Some of the most important tools that transportation planners have at their disposal are transportation models. Whether based on a disaggregate activity-based framework or a more traditional 4-step aggregate approach, all models attempt to make some assumptions and simplification of real world systems in order to formulate mathematical representations of everyday phenomena. In the following notebook, we have adopted the classical 4-step approach to help us quantify and understand the demand in the Local Hartford Metropolitan Area. In line with the scope of this project, only the first 3 steps have been generated. This includes Trip Generation, Trip Distribution, and Mode Choice. The final step, Traffic Assignment, was left aside for future work.
amitrm/Travel-Demand-Model-in-Python
Travel demand model developed completely in Python by students at the University of Connecticut
Jupyter Notebook