Modeling study demonstrates improved traffic dynamic prediction on expressway corridors using weather-specific calibration, highlighting the importance of weather adjustments in traffic flow models.
This study presents the calibration and validation of a weather-specific (two-state: normal versus rainy) macroscopic traffic-flow modelling framework based on the Metanet model. The analysis is conducted on a corridor-scale expressway segment of the Burapha Withi Expressway in Bangkok, Thailand, using traffic data under normal and rainy conditions. The results show that incorporating weather-specific calibration improves the model’s ability to capture traffic dynamics under varying conditions. The impact of traffic-flow heterogeneity is found to be limited under the relatively homogeneous characteristics of the study corridor. Sensitivity analysis further indicates that key traffic-flow parameters, such as free-flow speed, capacity and critical density, significantly influence model performance. The findings are specific to the analysed corridor and period and highlight the importance of accounting for weather conditions in macroscopic traffic-flow modelling. Future work should incorporate rainfall intensity and validate the model across more diverse traffic environments.
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Mejia et al. (2026) studied this question.
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