A Data-Limited Function-Weighted Method for Network-Level Congestion Assessment in Heterogeneous Urban Road Networks

Abstract

Network-level congestion assessment requires segment states to be aggregated across roads that differ in length, observed flow, capacity, and functional role. In data-limited settings, however, traffic agencies may only have road class, segment length, traffic flow, capacity, and average speed, and the effect of the aggregation rule is rarely made explicit. This study formulates a segment-to-network congestion assessment problem for such settings. Road segments are classified with road-class-specific speed thresholds under three definitions—severe-only, moderate-or-worse, and mild-or-worse—and six benchmark rules are compared under identical segment classifications. A class-function-weighted ratio is then proposed to combine within-class congested mileage with each road class’s share of observed hourly flow–length exposure. The method is evaluated on 31 segments in a 39.615 km urban road network using a single audited data table. Under the severe-only definition, the six benchmark ratios range from 7.01% to 12.38%, whereas the proposed ratio is 9.98%. The proposed ratio is 32.89% for moderate-or-worse congestion and 94.92% for mild-or-worse congestion. Joint 5% and 10% perturbations in both directions of the cutoff defining each outcome produce ranges of 7.63–9.98%, 28.19–42.71%, and 91.17–98.14%, respectively. These results show that network diagnosis depends materially on both the congestion definition and aggregation rule. The proposed method is more interpretable for decisions where road-class function and auditable aggregation are important, while the numerical findings remain specific to the retained case data.