16 Jun Student | Wenhua Jiang | Design, Modelling and Simulation
Monash University (Supervisor: Inhi Kim)
PhD topic – Short-term rail passenger flow forecasting application
Short-term rail passenger flow forecasting plays a vital role in the intelligent transportation system with the aim of enhancing real-time system management. With a predictive capability, transport systems can provide services in a proactive manner instead of a reactive manner, which is beneficial to increase the operational efficiency and capacity of the transportation system.
The overview of this research is to conduct short-term passenger demand prediction and crowd management at a metro system. The objectives of this study include developing a comprehensive methodology to handle rail transit missing data problem, establishing reliable models to predict station-based passenger arrivals and OD flows at the network-level, and exploring optimized strategies for implementation of train operational strategies and passenger flow control strategies.
Expected completion date
- Active member to organize ITE-ANZ Student Leadership Summit in September 2018.
- Poster presenter at 98th Annual Meeting of the Transportation Research Board (Washington, D.C, 2019) for proposing imputation algorithm for rail transit missing data.
- Recipient of Monash Graduate Research International Travel Award (Sep 2019 – Feb 2020) for visiting MIT-NEU transit lab, USA.
Wenhua, J., Nan, Z., Paul, R., Inhi, K. Imputation of missing transfer passenger flow with self-measuring multi-task gaussian process. 98th Annual Meeting of the Transportation Research Board, Washington, D.C., January, 2019.
Wenhua, J., Zhenliang, M., Inhi, K., Seonha, L. Revealing Mobility Regularities in Urban Rail Systems. 11th International Conference on Ambient Systems, Networks and Technologies, Warsaw, Poland, April 2020.