Optimal and Safe Route for Freight Transportation in Rural Areas

The project aims to develop an optimal and safe route for freight transportation in rural areas. Transportation of goods in remote regions often faces challenges such as inadequate road infrastructure, limited access to real-time information, and potential safety hazards. This project seeks to address these issues by utilizing advanced technologies and data-driven approaches. The primary objective is to design an intelligent routing system that takes into account various factors, including road conditions, weather conditions, traffic congestion, and the nature of the cargo being transported. By leveraging historical and real-time data, the system will analyze and identify the most efficient and secure routes for freight transportation. To achieve this, the project will employ a combination of geographic information systems (GIS), machine learning algorithms, and sensor technologies. The GIS will provide a spatial framework for mapping rural areas and identifying potential routes. Machine learning algorithms will be trained using historical data to predict road conditions and traffic patterns. Sensors placed on vehicles will collect real-time data, enabling the system to dynamically adjust routes based on current conditions. The outcome of this project will be a robust and reliable routing system that enhances freight transportation efficiency and safety in rural areas. This will benefit businesses by reducing transportation costs, minimizing delivery delays, and ensuring the integrity of the cargo. Additionally, it will have a positive impact on rural communities by improving connectivity and fostering economic development.

• Record URL:
  https://www.cr2c2.com/research/major-research-initiatives/mri-3/project-3-1

Language

• English

Project

• Status: Active
• Funding: $239515
• Contract Numbers:

  69A3552348304

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Regional and Rural Connected Communities

  North Carolina A&T State University
  Greensboro, NC  United States  27411

  Florida Atlantic University, Boca Raton

  Boca Raton, FL  United States  33431
• Project Managers:

  Kaisar, Evangelos

• Performing Organizations:

  Florida Atlantic University, Boca Raton

  Boca Raton, FL  United States  33431

  North Carolina A&T State University

  1601 E. Market Street
  Greensboro, NC  United States  27411

  University of Kentucky, Lexington

  Lexington, KY  United States  40506-0281
• Principal Investigators:

  Chen, Mei

  Kaisar, Evangelos

  Ni, Zhen

  Pandey, Venktesh

• Start Date: 20230801
• Expected Completion Date: 20250731
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Economic analysis; Freight transportation; Intelligent transportation systems; Machine learning; Routes and routing; Rural areas; Transportation operations
• Subject Areas: Data and Information Technology; Freight Transportation; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01892503
• Record Type: Research project
• Source Agency: Center for Regional and Rural Connected Communities
• Contract Numbers: 69A3552348304
• Files: UTC, RIP
• Created Date: Sep 7 2023 9:40AM