Utilizing Cell Transmission Models to Alleviate Accident-Induced Traffic Congestion in Two-Way Grid Networks

The Cell Transmission Model (CTM) is a commonly used framework and cost-effective approach for evaluating transportation-related solutions, particularly for analyzing urban traffic congestion, due to its strong mathematical framework. Its effectiveness relies heavily on accuracy, making proper calibration essential for deriving reliable design decisions. This study utilizes CTM calibration techniques to design control strategies for mitigating accident-induced traffic congestion in two-way grid networks. By modifying the number of downstream cells and their vehicle capacity, we assess the impact of these adjustments on traffic flow efficiency within the grid structure. Additionally, we utilize MATLAB R2022a to design an intelligent transportation network simulation environment, providing a robust platform for testing and optimizing traffic management strategies specific to two-way grid networks. The findings of this research contribute to the introduction of a novel refinement to the traditional CTM by dividing only cell 9 into three smaller cells to accurately capture different movement directions, enhancing intersection modeling without increasing overall computational complexity.