Advantages and Challenges in BEV Algorithm Technology for Autonomous Vehicles from Environment Sensing

Yuexin Pan

doi:10.47297/taposatWSP2633-456924.20250602

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Advantages and Challenges in BEV Algorithm Technology for Autonomous Vehicles from Environment Sensing

Volume 6, Issue 2

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Advantages and Challenges in BEV Algorithm Technology for Autonomous Vehicles from Environment Sensing
Advantages and Challenges in BEV Algorithm Technology for Autonomous Vehicles from Environment Sensing
School of Sports Engineering, Beijing Sport University, Beijing, 100091, China
Vol. 6, Issue 2, Pages: 123-126(2025)
Published：25 February 2025
DOI：10.47297/taposatWSP2633-456924.20250602
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Pan Yuexin.Advantages and Challenges in BEV Algorithm Technology for Autonomous Vehicles from Environment Sensing[J].Theory and Practice of Science and Technology,2025,06(02):123-126.
DOI：

Pan Yuexin.Advantages and Challenges in BEV Algorithm Technology for Autonomous Vehicles from Environment Sensing[J].Theory and Practice of Science and Technology,2025,06(02):123-126. DOI： 10.47297/taposatWSP2633-456924.20250602.

摘要

Abstract

With the continuous development of China's artificial intelligence and computer vision field

the field of unmanned vehicles in the field of research has gradually become a research hotspot in the field of artificial intelligence

and nowadays

unmanned vehicles in our lives from "unattainable" to "within reach! Nowadays

driverless cars have changed from "out of reach" to "within reach" in our lives. The core of unmanned autonomous driving mainly relies on high - precision maps and sensors and other technologies

of which the BEV algorithm (i.e.

Bird's Eye View) provides a variety of technical routes. In this paper

we will focus on analysing the advantages and challenges brought by the three models in BEV algorithm to the automatic driving technology

and make an outlook on its future development.

关键词

Keywords

references

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ZHANG Xuyan,GUO Jianhong. Research on environment sensing system of driverless car based on LiDAR[J]. Auto Electric, 2023,(06):3 - 5.DOI:10.13273/j.cnki.qcdq.2023.06.013.

SHI Peicheng,DONG Xinlong,YANG Aixi,et al. Research progress of BEV sensing algorithm for autonomous driving[J/OL]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 1 - 24[2025 - 02 - 06].https://doi.org/10.13245/j.hust.250099.

Li Ping,Wang Lili. Research status and development trend of domestic multimodal technology: visualisation and analysis based on CiteSpace[J]. Intelligent Computer and Application, 2025,15(01):194 - 202.DOI:10.20169/j.issn.2095 - 2163.24062803.

Huang DQ, Huang HF, Huang DY, et al. A review of BEV perceptual learning in autonomous driving[J/OL]. Computer Engineering and Applications, 1 - 23[2025 - 02 - 06].http://kns.cnki.net/kcms/detail/11.2127.TP.20241031.1529.016.html.

HUANG XINXU. Turnip Express successfully test - runs driverless taxis in multiple cities, real landing still has challenges[N]. Daily Economic News, 2024 - 08 - 23(001).DOI:10.28571/n.cnki.nmrjj.2024.002404.

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