Congratulations to Dr. Hema Rayaprolu for “satisfying the requirements for the award of the degree of Doctor of Philosophy at the University of Sydney.”
Thesis Title: "The Co-evolution of Public Transport Access and Ridership "
Lead Supervisor: Professor David Levinson.
Abstract: Travel demand models take transport networks as input. Investments in transport net- works, on the other hand, are made when benefits from predicted demand outweigh costs. While the correlation between the two is obvious, causality is rarely addressed. Does one lead or lag? How does this relationship change over time? This thesis explores these questions by examining the co-evolution of the historical public transport network and ridership in the Greater Sydney region.
Causal research in transport ignored travel demand, especially that for public trans- port. Studies on the evolution of railway networks are common, however public transport network evolution as a whole has not been attempted. Even more so in the Australian context. This is because detailed historic data on public transport network, service levels, and ridership either have been incomplete or require large amounts of process- ing. Nevertheless, the insights that can be gained from an evolutionary perspective are invaluable. This dissertation leveraged Sydney’s unique archives of public transport net- work and ridership data, and generated a database of network and ridership measures since 1855, when train services commenced in the region. This involved digitising historic bus routes and timetables, generating historic General Transit Feed Specification files, measuring public transport access to population (and jobs where available), and collecting and processing historic station ridership data.
With longitudinal data on two or more variables, causal directions can be examined by testing if lagged information on one variable significantly improves predictions of the other. This approach, posited by Granger (1969), is the most popular econometric method of investigating causality. I conducted Granger causality tests on public trans- port ridership and network access and found a mutual feedback between the two in both aggregate and spatially disaggregate analyses.
I further explored interactions among the region’s public transport modes by investigating modal complementarity across a period of 160 years. For this, modal cases were defined with all combinations of train, tram, and bus services and investigated the level of access to population (and jobs where available) provided by the corresponding modes. The interactions were sub-additive. The benefit of transfers between modes was greater for higher time thresholds.
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