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. 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. 2018, Vol. 88, pp. 91-106. DOI: 10.1016/j.trc.2018.01.002
  2. Nassir, N.; Hickman, M.; Ma, Z-L. 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
  3. 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.
  4. Hassan, M.; Rashidi, T.; Nassir, N. Developing a Fuzzy Logic Based Sampling Protocol for Transit Route Choice Modeling. . Omnipress. 2018.
  5. Miller, E.; Sánchez Martínez, G.; Nassir, N. Estimation of Passengers Left Behind by Trains in High-Frequency Transit Service Operating Near Capacity. Transportation Research Record. SAGE Publications. 2018. DOI: 10.1177/0361198118794291
  6. Wen, J.; Chen, L.; Nassir, N.; Zhao, J. Transit-oriented autonomous vehicle operation with integrated demand-supply interaction. Transportation Research Part C: Emerging Technologies. Elsevier. 2018, Vol. 97, pp. 216-234. DOI: 10.1016/j.trc.2018.10.018
  7. Sharma, B.; Hickman, M.; Nassir, N. Park-and-ride lot choice model using random utility maximization and random regret minimization. Transportation. SpringerLink. 2017. DOI: 10.1007/s11116-017-9804-0
  8. Nassir, N.; Hickman, M. Recent Advances in Frequency-based Path Choice Modeling with Smart Card Data. . 3rd Transit Data Conference. 2017.
  9. 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. 2017, Vol. 2652, pp. 8-18. DOI: 10.3141/2652-02
  10. Sharma, B.; Hickman, M.; Nassir, N. A study on the utilization of Park-and-Ride lots in South East Queensland. . ATRF 2016. 2016.
  11. 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. 2016, Vol. 88, pp. 26-39. DOI: 10.1016/j.tra.2016.03.007
  12. 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.
  13. Hassan, M.; Rashidi, T.; Waller, S.; Nassir, N.; Hickman, M. Modeling Transit Users 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
  14. Sharma, B.; Hickman, M.; Nassir, N. Park-and-ride Lot Choice Model with Corrected Endongeneity. . 14th World Conference on Transport Research, Shanghai, China. 2016.
  15. Nassir, N.; Hickman, M.; Ma, Z-L. Activity detection and transfer identification for public transit fare card data. Transportation. 2015, Vol. 42, Issue 4, pp. 683-705. DOI: 10.1007/s11116-015-9601-6
  16. Nassir, N.; Hickman, M.; Ma, Z. Behavioral Findings from Observed Transit Route Choice Strategies in the Farecard data of Brisbane. . ATRF 2015. 2015.
  17. Nassir, N.; Hickman, M.; Malekzadeh, A.; Irannezhad, E. Modeling Transit Passenger Choices of Access Stop. Transportation Research Record: Journal of the Transportation Research Board. 2015, Vol. 2493, pp. 70-77. DOI: 10.3141/2493-08
  18. 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.
  19. Hassan, M.; Rashidi, T.; Nassir, N. Users Strategic Decisions in Transit Stop Choice Modelling. . IATBR 2015. 2015.
  20. Nassir, N.; Ziebarth, J.; Sall, E.; Zorn, L. Choice Set Generation Algorithm Suitable for Measuring Route Choice Accessibility. Transportation Research Record: Journal of the Transportation Research Board. 2014, Vol. 2430, Issue 1, pp. 170-181. DOI: 10.3141/2430-18

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