Sai Chand
OBJECTIVES:
1. Data analysis of crowdsourced travel time data from a selected platform, such as TomTom. HERE maps, Google, etc.
2. Co-develop the multi-modal simulation model for calibration and validation.
3. Review and assist in the deliverables, reports, and presentation to the final client (MHI).
DESCRIPTION:
Assessment of urban multi-modal networks (road and rail) networks in terms of determining demand and optimal operations of public transport and train services is critical. In a city, Road and Rail (metro in some cases) networks complement and compete with each other. For example, delayed train service in a tightly operated schedule can have a compounding effect for the rest of the day, with further delays and cancellations leading to unreliability and overcrowding at the stations. Unreliability of services may lead train riders, both captive and choice riders, to seek alternative transport options. Therefore, modelling the multi-modal networks which account for unreliability is critical. Both networks are intertwined, and the project's objective is to study the connection between the two networks to determine the demand, congestion patterns, reliability and patronage of trains and trams, which would then help evaluate different train and tram operational strategies. The city of Sydney, Australia, is selected as the case study.
