Model movement within the city
Bike usage patterns
03.2019 - 12.2019
Wrocław Open Data
ID | uid | bike_number | start_time | end_time | rental_place | return_place |
---|---|---|---|---|---|---|
20074 | 66240980 | 57809 | 2019-03-27 16:32:51 | 2019-03-27 16:33:35 | Traugutta / Pułaskiego | Traugutta / Pułaskiego |
20075 | 66239215 | 57359 | 2019-03-27 16:15:15 | 2019-03-27 16:33:53 | Wyszyńskiego / Szczytnicka | Bardzka / Piękna |
20076 | 66239036 | 57309 | 2019-03-27 16:13:14 | 2019-03-27 16:33:55 | Śrubowa / Strzegomska | Bardzka / Piękna |
20077 | 66239414 | 57850 | 2019-03-27 16:17:12 | 2019-03-27 16:34:05 | Śrubowa / Strzegomska | Kościuszki / Pułaskiego |
20078 | 66241086 | 57708 | 2019-03-27 16:34:09 | 2019-03-27 16:34:19 | Traugutta / Pułaskiego | Traugutta / Pułaskiego |
20079 | 66240196 | 57782 | 2019-03-27 16:24:47 | 2019-03-27 16:34:21 | Szewska / Kazimierza Wielkiego | Komandorska / Sanocka |
$204^2$ total paths Dijkstra Algorithm
Optimization based on travel time between nodes
"There's no such thing as a stupid question!"
Authors: Kemal Erdem, Dominika Kunc, Piotr Mazurek, Norbert Ropiak
https://burnpiro.github.io/wod-bike-dataset-generator/
Acknowledgements:
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