Research on target detection and automatic navigation algorithm for intelligent vehicles

Tao Ji; Yin Yuan; Meiyu Liang

doi:10.1117/12.3025220

21 February 2024 Research on target detection and automatic navigation algorithm for intelligent vehicles

Tao Ji, Yin Yuan, Meiyu Liang

Proceedings Volume 13080, International Conference on Frontiers of Applied Optics and Computer Engineering (AOCE 2024); 130800L (2024) https://doi.org/10.1117/12.3025220
Event: International Conference on Frontiers of Applied Optics and Computer Engineering, 2024, Kunming, China

Abstract

In order to advance the development of secure and effective self-driving technology, a novel approach for intelligent vehicle target detection and automated navigation has been introduced. To improve the exploitation of semantic information, we enhanced the FPN structure by using the Spatial Adaptive Filter (ASF) module and input it into the FPN structural layer. Then the ROS system is used to realize the function package to complete the configuration of parameters and the real-time construction of the map. On this basis, the elite ant colony algorithm is combined to realize the planning of optimal paths. The experimental outcomes demonstrate that in the improved algorithm scheme, the average accuracy mean under simple, medium, and complex categories is 87.12, 77.80, and 76.02 respectively. The set of four different types of obstacles can realize the path planning of the intelligent vehicle and obtain better results. To conclude, the effectiveness and feasibility of the program is verified by multiple sets of experimental data.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tao Ji, Yin Yuan, and Meiyu Liang "Research on target detection and automatic navigation algorithm for intelligent vehicles", Proc. SPIE 13080, International Conference on Frontiers of Applied Optics and Computer Engineering (AOCE 2024), 130800L (21 February 2024); https://doi.org/10.1117/12.3025220

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KEYWORDS

Detection and tracking algorithms

Target detection

3D acquisition

Autonomous vehicles

Autonomous driving

Object detection

Point clouds

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