A Methodology for Ranking Urban Road Segments Based on Morning/Evening Peak Load and Average Speed

Abstract

The paper proposes a calculation-based methodology for spatiotemporal assessment of operating conditions of an urban road network at the road-segment level. The input data comprise geospatial indicators of traffic load and average speed during the morning (AM) and evening (PM) periods. To ensure comparability across segments, min–max normalization is applied and a composite Congestion Index (CI) is constructed, integrating load and speed into a single dimensionless scale and enabling segment ranking by the level of operational deficiency. The methodology includes: forming a unified analytical dataset for road segments; computing CI separately for AM and PM; determining the maximum value, CImax, as an aggregated characteristic of peak-period criticality; and quantifying inter-period changes in operating conditions using ΔCI = CIpm − CIam. Based on CIam, CIpm, and ΔCI, segments are ranked and priority sections are identified for first-order traffic management or infrastructure interventions (signal timing optimization, improvement of traffic schemes, and localized capacity enhancement measures). The methodology is validated using an urban network dataset (case study: Ternopil), which makes it possible to compile a list of segments with the highest congestion-index values in AM/PM and to identify sections exhibiting the greatest deterioration of traffic conditions in the evening period. The proposed approach is reproducible and can be implemented in GIS and/or spreadsheet environments for regular monitoring, comparison of alternative traffic organization schemes, and preparation of analytical inputs for engineering design decisions in urban construction. The results can serve as an engineering-analytical basis for prioritizing design solutions and planning measures aimed at improving the efficiency of urban road network operation.