Efficient Generation of Geographically Accurate Transit Maps
Hannah Bast (1), Patrick Brosi (1), Sabine Storandt (2) ((1), University of Freiburg, (2) JMU W\"urzburg)

TL;DR
LOOM is an automated method for generating geographically accurate transit maps by optimizing line orderings to reduce crossings and separations, leveraging a custom ILP formulation and structural reductions for efficiency.
Contribution
This work introduces a novel ILP formulation and engineering techniques for efficient, geographically accurate transit map generation from GTFS data.
Findings
Reduced ILP constraints from 229,000 to 4,500
Solution times less than a second for large networks
Maps are suitable for tile-based map services
Abstract
We present LOOM (Line-Ordering Optimized Maps), a fully automatic generator of geographically accurate transit maps. The input to LOOM is data about the lines of a given transit network, namely for each line, the sequence of stations it serves and the geographical course the vehicles of this line take. We parse this data from GTFS, the prevailing standard for public transit data. LOOM proceeds in three stages: (1) construct a so-called line graph, where edges correspond to segments of the network with the same set of lines following the same course; (2) construct an ILP that yields a line ordering for each edge which minimizes the total number of line crossings and line separations; (3) based on the line graph and the ILP solution, draw the map. As a naive ILP formulation is too demanding, we derive a new custom-tailored formulation which requires significantly fewer constraints.…
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