From scores to strategy: Performance-based transportation planning in Texas

Area of Science:

• Transportation Engineering
• Urban Planning
• Operations Research

Background:

• Growing use of advanced mobility data collection technologies.
• Increasing reliance on multiple metrics for transportation system performance evaluation.
• Need for a consolidated performance score to simplify decision-making.

Purpose of the Study:

• To evaluate the performance of the Texas transportation system using a single, consolidated score.
• To develop a framework for combining multiple performance metrics into one comprehensive score.
• To identify key metrics influencing transportation system performance.

Main Methods:

• Data Envelopment Analysis (DEA) model applied to census tracts as decision-making units.
• Incorporation of six performance metrics aligned with the Texas Unified Transportation Program's five planning goals.
• Tobit regression model used to analyze the impact of individual metrics on the overall transportation score.

Main Results:

• The average transportation score across 5,265 Texas census tracts was estimated at 0.52.
• An average improvement of 0.48 is required for census tracts to achieve an optimal score of 1.00.
• The Tobit regression identified the specific impact of each of the six metrics on the overall transportation score.

Conclusions:

• The proposed framework effectively consolidates multiple performance metrics into a single, actionable transportation score.
• The study provides valuable performance rankings and insights for targeted transportation system improvements in Texas.
• This approach supports data-driven decision-making in performance-based transportation planning and programming.