This
thesis develops a method to automate journey fare calculation for Transport for
London. Today, fares for every possible origin-destination station pair within
the London Underground are prepared manually based on the zonal fare structure.
Multiple feasible paths often exist within the network for a given
origin-destination pair, each of which may produce a different journey fare.
Thus, manually adjusting journey fares after any alteration of the network or
fare structure is a time consuming task for staff and restricts Transport for
London's ability to implement changes in fare policy. This approach also lacks
transparency from the passenger's perspective. Automating Transport for
London's fare calculation requires automating the selection of travel paths.
This thesis adapts a label-correcting shortest path algorithm to produce
journey paths and fares based on four different selection rules: minimum fare,
minimum number of transfers, minimum travel time, and minimum distance. The
algorithm operates on a directed graph model of the network. This thesis
develops a method to structure the directed graph to capture the network's
intricacies. Given a network and fare structure, the modified shortest path
algorithm produces all path and fare information for an origin-destination pair
in less than one millisecond. Transport for London can then assess the
implications of a fare policy change by comparing the existing fares with those
generated under each path selection rule. Supplementing these comparisons with historical
data provides an estimate of the number of journeys affected and the possible
impact on fare revenue. This thesis uses a sample dataset to estimate these
impacts.
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