Integrating speed reduction index (SRI) and AADT for prioritizing road network mobility improvements: A case study on Thailand's national highway

Abstract

Efficient evaluation of road network mobility performance is a concern for highway departments worldwide, with critical implications for economic productivity and transportation sustainability. This study focuses on the evaluation of traffic congestion indices (TCI), with particular attention to the Speed Reduction Index (SRI), due to its straightforward interpretation of congestion severity. SRI is efficient for large-scale assessments, such as at the country or regional level. To assess mobility performance, we utilize an average road speed data obtained from “TomTom,” which meticulously captures nationwide driving speeds within small road sections (approximately 100 to 500 m per section). For highway departments grappling with limited annual budgets for road improvements, prioritizing road sections and areas for intervention presents a significant challenge. To address this, our study proposes a novel approach: the integration of SRI and Annual Average Daily Traffic (AADT) data. By combining the severity level (SRI interpretation) with the impact level on road users (AADT interpretation), a more informed and assessment of road network mobility emerges. To demonstrate the practicality of this methodology, we applied it to the Thai national highway, focusing on the highest road hierarchy (Road Hierarchies 1 and 2) and tested the rationale of use with factors that may cause a variation in road network mobility performance, such as urban density, elevation, lane count, delay, and speed limit. The results offer a comprehensive overview of roads in need of urgent improvement at the national level.