Enhancing Urban Mobility through Adaptive Traffic Analysis: A Case Study in Singapore
Banerjee Mohor,
Chidambaram Aditya Somasundaram,
Pahwa Ronak
et al.
Abstract:Traffic congestion is a significant issue in most urban landscapes, causing delays and affecting the daily commutes of thousands. This study, "Adaptive Traffic Learning and Analysis System" seeks to leverage the capabilities of Large Language Models (LLMs) to analyze data from urban traffic systems and provide detailed insights into congestion points. By using the Simulation of Urban MObility (SUMO) software, we replicate street layouts and traffic signals for specific locations in Singapore, facilitating real… Show more
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