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Forecast schedule recovery #22

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mileserickson opened this issue Jul 30, 2019 · 2 comments
Open

Forecast schedule recovery #22

mileserickson opened this issue Jul 30, 2019 · 2 comments
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enhancement New feature or request

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@mileserickson
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F08D7C73-1309-41EC-AC9C-115DBCBA2E42

Mukilteo-Clinton ferries typically stay on time in the AM (uni-directional peak volumes eastbound) but get progressively later throughout the afternoon (bi-directional peak volumes). They then gradually return to on-time operation in the late evening. Currently late ferries are predicted to stay late all night.

@anstosa
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anstosa commented Jul 30, 2019

Yeah the delay number could be more sophisticated. Here's my proposal for a first step for building a predictive model here:

  • Create the model on a nightly basis by pulling all sailing for a given weekly slot for the last 1-2 months (e.g. Saturday at 10:30am or Sunday at 9:30pm)
  • Calculate the average delta in departure delays between the previous slot and the current one (e.g. +11mins or -4mins)
  • Forecast delays by adding the current actual delay for the vessel to average delay delta for that weekly sailing slot

@anstosa anstosa added the enhancement New feature or request label Jul 30, 2019
@mileserickson
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I'd add: a first principles approach might be based on something like:
(1) It takes crossing_time to load pedestrians, untie, cross, and dock, and unload pedestrians.
(2) Before we can leave on our next trip, we need to unload n_unload cars at a rate of unload_rate per minute.
(3) We also need to load min(capacity, n_waiting) cars at a rate of load_rate per minute.

So the forecast additional delay and/or schedule recovery rate can be directly tied to the forecast vehicle loads.

@anstosa anstosa added this to Board Jul 28, 2024
@anstosa anstosa moved this to Backlog in Board Jul 28, 2024
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