An unmanned tractor trailer cluster intelligent scheduling management platform

Through a collaborative architecture of cloud platform, edge computing and vehicle terminal, combined with task allocation using genetic algorithm and reinforcement learning, efficient and intelligent scheduling and monitoring of unmanned towing trailer clusters were achieved, solving problems such as unreasonable task allocation and path conflicts in cluster operations, and improving operational efficiency and safety.

CN122450130APending Publication Date: 2026-07-24ZHENGZHOU YINFENG ELECTRONIC TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
ZHENGZHOU YINFENG ELECTRONIC TECHNOLOGY CO LTD
Filing Date
2026-05-25
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Unmanned towing trailer clusters suffer from problems such as unreasonable task allocation, path conflicts, high empty running rate, and weak collaborative obstacle avoidance capabilities. Traditional scheduling platforms suffer from high latency, slow emergency response, path planning that is not adapted to vehicle dynamics, decreased accuracy of perception systems, high deployment costs, and insufficient level of multi-vehicle collaborative conflict-free operation.

Method used

It adopts a three-layer collaborative architecture consisting of a cloud platform layer, an edge computing layer, and an in-vehicle terminal layer. It combines task allocation using genetic algorithms and reinforcement learning, multi-source perception and multi-modal fusion algorithms, hierarchical dynamic path planning, and multi-link redundant communication to support multi-vehicle collaboration and emergency response, thereby achieving intelligent scheduling and monitoring throughout the entire process.

Benefits of technology

It improves cluster operation efficiency, reduces the incidence of multi-vehicle conflicts and empty runs, enhances obstacle recognition accuracy in adverse weather conditions, ensures communication stability and operational safety, reduces deployment and maintenance costs, and supports highly dynamic task response.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application relates to the technical field of intelligent logistics equipment scheduling, and discloses an unmanned towing trailer cluster intelligent scheduling management platform based on a cloud edge end collaborative three-layer architecture design, which comprises a cloud platform layer, an edge computing layer and a vehicle-mounted terminal layer, the cloud platform layer is configured with core modules such as task management, global intelligent scheduling and path planning, adopts a scheduling strategy combining a genetic algorithm and reinforcement learning, and realizes accurate matching of transport capacity and tasks by fusing multiple constraint conditions; the path planning module is based on vehicle dynamics constraints, adopts a hierarchical architecture of global topology planning, local behavior decision and smooth trajectory generation, adapts to the physical characteristics of towing trailers and solves multi-trailer conflicts, and is matched with multi-link redundant communication of 5G, Wi-Fi, Beidou short message to guarantee stable data transmission, is suitable for multiple scenes such as factory areas, ports and warehouses, is compatible with unmanned towing trailers of different brands, and realizes intelligent, unmanned and efficient management of cluster operation.
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