Research on Improvement of Environment Perception Algorithm for Autonomous Driving Vehicles Based on YOLOv5

Autonomous driving relies heavily on vehicle object detection, and YOLOv5s is presently one of the best algorithms for this purpose. However, in extreme environments such as severe weather, cars have poor perception of the environment, and their ability to detect dynamic targets is greatly affected,

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.4108/eai.21-11-2024.2354630
Primary Topic
Regional Development and Environment
Type
article
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article

Research on Improvement of Environment Perception Algorithm for Autonomous Driving Vehicles Based on YOLOv5

Yuxi Yang
Regional Development and Environment
article

Research on Improvement of Environment Perception Algorithm for Autonomous Driving Vehicles Based on YOLOv5

Yuxi Yang
article en

Abstract

Autonomous driving relies heavily on vehicle object detection, and YOLOv5s is presently one of the best algorithms for this purpose. However, in extreme environments such as severe weather, cars have poor perception of the environment, and their ability to detect dynamic targets is greatly affected,

Climate action
Openalex Percentile: Top 93%
Regional Development and Environment
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Research on Improvement of Environment Perception Algorithm for Autonomous Driving Vehicles Based on YOLOv5 — Yuxi Yang · (2025) | TGRS Research Map | TGRS