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Proceedings of the 3rd International Conference on Mechanics, Electronics Engineering and Automation, ICMEEA 2026, April 24-26, 2026, Singapore, Singapore

Research Article

Technical Analysis of Autonomous Driving in Complex Road Conditions Based on Multimodal Perception Fusion

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  • @INPROCEEDINGS{10.4108/eai.24-4-2026.2364919,
        author={Yiming  Xie},
        title={Technical Analysis of Autonomous Driving in Complex Road Conditions Based on Multimodal Perception Fusion},
        proceedings={Proceedings of the 3rd International Conference on Mechanics, Electronics Engineering and Automation, ICMEEA 2026, April 24-26, 2026, Singapore, Singapore},
        publisher={EAI},
        proceedings_a={ICMEEA},
        year={2026},
        month={9},
        keywords={Intelligent driving multimodal perception data fusion feature fusion decision fusion},
        doi={10.4108/eai.24-4-2026.2364919}
    }
    
  • Yiming Xie
    Year: 2026
    Technical Analysis of Autonomous Driving in Complex Road Conditions Based on Multimodal Perception Fusion
    ICMEEA
    EAI
    DOI: 10.4108/eai.24-4-2026.2364919
Yiming Xie1,*
  • 1: Department of Electromechanical and Vehicle Engineering, Taiyuan University, Taiyuan, 030032, China
*Contact email: 4202350301428@stu.tyu.edu.cn

Abstract

With the continuous development of autonomous driving technology, single-modality perception has been unable to meet current development needs. Therefore, multi-modality perception fusion has become an important technology to ensure the safe driving of vehicles. This paper mainly analyzes the defects of single-modality perception and the feasibility of multi-modality perception in complex environments. In addition, this paper discusses the fusion methods and novel algorithms based on the data layer, feature layer, and decision-making layer of the auto drive system in recent years, and raises some questions. Utilizing these studies, this paper explains how multi-modality perception fusion overcomes the impact of complex environments on vehicle driving. Finally, this paper summarizes the current technological bottlenecks and limitations of autonomous driving and proposes future development directions and challenges.

Keywords
Intelligent driving, multimodal perception, data fusion, feature fusion, decision fusion
Published
2026-09-02
Publisher
EAI
http://dx.doi.org/10.4108/eai.24-4-2026.2364919
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