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A Freight Stop Purpose Model Using Enriched GPS Data
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2024-01-01
[PDF-1.30 MB]
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Abstract:Truck tour data are important for understanding freight truck operations and their impacts on the economy, congestion, and sustainability. Tour data capture the movements of trucks as they travel from their depots to make various stops before returning to their depots. Understanding the purpose of these stops (pickup, delivery, rest, etc.) is an essential component of freight truck tour analysis. Evaluating stop purposes is especially critical to evaluate truck electrification, resilience, supply chains, truck parking, and other emerging topics. Many studies use truck GPS data to infer truck activity, but most analyze trips instead of tours. Also, GPS data generally don’t have stop purpose information. Consequently, truck tour data with stop purpose information are a major freight data gap. We address this gap by developing a process to infer both truck tours and stop purposes. Our main contribution is developing a behavioral model that allows analysts to infer stop purposes and tour patterns. To do so, we first fuse truck GPS data with geospatial data on businesses and interstates. We enrich the new dataset by manually labeling the estimated stop purposes. We use the enriched data to develop behavior models that predict the purpose of each stop. Analysts can apply the resulting model to predict stop purposes for other GPS data, thereby filling an important need in truck touring data development.
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