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Vehicle Identification, Tracking and Control System for Unmanned Multi Vehicle Formation
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Ming-xi PANG, Chang-hua DAI, Zhi-hang WANG, Wen-shan XIAO, De-qian SHI, Ding-heng WANG*
Science Technology and Engineering | 2025, 25(10) : 4206 - 4215
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Science Technology and Engineering | 2025, 25(10): 4206-4215
Papers·Automation and Computational Technology
Vehicle Identification, Tracking and Control System for Unmanned Multi Vehicle Formation
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Ming-xi PANG, Chang-hua DAI, Zhi-hang WANG, Wen-shan XIAO, De-qian SHI, Ding-heng WANG*
Affiliations
  • Intelligent Equipment and Technology Research Office of Northwest Institute of Mechanical and Electrical Engineering, Xianyang 712099, China
Published: 2025-04-08 doi: 10.12404/j.issn.1671-1815.2402872
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In the context of unmanned multi-vehicle formation guided by manned vehicles, a system for vehicle recognition and trajectory tracking control of unmanned vehicles during formation driving was devised and executed. An algorithm for multi-sensor fusion moving target detection was proposed, leveraging data from lidar, camera, and mmWave radar sensors. The algorithm utilizes Euclidean clustering, deep learning, and kinematic reasoning techniques for target detection. Additionally, a fusion methodology was introduced to integrate detection outcomes from various sources for precise identification of vehicles in the vicinity. Paths were anticipated based on the trajectories of preceding vehicles, and a Kalman filter was developed to smooth and filter these paths. A vehicle dynamic model, vehicle road error model, and the robust H∞ controller was established for vehicle trajectory tracking control simulation. Outcomes from simulation and real vehicle validation show as follows. The average recognition accuracy of preceding vehicles in test scenarios exceeds 95%. The mean squared error and average trajectory deviation rate of real-time anticipated paths decrease by 17.3% and 48.6% respectively pre and post filtering. Lateral control position error and yaw angle error decrease by 29% and 41% correspondingly compared to PID control. Vehicle formations attain stable working at speeds of up to 54 km/h.

multi sensor data fusion  /  multi vehicle formation  /  autonomous driving  /  trajectory tracking  /  robust control
Ming-xi PANG, Chang-hua DAI, Zhi-hang WANG, Wen-shan XIAO, De-qian SHI, Ding-heng WANG. Vehicle Identification, Tracking and Control System for Unmanned Multi Vehicle Formation[J]. Science Technology and Engineering, 2025 , 25 (10) : 4206 -4215 . DOI: 10.12404/j.issn.1671-1815.2402872
Year 2025 volume 25 Issue 10
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Article Info
doi: 10.12404/j.issn.1671-1815.2402872
  • Receive Date:2024-04-19
  • Online Date:2025-07-09
  • Published:2025-04-08
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  • Received:2024-04-19
  • Revised:2024-12-31
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    Intelligent Equipment and Technology Research Office of Northwest Institute of Mechanical and Electrical Engineering, Xianyang 712099, China
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多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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