travel-modeling
There are 24 repositories under travel-modeling topic.
ActivitySim/activitysim
An Open Platform for Activity-Based Travel Modeling
matsim-org/matsim-code-examples
A repository containing code examples around MATSim
osPlanning/omx
Open Matrix (OMX)
RSGInc/DaySim
DaySim Activity-Based Model
CMAP-REPOS/cmap_abm
CMAP's activity-based model source code
SchweizerischeBundesbahnen/abm-in-visum
ABM-in-Visum: a collaborative project for activity-based transport demand modelling within the PTV Visum software hosted by Swiss Federal Railways (SBB).
kalgishah02/SnapLoc
SnapLoc is a product that does automatic image classification and spatio-temporal analysis in order to recommend the places of interest in a new city. The packages that I have used for creating the product are Python(Pandas, NumPy, Shapely, Keras, Leaflet) and TensorFlow
RSGInc/ActivityViz
ActivityViz - Travel and Activity Data Visualization Dashboard
RSGInc/bca4abm
Benefit Cost Analysis for Travel Demand Models
RSGInc/SOABM
ODOT Southern Oregon ABM
CMAP-REPOS/cmap_freight_model
CMAP’s tour-based and supply chain freight model source code
CMAP-REPOS/mhn_programs
Code for managing CMAP's Master Highway Network geodatabase
CMAP-REPOS/mrn_programs
Code for managing CMAP's Master Rail Network geodatabase
CMAP-REPOS/abm_scenario_creator
Code for modifying transit network policies in CMAP's Activity Based Model and analyzing the results
CMAP-REPOS/cmap_trip-based_model
CMAP's trip-based ("four-step") model source code
MetroModelingServices/metro_mce
Metro Multi-Criteria Evaluation (MCE) Toolkit
CMAP-REPOS/cmap_abm_report
Validation report for CMAP's activity-based model
wsp-sag/client_arc_activitysim
Atlanta Regional Commission (ARC) ActivitySim Implementation
bademiya21/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
Raajroi/TRAVEL_GUIDE_SYSTEM
JAVA WEB APPLICATION
stanvir/language-gisdk
Atom syntax highlighting for GISDK scripts
BayAreaMetro/TAZ_MAZ_Finder
MTC Travel Analysis Zone and Micro Analysis Zone Map Finder
CMAP-REPOS/trip-based-model-validation
Validation report for CMAP's trip-based ("four-step") model
Vaporjawn/Travel-Logger
Fullstack Javascript and JSON web-based travel log