Multi-line vehicle intelligent scheduling method and system, equipment and storage medium

By building a feature extraction network and a vehicle selection network, combining simulation environment and reinforcement learning algorithms, a reinforcement learning agent is built, and a vehicle scheduling problem that is difficult to deal with changes in complex instances in the existing technology is solved, and a more efficient and reliable multi-line vehicle intelligent scheduling is achieved.

CN119671185AActive Publication Date: 2025-03-21BEIJING UNIV OF POSTS & TELECOMM
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Patent Information

Application Number
CN202411821115.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-11
Publication Date
2025-03-21
Estimated Expiration
2044-12-11

AI Technical Summary

Technical Problem

The prior art is difficult to design a vehicle scheduling method that can cope with complex example changes, especially in multi-line vehicle operations, where the generalization performance of the existing method is limited.

Method used

By building a feature extraction network and a vehicle selection network, combining a simulation environment, a reinforcement learning agent is built, and reinforcement learning algorithms such as Proximal Policy Optimization (PPO) are used for training to generate a target scheduling plan.

Benefits of technology

It improves the ability to deal with complex vehicle scheduling problems, reduces the cost of testing and training in real scenarios, enhances the system's adaptability and processing capabilities to variable situations, and improves the accuracy and reliability of scheduling solutions.

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Abstract

The invention provides a multi-line vehicle intelligent scheduling method and system, equipment and a storage medium, and belongs to the technical field of intelligent vehicle scheduling, and the method comprises the steps: constructing a feature extraction network which is used for extracting a feature vector of first information; and constructing a vehicle selection network, wherein the vehicle selection network is used for selecting vehicles for scheduling. And constructing a simulation environment, wherein the simulation environment is used for simulating operation information of the vehicle. And constructing an intelligent agent based on the feature extraction network and the vehicle selection network. First information is generated based on the simulation environment, the intelligent agent is trained based on the first information and a reward function to obtain a reinforcement learning intelligent agent, the first information is historical operation information of the simulation vehicle, and the reward function is a reward value calculation function corresponding to the first information; and inputting second information into the reinforcement learning agent to obtain a target scheduling scheme, wherein the second information is multi-line vehicle information. According to the multi-line vehicle intelligent scheduling method and system, the equipment and the storage medium provided by the invention, the capability of coping with a complex vehicle scheduling problem can be improved.
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