Research on Safety Testing Method for Autonomous Driving Based on Visual System in Complex Urban Road Conditions

With the rapid development of autonomous driving technology, its safety issues have increasingly attracted attention. Through in-depth analysis of autonomous driving technology, this paper focuses on combing the role of the Vision System in the autonomous driving system architecture, and points out its key position in information perception, environmental modeling, and decision planning. The existing safety test methods are systematically evaluated, and their limitations in adapting to rapidly changing driving environments are identified. Aiming at the specific needs of the visual system, a new safety test method framework is proposed, covering Data Preparation, Testing Process, Evaluation Metrics and other aspects. It provides a new theoretical basis and practical guidance for autonomous driving safety testing assisted by the visual system, and promotes the further development of this field.

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Publication Details

Journal
Innovative applications of AI.
Published
2025-03-31
DOI
https://doi.org/10.70695/iaai202501a1
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Safety Testing Method for Autonomous Driving Based on Visual System in Complex Urban Road Conditions

Zhanwei Guo, Yunhui Wen
Innovative applications of AI.
Autonomous Vehicle Technology and Safety
article

Research on Safety Testing Method for Autonomous Driving Based on Visual System in Complex Urban Road Conditions

Zhanwei Guo, Yunhui Wen
article en

Abstract

With the rapid development of autonomous driving technology, its safety issues have increasingly attracted attention. Through in-depth analysis of autonomous driving technology, this paper focuses on combing the role of the Vision System in the autonomous driving system architecture, and points out its key position in information perception, environmental modeling, and decision planning. The existing safety test methods are systematically evaluated, and their limitations in adapting to rapidly changing driving environments are identified. Aiming at the specific needs of the visual system, a new safety test method framework is proposed, covering Data Preparation, Testing Process, Evaluation Metrics and other aspects. It provides a new theoretical basis and practical guidance for autonomous driving safety testing assisted by the visual system, and promotes the further development of this field.

Innovative applications of AI.Vol. 2(1)
Openalex Percentile: Top 95%
Autonomous Vehicle Technology and Safety
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