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Auto-computing intercity ridership demand - an attempt

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Hey there,

I am looking for a way to automatically compute ridership numbers for my country's intercity railway services. I did a first attempt at an excel sheet, which spits out numbers of travellers between one of 34 agglomerations in Kojo. The next step would be to allocate those numbers on route segments to visualise accurate cross sections of passenger flows on the system, but I'm not sure I know how to get their from a technical stand point. Advise is very welcome.

Here's the link, and there's a preview down below.

I just want to put these 5 notes here for everyone to read who wants to have a look at this or might fool around with it themselves:

1) "Spawn" and "destination" does not imply a trip from spawn A to destination B. Rather, cell J7 for example says: There are 1934 trips taking place per day between Kwaengdō and the Finkyáse agglomeration, where the trip maker is living in Kwaengdō and temporarily staying in Finkyáse. Combine that with the 1479 trips where a Finkyásenian is visiting their grandmother in Kwaengdō, and you get a total of 3143 trips per day between the two cities, or roughly 1570 per direction.

2) A number of riders "gets lost" in the formulars, as the attraction shares never add up to exactly 100%. For example journeys from Pyingshum to Pyingshum are obviously not taken into account; that means the number of trips per person and year should be set slightly higher than the actual value.

3) While the attraction share can kinda compensate for this, one should keep in mind that in the real world for example a young student city will spawn much more trips per inhabitant than let's say a former industrial town with much poverty. This model assumes every city spawns the same amount of trips per inhabitant, and just their destinations are determined by the attractiveness of their destination city.

4) Neither the distance, nor the ease of travelling (by train) between two cities is taken into account. I feel like partly this cancels out with other effects, for example really close cities might have a higher travel demand to each other, but on the other side regional trains might become a more attractive alternative on those relations. But obviously the 27+45 travellers between Shangmē/Chin-Jōrin and Oreppyo would much rather take the bus for a quick 1 1/2 hour trip than taking a 150 km detour via Pyingshum.

5) This excel sheet is ignoring the (quite significant) cross-border traffic, for example to Ataraxie-Ville.

Preview

Thank you for your interest, and hopefully your feedback! Cheers,

Leo


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