Evangelos I. Kaisar, Ph.D. (PI)
Professor, Department of Civil, Environmental and Geomatics Engineering
Florida Atlantic University
ekaisar@fau.edu

Proposal Summary and Objectives

Port operation possesses a significant impact on the national economy of the USA as it contributes almost $5.4 trillion, nearly 23.5% of the total GDP in 2021. However, a higher transportation time within a port facility may increase the opportunity cost which ultimately results in larger transportation costs. On the other hand, port-related emissions are becoming increasingly problematic which is exacerbating the current global warming issue. Therefore, the objectives of the current project are to develop concept of operations (ConOps) to reduce transportation times while also lowering greenhouse gas (GHG) emissions from ports. To improve the port efficiency, this project proposes operations of automated ground vehicle (AGV) along with the platooning tool within the port facility as this system is capable of reducing dwell time, which leads to a reduction in opportunity cost. The proposed AGV's batteries can be charged within the grid, where it can also be used as a backup for the electric grid. As a result, the reliance on burning fossil fuels to generate electricity will be reduced, resulting in lower carbon emissions. In addition, renewable energy systems (e.g. solar panels, wind turbines etc.) can be employed to produce electricity for the grid. Furthermore, the management of queuing and waiting for loading/unloading in the port can influence the risk of fatigue for heavy truck drivers if it extends work hours or makes resting difficult for drivers, which is considered a part of equity for the port operation. Thus, the current study proposes a truck appointment system (TAS) in which drivers will be assigned to specific heavy trucks moving out of ports, ensuring that trips are completed within their assigned working hours. The study intends to accomplish its objectives by developing and solving multi-objective mixed integer linear programming optimization problems, such as determining the optimal number of AGV to reduce transportation costs and times, as well as GHG emissions from the AGV, and ensuring equity for heavy truck drivers. This research will help government officials, logistics service providers, and other relevant decision makers plan for long-term urban logistics

Funding Amount:
Status: Active
Duration: June 1, 2022 – May 31, 2023