# Jittering: a flexible approach for converting OD data into geographic desire lines, routes and route networks for transport planning Intro: At the first step authors are invited to submit abstracts written in English comprising between 800 and 1000 words and containing sufficient details for evaluation (including the approach, results, concepts, reasons why it should be considered and why it would be interesting for the audience). Details: https://2022.foss4g.org/cfp-academic_track.php
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Robin
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Chaco pancake day

Tuesday 13th Feb from 6pm

2/9/2024
Modelling world ideas

Open source vs open access

10/31/2023
Untitled

Update on this: Dustin and I had a brief conversation about this today and we made some progress on thinking through the options laid out below and prioritisation. It would be really helpful to get your thoughts on this Ciro and Fred but essentially it seems that #3, simulating dense pedestrian movements, with a focus on Sao Miguel Paulista, may represent most boom for buck of Dustin's valuable time on this. This could include: Counting 'overcrowded pavement' events as outlined by Dustin below, a reduction in these events resulting from changed infrastructure would be a big win. This is well captured in this issue: https://github.com/a-b-street/abstreet/issues/859 Reducing the speed of pedestrians on bad (either narrow, crowded or other) sidewalks, e.g. by making them stop when forced to overlap as shown in Dustin's overcrowding.mp4 video Making people wait longer to cross on busier/wider roads as per https://github.com/a-b-street/abstreet/issues/517 I think the focus on pedestrians on the A/B Street makes sense, it's 'USPs' are its ability to represent scenarios of infrastructure change and communicate what it's like using different modes (primarily active/transit friendly being the focus here) in specific places.

4/21/2022
Geocompy ideas

Set-up Quarto does not recognise cells within D 1 Intro 2 Geographic data in R 3 Attribute data operations

3/2/2022
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