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Research on the Mechanism of Multi-Sensor Fusion Configuration Based on the Optimal Principle of the Vehicle
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Binggen Zhao, Dong Zeng, Haoyu Lin, Xubo Qiu, Pijie Hu
Automobile Technology | 2024, (10) : 28 - 37
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Automobile Technology | 2024, (10): 28-37
• Selected Papers of SAECCE 2024 •
Research on the Mechanism of Multi-Sensor Fusion Configuration Based on the Optimal Principle of the Vehicle
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Binggen Zhao, Dong Zeng, Haoyu Lin, Xubo Qiu, Pijie Hu
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  • Automotive Research Institute, BYD Auto Industry Company Limited, Shenzhen 518118
Published: 2024-10-24 doi: 10.19620/j.cnki.1000-3703.20240707
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In order to address the issue of sensor configuration redundancy in intelligent driving, this paper constructs a multi-objective optimization model that considers cost, coverage ability, and perception performance. And then, combining a specific set of parameters, the NSGA-II algorithm is used to solve the multi-objective model established in this paper, and a Pareto front containing 24 typical configuration schemes is extracted after considering empirical constraints. Finally, using the decision preference method proposed in this paper that combines subjective and objective factors, decision scores are calculated and ranked for various configuration schemes from both cost and performance preferences. The research results indicate that the multi-objective optimization model established in this paper can screen and optimize various configuration schemes from the optimal principle of the vehicle, and the optimized configuration schemes can be quantitatively ranked to obtain the decision results for the vehicle under different preference tendencies.

Multi-sensor fusion  /  Intelligent driving  /  Multi-objective optimization  /  Vehicle optimization
Binggen Zhao, Dong Zeng, Haoyu Lin, Xubo Qiu, Pijie Hu. Research on the Mechanism of Multi-Sensor Fusion Configuration Based on the Optimal Principle of the Vehicle[J]. Automobile Technology, 2024 , (10) : 28 -37 . DOI: 10.19620/j.cnki.1000-3703.20240707
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Article Info
doi: 10.19620/j.cnki.1000-3703.20240707
  • Online Date：2025-12-22
  • Published：2024-10-24
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  • Revised：2024-08-12
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    Automotive Research Institute, BYD Auto Industry Company Limited, Shenzhen 518118
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