Development of National Freight Transport Analytics System Using GPS-Based Truck Data
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Abstract
Road freight transport by trucks is the dominant freight transport mode in Thailand and plays a crucial role in the national economy and supply chains. However, freight transport planning and management at the national level has long been constrained by the lack of detailed data that accurately reflects real freight movement patterns in both spatial and temporal dimensions. This academic article aims to present the development process of National Freight Transport Analytics system using GPS-based truck data. The system utilizes GPS data collected from trucks, integrated with big data analytics techniques, to generate insights into freight movement patterns, supply chain structures, and truck operational behaviors. The developed system (validated with average trip lengths and traffic counts on road within acceptable limit’s results) is capable of processing massive volumes of GPS data, amounting to hundreds of millions of records per day, and visualizing the results through key performance indicators (KPIs). For instance, the system is capable of analyzing the overall freight movements of more than three million trips per month, derived from more than 5,000 of unique activity patterns at truck stop points and commodity trip chain. These outputs support evidence-based policymaking, logistics infrastructure planning, and freight transport management at the national scale.
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Copyright belongs to Srinakharinwirot University Engineering Journal
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