A Real-Time Obstacle Avoidance Method for Autonomous Vehicles Using an Obstacle-Dependent Gaussian Potential Field. (23rd August 2018)

• Record Type: Journal Article
• Authors: Cho, Jang-Ho; Pae, Dong-Sung; Lim, Myo-Taeg; Kang, Tae-Koo
• Other Names: Naranjo Jose E. Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2018(2018)
• Publication Date: 2018-08-23
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2018/5041401
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : A new obstacle avoidance method for autonomous vehicles called obstacle-dependent Gaussian potential field (ODG-PF) was designed and implemented. It detects obstacles and calculates the likelihood of collision with them. In this paper, we present a novel attractive field and repulsive field calculation method and direction decision approach. Simulations and the experiments were carried out and compared with other potential field-based obstacle avoidance methods. The results show that ODG-PF performed the best in most cases.