Feng Luo;Jian Zhang;Liang Chen

Frequent Co-Authors

Hai-Jun Huang
Hai-Jun Huang Beihang University
Yonghong Wu
Yonghong Wu Curtin University
Sze Chun Wong
Sze Chun Wong University of Hong Kong
Hai Yang
Hai Yang Hong Kong University of Science and Technology
Xiaobo Qu
Xiaobo Qu Xiamen University
H.M. Zhang
H.M. Zhang University of California, Davis

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Related Online Degrees & Career Pathways

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Considering the easiest counseling degree options may appeal to engineers who want to supplement their technical background with soft skills without committing to longer programs. Online degrees can provide flexible learning schedules, allowing professionals to upskill while working.

For those considering advanced certifications, enrolling in a BCBA accelerated program in applied behavior analysis could open doors in specialized engineering fields such as robotics or AI-driven systems, where behavioral insights can enhance design and user interaction.

Finally, understanding the requirements for graduate studies, as outlined in the SLP grad school section, offers valuable insights for engineers aiming to pivot toward speech-language pathology or interdisciplinary research involving communication technologies. Knowing acceptance rates and prerequisites can help plan a smoother transition.

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