The Road to Autonomous Trucking : A Linear Programming Model for Minimizing Costs of Logistics within the Trucking Industry

Surface transportation in the United States of America has historically consisted of conventional trucks with drivers and railways. The industry is massive, with over 300 billion miles covered annually at the cost of $500 billion. However, despite employing over 3.39 million drivers, an additional 80,000 drivers are needed now, and this figure is expected to double by 2030. New technologies are being introduced to alleviate driver shortage issues and reduce total transportation costs. These new technologies are electric trucks and autonomous trucks. Using the four surface modes of transportation, including conventional trucking, railways, electric trucks, and autonomous trucks, we seek to create a linear programming model that optimizes the mix of modes to reduce total transportation costs dramatically while potentially solving driver shortage concerns. Our program demonstrates that at peak optimization, the average cost per mile can be reduced by over 15%, resulting in potential savings of over $50 billion per year