The complexity and dynamics of multimodal freight transportation networks present a significant challenge in determining optimal freight routes in rural areas. The transportation of goods in remote regions often faces challenges such as inadequate road infrastructure including insufficient truck parking, improper road conditions, limited access to real-time information, and potential safety hazards. However, transportation planners have limited understanding of the safest and best routes for freight movement in rural areas. Therefore, this project aims to develop an intelligent routing system for multimodal freight transportation in rural areas of Florida, North Carolina, and Kentucky in order to enhance efficiency and safety in these regions. An extensive literature review is being carried out to determine factors contributing to rural transportation congestion and their impact on freight transport. The ongoing tasks will continue to further perform geospatial analysis to identify potential routes, integrating relevant data layers and train machine learning algorithms using historical data to predict optimal and safe route conditions and traffic patterns for freight vehicles.

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