Professor Majid Sarvi

  • Room: Level: 02 Room: B205
  • Building: Engineering Block B
  • Campus: Parkville

Research interests

  • Transportation Engineering

Biography

Majid Sarvi is the chair in Transport Engineering and the professor in Transport for Smart Cities at the University of Melbourne. He is the founder and the director of the AIMES (Australian Integrated Multimodal EcoSystem). AIMES is the world’s first urban testing ecosystem for implementing and testing of emerging connected transport technologies at large scale and in complex urban environment which involves 37 partners from government and leading Australian and global industry partners.

He has over 22 years of professional, academic and research experience in the areas of traffic and transport engineering. His researches are multidisciplinary with international outlook and both theoretically oriented and applied in nature. His fields of research cover a range of topics, including: connected multimodal transport network modelling and analysis, crowd dynamic modelling and simulation and network vulnerability assessment and optimization. He has been the author/co-author of over 250 refereed publications in top transportation journals and various conference and symposia proceedings. This includes over 140 ISI publications listed in Scopus and 7 papers in the International symposium of Traffic and Transportation Theory (ISTTT). He currently serves on the editorial board of several journals including Transportation Research Part C, Transportmetrica, and Journal of Transportation Letters.

He has served on several international research committees, the Network Modelling Committee (ADB30), Traffic Flow Theory and Characteristics Committee (AHB45), and the Emergency Evacuation Task Force of the Transportation Research Board (TRB) of the U.S. National Research Council. He is also the co-founder and co-chair of the Crowd Dynamic Modelling Subcommittee AHB45(2) of TRB.

Recent publications

  1. Haghani M, Sarvi M. Simulating pedestrian flow through narrow exits. Physics Letters, Section A: General, Atomic and Solid State Physics. Elsevier Science. 2019, Vol. 383, Issue 2-3. DOI: 10.1016/j.physleta.2018.10.029
  2. Gu Z, Saberi M, Sarvi M, Liu Z. A big data approach for clustering and calibration of link fundamental diagrams for large-scale network simulation applications. 22nd International Symposium on Transportation and Traffic Theory (ISTTT). Pergamon-Elsevier Science. 2018, Vol. 94. DOI: 10.1016/j.trc.2017.08.012
  3. Asadi Bagloee S, Asadi M, Sarvi M, Patriksson M. A hybrid machine-learning and optimization method to solve bi-level problems. EXPERT SYSTEMS WITH APPLICATIONS. Pergamon. 2018, Vol. 95. DOI: 10.1016/j.eswa.2017.11.039
  4. Kaviani Arani A, Thompson R, Rajabifard A, Sarvi M. A model for multi-class road network recovery scheduling of regional road networks. Transportation. Springer. 2018. DOI: 10.1007/s11116-017-9852-5
  5. Asadi Bagloee S, Sarvi M. An outer approximation method for the road network design problem. PLOS ONE. Public Library of Science. 2018, Vol. 13, Issue 3. DOI: 10.1371/journal.pone.0192454
  6. Haghani M, Sarvi M. Crowd behaviour and motion: Empirical methods. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL. Pergamon-Elsevier Science. 2018, Vol. 107. DOI: 10.1016/j.trb.2017.06.017
  7. Kaviani Arani A, Thompson R, Rajabifard A, Sarvi M. Hybrid machine learning and optimisation method to solve a tri-level road network protection problem. 25th World Congress on Intelligent Transport Systems (ITS). Institution of Engineering and Technology. 2018, Vol. 12, Issue 9. DOI: 10.1049/iet-its.2018.5168
  8. Haghani M, Sarvi M. Hypothetical bias and decision-rule effect in modelling discrete directional choices. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE. Pergamon. 2018, Vol. 116. DOI: 10.1016/j.tra.2018.06.012
  9. Hoogendoorn SP, Daamen W, Knoop VL, Steenbakkers J, Sarvi M. Macroscopic Fundamental Diagram for pedestrian networks: Theory and applications. Transportation Research Part C: Emerging Technologies. Pergamon-Elsevier Science. 2018, Vol. 94. DOI: 10.1016/j.trc.2017.09.003
  10. Asadi Bagloee S, Sarvi M, Patriksson M, Asadi M. Optimization for Roads' Construction: Selection, Prioritization, and Scheduling. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING. Blackwell. 2018, Vol. 33, Issue 10. DOI: 10.1111/mice.12370
  11. Shahhoseini Z, Sarvi M, Saberi M. Pedestrian crowd dynamics in merging sections: Revisiting the "faster-is-slower" phenomenon. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS. Elsevier BV. 2018, Vol. 491. DOI: 10.1016/j.physa.2017.09.003
  12. Gu Z, Saberi M, Sarvi M, Liu Z. A Big Data Approach for Clustering and Calibration of Link Fundamental Diagrams for Large-Scale Network Simulation Applications. 22nd International Symposium on Transportation and Traffic Theory (ISTTT). Elsevier BV. 2017, Vol. 23. Editors: Mahmassani H, Nie Y, Smilowitz K. DOI: 10.1016/j.trpro.2017.05.050
  13. Ebrahim MP, Sarvi M, Yuce MR. A Doppler Radar System for Sensing Physiological Parameters in Walking and Standing Positions. SENSORS. Molecular Diversity Preservation International. 2017, Vol. 17, Issue 3. DOI: 10.3390/s17030485
  14. Asadi Bagloee S, Sarvi M, Patriksson M. A Hybrid Branch-and-Bound and Benders Decomposition Algorithm for the Network Design Problem. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING. Blackwell. 2017, Vol. 32, Issue 4. DOI: 10.1111/mice.12224
  15. Asadi Bagloee S, Sarvi M, Patriksson M, Rajabifard A. A Mixed User-Equilibrium and System-Optimal Traffic Flow for Connected Vehicles Stated as a Complementarity Problem. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING. Blackwell. 2017, Vol. 32, Issue 7. DOI: 10.1111/mice.12261

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile