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novalis edited this page Jul 17, 2012 · 2 revisions

Plain time-dependent A*: With limited resources, this can kill off states with less (say) walk but more weight, even though the replacement states will not be able to reach the destination.

Building a version of the transit network plus shortcuts between transit stops. The shortcuts were simply the min cost of all lowest-cost paths for some mode (walk, wheelchair, bike-fast, bike-safe, bike-flat). Then I post-processed paths to find out if they were truly possible with the actual combination of options. This did not work, probably because the branching factor is really high.

Pre-processing hops to find "reverse-avoidable" hops -- those which were not on shortest paths where the origin was past the end of the hop and the destination was before the beginning. If all hops were reverse-avoidable, this would be a big win. But (a) searches found very few reverse-avoidable hops and (b) that was even before I realized that those searches would have to take walking transfers into account, and thus would depend on walking parameters.

Contraction hierarchies: these depend on specific options.

Reach: ditto, although an extremely limited version does seem to help a little bit: pre-processing paths to find out those that are not on any shortest path between two transit stops, and refusing to use them for transfers. (This will also potentially be a bit messed up with the bike triangle, but probably survivable).

SHARC: We haven't actually implemented this because handling scheduling is extremely complex.

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