A Compartmental Model of Traffic Congestion with Adaptive Driver Behavior: Role of Awareness-Driven Interventions in Congestion Control
DOI:
https://doi.org/10.37134/jsml.vol14.2.12.2026Keywords:
SIR model , Adaptive behavior , Traffic congestion , Basic reproduction number , Sensitivity analysis , Numerical simulationAbstract
Urban traffic congestion imposes substantial societal costs through time delays, fuel waste, and environmental degradation. Traditional mathematical models often overlook the influence of driver awareness and adaptive behavior, despite their increasing relevance in the era of real-time traffic information systems. This study presents a novel SIR-based compartmental model that integrates behavioral adaptation by introducing an “Aware” class of drivers who modify their travel decisions to avoid congestion. Qualitative analysis confirms the model’s positivity and boundedness, while a stability analysis identifies a threshold condition governed by a basic congestion reproduction number, . Results indicate that when < 1, congestion dissipates over time, while > 1 leads to sustained congestion. Numerical simulations reveal that increasing the rate of awareness acquisition significantly lowers , reducing both the peak and duration of congestion. These findings highlight the potential of awareness-driven such as real-time traffic advisories and navigation systems, as effective and low-cost strategies for congestion mitigation.The results provide theoretical insights that can inform the design of integrated traffic management policies combining behavioral and infrastructure-based approaches.
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Copyright (c) 2026 Jonecis Dayap, Fahad Al Basir, Vincent L. Banot, Jeanievic Idjao, Mark Vincent Cortez
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