Logistics vehicle and cargo intelligent matching system and method based on carbon footprint

By analyzing vehicle and cargo characteristics, using a quantile energy consumption regression model to predict carbon emissions, assessing robustness, and selecting the optimal logistics trajectory, the uncertainty of carbon emissions in vehicle-cargo matching in logistics is solved, achieving low-carbon and efficient logistics transportation.

CN122022639AActive Publication Date: 2026-05-12HANGZHOU CHENGFENGLAI DIGITAL TECH CO LTD +1
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Patent Information

Application Number
CN202610484969.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-14
Publication Date
2026-05-12
Estimated Expiration
2046-04-14

AI Technical Summary

Technical Problem

Existing methods for matching logistics vehicles with cargo fail to effectively account for the uncertainty of carbon emissions under different conditions, resulting in discrepancies between predicted and actual carbon emissions. This could lead to excessive carbon emissions or an inability to effectively reduce them.

Method used

By acquiring characteristic data of vehicles and goods, analyzing the degree of fit, generating logistics trajectories, using quantile energy consumption regression models to predict vehicle energy consumption and carbon emissions, assessing the robustness of carbon emissions, selecting the optimal logistics trajectory, determining target vehicles by combining time and carbon emission weights, and using reusable packaging for transportation.

Benefits of technology

It improves the accuracy of carbon emissions in the logistics and transportation process, reduces carbon emission risks, takes into account transportation efficiency, and achieves energy-saving and environmentally friendly logistics and transportation.

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Abstract

The invention discloses a carbon footprint-based logistics vehicle and cargo intelligent matching system and method, and relates to the technical field of logistics vehicle and cargo matching, and the method comprises the steps: analyzing the adaptation degree between a vehicle and a target cargo, and obtaining a candidate vehicle; obtaining a logistics trajectory set, analyzing energy consumption distribution conditions of candidate vehicles under different logistics trajectories in the logistics trajectory set, analyzing carbon emission uncertainty degrees of the candidate vehicles under the different logistics trajectories, and evaluating carbon emission steady conditions of the candidate vehicles in the different logistics trajectories; acquiring target track carbon emission data of different candidate vehicles, analyzing logistics matching degrees of the different candidate vehicles and the target goods, and determining a target vehicle; according to the method, the target logistics track of the target vehicle is obtained, and the target cargo is subjected to logistics transportation according to the target logistics track, so that the carbon emission in the transportation process of the target cargo is greatly reduced, the logistics efficiency is also considered, and energy conservation and environmental protection are truly realized in the field of traffic transportation.
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