Authors:
Ardi Prasetya Hernawan
MIT Supply Chain Management Program
75
Summary:
This thesis investigates the role of truck stops in the U.S. trucking industry using data from Electronic Logging Devices (ELDs), focusing on how these truck stops can adapt to future requirement, including autonomous trucking and pandemics. By applying machine learning techniques for clustering and classification, the project identifies stop locations and categorizes stop activities, providing new insights into truck stop functions. The outcomes reveal potential for truck stops to serve as pivotal nodes in future supply chains, highlighting their capability to support both pandemic response and the integration of autonomous trucking
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