An Obstacle Detection Method Based on Longitudinal Active Vision

Author:

Shi Shuyue1,Ni Juan1,Kong Xiangcun1,Zhu Huajian1,Zhan Jiaze1,Sun Qintao1,Xu Yi12

Affiliation:

1. School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China

2. Qingte Group Co., Ltd., Qingdao 266106, China

Abstract

The types of obstacles encountered in the road environment are complex and diverse, and accurate and reliable detection of obstacles is the key to improving traffic safety. Traditional obstacle detection methods are limited by the type of samples and therefore cannot detect others comprehensively. Therefore, this paper proposes an obstacle detection method based on longitudinal active vision. The obstacles are recognized according to the height difference characteristics between the obstacle imaging points and the ground points in the image, and the obstacle detection in the target area is realized without accurately distinguishing the obstacle categories, which reduces the spatial and temporal complexity of the road environment perception. The method of this paper is compared and analyzed with the obstacle detection methods based on VIDAR (vision-IMU based detection and range method), VIDAR + MSER, and YOLOv8s. The experimental results show that the method in this paper has high detection accuracy and verifies the feasibility of obstacle detection in road environments where unknown obstacles exist.

Funder

Shandong Province Youth Innovation Team Plan for Universities

Natural Science Foundation of Shandong Province

Publisher

MDPI AG

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