Dr Neema Nassir

  • Room: Level: 02 Room: 202A
  • Building: Engineering Block B
  • Campus: Parkville

Research interests

  • Automated vehicles and emerging transport technologies
  • Modelling, simulation, planning and operations of public transport systems
  • Multimodal travel demand models
  • Public transport big data for planning and operations
  • Traffic simulation

Biography

I recently joined University of Melbourne as a Lecturer in Transport Engineering at the Department of Infrastructure Engineering, and a member of the AIMES team in the Melbourne School of Engineering. My research is focused on new methods to simulate, predict, design and manage public transport, shared-mobility, and connected multimodal systems. I am also a Research Affiliate at Urban Mobility Lab of the Massachusetts Institute of Technology (USA). Prior to joining University of Melbourne, I was a senior researcher at Transit Lab and Urban Mobility Lab of MIT, where I closely collaborated with transport authorities in the USA, Europe, Asia and Australia.

Recent publications

  1. Wen, J.; Nassir, N.; Zhao, J. Value of demand information in autonomous mobility-on-demand systems. Transportation Research Part A: Policy and Practice. Elsevier. 2019, Vol. 121, pp. 346-359. DOI: 10.1016/j.tra.2019.01.018
  2. Tajtehranifard, H.; Bhaskar, A.; Nassir, N.; Haque, MM.; Chung, E. A path marginal cost approximation algorithm for system optimal quasi-dynamic traffic assignment. Transportation Research Part C: Emerging Technologies. PERGAMON-ELSEVIER SCIENCE LTD. 2018, Vol. 88, pp. 91-106. DOI: 10.1016/j.trc.2018.01.002
  3. Nassir, N.; Hickman, M.; Ma, ZL. A strategy-based recursive path choice model for public transit smart card data. Transportation Research Part B: Methodological. 2018. DOI: 10.1016/j.trb.2018.01.002
  4. Nassir, N.; Zhao, J.; Attanucci, J.; Salvucci, F.; Wilson, N. Bayesian Inference of Passenger Boarding Strategies at Express Stops with Real-Time Bus Arrival Information. . Omnipress. 2018.
  5. Hassan, M.; Rashidi, T.; Nassir, N. Developing a Fuzzy Logic Based Sampling Protocol for Transit Route Choice Modeling. . Omnipress. 2018.
  6. Miller, E.; Sánchez-martínez, GE.; Nassir, N. Estimation of Passengers Left Behind by Trains in High-Frequency Transit Service Operating Near Capacity. Transportation Research Record: Journal of the Transportation Research Board. SAGE Publications. 2018, pp. 036119811879429-036119811879429. DOI: 10.1177/0361198118794291
  7. Wen, J.; Chen, YX.; Nassir, N.; Zhao, J. Transit-oriented autonomous vehicle operation with integrated demand-supply interaction. Transportation Research Part C: Emerging Technologies. PERGAMON-ELSEVIER SCIENCE LTD. 2018, Vol. 97, pp. 216-234. DOI: 10.1016/j.trc.2018.10.018
  8. Sharma, B.; Hickman, M.; Nassir, N. Park-and-ride lot choice model using random utility maximization and random regret minimization. Transportation. SpringerLink. 2017, pp. 1-16. DOI: 10.1007/s11116-017-9804-0
  9. Nassir, N.; Hickman, M. Recent Advances in Frequency-based Path Choice Modeling with Smart Card Data. . 3rd Transit Data Conference. 2017.
  10. Nassir, N.; Hickman, M.; Ma, Z. Statistical Inference of Transit Passenger Boarding Strategies from Farecard Data. Transportation Research Record: Journal of the Transportation Research Board. NATL ACAD SCIENCES. 2017, Vol. 2652, Issue 2652, pp. 8-18. DOI: 10.3141/2652-02
  11. Sharma, B.; Hickman, M.; Nassir, N. A study on the utilization of Park-and-Ride lots in South East Queensland. . ATRF 2016. 2016.
  12. Nassir, N.; Hickman, M.; Malekzadeh, A.; Irannezhad, E. A utility-based travel impedance measure for public transit network accessibility. Transportation Research Part A: Policy and Practice. PERGAMON-ELSEVIER SCIENCE LTD. 2016, Vol. 88, pp. 26-39. DOI: 10.1016/j.tra.2016.03.007
  13. Nassir, N.; Hickam, M. Frequency-based path choice models from smart card data. . 2nd International Workshop on Automated Data Collection Systems: Improving Urban Public Transport Planning and Operations. 2016.
  14. Hassan, MN.; Rashidi, TH.; Waller, ST.; Nassir, N.; Hickman, M. Modeling transit user stop choice behavior: Do travelers strategize?. Journal of Public Transportation. 2016, Vol. 19, Issue 3, pp. 98-116. DOI: 10.5038/2375-0901.19.3.6
  15. Sharma, B.; Hickman, M.; Nassir, N. Park-and-ride Lot Choice Model with Corrected Endongeneity. . 14th World Conference on Transport Research, Shanghai, China. 2016.
  16. Nassir, N.; Hickman, M.; Ma, Z-L. Activity detection and transfer identification for public transit fare card data. Transportation. SPRINGER. 2015, Vol. 42, Issue 4, pp. 683-705. DOI: 10.1007/s11116-015-9601-6
  17. Nassir, N.; Hickman, M.; Ma, Z. Behavioral Findings from Observed Transit Route Choice Strategies in the Farecard data of Brisbane. . ATRF 2015. 2015.
  18. Nassir, N.; Hickman, M.; Malekzadeh, A.; Irannezhad, E. Modeling Transit Passenger Choices of Access Stop. Transportation Research Record: Journal of the Transportation Research Board. NATL ACAD SCIENCES. 2015, Vol. 2493, Issue 2493, pp. 70-77. DOI: 10.3141/2493-08
  19. Nassir, N.; Hicman, M. Statistical Inference of Transit Passenger Boarding Strategies from Farecard Data. . Conference on Advanced Systems in Public Transport (CASPT), Rotterdam, The Netherlands.. 2015.
  20. Hassan, M.; Rashidi, T.; Nassir, N. Users Strategic Decisions in Transit Stop Choice Modelling. . IATBR 2015. 2015.

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