TDM-INP-Transit-Updates-Comparison

UTA Transit Boardings Comparison

This Python script analyzes and compares daily transit boardings between two Travel Demand Model (TDM) scenarios:

• TDM1: Base Scenario
• TDM2: UTA Proposed Changes

The goal is to evaluate ridership impacts across transit modes, routes, and service districts.

Workflow Summary

1. Initialization

• Import Python and ArcPy libraries
• Set working, data, results, and lookup directories

2. Data Preparation

• Convert TDM .dbf files to .csv using arcpy
• Read and verify shape of datasets

3. Data Processing

• Merge TDM1 and TDM2 datasets by TDM_Name
• Calculate differences in:
  • Total daily boardings
  • Walk-access boardings
  • Drive-access boardings
• Join with route metadata (RouteInfo.csv)

4. Visualization & Analysis

Generates bar charts and summary tables for:

• Total boardings by transit mode
• Total boardings by service district
• Route-level comparisons for:
  • Local Bus
  • BRT / CRT / LRT
  • Express Bus
• Walk vs. Drive access impacts

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Example Output Metrics

Boardings by Mode (System-Wide)

Mode	Base	UTA Changes	Diff	% Diff
Local Bus	82,595	79,579	-3,016	-3.7%
LRT	65,369	60,859	-4,509	-6.9%
CRT	24,984	24,138	-846	-3.4%
BRT III	14,575	13,328	-1,247	-8.6%
Express Bus	3,794	3,751	-43	-1.1%
BRT I	1,757	1,597	-160	-9.1%
Total	193,073	183,252	-9,821	-5.1%

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Boardings by Service District

Service District	Base	UTA Changes	Diff	% Diff
Salt Lake	154,300	147,019	-7,280	-4.7%
Provo	23,889	22,154	-1,735	-7.3%
Ogden	14,884	14,078	-805	-5.4%
Total	193,073	183,252	-9,821	-5.1%

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Walk vs. Drive Access Impacts (Total by Mode)

Mode	Walk % Diff	Drive % Diff
BRT I	-9.3%	-1.1%
BRT III	-9.0%	+11.7%
CRT	-4.5%	-1.3%
Express Bus	-6.4%	+29.1%
LRT	-6.6%	-8.9%
Local Bus	-4.1%	+1.0%
Total	-5.5%	-2.0%

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Charts

• All key comparisons are visualized using Matplotlib
• Custom coloring and formatting for clarity
• Grouped charts include:
  • Daily boardings by mode and district
  • Walk and drive access boarding comparisons
  • Route-level bar charts for each district and transit type

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Requirements

• Python 3.x
• ArcPy (must be run within ArcGIS Pro environment) just to convert DBF
• pandas, numpy, matplotlib