A green vehicle abnormal transportation state detection method based on highway OD data

Abstract

This invention belongs to the field of intelligent transportation technology, specifically relating to a method for detecting abnormal transportation status of green channel vehicles based on highway OD data. This invention overcomes the limitations of traditional manual spot checks and simple weighing comparisons, which can only address explicit problems, through the coordinated operation of data acquisition, origin anomaly judgment, weight loss anomaly judgment, and comprehensive early warning. It accurately identifies non-overweight transportation anomalies with strong concealment, such as substandard loading rates, mixed loading of light and heavy goods to increase weight, and false declaration of goods, filling a gap in existing technology in this field. Based on big data such as highway OD, this invention conducts intelligent screening from the macro-level patterns of transportation behavior, significantly reducing the hardware investment and operating costs of green channel policy supervision. At the same time, it overcomes the drawbacks of low efficiency, narrow coverage, and strong subjectivity of manual detection, achieving automated and comprehensive screening of the transportation status of green channel vehicles, greatly improving regulatory efficiency and coverage.

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