An efficient remote driving shift control method of unmanned heavy tracked vehicles based on manned data mining

Weijian Jia ¹, Yao Zhao ², Haiwen Zheng ³

⁰Zhengzhou Campus, Army Artillery and Air Defense Forces Defense Academy, Zhengzhou, 450052, China. jwjyxsl@163.com.

Scientific Reports +

|

December 29, 2025

View abstract on PubMed

Summary

This study developed a new shift control strategy for heavy tracked vehicles undergoing remote driving. The strategy improves shift smoothness and reduces shift time, enhancing ride comfort after unmanned transformation.

Area Of Science

Mechanical Engineering
Robotics
Control Systems

Background

Unmanned transformation of heavy tracked vehicles presents challenges in remote driving, specifically low shift smoothness and prolonged shift times.
Existing control strategies may not adequately address the complexities of remote gear shifting in tracked vehicles.

Purpose Of The Study

To develop an auxiliary decision-making model for shift timing in remote driving of heavy tracked vehicles.
To design an integrated shift control strategy for tracked vehicle power transmission to enhance remote driving performance.

Main Methods

Mining manned driving data to develop an auxiliary decision-making model for shift timing.
Designing an integrated shift control strategy using a hierarchical finite state machine.
Verifying the strategy through bench and real vehicle testing.

Main Results

The developed strategy significantly improved shift smoothness, with an average shift impact of 9.02.
The average shift time was reduced to 4.6, indicating faster gear changes.
The vehicle demonstrated good ride comfort during the entire shifting process.

Conclusions

The proposed remote control shift strategy effectively enhances the shift performance of heavy tracked vehicles after unmanned transformation.
The research provides a foundation for advanced driving and trajectory tracking control in unmanned tracked vehicles.
The findings are valuable for improving the operational capabilities and comfort of remotely operated heavy machinery.

Keywords:

Data mining Shift smoothness control Unmanned heavy tracked vehicles

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