World's Best Scientists 2026 revealed!
Martin Treiber

Martin Treiber

D-Index & Metrics

Engineering and Technology

D-Index
60
Citations
22292
World Ranking
2124
National Ranking
61

Martin Treiber 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 Martin Treiber 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: 204 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

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

Martin Treiber 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 Martin Treiber 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: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Martin Treiber is affiliated with TU Dresden in Germany and has a research focus primarily within the field of Engineering. Their work spans multiple subfields, including Control and Systems Engineering, Automotive Engineering, Transportation, Building and Construction, and Ocean Engineering.

The scientist has contributed extensively to topics such as Traffic control and management, Transportation Planning and Optimization, Autonomous Vehicle Technology and Safety, Traffic Prediction and Management Techniques, Evacuation and Crowd Dynamics, Traffic and Road Safety, and Vehicle emissions and performance.

Their recent published papers include the following:
"Empirical and experimental study on the growth pattern of traffic oscillations upstream of fixed bottleneck and model test" (2022, Transportation Research Part C Emerging Technologies), "Review of the cellular automata models for reproducing synchronized traffic flow" (2020, Transportmetrica A Transport Science), "Calibrating Wiedemann-99 Model Parameters to Trajectory Data of Mixed Vehicular Traffic" (2021, Transportation Research Record Journal of the Transportation Research Board), "Towards robust car-following based on deep reinforcement learning" (2024, Transportation Research Part C Emerging Technologies), and "Formulation and validation of a car-following model based on deep reinforcement learning" (2021, arXiv (Cornell University)).

The scientist frequently publishes in venues such as arXiv (Cornell University), Transportation Research Part C Emerging Technologies, Physica A Statistical Mechanics and its Applications, SSRN Electronic Journal, and Transportmetrica A Transport Science.

  • Ostap Okhrin
  • Ankit Anil Chaudhari
  • Venkatesan Kanagaraj
  • Junfang Tian
  • Shiteng Zheng

Frequent co-authors include Ostap Okhrin, Ankit Anil Chaudhari, Venkatesan Kanagaraj, Junfang Tian, and Shiteng Zheng.

Best Publications

  • Congested traffic states in empirical observations and microscopic simulations

    Martin Treiber;Ansgar Hennecke;Dirk Helbing

  • Traffic Flow Dynamics

    Martin Treiber;Arne Kesting

  • General Lane-Changing Model MOBIL for Car-Following Models

    Arne Kesting;Martin Treiber;Dirk Helbing

  • Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity

    Arne Kesting;Martin Treiber;Dirk Helbing

  • Adaptive cruise control design for active congestion avoidance

    Arne Kesting;Martin Treiber;Martin Schönhof;Dirk Helbing

  • Delays, inaccuracies and anticipation in microscopic traffic models

    Martin Treiber;Arne Kesting;Dirk Helbing

  • Calibrating Car-Following Models by Using Trajectory Data: Methodological Study

    Arne Kesting;Martin Treiber

  • Traffic Flow Dynamics: Data, Models and Simulation

    Martin Treiber;Arne Kesting;Christian Thiemann

  • Estimating Acceleration and Lane-Changing Dynamics from Next Generation Simulation Trajectory Data

    Christian Thiemann;Martin Treiber;Arne Kesting

  • Derivation, properties, and simulation of a gas-kinetic-based, nonlocal traffic model

    Martin Treiber;Ansgar Hennecke;Dirk Helbing

  • Micro- and macro-simulation of freeway traffic

    D. Helbing;A. Hennecke;V. Shvetsov;M. Treiber

  • Gas-Kinetic-Based Traffic Model Explaining Observed Hysteretic Phase Transition

    Dirk Helbing;Martin Treiber

  • Phase Diagram of Traffic States in the Presence of Inhomogeneities

    Dirk Helbing;Dirk Helbing;Ansgar Hennecke;Martin Treiber

  • Reconstructing the spatio-temporal traffic dynamics from stationary detector data

    Martin Treiber;Dirk Helbing

  • MASTER: macroscopic traffic simulation based on a gas-kinetic, non-local traffic model

    Dirk Helbing;Ansgar Hennecke;Vladimir Shvetsov;Martin Treiber

  • Estimating Acceleration and Lane-Changing Dynamics Based on NGSIM Trajectory Data

    Christian Thiemann;Martin Treiber;Arne Kesting

  • Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts

    Martin Treiber;Arne Kesting;Dirk Helbing

  • Calibrating Car-Following Models using Trajectory Data: Methodological Study

    Arne Kesting;Martin Treiber

  • Memory effects in microscopic traffic models and wide scattering in flow-density data.

    Martin Treiber;Dirk Helbing

  • Understanding widely scattered traffic flows, the capacity drop, and platoons as effects of variance-driven time gaps.

    Martin Treiber;Arne Kesting;Dirk Helbing

  • Reconstructing the spatio-temporal traffic dynamics from stationary detector data; Cooperative Transportation Dynamics

    Martin Treiber;Dirk Helbing

Frequent Co-Authors

Arne Kesting
Arne Kesting TU Dresden
Dirk Helbing
Dirk Helbing ETH Zurich
Rui Jiang
Rui Jiang Beijing Jiaotong University
Hani S. Mahmassani
Hani S. Mahmassani Northwestern University
Serge P. Hoogendoorn
Serge P. Hoogendoorn Delft University of Technology
Meng Wang
Meng Wang TU Dresden
Winnie Daamen
Winnie Daamen Delft University of Technology
Katsuhiro Nishinari
Katsuhiro Nishinari University of Tokyo
Bart van Arem
Bart van Arem Delft University of Technology
Tamás Vicsek
Tamás Vicsek Eötvös Loránd University

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