Minnerva has supported SDG
in modelling public transport for schemes to introduce rapid transit
type systems into the cities of Leeds and Dublin.
The work for Dublin required particular attention
to making the best of the available data that came from varied sources
and which, inevitably, displayed various inconsistencies and limitations.
Much of the work was
concerned with estimating trip matrices through combining information
from bus surveys, bus electronic-ticketing machine data, and from
rail-based PT matrices.
The project was also concerned
to produce a combined public transport matrix, rather than the separate
bus and rail matrices that had been used hitherto, but in order
to model the interaction between the modes it was necessary to analyse
and enhance aspects of the public transport network modelling.
An important requirement
of the public transport demand modelling was to segment the demand
on the basis of valuations of time by travellers. This was because
Stated Preference surveys had shown some travellers had unusually
low valuations of time. Once the demand had been segmented, it was
necessary to adapt the modelling to cater for multi-class public
The work included using TRIPS-based matrix estimation
methods to integrate the data sources, as well as developing GIS-based
functionality to segment trip matrices according to different valuations
of time associated with different population characteristics.