We released a new journal paper about the tool for traffic analysis in mixed traffic condition

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We are thrilled to announce the publication of our latest research paper, “TRAMON: An automated traffic monitoring system for high density, mixed and lane-free traffic,” in the prestigious IATSS Journal. This paper represents the culmination of several years of dedicated effort and research, and it showcases the development of an AI model with remarkable accuracy and reliability in detecting and tracking vehicles in complex traffic scenarios.

The emergence of this AI model marks a significant breakthrough in the realm of traffic monitoring and management. Its ability to handle mixed traffic conditions, including high-density and lane-free environments, holds immense potential for enhancing traffic flow, improving road safety, and optimizing transportation infrastructure.

Particularly noteworthy is the real-time performance of our AI model. This attribute is crucial for any practical traffic monitoring system, and it speaks volumes about the efficacy of our deep learning approach.

We are confident that this research will make a substantial contribution to the field of traffic engineering and pave the way for the development of even more sophisticated and effective traffic management solutions.

The link of the paper: