Identifying the role of route choice behavior of motorcycle riders in microscopic simulation modeling under mixed traffic conditions

• Integrating route choice function into micro-simulation improved model precision. • Observed dynamic route choice behavior of motorcyclists in mixed traffic contexts. • Motorcycles adapt routes by encountered traffic conditions, not only shortest path. • Real-time traffic report systems essential for improving route choice efficiency. • Traffic information provision results in up to 84% network performance improvements. Microscopic simulation models are pivotal in transportation planning for their ability to intricately capture complex traffic patterns. This study specifically explores the role of dynamic route choice behavior within micro-simulation frameworks, emphasizing its application in the context of motorcycle-dominated traffic in Ninh Kiều District, Cần Thơ, Vietnam. By integrating discrete choice models for route selection with rigorous calibration and validation in AIMSUN, the study developed a comprehensive traffic simulation model for large-scale networks. Findings reveal that motorcycles dynamically adjust routes based on current traffic conditions rather than adhering strictly to shortest path strategies. However, the availability of roadside traffic information systems accessible to motorcycles in developing countries is limited, hindering optimal route choices. To address this gap and encourage the enhancement of route choice behavior, the study evaluates the impact of real-time traffic information provision using Macroscopic Fundamental Diagrams within the micro-simulation model. The results demonstrate significant improvements in network efficiency when informed route selection behaviors are facilitated, particularly with comprehensive coverage across all road types. Higher compliance rates notably improved network capacity by up to 84%. Overall, this study contributes methodologically by increasing model precision and practical insights into managing heterogeneous traffic environments, highlighting the transformative potential of traffic information systems and advocating for broader implementation in similar motorcycle-centric regions, which currently still rarely extend beyond toll roads. Future research should extend these methodologies to diverse urban contexts for broader validation and application.