Difference between revisions of "4.5 Auxiliary Demand"

Revision as of 05:28, 13 March 2023

Freight

As described earlier, JAX port freight trips are generated by a Python script (interpolate_port_truck_tt.py) that interpolates the JAXPORT demand for 2012 and 2040 to the analysis year between 2010 and 2040 (or beyond) based on the implied growth. The Python script makes use of Visum's Python API to import the JAXPORT trip table into Visum version file.

Non-HH

These trip tables are created by the tgen_main.py Python script using Visum's Python API to access all inputs and import the production (P) and attraction (A) vectors into the version file. These Ps and As are distributed using Trip Distribution procedures in Visum to generate Non-HH trip tables that are combined with DaySim trip tables for assignment.

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 <h3>Freight</h3>
-As described earlier, JAX port freight trips are generated by extracting a sub-area from the statewide model. The application “Develop Freight Truck Trip Tables from SWM” outputs a trip table to {SCENARIO_DIR}\output\PORT_TRK_24H_{Year}.MAT.
+As described earlier, JAX port freight trips are generated by a Python script (''interpolate_port_truck_tt.py'') that interpolates the JAXPORT demand for 2012 and 2040 to the analysis year between 2010 and 2040 (or beyond) based on the implied growth. The Python script makes use of Visum's Python API to import the JAXPORT trip table into Visum version file.
 <h3>Non-HH</h3>
-These trip tables are created by the “Generation” and “Distribution” applications of the model and finally out a trip table to {SCENARIO_DIR}\output\VTRIP1.MAT.
+These trip tables are created by the ''tgen_main.py'' Python script using Visum's Python API to access all inputs and import the production (P) and attraction (A) vectors into the version file. These Ps and As are distributed using Trip Distribution procedures in Visum to generate Non-HH trip tables that are combined with DaySim trip tables for assignment.