Disaster scene-based cargo unloading accessibility determination method based on multi-source data fusion
By constructing a road network model through multi-source data fusion and combining column generation algorithms and multi-dimensional evaluation indicators, the problem of rapid and accurate determination of truck unloading accessibility in disaster scenarios was solved, realizing efficient accessibility determination of cargo unloading in disaster environments.
Patent Information
- Application Number
- CN202610372116.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-25
- Publication Date
- 2026-07-17
AI Technical Summary
In disaster scenarios, existing technologies struggle to quickly and accurately determine whether trucks are capable of safely completing cargo handover and unloading tasks, especially in situations such as road blockages and communication disruptions. Existing solutions suffer from high computational complexity or limited applicability, failing to meet the needs of emergency material transportation.
A multi-source data fusion method is used to construct a directed graph model of the road network. By combining real-time driver location, disaster area data and unloading point attributes, candidate paths are generated through a column generation algorithm. The improved Dijkstra algorithm and multi-dimensional evaluation indicators are used to screen reachable paths, and a heuristic scoring function is constructed for judgment.
It enables multi-path generation and reachability determination within minutes, accurately identifies potential risk bottlenecks, significantly reduces reliance on high-end computing power and GPU memory resources, provides real-time and accurate cargo unloading reachability determination, and avoids local high-risk omissions.
Smart Images
Figure CN122414949A_ABST
Abstract
Citation Information
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