origin-destination
There are 1 repository under origin-destination topic.
- Language:R 412
Esri / large-network-analysis-tools
Tools and code samples for solving large network analysis problems in ArcGIS Pro
Language:Python 58tsinghua-fib-lab / OD_benckmark
The benchmark related to the survey: An Interdisciplinary Survey on Origin-destination Flows Modeling: Theory and Techniques
rajesvariparasa / spatial-routing-libraries-and-services
Using OSMnx, OSRM, and Google Maps Directions API with Python to calculate shortest, fastest, and traffic-based most-efficient routes for a set of origin and destination points
Language:Jupyter Notebook 14Geometrein / helsinki-city-bikes
Helsinki City Bike system analysis.
Language:Jupyter Notebook 12Robinlovelace / foss4g22
Paper testing different jittering and routing options for converting OD data to route networks
Language:TeX 6- Language:Python 4
sullivannicole / Freight-O-D
Wrangle StreetLight freight origin-destination analysis
DenisCobeti / Mogen
Vehicle simulator that exports mobility traces written from real-world maps
Language:Java 3- Language:Python 2
alvincyh / Arc-Trajectories-For-R
Compute Arc Trajectories for OD data in R
Language:R 1bademiya21 / Identifying-Commuter-Travel-Patterns-In-Bus-Services
A project I did with Land Transport Authority, a statutory board, whose main role is to manage the transportation infra of Singapore which includes public transport like bus and trains. The agency was interested to understand how the bus services were being utilized by commuters during peak hours and if interventions could be introduced to further enhance commuter experience on bus services e.g. shorter waiting time, faster trips with skipping of bus stops etc. This required understanding archetypes of travel patterns by commuters in bus services. This project is an extension of what was previously done here: https://blog.data.gov.sg/fingerprint-of-a-bus-route-73e5be53dcf0
Language:Jupyter Notebook 1gflowiz / arabesque-doc
Documentation of the Arabesque flow mapping web application
Language:TeX 1soukhova / TTS2016R
A data-package including the 2016 TTS origins, TTS destinations, number of jobs and workers at origin and destination, calculated travel times by car and a developed vignette demonstrating analysis which can be conducted using this package.
Language:TeX 1gitAtila / estimate_od
Estimate origin and destination positions based on smartcard usage time and transit position.
Language:Python 0- Language:Python 0
YannisZa / stochastic-travel-demand-modelling
Stochastic modelling of urban travel demand
Language:Jupyter Notebook 0
