Railway dedicated line intelligent scheduling method, device and equipment based on vehicle identity automatic identification, and medium

By using multimodal evidence fusion and digital twin models, the shortcomings of single-sensor identification in railway vehicle dispatching are addressed, enabling accurate vehicle identification and dynamic dispatching optimization, thereby improving the reliability and efficiency of the dispatching system.

CN121119631APending Publication Date: 2025-12-12方国栋
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Patent Information

Application Number
CN202511641142.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-11-11
Publication Date
2025-12-12

AI Technical Summary

Technical Problem

In existing railway vehicle dispatching systems, vehicle identification relies on a single sensor and is susceptible to environmental interference, leading to identification failures or misidentifications. Dispatch decisions fail to fully utilize historical features and struggle to reconstruct credible identities when evidence conflicts, resulting in limited dispatching efficiency and accuracy.

Method used

By collecting and preprocessing multimodal evidence (trackside RFID, visual OCR, UWB positioning, acoustic-vibration fingerprint, track events), constructing an identity confidence map for evidence fusion, binding real-time location information using a digital twin model, and combining the track section status for scheduling solutions, train dispatch instructions are generated.

Benefits of technology

It improves the accuracy and robustness of vehicle identification, reduces the risk of misjudgment, realizes dynamic scheduling optimization based on historical information, improves the timeliness and rationality of scheduling, and reduces human error.

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Abstract

The invention relates to a railway special line intelligent scheduling method and device based on vehicle identity automatic identification, equipment and a medium. The method comprises the following steps: acquiring a multi-modal evidence of a vehicle with a to-be-identified identity, and preprocessing the multi-modal evidence to obtain an evidence set; according to the evidence set, constructing an identity confidence map of the to-be-identified vehicle, and based on the identity confidence map, performing evidence fusion and confidence calculation on the to-be-identified vehicle to obtain a vehicle identity label and confidence thereof; if the confidence exceeds a preset threshold, determining a corresponding digital twinborn model according to the vehicle identity, and binding the real-time position information associated with the UWB positioning evidence into the digital twinborn model to obtain digital twinborn update information; and based on the state constraint and the safety constraint of the current track section, scheduling solution is performed according to the digital twin update information, and a driving scheduling instruction is generated. By adopting the method, the vehicle identity recognition is more reliable through evidence flow driving, and the scheduling decision is more accurate and predictable.
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