Modeling the Impacts of Policy and Infrastructure Investments on Freight Emissions and Congestion: An Agent-Based Simulation Approach
The growing demand for freight transport has increased emissions and congestion in traditional road and rail systems, emphasizing the need for sustainable alternatives. Inland waterways offer significant potential, but limited research has examined the combined effects of policy interventions and infrastructure investments on freight mode choices and overall system performance. This study addresses this gap by employing an Agent-Based Simulation (ABS) model using SimPy to evaluate the impacts of various scenarios on emissions, travel times, and congestion levels. The simulation focuses on freight movement between Houston and San Antonio, testing scenarios with freight shifts to waterways ranging from 10% to 75%. It incorporates policies such as carbon taxes, barge and rail subsidies, and road pricing alongside infrastructure investments aimed at alleviating bottlenecks. Results demonstrate that a 75% shift to barge transport achieves the lowest CO₂ emissions, while dynamic congestion charges effectively reduce peak truck usage and road congestion. Infrastructure enhancements in barge and rail capacity further improve network efficiency by mitigating bottlenecks and enhancing flow. These findings provide practical insights for policymakers, highlighting effective combinations of policies and infrastructure investments to achieve a balanced and sustainable freight transport system. Future research could explore strategies for optimizing freight distribution networks through multi-modal logistics and adaptive infrastructure planning. Integrating real-time data analytics and digital platforms could facilitate improved coordination among trucks, trains, and barges, reducing delays and maximizing capacity utilization. These advancements improve operational efficiency and provide support for long-term environmental sustainability by minimizing resource wastage and emissions.
Author(s):
Senjuti Rahman | Graduate Research Assistant | Texas Tech University
Md Mehedi Hasan | Graduate Research Assistant | Texas Tech University
Fan Bu | Assistant Professor | Texas Tech University
Hong Xu | Graduate Research Assistant | Texas Tech University
She is a graduate research assistant. She received her Undergraduate from Wuhan University of Technology.Her major was Logistics Management.
Modeling the Impacts of Policy and Infrastructure Investments on Freight Emissions and Congestion: An Agent-Based Simulation Approach
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Abstract Submission
Description
Primary Track: Logistics & Supply ChainSecondary Track: Modeling & Simulation
Primary Audience: Academician