World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
70
Citations
18475
World Ranking
1040
National Ranking
352

Matthew Barth 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 Matthew Barth 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: 373 publications — 86th percentile

86% of scientists in this discipline score the same or lower.

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

Matthew Barth 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 Matthew Barth 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: 70 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2014 - IEEE Fellow For pioneering research in intelligent transportation systems

Overview

Matthew Barth is affiliated with the University of California, Riverside in the United States. Their research work is primarily situated within the field of engineering, with significant contributions to subfields including automotive engineering, control and systems engineering, electrical and electronic engineering, transportation, and computer vision and pattern recognition.

The scientist's recent publications focus on topics related to intelligent transportation systems, autonomous vehicles, and traffic management. Notable recent papers include:

  • Hybrid Reinforcement Learning-Based Eco-Driving Strategy for Connected and Automated Vehicles at Signalized Intersections (2022), published in IEEE Transactions on Intelligent Transportation Systems
  • Cooperative Ramp Merging Design and Field Implementation: A Digital Twin Approach Based on Vehicle-to-Cloud Communication (2021), published in IEEE Transactions on Intelligent Transportation Systems
  • Driver Behavior Modeling Using Game Engine and Real Vehicle: A Learning-Based Approach (2020), published in IEEE Transactions on Intelligent Vehicles
  • Game Theory-Based Ramp Merging for Mixed Traffic With Unity-SUMO Co-Simulation (2021), published in IEEE Transactions on Systems Man and Cybernetics Systems
  • Infrastructure-Based Object Detection and Tracking for Cooperative Driving Automation: A Survey (2022), presented at the 2022 IEEE Intelligent Vehicles Symposium (IV)

The main topics covered by Matthew Barth in their research include:

  • Traffic control and management
  • Autonomous vehicle technology and safety
  • Vehicle emissions and performance
  • Transportation planning and optimization
  • Vehicular Ad Hoc Networks (VANETs)
  • Electric vehicles and infrastructure
  • Traffic prediction and management techniques

Frequent co-authors with whom they have collaborated include Cristina Olaverri-Monreal, Guoyuan Wu, Christoph Mecklenbraeuker, Nikos Papanikolopoulos, and Javier Barria.

The venues where Matthew Barth publishes most frequently reflect their focus on intelligent transportation and vehicular technologies:

  • IEEE Transactions on Intelligent Transportation Systems
  • arXiv (Cornell University)
  • IEEE Intelligent Transportation Systems Magazine
  • Transportation Research Record Journal of the Transportation Research Board
  • IEEE Transactions on Intelligent Vehicles

Their contributions have been recognized by professional organizations, including being named an IEEE Fellow in 2014 for pioneering research in intelligent transportation systems.

Best Publications

  • The global positioning system and inertial navigation

    Jay Farrell;Matthew Barth

  • Real-World Carbon Dioxide Impacts of Traffic Congestion

    Matthew Barth;Kanok Boriboonsomsin

  • Energy and emissions impacts of a freeway-based dynamic eco-driving system

    Matthew J Barth;Kanok Boriboonsomsin

  • Eco-Routing Navigation System Based on Multisource Historical and Real-Time Traffic Information

    K. Boriboonsomsin;M. J. Barth;Weihua Zhu;A. Vu

  • Simulation model performance analysis of a multiple station shared vehicle system

    Matthew Barth;Michael Todd

  • Development of a Heavy-Duty Diesel Modal Emissions and Fuel Consumption Model

    Matthew Barth;Theodore Younglove;George Scora

  • A Survey on Cooperative Longitudinal Motion Control of Multiple Connected and Automated Vehicles

    Ziran Wang;Yougang Bian;Steven E. Shladover;Guoyuan Wu

  • Modal Emissions Modeling: A Physical Approach

    Matthew Barth;Feng An;Joseph Norbeck;Marc Ross

  • Battery state-of-charge estimation

    Shuo Pang;J. Farrell;Jie Du;M. Barth

  • Lane Change and Merge Maneuvers for Connected and Automated Vehicles: A Survey

    David Bevly;Xiaolong Cao;Mikhail Gordon;Guchan Ozbilgin

  • Impacts of Road Grade on Fuel Consumption and Carbon Dioxide Emissions Evidenced by Use of Advanced Navigation Systems

    Kanok Boriboonsomsin;Matthew Barth

  • Development and Application of an International Vehicle Emissions Model

    Nicole Davis;James Lents;Mauricio Osses;Nick Nikkila

  • Arterial velocity planning based on traffic signal information under light traffic conditions

    Sindhura Mandava;Kanok Boriboonsomsin;Matthew Barth

  • Shared-use vehicle systems: Framework for classifying carsharing, station cars, and combined approaches

    Matthew Barth;Susan A. Shaheen

  • Dynamic ECO-driving for arterial corridors

    Matthew Barth;Sindhura Mandava;Kanok Boriboonsomsin;Haitao Xia

  • Real-time differential carrier phase GPS-aided INS

    J.A. Farrell;T.D. Givargis;M.J. Barth

  • DEVELOPMENT OF COMPREHENSIVE MODAL EMISSIONS MODEL: OPERATING UNDER HOT-STABILIZED CONDITIONS

    Feng An;Matthew Barth;Joseph Norbeck;Marc Ross

  • Reinforcement Learning for Hybrid and Plug-In Hybrid Electric Vehicle Energy Management: Recent Advances and Prospects

    Xiasong Hu;Teng Liu;Xuewei Qi;Matthew Barth

  • Deep reinforcement learning enabled self-learning control for energy efficient driving

    Xuewei Qi;Yadan Luo;Guoyuan Wu;Kanok Boriboonsomsin

  • Real-Time Computer Vision/DGPS-Aided Inertial Navigation System for Lane-Level Vehicle Navigation

    Anh Vu;A. Ramanandan;Anning Chen;J. A. Farrell

  • Traffic Congestion and Greenhouse Gases

    Matthew Barth;Kanok Boriboonsomsin

  • Development of a Comprehensive Modal Emissions Model

    Matthew J Barth;Feng An;Theodore Younglove;George Scora

Frequent Co-Authors

Kanok Boriboonsomsin
Kanok Boriboonsomsin University of California, Riverside
Jay A. Farrell
Jay A. Farrell University of California, Riverside
Michael D. Todd
Michael D. Todd University of California, San Diego
Susan Shaheen
Susan Shaheen University of California, Berkeley
Huan Liu
Huan Liu Tsinghua University
Yi Zhang
Yi Zhang Nanyang Technological University
Robert Cervero
Robert Cervero University of California, Berkeley
Thomas D. Durbin
Thomas D. Durbin University of California, Riverside
Evelyn Blumenberg
Evelyn Blumenberg University of California, Los Angeles
Martin Wachs
Martin Wachs University of California, Los Angeles

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