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SPO-VCS: An End-to-End Smart Predict-then-Optimize Framework with Alternating Differentiation Method for Relocation Problems in Large-Scale Vehicle Crowd Sensing

arXiv — cs.LG•Wednesday, November 12, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
The development of the Smart Predict-then-Optimize (SPO) framework marks a significant advancement in vehicle crowd sensing (VCS), which utilizes mobile devices to gather urban data. Traditional methods often struggle with biased coverage due to varying trip requests and routes, leading to suboptimal vehicle relocation strategies. The SPO framework innovatively combines optimization with prediction within a deep learning architecture, aiming to minimize discrepancies between actual vehicle distributions and target sensing distributions. This approach not only enhances the accuracy of vehicle relocation but also addresses critical challenges in urban data acquisition, making it a pivotal development in the field of intelligent transportation systems.
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