The MxT Model: Leveraging Social Media Data for Real-Time Route Optimization in Disaster-Prone Urban Transport Networks

The modified xTRoad (MxT) model, an innovative route optimization framework, is presented to enhance urban traffic management within disaster-prone regions.This model uniquely integrates static and real-time data derived from the social media platform X (formerly known as Twitter) to improve route mitigation strategies, particularly during emergencies.The methodology employs a refined social media data extraction process using Boolean logic and a score-based evaluation system to identify disruptions, including flooding, obstructive debris, and public demonstrations.To validate the accuracy of the model, ground truth validation techniques were implemented, confirming the system's efficacy in detecting obstacles and generating alternative routes.Performance testing was conducted on key transport arteries in Jakarta, where the MxT model demonstrated a detection accuracy exceeding 91.6% for traffic disruptions.Furthermore, the model achieved an average reduction in travel time by 15% compared to traditional traffic management systems.The MxT model dynamically adapts to real-time conditions, offering safer and more efficient navigation options in complex urban settings.The results underscore the MxT model's potential as a scalable, adaptable solution for intelligent transport management during disaster scenarios, thereby contributing to the advancement of resilient urban infrastructure.