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

Abstract

With the rise of advanced mobility data collection technologies, there has been growing interest in performance-based planning and programming. As a result, transportation agencies are increasingly using multiple metrics to evaluate system performance. However, relying on multiple indicators can complicate decision-making, highlighting the need for a single, consolidated performance score. This study evaluates the performance of the transportation system in Texas using a data envelopment analysis model. The analysis incorporates six performance metrics aligned with five planning goals outlined in Texas Unified Transportation Program. The decision-making unit was set as census tracts, and the transportation score was defined as the relative performance of the six metrics in comparison to population and land area. The results showed that the transportation score across 5265 census tracts was estimated to be 0.52 on average. This suggests that an average improvement of 0.48 is needed across census tracts to reach the optimal transportation score of 1.00. Additionally, the impact of six metrics on estimated transportation score was identified using the Tobit regression model. The proposed framework contributes to the transportation planning process by combining multiple metrics into a single score and providing both performance rankings and actionable insights for system improvement.