Mr Tanapon Lilasathapornkit

Mr Tanapon Lilasathapornkit

Research Associate
  • PhD in Civil & Environmental Engineering (Transportation), UNSW, Australia (2018-2022)
  • BS in Civil & Environmental Engineering (Transportation), UNSW, Australia (2014-2016)
  • BS in Civil & Environmental Engineering, Thammasat University, Thailand (2011-2016)
Engineering
Civil and Environmental Engineering

Dr. Lilasathapornkit is a Postdoctoral Research Associate in the School of Civil and Environmental Engineering at University of New South Wales (UNSW), Sydney, Australia. He holds Bachelor and PhD degrees in Civil Engineering from UNSW. His research focuses on exploring network-wide pedestrian bidirectional dynamics, developing frameworks for static and dynamic pedestrian network traffic assignment models, and estimating an empirical pedestrian route choice model using revealed preference data. The static model, user equilibrium traffic assignment problem (UE-pTAP), enables transport engineers and urban planners to understand the network-wide impact of pedestrians in the urban context for long-term strategic planning applications. The dynamic model, dynamic pedestrian network traffic assignment (DPTA), enables transport engineers to simulate planned interruptions, such as signal control. The DPTA can also replicate unplanned disruptions, for example, capacity reduction due to incidents with essential pedestrian dynamic properties and the propagation of shockwaves on a large scale. 

Location
Room 111, School of Civil & Environmental Engineering (H20) Kensington Campus
  • Journal articles | 2022
    Lilasathapornkit T; Rey D; Liu W; Saberi M, 2022, 'Traffic assignment problem for footpath networks with bidirectional links', Transportation Research Part C: Emerging Technologies, 144, http://dx.doi.org/10.1016/j.trc.2022.103905
    Journal articles | 2022
    Lilasathapornkit T; Saberi M, 2022, 'Dynamic pedestrian traffic assignment with link transmission model for bidirectional sidewalk networks', Transportation Research Part C: Emerging Technologies, 145, http://dx.doi.org/10.1016/j.trc.2022.103930
    Journal articles | 2021
    Nourmohammadi Z; Lilasathapornkit T; Ashfaq M; Gu Z; Saberi M, 2021, 'Mapping urban environmental performance with emerging data sources: A case of urban greenery and traffic noise in Sydney, Australia', Sustainability (Switzerland), 13, pp. 1 - 16, http://dx.doi.org/10.3390/su13020605
  • Conference Presentations | 2023
    Lilasathapornkit T; Saberi M; Lilasathapornkit T, 2023, 'Mapping sidewalks and Street furniture with artificial intelligence and computer vision', presented at State of the Map US 2023, Richmond, Virginia, USA, 08 July 2023 - 11 July 2023, https://2023.stateofthemap.us/schedule/
    Conference Presentations | 2023
    Lilasathapornkit T; Saberi M, 2023, 'Estimating walking and cycling volumes across NSW Six Cities Region using crowdsourced datasets', presented at Australian Walking and Cycling Conference, Unley, South Australia, 19 October 2023 - 20 October 2023, https://www.walkingandcycling.com.au/
    Conference Presentations | 2023
    Lilasathapornkit T; Saberi M, 2023, 'Mapping for Mitigation: Assessing Heat-Related Illness Risks at Bus Stops in Cranebrook, NSW', presented at State of the Map Asia 2023, Bangkok, Thailand, 16 November 2023 - 18 November 2023, https://2023.foss4g.in.th/
    Preprints | 2020
    Lilasathapornkit T; Rey D; Liu W; Saberi M, 2020, Traffic Assignment Problem for Footpath Networks with Bidirectional Links, , http://dx.doi.org/10.48550/arxiv.2012.03389

SIDRA SOLUTIONS Postgraduate Award 2022

He contributes to two Australian Research Council (ARC) Discovery Projects under the supervision of Assoc. Prof. Meead Saberi. He developed new macroscopic and network-wide transport modelling and optimisation methodologies for large-scale footpath network planning applications under a project called "Rethinking walking infrastructure: AI-assisted footpath network modeling". He also developed a cycling route choice model under a project called "Sustainable mobility: city-wide exposure modeling to advance bicycling".