Professor Majid Sarvi

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

Research interests

  • Transportation Engineering


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. Bagloee SA, 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
  2. 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
  3. 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
  4. 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
  5. 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. Transportation Research Part C: Emerging Technologies. Pergamon-Elsevier Science. 2017. DOI: 10.1016/j.trc.2017.08.012
  6. 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
  7. 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
  8. 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
  9. Asadi Bagloee S, Sarvi M. A modern congestion pricing policy for urban traffic: subsidy plus toll. JOURNAL OF MODERN TRANSPORTATION. Dr Dietrich Steinkopff Verlag. 2017, Vol. 25, Issue 3. DOI: 10.1007/s40534-017-0128-8
  10. Long TT, Currie G, Sarvi M. Analytical and simulation approaches to understand combined effects of transit signal priority and road-space priority measures. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. Pergamon-Elsevier Science. 2017, Vol. 74. DOI: 10.1016/j.trc.2016.11.020
  11. Shahhoseini Z, Sarvi M. Collective movements of pedestrians: How we can learn from simple experiments with non-human (ant) crowds. PLOS ONE. Public Library of Science. 2017, Vol. 12, Issue 8. DOI: 10.1371/journal.pone.0182913
  12. Haghani M, Sarvi M. Following the crowd or avoiding it? Empirical investigation of imitative behaviour in emergency escape of human crowds. ANIMAL BEHAVIOUR. Academic Press. 2017, Vol. 124. DOI: 10.1016/j.anbehav.2016.11.024
  13. Haghani M, Sarvi M. How perception of peer behaviour influences escape decision making: The role of individual differences. JOURNAL OF ENVIRONMENTAL PSYCHOLOGY. Academic Press. 2017, Vol. 51. DOI: 10.1016/j.jenvp.2017.03.013
  14. Asadi Bagloee S, Sarvi M, Thompson R, Rajabifard A. Identifying Achilles-heel roads in real-sized networks. JOURNAL OF MODERN TRANSPORTATION. Dr Dietrich Steinkopff Verlag. 2017, Vol. 25, Issue 1. DOI: 10.1007/s40534-016-0121-7
  15. Asadi Bagloee S, Sarvi M, Wolshon B, Dixit V. Identifying critical disruption scenarios and a global robustness index tailored to real life road networks. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW. Pergamon-Elsevier Science. 2017, Vol. 98. DOI: 10.1016/j.tre.2016.12.003

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